Timetable: SpliTech2019 Program

Hotel Elaphusa, Bol (island of Brač), Tuesday, June 18

07:30* REGISTRATION*

TIME/HALL HVAR ŠOLTA KORČULA

09:00-10:30 S1: Smart Cities-Infrastructure S2: IoT-Hardware S3: Energy-Efficiency I

10:30-11:00 Coffee Break

11:00-12:30 S4: Smart Cities-Radio and

Monitoring S5: IoT-Systems and

Software I S6: Energy-Efficiency II

12:30-13:00 Invited: L. Catarinucci, “Electromagnetic Design of RFID Sensing Platforms: Evolution

and Advances in View of the 5G Era” (BRAČ)

13:15-14:30 Lunch

14:30-15:00 Invited talk: K. Gabriel, “The Role of Innovation in Higher Education: Pathway to

Building an Innovation-Driven Society” (BRAČ)

15:30-16:00 Invited: V. Zanki, "Smart Energy Services for Decarbonisation of Energy Utility Sector"

(BRAČ)

16:00-17:30 S7: Smart Cities-Image and

Data Processing S8: IoT-Systems and

Software II S9: Energy-Batteries

Hotel Elaphusa, Bol (island of Brač), Wednesday, June 19

TIME/HALL HVAR ŠOLTA KORČULA

08:30-10:00 S10: Smart Cities-Building Monitoring and Intelligence

S11: eHealth-HW and SW S12: Energy-

Photovoltaics and Applications I

10:00-10:30 Invited: D. Čulibrk, “Bridging the Gap Between Academia and Industry: The

Tandemlaunch Deep Tech Start Up Foundry Model” 10:00-11:00 Poster Session and Coffee Break

11:15-12:30

OPENING CEREMONY (BRAČ)

Keynote speeches: L. Atzori, “The Great Potentials of Objects Collaborations in the IoT”

D. Wilkinson, “Electrochemical Energy Storage Technologies for the 21st Century” 12:30-13:30 Lunch

13:30-14:00 Invited: D. Mance, "Insight Mission to Mars: Challenges and Achievements" (BRAČ) 14:00-14:30 Invited: J. J. Klemeš, "Internet of Things for Green Cities Transformation" (BRAČ)

14:30-16:00 S13: Smart Cities-

Communications and Coding S14: eHealth-Effectiveness

Studies

S15: Energy-Photovoltaics and

Applications II

16:00-16:30 Coffee Break

17:00-17:30 Invited: V. Prodanović, "Building Sustainable Infrastructure: Advanced Spray and Jet

Cooling for New Materials and Technologies" (BRAČ)

17:30-18:00 Invited: A. M. Papadopoulos, "Micro-Grids, CHP and RES: An Option for Sustainable

Energy Communities" (BRAČ)

Hotel Elaphusa, Bol (island of Brač), Thursday, June 20

TIME/HALL HVAR ŠOLTA KORČULA

08:30-10:00 S16: Energy-Grids and

Machine Learning II

S17: Energy- Engineering Applications and

Modelling I S18: Energy-Systems I

10:00-10:30 Invited: V. Čongradac, "Integrated BMS and its Impact on Building Energy Efficiency"

(BRAČ)

10:30-11:00 Invited talk: C. T. Lee, “Closing the loops towards Zero-waste: from Waste

Management to Sustainable Agriculture and Food Production” (BRAČ) 12:00-12:45 Lunch

Traveling to Split

18:30 Guided Tour of Split

20:45 Conference Dinner and Cocktails in Split

Timetable: SpliTech2019 Program

Hotel Elaphusa, Bol (island of Brač), Tuesday, June 18

07:30* REGISTRATION*

TIME/HALL BRAČ VIS

09:00-10:30 P1: Engineering Modelling EURFID1

10:30-11:00 Coffee Break

11:00-12:30 P2: Innovations EURFID2

12:30-13:15 Invited talk: L. Catarinucci, “Electromagnetic Design of RFID Sensing Platforms:

Evolution and Advances in View of the 5G Era” (BRAČ)

13:15-14:30 Lunch

14:30-15:00 Invited talk: K. Gabriel, “The Role of Innovation in Higher Education: Pathway to Building an Innovation-Driven Society” (BRAČ)

15:30-16:00 Invited: V. Zanki, "Smart Energy Services for Decarbonisation of Energy Utility Sector"

(BRAČ)

15:00-16:30 P3: Applications EURFID3

Hotel Elaphusa, Bol (island of Brač), Wednesday, June 19

TIME/HALL BRAČ VIS MEET ROOM

08:30-10:00 S19: Engineering Modelling I EURFID4 Companies F2F Meetings

10:00-10:30 Invited: D. Čulibrk, “Bridging the Gap Between Academia and Industry: The

Tandemlaunch Deep Tech Start Up Foundry Model”

10:00-11:00 Poster Session and Coffee Break

11:15-12:30

OPENING CEREMONY (BRAČ)

Keynote speeches: L. Atzori, “The Great Potentials of Objects Collaborations in the IoT”

D. Wilkinson, “Electrochemical Energy Storage Technologies for the 21st Century”

12:30-13:30 Lunch

13:30-14:00 Invited: D. Mance, "Insight Mission to Mars: Challenges and Achievements" (BRAČ

14:00-14:30 Invited: J. J. Klemeš, "Internet of Things for Green Cities Transformation" (BRAČ)

14:30-16:00 S20: Engineering Modelling II EURFID5 S21: Energy-Grids and Machine

Learning I

16:00-16:30 Coffee Break

17:00-17:30 Invited: V. Prodanović, "Building Sustainable Infrastructure: Advanced Spray and Jet

Cooling for New Materials and Technologies" (BRAČ)

17:30-18:00 Invited: A. M. Papadopoulos, "Micro-Grids, CHP and RES: An Option for Sustainable

Energy Communities" (BRAČ)

18:00-18:45

RT: V. Prodanović, “Leading the change in engineering education”

(HVAR)

Thermtest: “Testing Thermal Conductivity - Applications and Methods” (KORČULA)

Hotel Elaphusa, Bol (island of Brač), Thursday, June 20

TIME/HALL BRAČ VIS MEET ROOM

08:30-10:00 S22: Energy-Green Cities

and Sustainability S23: Engineering

Modelling III S24: Energy-Systems II

10:00-10:30 Invited: V. Čongradac, "Integrated BMS and its Impact on Building Energy Efficiency"

(BRAČ)

10:30-11:00 Invited talk: C. T. Lee, “Closing the loops towards Zero-waste: from Waste

Management to Sustainable Agriculture and Food Production” (BRAČ) 12:00-12:45 Lunch

Traveling to Split

18:30 Guided Tour of Split

20:45 Conference Dinner and Cocktails in Split

*Registrations: Tuesday (07:00 – 17:30), Wednesday (07:30 – 18:00), Thursday (08:00 – 11:00), Friday (08:30 –

13:00) with pauses during lunchtime

University of Split, FESB, Friday, June 21

TIME/HALL LOBBY BIG HALL SMALL HALL

09:00-11:00 IoT Day by SpliTech – iotday.splitech.org

(09:00-16:30)

Workshop on Smart and Efficient Cooling Techniques for

Photovoltaic Technologies

Tutorial: D. Poljak et al. “Interaction of Humans with

Electromagnetic Fields”

11:00-12:30 Meet the Editor: Jiri

Jaromir Klemeš

4th International Conference on Smart and Sustainable Technologies

2019 Program

Time BRAČ HVAR KORČULA MEET

ROOM ŠOLTA VIS Session

Tuesday, June 18

09:00-

10:30

P1: Enginee

ring

Modelling

S1: Smart

cities-

Infrastructure

S3: Energy-

Efficiency I

S2: IoT-

Hardware

11:00-

12:30

P2: Innovati

ons

S4: Smart

Cities-Radio

and

Monitoring

S6: Energy-

Efficiency II

S5: IoT-

Systems

and

Software I

15:00-

16:30

P3: Applicat

ions

16:00-

17:30

S7: Smart

Cities-Image

and Data

Processing

S9: Energy-

Batteries

S8: IoT-

Systems

and

Software II

Wednesday, June 19

08:30-

10:00

S19: Engine

ering

Modelling I

S10: Smart

Cities-

Building

Monitoring

and

Intelligence

S12: Energ

y-

Photovolta

ics and

Applicatio

ns I

S11: eHeal

th-HW and

SW

10:00-

11:00

PS: Poster

session

14:30-

16:00

S20: Engine

ering

Modelling II

S13: Smart

Cities-

Communicati

ons and

Coding

S15: Energ

y-

Photovolta

ics and

Applicatio

ns II

S21: Ener

gy-Grids

and

Machine

Learning I

S14: eHeal

th-

Effectivene

ss Studies

Thursday, June 20

08:30-

10:00

S22: Energy

-Green

Cities and

S16: Energy-

Grids and

Machine

S18: Energ

y-Energy

S24: Ener

gy-Energy

S17: Energ

y-

Engineerin

S23: Engine

ering

Modelling

Sustainabili

ty

Learning II Systems I Systems II g

Applicatio

ns and

Modelling

III

Tuesday, June 18

Tuesday, June 18 9:00 - 10:30

P1: Engineering Modelling

Room: BRAČ

Area of Hysteresis Loop of a Generic Memristor Emulator

Santanu Mandal and Nune Partyusha (VIT-AP University, India); Rohit Bhargav Peesa (VITAP,

India); Mohammed Suhail (VIT-AP University, India)

Extensive research demonstrated that a memristor can be used as a memory storage system.

Subsequent studies have been carried out to facilitate the use of memristor as an electronic synapse.

However, the price of the memristor is very high due to the high cost of fabricating a memristor. In

order to continue research in this field, it is necessary to design memristor models and emulators.

One of three significant fingerprints of the memristor is, Hysteresis Loop. The Hysteresis loop area is

useful to measure the memory effect of a memristor. In this paper, the relation between frequency

and loop area is studied. A generic memristor emulator and its mathematical model are considered

here. This emulator circuit design is developed using Multisim software with specific electronic

components. All three fingerprints of the memristor are realised here. The mathematical formula of

loop area of this particular emulator is derived. Different loop areas are studied mathematically for

different frequencies to realize the memory effect of this memristor emulator. The results obtained

are verified by Multisim simulations.

Influence of Channel and Substrate Hydrophobicity on the Dynamic Water Transport Inside PEM

Fuel Cell Channels

Željko Penga (University of Split, Faculty of FESB, Croatia); Jure Penga and Frano Barbir (University of

Split, FESB, Croatia)

The occurrence of liquid water inside Proton Exchange Membrane (PEM) fuel cell can have

detrimental effects on the performance of the cell, resulting from non-uniform reactant supply along

the active area of the cell or neighboring channels and the accompanying non-uniform heat transfer,

to severe flooding and starvation of the cell. Liquid water transport inside the cell is investigated by

developing a transient 3D numerical model using Computational Fluid Dynamics (CFD) analysis and

Volume of Fluid (VoF) methodology. Several different commercially used bipolar plate materials, with

different hydrophobicities, are mutually compared in regard to the dynamic water transport and the

transient information on the gas diffusion layer substrate surface coverage. The effect of gas

diffusion layer aging is also investigated in conjunction with different bipolar plate materials. The

numerical model is developed for a single-channel serpentine of a commercial 100 cm2 single-cell.

Numerical analysis is also conducted to correlate the required pressure potential between the inlet

and outlet of the cell to expell the liquid water plug for a rectangular channel with uniform cross-

section and trapezoid channel with two reductions in the cross-section in the downstream direction.

The influence of the cell positioning, i.e. gravity, on the net liquid water transport is also investigated

and the results also indicate the potential for development of a diagnostic strategy for determining

the predominant water transport mechanism inside the channel based on the net pressure drop.

Computational Fluid Dynamics Analysis of Sea Water Mixing Inside a Ballast Tank Using Volume of

Fluid Method

Jure Penga (University of Split, FESB, Croatia); Željko Penga (University of Split, Faculty of FESB,

Croatia)

Numerical analysis is conducted using Computational Fluid Dynamics (CFD) modeling methodology to

investigate different strategies for sea water mixing and species homogenization via bubbling for a

commercial-scale sea vessel ballast tank. Mixing of the ballast sea water is achieved by incorporating

a novel approach, the internal combustion engine exhaust gases are used instead of inert gases

supplied by the compressors, to suppress the genesys and multiplication of invasive biological

organisms inside the ballast sea water tanks. Additionally, the effect of mixing is also investigated as

means to reduce the occurrence of sea water freezing inside the balast tanks while the vessel is

cruising in sub-zero atmospheres, achieved by disturbing the free surface of the sea water inside the

tanks. One commercially available configuration of the supply pipes is chosen as a reference, and 2D

CFD model incorporating Volume of Fluid (VoF) method is developed to study the transient

formation and transport of the exhaust gas bubbles inside the ballast tank. Several different design

configurations are analyzed as well as different bubble mass flow rates to determine the most

efficient and economically viable solution.

Level set topology optimization based on isogeometrical formulation of plane elasticity problems

Andela Bartulovic and Željan Lozina (University of Split, Croatia)

In this paper a level-set approach to topology optimization is presented where level set function is

parameterized using non-uniform rational basis splines (NURBS). Isogeometrical numerical method is

used for calculating objective function, i.e. for performing structural analysis. Objective function is

based on minimizing compliance to find the optimal distribution of material in the design domain

under a specified volume constraint. Two benchmark examples are presented to illustrate the

method.

Hybrid cross approximation accelerated boundary-domain integral method

Jan Tibaut (University of Maribor, Slovenia); Jure Ravnik (University of Maribor, Faculty of Mechanical

Engineering, Slovenia)

In this study, we propose an acceleration of an algorithm to solve the modified Helmholtz equation

using the Boundary-Domain Integral Method (BDIM). The BDIM is a boundary element method based

method, thus its computational demands scale as O(N2), where N is the number of grid nodes. This is

due to the fact that the discretization procedure leads to fully populated matrices. By transforming

the fully populated matrices into matrix parts with the H-matrix structure procedure and by applying

approximation techniques, we can reduce the computational complexity of the method. We employ

the modified Helmholtz fundamental solution. We compare the newly developed approximation

technique with the original algorithm.

S1: Smart cities-Infrastructure

Room: HVAR

A heuristic method for developing innovative city logistics concepts

Augusto Urru, Marco Bonini, Tamara Engel, Tobias Thomas Lenhart, Timo Pischzan, Dennis Thomas

Taebel, Jan Philipp Wezel, Sina Wolfangel and Wolfgang Echelmeyer(Reutlingen University, Germany)

Rapidly growing population and increasing amount of shipments induced by the e-commerce are two

of the main reasons for the constantly rising urban freight traffic. City are therefore overwhelmed by

a growing stream of goods and the available infrastructure, shared between people and goods traffic,

often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of

space are direct consequences of this trend and their impact on the quality of life in the city is not

negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt

alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained

in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented.

Thanks to a modular approach accounting for stakeholders´ requirements, possible different

scenarios and available technologies, the development of new city logistic concepts is supported. The

proposed method is then applied to a case study concerning the city of Reutlingen (Germany).

Results are presented and a brief discussion leads to the conclusion.

Analysing the Sentiments of Opinion Leaders in Relation to Smart Cities' Major Events

Manar Alkhatib (British University in Dubai, United Arab Emirates); Abolfazl AleAhmad (University of

Tehran, Iran); May El Barachi (University of Wollongong Dubai, United Arab Emirates); Farhad

Oroumchian (University of Wollongong in Dubai, Iran); Khaled F. Shaalan (The British University in

Dubai & Cairo University, United Arab Emirates)

With the constant social, economic, and political changes witnessed in the world, numerous events

occur in cities, and lead to important reactions from the public, including riots, civil disorder, and

violent actions. During those events, situational awareness is crucial to gain a good understanding of

the events and their impact on public opinion, which is typically difficult to measure. Opinion leaders

are influential people who are able to shape the thoughts of others in the society, through eloquent

and inspirational opinions and posts. Analyzing the sentiments of opinion leaders can give a strong

indication about the sentiment in the street, due to the high influence that those leaders have on

their followers. The purpose of this work is to build an opinion leaders' sentiment monitoring

framework that would serve as decision support tool for government officials. Our framework

leverages our previously proposed opinion leader identification algorithm, along with text mining,

text classification, and sentiment annotations to extract sentiment intelligence from opinion leaders'

posts, for effective analysis of public opinion about ongoing events. The proposed framework was

implemented and tested using datasets collected from 27,000 Twitter accounts over a 15 months'

span. Opinion leaders were identified in five domains (economics, politics, health, sports, and

education) based on their competency and popularity. Furthermore, a linear Support Vector Machine

(SVM) classifier along with sentiment annotations were used to perform sentiment analysis on the

tweets posted by 43 opinion leaders in relation to a major political event. The results obtained are

very promising and indicate the potential of leveraging high impact social media content to gain

insights about public opinion.

Inclusion as an Enabler to Sustainable Innovations in Smart Cities: A Multi-Level Framework

Payyazhi Jayashree and Feras Hamza (University of Wollongong in Dubai, United Arab Emirates); May

El Barachi (University of Wollongong Dubai, United Arab Emirates); Ghazaleh Gholami (University of

Wollongong in Dubai, United Arab Emirates)

Smart cities aim to offer an improved quality of life to citizens, promote economic growth, establish a

sustainable approach to development, and ensure efficient service delivery. The main focus in smart

cities' research is on the technological aspects of those cities. However, without aligning the design

of smart cities with the socio-cultural elements of the communities involved, and without bringing

the voices of all stakeholders into the design and implementation of smart cities, sustainable urban

development cannot be achieved. Indeed, a holistic approach that emphasis social inclusion of all

categories of citizens through a participatory innovation process is needed to achieve sustainable

smart cities. Focusing on the social aspects of smart cities, in this work, we examine the impact of

gender inclusivity on sustainable engineering, innovation, and the design of future smart cities.

Adopting a holistic and synergistic approach, we study how gender inclusivity and innovation

intersect with the sustainability agenda in the engineering profession, at three complementary

levels: 1) the Micro level, representing individual skills; 2) the Meso level, representing organizations

and innovation at the groups' level; and 3) the Macro level representing governments and

sustainability at the city level. Using a qualitative research approach with targeted sampling, we

conducted semi-structured interviews with male and female directors working at an international

engineering and consultancy firm in Dubai, and conduced a focus group discussion with a group of

university students who won the innovation category in the Solar Decathlon Middle East 2018

competition for their net-zero energy, dementia friendly home design. Thematic analysis of the data

collected was conducted, and a multi-level inclusion framework was proposed based on our findings.

The results obtained provide interesting insights on the impact of inclusion on sustainability and

innovation, and can have practical applications in the design of future smart cities.

Methodological Framework for Digital Transition and Performance Assessment of Smart Cities

Dessislava Georgieva Petrova-Antonova and Sylvia Ilieva (Sofia University, Bulgaria)

The ultimate goal of smart cities is to improve citizens' quality of life in a scenario where

technological solutions challenge urban governance. However, the knowledge and framework for

data use for smart cities remain relatively unknown. The actual translation of city problems into

diverse actions requires specific methodologies to guide digital transitions of cities and to assess to

what extent the smart cities' initiatives pursue sustainable development goals. This paper proposes a

methodological framework for digital modelling of cities allowing assessment of their performance

and supporting decision making. The city model adopts the concept of digital twin as a powerful tool

for discussion between stakeholders, as well as citizens to find the smartest solutions and get

valuable insight after their deployment. The methodological framework is presented as a set of

digital twin concept, stages of digital twinning and implementation strategy. Furthermore, the most

common city information models, suitable for implementation of digital twins are summarized.

Maritime situational awareness with OCULUS Sea C2I and forensics tools for a Common

Information Sharing Environment (CISE)

Stelios C. A. Thomopoulos (NCSR Demokritos, Greece)

CISE stands for Common Information Sharing Environment and refers to an architecture and set of

protocols, procedures and services for the exchange of data and information across Maritime

Authorities of EU (European Union) Member States (MS's). In the context of enabling the

implementation and adoption of CISE by different MS's, EU has funded a number of projects that

enable the development of subsystems and adaptors intended to allow MS's to connect and make

use of CISE. In this context, the Integrated Systems Laboratory (ISL) has led the development of the

corresponding Hellenic and Cypriot CISE by developing a Control, Command & Information (C2I)

system that unifies all partial maritime surveillance systems into one National Situational Picture

Management (NSPM) system, and adaptors that allow the interconnection of the corresponding

national legacy systems to CISE and the exchange of data, information and requests between the two

MS's. Furthermore, a set of forensics tools that allow geospatial & time filtering and detection of

anomalies, risk incidents, fake MMSIs, suspicious speed changes, collision paths, and gaps in AIS

(Automatic Identification System), have been developed by combining motion models, AI, deep

learning and fusion algorithms using data from different databases through CISE. This paper

discusses these developments within the EU CISE-2020, Hellenic CISE and CY-CISE projects and the

benefits from the sharing of maritime data across CISE for both maritime surveillance and security.

S2: IoT-Hardware

Room: ŠOLTA

Liquid Cooling Performance of the Single and Multi Led Circuit Boards Used in Automotive Lighting

Systems

Muhsin Kılıç (Uludağ University, Turkey); Mehmet Aktas (Magneti Marelli Mako Elektrik,

Turkey); Gökhan Sevilgen (Uludağ University, Turkey)

In this paper, the thermal performance of a liquid cooling block designed for automotive lighting

components integrated with high power Light Emitting Diode (LED) was investigated, numerically and

experimentally. Single and multi-chip on the printed circuit board (PCB) were selected to get

comparative numerical results in view of temperature differences on PCB surfaces for automotive

lighting systems. In the numerical simulations, three-dimensional Computational Fluid Dynamics

(CFD) model with natural convection effects was developed for predicting temperature distributions

of PCB surfaces. For this purpose, the single and multi 5-cell high power LED lighting system with

cooling block design were modeled. On the other hand, the effect of aspect ratio of cooling channel

and block material on the thermal performance of circuit boards with single and multi-chip was also

investigated numerically due to needing for weight reduction for automotive lighting applications.

From the results, higher temperature gradients were measured and predicted near the LED chip due

to the heat production of LEDs. Block material had little impact on the LED temperature but using

different materials aid to reduce block weight for automotive application. From the comparison of

the numerical data obtained for each PCB, the LED junction temperature was similar therefore same

cooling block design can also be used for multi-LED chip applications for Automotive Lighting

Systems. This Multi LED design using with liquid cooling block gives more opportunities for future

head and rear lamp applications of vehicles.

UAV-aided Sustainable Communication in Cellular IoT System with Hybrid Energy Harvesting

Zhenjie Tan and Gongye Ren (Xi'an Jiaotong University, P.R. China)

Green communication in smart city, where internet of things (IoT) applications are extensively

deployed, is a great concern of 5G cellular network design. In this paper, we adopt Ginibre

Determinant Point Process to characterize distribution of machine type communication gateways in a

single cellular coverage. Drone-based access point is introduced to establish favorable wireless

channel. We then establish a large-scale LP problem to find the minimum electric power

consumption of the IoT system where ambient radio and on-chip battery are the sole energy sources.

Specifically, a hybrid energy harvesting protocol combining millimeter wave and microwave below

6GHz is presented to enhance system sustainability. Two typical energy harvesting modes are

proposed, of which the first mode performs better when dealing with long-term M2M

communication service, while the second mode is more suited to occasional short-term energy

sharing. When machine type communication device is abundantly charged at the beginning, we

further obtain the closed-form expression revealing the ratio relationship between average electric

power consumption under both modes, which is explicitly related to: (a) initial battery energy level of

machine type network nodes, (b) service-oriented hybrid EH protocol configuration, (c) system

operation time and (4) fundamental electric and battery consumption of the whole system. Extensive

experiments are conducted using rejection sampling method and interior-point method through

MATLAB simulation.

Windows Monitoring and Control for Smart Homes based on Internet of Things

Sinara Medeiros (National Institute of Telecommunications (Inatel), Brazil); Joel J. P. C.

Rodrigues (National Institute of Telecommunications (Inatel), Brazil & Instituto de Telecomunicações,

Portugal); Mauro Cruz (Instituto Nacional de Telecomunicações, Brazil); Ricardo Rabelo (Federal

University of Piaui (UFPI), Brazil); Kashif Saleem (King Saud University, Saudi Arabia); Petar

Šolid (University of Split & FESB, Croatia)

The goal of interconnecting devices over the Internet justifies the vast expansion of the Internet of

Things (IoT). These devices are created with the purpose of autonomous interaction among them and

with users at affordable prices in their construction and development process. One of the sought

aspects of this concept are the smart homes, where house objects such as windows, curtains, doors,

and lights are integrated with technology, becoming with intelligent support, autonomous, and can

meet the preferences and needs of their users. Then, this paper introduces a system of automated

and sensor-monitored smart windows for a smart home scenario following an IoT-enabled approach.

In the proposed solution, the windows can be remotely controlled through a mobile app or via Web,

or operate automatically according to the environmental data obtained by the sensors and

predefined by users. This solution is evaluated, demonstrated, and validated, and it is ready for use.

Building Soft Sensors using Artificial Intelligence: Use Case on Daily Solar Radiation

Ivana Nizetic Kosovic and Toni Mastelic (Ericsson Nikola Tesla, Croatia); Ana Božid (Faculty of

Electrical Engineering and Computing, University of Zagreb, Croatia); Damir Ivankovid (Institute of

Oceanography and Fisheries, Croatia)

The concept of a soft sensor, a software replacement for unavailable, delayed or simply an expensive

physical sensor, has received a lot of attention in the last decade. Its ability to estimate values of an

observed phenomenon based on the expert knowledge defined in a form of theoretical or empirical

models gives it a wide application and considerably lower costs. Furthermore, with the advent of

artificial intelligence and data mining, soft sensors can be built purely by extracting correlations

between different sensor data. However, both approaches can lead to either over-fitting or over-

generalization. In this paper, both approaches are compared and combined in order to utilize the

best of both worlds. Procedure for building soft sensors is defined and evaluated on a real-world use

case for estimating daily solar radiation. The results show the best performance on the artificial

neural network with RMSE of 1.454 and RRMSE of 3.42%.

Capacity in LoRaWAN Networks: Challenges and Opportunities

Jelena Čulid Gambiroža and Toni Mastelic (Ericsson Nikola Tesla, Croatia); Petar Šolid (University of

Split & FESB, Croatia); Mario Cagalj (University of Split, FESB, Croatia)

Internet of Things (IoT) concept is growing in last few years and number of IoT devices is increasing

rapidly. Individual IoT sensors communicate over network. The LPWAN (Low Power Wide Area

Network) networks possess the ability to offer low-cost connection for huge number of low-power

devices distributed over large areas. LoRaWAN is a prominent LPWAN solution and in this paper

existing research work related to LoRaWAN capacity is surveyed, presented and discussed.

Performance Assessment of Software Defined Networks Management Protocol in Real

Environments

Thiago Costa (National Institute of Telecommunications, Brazil); Jonathan de Carvalho Silva (Instituto

Nacional de Telecomunicações & Inatel, Brazil); Joel J. P. C. Rodrigues(National Institute of

Telecommunications (Inatel), Brazil & Instituto de Telecomunicações, Portugal); Ricardo

Rabelo (Federal University of Piaui (UFPI), Brazil); Neeraj Kumar(Thapar University Patiala,

India); Petar Šolid (University of Split & FESB, Croatia)

Software Defined Networks (SDN) determinate a new paradigm for the development of a computer

network. Up to now, SDN gained attention from both the academic and industry communities. So far,

it has been focused on the standard OpenFlow, a network protocol that turned this approach

possible. However, SDNs extend beyond OpenFlow, opening new perspectives in terms of

abstractions, control environments, and network applications. Thus, this work proposes an SDN-

based mechanism for network management in the context of the Internet of Things (IoT) using the

OpenDayLight platform with a customized OpenFlow. For IoT, data collection and analysis is the point

where the SDN provides the flexibility to include multiple scenarios. It is also discussed how

OpenFlow and other proposals available in the literature contribute to the flexibilization of IoT

networks. Experimental results showed the benefits that can be achieved with this architecture,

including, energy savings, lower costs, and better traffic control. However, it is concluded that the

OpenFlow protocol is not feasible for an IoT scenario due to the obtained high error message

percentage while performing management of an SDN network.

S3: Energy-Efficiency I

Room: KORČULA

How a proper spent nuclear fuel management strategy can enhance the continuity of nuclear

power in the energy mix. The Mariño Model

Laura Rodriguez-Penalonga and B. Yolanda Moratilla Soria (Universidad Pontificia Comillas, Spain)

This paper presents the Mariño Model, a model created to estimate the costs of different strategies

for spent nuclear fuel management in Spain. One of the main purposes of the paper is to determine

which strategy accommodates better the particularities of the Spanish context, in order to help

establish a stable plan for spent nuclear management in Spain. As nuclear waste is one of the major

issues towards nuclear acceptance amongst the public, if it were to be properly solved and the public

is well informed and involved in the decision-making process, its acceptability could be increased.

Thus, nuclear power could still have an important role in mitigating climate change.

Energy Efficiency Improvement - A Case Study of Electricity consumption in Polish Households

Wiktoria Grycan (Wroclaw University of Technology, Poland)

European actions in the field of energy focus largely on improving energy efficiency. This article

analyses the problem in the context of Polish households, including the review and assessment of

current and planned programs to promote energy efficiency. Households are the third largest

consumer of electricity in Poland, and this group of consumers will have a significant impact on the

dynamics of its consumption in the coming decades. The potential for savings seems to be significant,

but is still not used to the proper extent. This is why it is worth considering whether households

should not be supported more regarding the saving of electricity.

Energy Efficiency Implication in a Fabric Finishing Factory in Turkey

Betül Özer and Behçet Güven (Kırklareli University, Turkey)

Energy efficiency efforts are getting more importance due to increased difficulty to access the energy

resources and global environmental problems especially climate change. Since the industrial sector

has a large share of energy consumption, efficiency studies have focused on this sector. Textile is an

energy-intensive industry by using large amounts of electricity and fuel. That is one of the sectors

that take part in the locomotive of Turkey's economic development due to the manufacturing

process and highly shared exportation. Energy efficiency is a vital issue for Turkey like all the other

countries to continue sustainable development. This study analyses energy efficiency studies and

energy saving potential in a textile finishing factory in Turkey that has an energy management system

(EnMS) application with a capacity of approximately 6500 TEP annual energy consumption. The

energy saving rate of the factory is determined approximately 7% of the energy consumption value

of 2016.

Energy Efficiency in the framework of Sustainable Smart Factories: a literature review

Dorian Oswaldo Mora Sanchez (Universidad UTE, Ecuador)

New energy technologies are providing benefits in different applications, and together with the

Industry 4.0 paradigm, the sustainable advantages focus on the industry business. The

implementation of this fourth revolution implies new environmental and social risks and challenges.

In the present article, a second Industry 4.0 exploratory analysis was executed based on the new

energy technological advances that have contributed to make more sustainable the smart factories.

It started with a short review of the industrial revolutions, energy efficient Industry 4.0, risks and

challenges, an energy Industry 4.0 approach proposal, and finally the Sustainable Development Goals

which are impacted by energy efficient Industry 4.0 are also presented. After the analysis it was

noted that big data, as an enabling Industry 4.0 technology, would help for energy monitoring in real

time and the use of data analytics would facilitate decision making properly and effectively, towards

a progressively optimizing energy consumption. In conclusion, industry 4.0 technologies would

contribute to new industrial benefits, but new energy technologies applied to the Industry 4.0 would

introduce energy efficiency benefits. This new Industry 4.0 paradigm should be deeply analyzed in

order to avoid any type of environmental or social negative impact.

Tuesday, June 18 11:00 - 12:30

P2: Innovations

Room: BRAČ

Adaptation of the UTAUT Model - Customers influence on Technology Adoption

Visvanathan Naicker (Cape Peninsula University of Technology, South Africa)

The study considered the influence of competitive forces on SME technology adoption in developing

economies, focusing on customers. A mixed method exploratory research was conducted. The

Unified Theory of Acceptance and Use of Technology model was used as a baseline. The findings

have shown that technology adoption, in relation to competitive forces, is linked to Age, Experience

and Voluntariness of Use. The UTAUT model was adapted and is now dedicated to SMEs in

developing economies, which highlights the influence that customers have on SME technology

adoption. The emphasis on customers has not been highlighted in previous technology acceptance

models.

The Role of Innovation in Higher Education: Pathway to Building an Innovation-Driven Society

Kamiel Gabriel (UOIT, Canada)

In a knowledge-based, innovation-driven economy, science is the essential resource. Innovation-

driven economies have the foundation and impetus to create new jobs and new products and

services. Research is at the core of the knowledge-based economy. In economic terms, knowledge-

capital that is innovative - meaning it modifies or develops more effective processes, products and

ideas - is the most valuable. Innovative products, services or systems have the potential to

completely displace the previous status quo to create an innovation eco-system. Support for

research and development activities in universities and higher technology colleges is essential to

reaching this goal. This paper will highlight a pathway to creating a link between R&D activities and

the end users.

Analysis of differences between calculated and measured energy consumption of schools by

educational stages in Korea

Sumin Jeon, Jae-Sik Kang and Kyeong-seok Choi (Korea Institute of Civil Engineering and Building

Technology(KICT), Korea); Seungmin Lee (Korea Institute of Sustainable Design and Educational

Environment, Korea)

In Korea, as a part of efforts in order to reduce carbon emission in building sector, when schools

build a new building, the building is assessed for energy efficiency by the energy simulation software

name of "ECO2" based on ISO 52016. But the assessment for schools is conducted by same space

profiles without regard to educational stages of schools. This study was started from a hypothesis

that energy consumption of schools differs by educational stages of schools. The aim of the study is

to verify differences between energy consumption of schools by educational stages and to compare

and analyse them for validating whether it is necessary to modify space profiles of ECO2 software by

educational stages or not. In chapter 2, through statistical methods, differences of energy

consumption by school types within each data type were verified and its reasons were analysed. In

chapter 3, differences verified in previous chapter were quantified by regression analysis. The result

of the study proved that energy consumption of school in Korea have differences by educational

stages and that it is necessary to reflect basic condition factors such as space profile by school types

to ECO2 software. The meaning of the paper is to elucidate the necessity of subdivision of school

buildings for energy performance evaluation by ECO2 software and to suggest ways to improve the

appropriateness of prediction for building energy performance.

S4: Smart Cities-Radio and Monitoring

Room: HVAR

PmA: a solution for people mobility monitoring and analysis based on WiFi probes

Marco Uras (University of Cagliari, Italy); Raimondo Cossu (University of Cagliary, Italy); Luigi

Atzori (University of Cagliari, Italy)

The analysis of people mobility in urban contexts is of key importance to tackle major issues in

different fields, such as those related to urban planning, citizen safety, telecommunications services

planning, public transport service deployment.Such an analysis should provide key indicators, such as

crowd density per area of interest, people flows, recurrent mobility pat-terns, mobility heat maps,

just to cite a few. In the present paper, we provide a solution named PmA, which relies on the

monitoring of WiFi and Bluetooth traffic, which is also solicited through the generation of probe

requests. The main features of the solution are the followings: preservation of user privacy,

extraction of key metrics on user return and permanences, computation of mobility heat maps.

Extensive sessions of monitoring and analysis have been carried out in three different pilots: an

university campus during classes, an international fair, and a roundabout.

Location Privacy and Changes in WiFi Probe Request Based Connection Protocols Usage Through

Years

Ante Dagelic, Toni Perkovic and Mario Cagalj (University of Split, FESB, Croatia)

Location privacy is one of most frequently discussed terms in the mobile devices security breaches

and data leaks. With the expected growth of the number of IoT devices, which is 20 billions by 2020.,

location privacy issues will be further brought to focus. In this paper we give an overview of location

privacy implications in wireless networks, mainly focusing on user's Preferred Network List (list of

previously used WiFi Access Points) contained within WiFi Probe Request packets. We will showcase

the existing work and suggest interesting topics for future work. A chronological overview of

sensitive location data we collected on a musical festival in years 2014., 2015., 2017. and 2018. is

provided. We conclude that using passive WiFi monitoring scans produces different results through

years, with a significant increase in the usage of a more secure Broadcast Probe Request packets and

MAC address randomizations by the smartphone operating systems.

Measurements and Statistical Characterization of Time-varying WiFi Indoor Radio Channel

Ante Lojid Kapetanovid, Zoran Blaževid and Maja Škiljo (University of Split, Croatia)

This paper presents analysis of temporal variations of WiFi indoor radio channel, measured by simple

and affordable equipment. It has been shown that, by the normalization of the received signal

amplitude to its local mean value, the whole indoor WiFi propagation environment can be

represented as a Rician channel regardless of whether the visibility between the transmitter and the

receiver exists or not.

Impact of Different Concrete Types on Radio Propagation: Fundamentals and Practical RF

Measurements

Ari Asp, Tuomo Hentilä, Mikko Valkama and Jussa Pikkuvirta (Tampere University, Finland); Arto

Hujanen (VTT Technical Research Centre of Finland, Finland); Ismo Huhtinen(VTT, Finland)

By the 1960's, European countries faced a massive housing shortage due to changes in social

structure and migration from rural areas to towns. This led to a rapid growth of suburban areas in the

1960's and 1970's. Concrete, as a building material became, became popular as the prefabrication

techniques of precast concrete structures developed rapidly during this era, and these trends

continue even today. In the near future, the number of frequency bands used by mobile wireless

communication systems will increase and, in general, the trend is towards higher frequencies. This

paper presents the results of measurements in which the RF attenuations of several different

concrete types were determined on the basis of the permittivity of the material samples. The

frequency ranges used in the measurements were 4.5 to 19 GHz and 26 to 40 GHz. In particular, at

higher frequencies, the attenuation of various concrete grades is very different, and the level of RF

attenuation of the outer wall cannot be predicted without knowing the age of the building and the

concrete quality used in the element.

Average Fade Duration of Triple Nakagami-m Random Process and Application in Wireless Relay

Communication System

Ivan Vulid (University of Defence, Belgrade, Serbia); Dragana Krstid (Faculty of Electronic Engineering,

University of Niš, Serbia); Petar Nikolid (Tigar Tyres, Pirot, Serbia); Sinisa Minid (Teachers College in

Prizren - Leposavic, Serbia); Mihajlo Stefanovid (University of Nis, Serbia)

In this paper, the average fade duration (AFD) of the wireless relay communication system with three

sections in the presence of Nakagami-m fading is determined and presented graphically. AFD is used

to show how long a user is in continuous outage, below a specified level, after crossing that level in a

downward direction. This result is useful in information theory, for example for coding design.

S5: IoT-Systems and Software I

Room: ŠOLTA

A Blockchain based Architecture for the Detection of Fake Sensing in Mobile Crowdsensing

Mohamad Arafeh (Lenabese American University, Lebanon); May El Barachi (University of

Wollongong Dubai, United Arab Emirates); Azzam Mourad (Lebanese American University,

Lebanon); Fatna Belqasmi (Zayed University, United Arab Emirates)

With the emergence of mobile crowdsensing (MCS) we now have the possibility of leveraging the

sensing capabilities of mobile devices to collect information and intelligence about cities and events.

Despite the promise that MCS brings, this new concept opens the door to a multitude to security and

privacy threats and attacks. Indeed, the human involvement in the crowdsensing process and the

openness of this process to any participant, render the task of securing MCS environments a very

challenging task. In this work, we propose a Blockchain based hybrid architecture for the detection

and prevention of fake sensing activities in MCS. Our architecture leverages the capabilities of the

Blockchain network and introduces a new role to the MCS architecture to ensure the validation of

the collected information. Combining both data quality metrics along with behavioral analysis based

participants' reliability scoring, our solution is able to detect variations in behavior and quality of

contributions. The proposed solution was tested with real life data collected from 200 mobile users,

over the span of 2 years, and the results obtained are very promising.

A context agnostic air quality service to exploit data in the IoE era

Stefano Pino (Engineering Ingegneria Informatica Spa, Italy); Alessio Camillò, Marco Pinnella, Enza

Giangreco, Marco Del Coco and Davide Storelli (Engineering Ingegneria Informatica S.p.A.,

Italy); Giovanni Aiello (Eng'g Ingegneria Informatica SPA, Italy)

The upcoming IoE paradigm is taking the IoT era to a new shift, and that because of the natural inter-

connection of processes, people, devices and stakeholders. From the smart city perspective, the

main goal is to make well-informed decisions, on the base of a variable number of sensors and

sources, exposing different data with different protocols and structures. The urban contexts may

change, and with them, the number of sensors deployed. The novel smart city service must go

beyond an integration strategy, it needs an exploitation model to optimally retrieve useful and highly

contextualized information. In this paper we focus on the development of a model which fuses

together the IoE potential and machine learning techniques for the cognitive smart city: retrive

useful intelligent information, optimally exploiting the infrastructure the specific physical context

may offer. We propose an approach and related techniques for realizing context agnostic services,

namely services that do not depend on the enabling infrastructure beneath. The purpose is to create

an IoE-based self-contextualizing service, which potentially consider the entire range of data that is

being collected in smart cities and use such data to provide highly-personalized information about

each environment, i.e., information that best suits the context of each Smart City. To prove the

proposed context agnostic service, we take into account the air quality observation issue: we provide

two high-contextualized informative services to leverage data related to two different physical

environments, thus building location awareness for different geographic areas and stakeholders. But

still managed by the same application which can adapts itself. Finally we present the evaluation of

this prototype to illustrate the benefits of our solution and the future work.

A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost

Amin Shahraki, Marius Geitle and Øystein Haugen (Østfold University College, Norway)

Internet of Things (IoT) will be connecting more than 50 billion heterogenous devices around the

world by 2020. As an Ultra Dense Network (UDN), which needs high resources to establish, different

technologies are emerging to improve the efficiency of IoT. Fog is a new phenomenon that uses close

powerful nodes to help end users achieve reduced delays, optimize resource consumption, and

improve the quality of service, etc. In techniques such as routing, clustering, caching, etc., nodes

need to select pairing nodes or the next hop nodes which are used to help nodes transfer or process

data. In this paper, a new mathematical fuzzy-based method is proposed to evaluate the suitability of

a nodes neighbors. Nodes broadcast their information to inform neighbors about their situations,

and each node compares itself to its neighbors and broadcasts a score that shows its tendency to be

a pairing node. The proposed method is application-agnostic and can be used in different techniques

regarding parameters that are considered to evaluate. A fuzzy method is used to integrate the

parameters and calculate the score. As a new attitude, we use the XGBoost algorithm to extract the

fuzzy rules from examples. After receiving the score, another fuzzy method is used to give other

eligible neighbors the chance to be the next hop due to support network load balancing. Riverbed

Modeler, MATLAB and Python are used to evaluate the node assessment model.

A Smart Approach able to face Distraction Issue due to Smartphone Usage running Social Networks

Luca Podo, Benito Taccardi, Alessandro Colonna and Luigi Patrono (University of Salento, Italy)

Smartphones are more and more an essential tool for everybody's life. They support daily activities

and often they make easier people's life style. Nevertheless, the usage of smartphones has not got

only positive aspects. There are several distractions which came from this device which might affect

badly some activities in which concentration is fundamental. Studying, working or just socializing

might became complex activities if they are carried out with smartphones and their distractions. The

proposed smart service, called '9Seconds', establishes an ambitious goal, which is fighting

smartphone's addiction using the smartphone itself. It is based on a work-reward system which

rewards the user according to how much he/she stays away from smartphone's distractions.

'9Seconds' is based on a user-friendly game, which includes challenges among users. They might

challenge each other, keep disconnected and earn points. Challenges might be done by two remote

users. Alternatively, a business activity might throw an event-challenge which allows users going into

the locale, make some socialization, eat a meal and earn further points. These points will be spent by

users to get some awards which will be bid by business activities. Therefore, '9Seconds' consists of a

multiplatform mobile application which combines mobile technologies with Cloud services in order

to providing the best solution to smartphone's addiction problem. In order to explain better main

features of the '9Seconds' service, a proof-of-concept has been included to report a functional

validation of the whole project.

A model for Reflective Middleware based on fuzzy rule for context-awareness injection in

ubiquitous computing environments

Francesco Nocera (Politecnico of Bari, Italy); Marina Mongiello (Politecnico di Bari, Italy); Angelo

Parchitelli (Politecnico of Bari, Italy); Eugenio Di Sciascio (Politecnico di Bari, Italy); Luigi

Patrono (University of Salento, Italy)

The next wave of communication and applications will rely on new services provided by the Internet

of Things (IoT) which is becoming an important aspect in human and machines future. IoT services

are a key solution for providing smart environments in homes, buildings, and cities. In the era of

massive number of connected things and objects with high growth rate, several challenges have been

raised, such as new modeling techniques, patterns, and paradigms for composing and developing

software and services able to deal with changing context and requirements. There are several factors

to be considered in the design and implementation of IoT platform. One of the most important and

challenging problems is the heterogeneity of different objects. This problem can be addressed by

deploying a suitable "middleware" which sits between things and applications as a reliable platform

for communication among things with different interfaces, operating systems, and architectures. In

this paper, we propose a solution allowing an IoT middleware to conform with reflective

programming paradigm to get more flexibility and adaptivity with reference to the external context.

The approach is based on a formal model in which fuzzy rules enable possible actions by the system.

We implemented and validated the proposed model on a real IoT middleware in a smart home

scenario.

S6: Energy-Efficiency II

Room: KORČULA

Analysis of Space Heating and DHW Charges of Apartment Buildings by Insulation Standards in

South Korea

Ji-Hyeon Kim, Wang-Je Lee, Jeong-Hwan Cheon and U-Cheul Shin (Daejeon University, Korea)

To evaluate the effectiveness of Korea's insulation standards reinforcement, this study analyzed

space heating and domestic hot water (DHW) charges in 2017 for 157,288 household in 207

apartment complexes that were completed from 1997 to 2016. The insulation standards applied to

these apartments were revised three times (in 1987, 2001 and 2010). The Anderson-Darling test was

used to review the normality of the space heating and DHW charges, showing that each p-value is

greater than 0.05 and follows the normal distribution. The annual average space heating charges per

unit area of apartments with the insulation standards of 1987 were $4.69/㎡a. The charges with the

strengthen standards of 2001 and 2010 were $4.32/㎡a and $3.29/㎡a, respectively, which

decreased by 7.9% and 23.8%. on the other hand, compared to each previous standard, DHW

charges decreased by 12.5%, then increased by 3%, showing there's no correlation between

insulation standards reinforcement and DHW charges.

Techno-Economic Analysis of Diabatic CAES Systems with Above-Ground Artificial Storage

Coriolano Salvini (Università degli Studi ROMA TRE, Italy); Ambra Giovannelli (Roma Tre University,

Italy); Daniele Sabatello (Università degli Studi ROMA TRE, Italy)

In the present paper, the techno-economic performance of a Diabatic Compressed Air Storage

System (D-CAES) with above-ground artificial storage is investigated. The influence on efficiency,

capital and operating costs of key design quantities is analyzed in detail and widely discussed. Finally,

the most promising D-CAES design solutions are compared with BES based storage systems by using

the Levelized Cost of Storage (LCOS) method. Results show that the adoption of D-CAES can lead to a

better economic performance in respect to mature and emerging BES technologies.

Economic Evaluation of Net-Zero Energy Houses

Heewon Lim, Hyeon-Seung Lee, Beob-Jeon Kim and U-Cheul Shin (Daejeon University, Korea)

This study analyzed and evaluated the energy performance and cost using electricity data from

KEPCO (Korean Electric Power Corporation) and actual PV generate data. The analysis was conducted

in two houses with different location and size. The empirical houses were constructed with high

thermal insulation and air tightness, and also designed as all-electric houses where all the energy

supplies (including heating and cooking) are made of electricity which reduces the maintenance cost

and makes maintenance easier. 6kWp grid connected photovoltaic system and air source heat pump

for heating and hot water were applied to both houses. The result is summarized as follows. First, for

two years, all energy (including plug load, heating, cooling, lighting, hot water supply and ventilation)

was supplied by PV system and consequentially zero energy was achieved in both houses. Second, as

a result of load matching analysis, in both houses, LCF in summer was relatively higher than that in

other seasons and SCF in winter was relatively higher than that in other seasons. Third, monthly

electricity bill by the amount of used were not charged, however, additional fees by domestic

electricity charging system were charged such as basic electricity fee, VAT on receiving electricity and

development fund; average $115 were paid per household.

Using high-temperature seawater heat pump for pool heating and domestic hot water preparation

in a special hospital

Tena Maruševac (University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture,

Croatia); Boris Dosid (FMENA, Croatia); Neven Duic (University of Zagreb, Croatia)

Heat pumps are recognized as energy efficient and environmentally friendly technologies for cooling

and heating. The objective of this paper is to identify the economic and environmental potential of

seawater heat pump installed in a specialized hospital on the Mediterranean coast. A seawater heat

pump is operating in the heating mode throughout the whole year and it is used for pool heating and

domestic hot water production. Energy demand was studied for a whole year, and the economic

benefits, as well as primary energy savings and CO2 emissions reduction, were analysed. The analysis

showed that the seawater heat pump would lead to 25% lower costs, 52% primary energy savings

and 63% of CO2 emission reduction in comparison to fuel oil boiler.

Tuesday, June 18 15:00 - 16:30

P3: Applications

Room: BRAČ

YOLOv3 algorithm for object detection in aerial photos using standard pre trained networks

Ana Šarid Gudelj, Tea Marasovic and Vladan Papic (University of Split, Croatia)

In this article we made test of object detection on three sets of images using YOLO v3 algorithm and

deep neural network (DNN) Darknet framework. The concept of DNN Darknet framework and CUDA

is explained, with accent on processing speed. Behavior of the used architecture with pre trained

Alexnet and ImageNet convolutional neural network when aerial orthogonal photos are used as input

was investigated. Obtained results were compared to results of standard images.

Customised OpenEMR for dental practice - clinical case

Damir Ivankovid (Institute of Oceanography and Fisheries, Croatia)

Customised open source OpenEMR has been used in private dental practice for the last eight years.

Some important modifications were maid for better clinical practice.

Cogeneration and Non-Electric Applications using Nuclear Energy: IAEA Activities and Tools

Rami El-Emam and Ibrahim Khamis (IAEA, Austria)

Nuclear energy is one of the main routes to consider for achieving energy-supply sustainability in

environment-friendly manner. Cogeneration using nuclear energy has broadened the scope of

nuclear energy utilization and widen the range of its applicability for serving industrial and residential

applications other than power production. In addition, the recovery of waste heat from nuclear

power plants for cogeneration applications an efficient energy management approaches that leads to

a direct reduction in overall plant losses and brings benefits in terms of economic, environmental and

sustainable energy aspects. The recovered heat can be used to produce a range of products such as

fresh water, process heat, district heating or cooling applications, or also a combination of these

applications. As a result, many applications which are primarily dependent on the use of

conventional fossil fuel as heat sources would make use of the recovered nuclear waste heat. This

would be a key step in the elimination of dependency on fossil fuels accompanied by improved

energy and water security. Similarly, using the recovered nuclear waste heat in industrial applications

leads to a drastic reduction in the environmental impact caused by fossil-fuel based systems.

Furthermore, advanced nuclear reactors incorporating cogeneration features are expected to

provide more environmentally benign energy systems operating at higher energy efficiency.

Depending on the technology (e.g. reactor, fuel type, and temperature level), different applications

can be integrated with nuclear power plants for cogeneration applications, this include hydrogen

production, petrochemical industries, steelmaking, industrial process steam, seawater desalination,

district heating and cooling and others. Nuclear cogeneration also serves towards enabling the load-

following capability of the nuclear power plant where heat can be directed for the other applications

during off-peak time - including hydrogen production and storage - to cover up the electric power

high demands at later time. In recent years, several countries have shown stronger interest and

commitment than ever to introducing nuclear energy in order to address issues of fast-growing

energy demand, energy trade and security, and sustainability of energy use, most of these

considered cogeneration applications. In support of its Member States interested in the use of

nuclear energy for cogeneration and non-electric applications, the International Atomic Energy

Agency (IAEA) conducts several activities on the topic with focus on desalination and hydrogen

production. The IAEA also developed tools and toolkits to elaborate on the feasibility and

technoeconomics of different nuclear cogeneration options. These tools are the Hydrogen Economic

Evaluation Programme (HEEP), the Desalination Economic Evaluation Programme (DEEP), and the

Desalination Thermodynamics Optimization Programme (DE-TOP). In addition, the IAEA developed

two toolkits on nuclear desalination and nuclear hydrogen production to provide up-to-date

information on the current-status of related technologies as well as the conducted and considered

activities related to these topics. Additionally, several publications have been produced by the IAEA

covering the issues related to nuclear cogeneration, including the status and development in the

incorporated technologies, safety of coupling, and their technoeconomics. Moreover, in continue to

its activities on nuclear hydrogen production and in response to the growing interest in hydrogen

economy worldwide, the IAEA recently started a new coordinated research project on assessing

technical and economic aspects of nuclear hydrogen production for near-term deployment. This

paper discusses the different aspects of nuclear energy cogeneration systems and their applications

towards achieving the sustainability in the related sectors. In addition, the IAEA activities, tools and

toolkits, which are developed to provide support to Member for better understanding of the

economic viability of nuclear cogeneration options are highlighted.

Tuesday, June 18 16:00 - 17:30

S7: Smart Cities-Image and Data Processing

Room: HVAR

String pattern searching algorithm based on characters indices

Ivan Markid (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Bosnia

and Herzegovina); Maja Štula and Marija Zorid (Faculty of Electrical Engineering, Mechanical

Engineering and Naval Architecture, Croatia)

The pattern search is applied in almost all branches of science. Pattern searching algorithms in

sequences of symbols, i.e. strings, are used in areas such as bioinformatics, information security, text

mining, etc. In the context of continuous increase of data, in the Big data era, efficient algorithms are

necessary to ensure that one can find a pattern in a sequence in a fast and accurate manner. Pattern

searching solves the problem of finding a pattern exhibiting certain properties within a given

sequence of symbols. This article presents concept of the new algorithm, based on a character index

in a pattern, aiming at, but not limited to patterns in DNA sequences.

Application of KNN and Decision Tree Classification Algorithms in the Prediction of Education

Success from the Edu720 Platform

Omar Derviševid (Mistral Technologies & Faculty of Electrical Engineering, Bosnia and

Herzegovina); Emir Žunid (Info Studio, Bosnia and Herzegovina); Dzenana Donko (, unknown); Emir

Buza (University of Sarajevo, Bosnia and Herzegovina)

Data mining is the process of knowledge discovery in a certain amount of data. Knowledge discovery

in data reflects in the application of sophisticated machine learning methods such as regression,

classification, clustering, etc. The focus of this study is the analysis of data from the real production

system called Edu720, which is intended for internal education of employees in companies and which

is used by numerous companies in Bosnia and Herzegovina and its region. A complex process of data

preprocessing, including data cleaning and data transformation, was applied to the considered data

set so it can be used in numerous classification tasks. The main goal of this study is to predict the

success of the education that the company wants to set up for its employees. Information such as

the number of questions in education, the average number of questions in education, the number of

employees and the duration of the educational video resource represented in seconds were used as

attributes for applied classification methods. Class output represents the level of success for certain

educations. K-nearest neighbors and decision tree algorithms were used for classification tasks and

the accuracy of the classification was determined by the holdout method. The influence of applying

the more sophisticated method for data set partitioning, which uses the K-means clustering method,

is also presented.

The Optical Subsystem for the Empty Containers Recognition and Sorting in a Reverse Vending

Machine

Andrey N. Kokoulin (Perm National Research Polytechnical University & PNIPU, Russia); Dmitriy A.

Kiryanov (Federal Scientific Center for Medical and Preventive Health Risk Management, Russia)

A reverse vending machine (RVM) is a machine where people can return empty beverage containers

like plastic bottles and cans for recycling taking back a deposit or refund amount. Reverse vending

machines are a key part of container deposit systems in Europe and United States. Waste recognition

and sorting in RVM machines can be performed by any of the following procedures: by determining

the container material (e.g. using the IR-spectrometer), by recognition of the container type by its

shape, or by the barcode identification. These three basic control-procedures make any attempt of

the fraud completely impossible. But the same time it makes the RVM too expensive. With the

modern computer vision technologies we can design another kind of efficient and non-expensive

RVM having the same functionality using energy-efficient IoT MCUs. In our paper we consider some

approaches in computer vision and image processing and their application to the problem of

automatic recognition of empty recyclable containers (bottles and cans) and detecting fraud. We

have to restrict the list of the available methods and frameworks because of IoT controllers and tiny

single-board computers we use have memory and computational restrictions. Our aim is to classify

the image inside the RVM by three possible classes: PET bottle, aluminium can or fraud (everything

that doesn't match PET bottle or can). We take into attention that those cans or bottles could be

twisted or jammed. Also we analyse the performance of image recognition procedures in Python and

C ++ languages.

A Review of Methodologies and Applications in Visual Internet of Things

Maja Braovid (University of Split - FESB, Croatia); Ljiljana Šerid (University of Split - Faculty of El. Eng.,

Mech. Eng. and Naval Arch., Croatia); Darko Stipaničev (University of Split - Faculty of Electr. Eng.,

Mech. Eng. and Naval Arch., Croatia)

Internet of Things is a widespread concept associated with devices equipped with sensors, connected

to the Internet, and able to communicate to each other and with the end user. The ultimate goal of

Internet of Things is to make people's lives easier, simpler and safer, and a number of applications

that are steering Internet of Things in that direction already exist. This paper presents a review of

Internet of Things methodologies and applications that use visual data, i.e. where the main focus is

on Internet of Things methodologies and applications where one of the primary sensors that is being

used is a digital camera. This sub-field of Internet of Things is also known as Visual Internet of Things.

CNN-based Method for Lung Cancer Detection in Whole Slide Histopathology Images

Matko Saric, Mladen Russo, Maja Stella and Marjan Sikora (University of Split, Croatia)

Early diagnosis of lung cancer is critical for im- provement of patient survival. Histopathological

assessment of tissue is standard procedure needed for early diagnosis. Tis- sue analysis is usually

performed by pathologist review, but this procedure is time-consuming and error-prone. Automated

detection of cancer regions would significantly speed up the whole process and help the pathologist.

In this paper we propose fully automatic method for lung cancer detection in whole slide images of

lung tissue samples. Classification is performed on image patch level using convolutional neural

network (CNN). Two CNN architectures (VGG and ResNet) are trained and their performance are

compared. Obtained results show that CNN based approach has potential to help pathologists in lung

cancer diagnosis.

S8: IoT-Systems and Software II

Room: ŠOLTA

An Ontology for Collaborative Navigation Among Autonomous Cars, Drivers, and Pedestrians in

Smart Cities

Meirman Syzdykbayev and Hadi Hajari (School of Computing and Information, University of

Pittsburgh, USA); Hassan Karimi (University of Pittsburgh, USA)

While existing transportation research is mostly focused on taking the behavior of different travelers

(mostly drivers) into account in traffic situations, currently there is a gap in research that addresses

collaboration among all travelers. To fill this gap, we propose to develop the foundational knowledge

for collaboration among travelers and the surrounding infrastructure using advanced navigation

systems. Our vision is that unlike current navigation systems that assist drivers and pedestrians with

navigation within urban cities in isolation, the future generation of navigation systems will be

collaborative where drivers, autonomous cars, and pedestrians will interact and share their mobility

needs and preferences to meet a specific objective. These objectives could be car crash avoidance,

pedestrian accident avoidance, or environmentally friendly mobility, among other things. This paper

presents an ontology as the foundation for the proposed collaborative navigation, which is an

important feature of smart cities. Navigation sensors, which are commonplace and anticipated to be

widespread in smart cities, constitute the underlying information for the proposed ontology where

interactions between different participants are conceptualized.

Performance Evaluation of MQTT Brokers in the Internet of Things for Smart Cities

Davi Luis de Oliveira (Universidade Federal do Piauí, Brazil); Artur Veloso (Faculdade Estácio CEUT,

Brazil); José Victor Vasconcelos Sobral (Instituto de Telecomunicações, University of Beira Interior &

Federal Institute of Maranhão, Portugal); Ricardo Rabelo (Federal University of Piaui (UFPI),

Brazil); Joel J. P. C. Rodrigues (National Institute of Telecommunications (Inatel), Brazil & Instituto de

Telecomunicações, Portugal); Petar Šolid (University of Split & FESB, Croatia)

The Internet of Things (IoT) has become of great importance in the last decades. The term is used to

denote the connectivity between electronic devices that allows the collect and sharing of data

through the Internet. IoT technologies can be applied to automate and minimize problems related to

urbanization in Smart City scenarios. In this context, MQTT brokers (Message Queuing Telemetry

Transport) are used to enable communication between IoT devices. Brokers are responsible for

enabling connection and sending of messages between devices. The current literature presents a

wide variety of brokers and to choose the suitable solution for the project, which can lead to

performance problems, may become a hard task. Thus, the objective of this paper is to analyze the

performance of MQTT brokers regarding latency in the data packets sending, and to present

advantages and drawbacks of the solutions in Smart Cities scenarios. Results showed that the

computer hardware features and the bandwidth used have a greater impact on the latency, showing

that several factors can influence the performance of brokers.

IoT-oriented Waste Management System based on new RFID-Sensing Devices and Cloud

Technologies

Luca Catarinucci, Riccardo Colella, Stefano Irno Consalvo, Luigi Patrono and Claudia Rollo (University

of Salento, Italy); Alfredo Salvatore (Sensor ID, Italy); Ilaria Sergi(University of Salento, Italy)

Waste management is one of the basic and fundamental services provided by municipal authorities

and it is also one of the most expensive services. Although progress has been made in recent years,

much still needs to be done to make this service as efficient as possible and to increase citizens'

collaboration in the process of separate waste collection. In this paper, a waste management system

is proposed mainly based on the use of an innovative Radio Frequency Identification tag equipped

with low-cost sensors and a cloud-based software system able to manage and extract important

information from the collected data. This information will be displayed by several users (citizens,

municipal authorities, waste companies) in form of web dashboard and used to improve the waste

management process.

An Innovative Smart System based on IoT Technologies for Fire and Danger Situations

Giorgio Cavalera (Cavalera srl, Italy); Roberto Conterosito and Vincenzo Lacasa (ITS, Italy); Marina

Mongiello (Politecnico di Bari, Italy); Francesco Nocera (Politecnico of Bari, Italy); Luigi

Patrono and Ilaria Sergi (University of Salento, Italy)

The SAFETY project aims to create a system able to support rescuers such as Fire Brigade in presence

of danger events, especially when they have to intervene in large buildings with many floors and

rooms, with different access points, and with numerous users. In these cases, in fact, it is very

important to provide a smart decision support system able to promptly guide rescuers to the critical

points of the building where there is the certainty that there are users to be rescued or artworks to

be kept safe, without wasting resources. In order to achieve this goal, an innovative system

architecture based on the use of technologies enabling the Internet of Things including sensors,

mobile devices, Cloud technologies, mobile Apps, and embedded devices have been designed and

developed in the SAFETY project.

S9: Energy-Batteries

Room: KORČULA

Electrochemical Activation of Mn3O4 (Hausmannite) for a Rechargeable Aqueous Zn/Mn- Oxide

Battery for Energy Storage Applications

David Wilkinson, Arman Bonakdarpour, Ivan Stosevski and Sharon Ting Voon (University of British

Columbia, Canada)

Aqueous zinc/manganese dioxide batteries are excellent candidates for stationary energy storage

applications due to several advantages, including low cost, the earth-abundance of Zn and Mn-

oxides, high theoretical volumetric and specific capacity. The hausmannite phase of manganese oxide

(Mn3O4) has been studied for rechargeable near-neutral (2 MZnSO4) zinc-manganese oxide battery

applications. Electrochemical investigation in coin cell hardware reveals that Mn3O4 activation

occurs during the initial 45 cycles, after which maximum capacity was achieved. More than 65% of its

maximum capacity was retained for more than 800 charge/discharge cycles showing excellent

reversibility of the material. XRD analysis shows no phase change of Mn3O4 during the cycling.

Formation of layered double hydroxide (Zn4SO4(OH)6·xH2O) was observed at the surface of Mn3O4

by XRD, XPS and ICP-OES which forms probably as consequence of pH increase due to a proton

intercalation.

Model-based internal short circuit detection of lithium-ion batteries using standard charge profiles

Minhwan Seo (Pohang University of Science and Technology (POSTECH), Korea); Minjun

Park (POSTECH, Korea); Youngbin Song (Pohang University of Science and Technology (POSTECH),

Korea); Sang Woo Kim (POSTECH, Korea)

As a latent risk, soft internal short circuit (ISCr) occured in lithium-ion batteries may cause thermal

runaway with fire and explosion. To secure battery safety for users, detection of soft ISCr is

important. However, ISCr detection of existing model-based methods is totally dependent on type of

load currents. Therefore, the ISCr must be detected with standard charge profiles instead of

particular load currents, which are measured with high sampling rate and have big fluctuations. In

this paper, using constant currents and terminal voltages for charge of the battery, a model-based

ISCr detection algorithm is proposed. Equivalent circuit model of the battery is used to estimate ISCr

resistance as a fault index. The proposed method is verified in simulations for varied ISCr faults.

Accuracy of the estimated ISCr resistances is above 93.37%, thereby leading to early detection of the

ISCr.

Improved SOC estimation of lithium-ion batteries with novel SOC-OCV curve estimation method

using equivalent circuit model

Youngbin Song (Pohang University of Science and Technology (POSTECH), Korea); Minjun

Park (POSTECH, Korea); Minhwan Seo (Pohang University of Science and Technology (POSTECH),

Korea); Sang Woo Kim (POSTECH, Korea)

The OCV-SOC curve is commonly used in SOC estimation and other battery management system

(BMS) applications. Since the OCV indicates the magnitude of the charged battery voltage, the differs

between estimated OCV-SOC curve and actual OCV-SOC curve are directly reflected in the accuracy

of the SOC estimation and terminal voltage of model simulation. Thus, accurate OCVs are very

needed but it is hard to obtain the suitable OCV-SOC curve for various current conditions.

Furthermore, preliminary experiments for obtaining OCV-SOC curve spend lots of time due to

repeats of the constant current discharge and taking enough rest time. In this paper, the new OCV-

SOC curve estimation method is proposed to improve the accuracy of estimated SOCs and simulated

terminal voltages of battery model without preliminary experiments. The proposed method uses

equivalent circuit model (ECM) with parameter identification of recursive least square (RLS)

algorithm, and is verified by experiments of various current conditions. Using the estimated OCV-SOC

curve of proposed method, model accuracy is improved with lowered RMSE of simulated ECM

terminal voltage and the SOCs were estimated less than 2% error.

Wednesday, June 19

Wednesday, June 19 8:30 - 10:00

S10: Smart Cities-Building Monitoring and Intelligence

Room: HVAR

Assessment of Building Intelligence Requirements for Real Time Performance Testing in Smart

Buildings

Elena Markoska (SDU, Denmark); Nebojsa Jakica, Sanja Lazarova-Molnar and Mikkel Kragh (University

of Southern Denmark, Denmark)

Buildings contribute with 32% to the world's overall energy consumption. Given documented

discrepancies between the design and operation of buildings, concepts such as continuous

commissioning and performance testing (PTing) have emerged. To increase the applicability and

customizability of real-time performance monitoring, performance testing frameworks utilize

metadata schemas and generic libraries of tests. However, real-time PTing requires enhanced

instrumentation in the building, such as meters and sensors. Considering the usage and age of

buildings, different buildings might impose more stringent requirements for sensing equipment in

terms of applicability of PTing. Prior work establishes a framework for automatic discovery of

performance tests, and their continuous execution without human intervention. In this paper, we

provide an algorithm automatic estimation of the Smart Readiness Indicator (SRI), which is a metric

for measuring the technological readiness of a building proposed by the European Commission. In

line with our PTing framework, we estimate a minimal SRI for PTing (PT-SRI) to be 23%, implying high

applicability across a variety of buildings. We evaluate a case study building for its SRI and perform

sensitivity analyses of the SRI specific requirements against the PT-SRI.

Structural health continuous monitoring of buildings - A modal parameters identification system

Mirco Muttillo, Luca Di Battista and Tullio de Rubeis (University of L'Aquila, Italy); Iole Nardi (ENEA

Casaccia Research Center, Italy)

Monitoring systems play a key role in maintaining the buildings' structural health. Although in the

last decades the structural monitoring has experienced a considerable growth, the monitoring

systems still require remarkable installation efforts and significant costs. Due to these disadvantages,

the spread of such systems was scarce, and the duration of experimental phases was often short. The

aim of this work is the design of a Structural Health Monitoring (SHM) system to continuously

monitor and check the structural behavior throughout the buildings' lifespan. The system, made up

of a customized datalogger and slave devices, allows the continuous monitoring of structures'

acceleration thanks to its ease of installation and low cost. The proposed system is mainly based on a

microcontroller that: i) communicates with the nodes via RS485 bus, ii) synchronizes the acquisition

samples, iii) acquires the data measured by the nodes. The system was tested on a cantilever

aluminum structure, through three different experimental campaigns and the measured data,

collected in an internal memory of the datalogger, were post-processed via Matlab algorithm. The

results allowed to evaluate the modal parameters (frequencies, damping and modal shapes) of the

analyzed structure and its health.

Distributed Intelligent Illumination Control in the Context of Probabilistic Graphical Models

Mirsad Cosovic, Tijana Devaja and Dragana Bajovic (University of Novi Sad, Serbia); Juraj

Machaj (University of Zilina, Slovakia); Graeme McCutcheon (Ramboll UK, Glasgow, United Kingdom

(Great Britain)); Vladimir Stankovic and Lina Stankovic (University of Strathclyde, United Kingdom

(Great Britain)); Dejan Vukobratovid (University of Novi Sad, Serbia)

Lighting systems based on light-emitting diodes (LEDs) possess many benefits over their incandescent

counterparts including longer lifespans, lower energy costs, better quality of light and no toxic

elements, all without sacrificing consumer satisfaction. Their lifespan is not affected by switching

frequency allowing for better illumination control and system efficiency. In this paper, we present a

fully distributed energy-saving illumination control strategy for the arrangements of a lighting

network which consists of a group of LEDs and user-associated devices. All LEDs have a dimming

feature in order to meet the illumination requirements of every user. In order to solve the

optimization problem, we are using a distributed approach that utilizes factor graphs and the belief

propagation algorithm. Using probabilistic graphical models to represent and solve the system model

provides for a natural description of the problem structure, where user devices and LED controllers

exchange data via line-of-sight communication.

S11: eHealth-HW and SW

Room: ŠOLTA

EpiSense: Towards a smart solution for epileptic patients' care

May El Barachi (University of Wollongong Dubai, United Arab Emirates); Farhad

Oroumchian (University of Wollongong in Dubai, Iran); Rabia Rauf, Uroosa Khan, Beschier Al

Hassooni, Alexander Al Basosi and Shaza Kazia (University of Wollongong in Dubai, United Arab

Emirates)

Epilepsy is a chronic neurological brain disorder that affects 50 million people globally. There are

several challenges associated with the care of epileptic patients, including: 1) the timely and accurate

diagnosis of the condition; 2) the long-term non-intrusive monitoring and detection of epileptic

seizures in real time for suitable interventions; 3) alleviating the mental health issues associated with

epilepsy, such as anxiety and depression; and 4) the lack of availability of large scale datasets related

to epileptic patients with different profiles, needed to advance research in epilepsy. In this work, we

propose EpiSense - a smart healthcare solution for epileptic patients' care. EpiSense leverages

sensory, mobile, and web technologies, as well as machine learning techniques for the real-time

detection of epileptic seizures. As part of the system, a patient's mobile app. is provided to allow the

detection of seizures' occurrence in real time and the sending of alarm notifications to care takers,

for appropriate actions. Moreover, a web portal enables doctors to view the progress of their

patients and get notified about seizures' occurrence and statistics. The EpiSense system was

designed and implemented, and three machine learning models were tested for real-time epileptic

seizure detection. This work gives interesting insights about the possibility of using sensory

technologies and data analytics for the improvement of epileptic patients' care, and offers the

possibility of personalized healthcare management.

An mHealth application for female fertility assistance

Mitko Shopov and Irina Kakanakova (Technical University of Sofia, Bulgaria); Nikolay R

Kakanakov (Technical University of Sofia Branch Plovdiv, Bulgaria); Borislav Mateev(University of

Plovdiv, Bulgaria)

The paper presents an mHealth solution aimed at assisting the communication, medical procedures

and decision making of patients and specialists in the field of fertility and female health as a general.

The solution consists of server-side cloud-based services (fHealth services) and two client-side

Android applications - for patients (fHealth Patient App) and for medical personnel (fHealth Doctor

App). The server-side is implemented on several Virtual Machines with load balancer and includes

two data storage components - NoSQL for internal application data (e.g. user profiles, messages,

events, etc.) and time-series for sensor data and continuous measurements. A use-case for ovulation

detection from collected body temperature measurements in the field of female fertility is proposed.

The use-case discuss the use of data mining techniques for pattern extraction from data series with

low accuracy measurements and data gaps.

OSA patient monitoring system based on the Internet of Things framework

Liangming Cai (PHD & Zhicheng College, USA); Minchen Zhu (Fuzhou University, P.R. China); Jinping

Jiang (College of Electrical Engineering & Automation, P.R. China); Min Du (Fu zhou University, P.R.

China); Danhong Zhu and Haiyan Jiang (Fuzhou University, P.R. China); Jiefeng Huang (Fujian Medical

University, P.R. China); Rituparna Datta(University of South Alabama, USA); Weimin Lin (Xiamen

University of Technology, P.R. China); Yurong Li (Fuzhou University, P.R. China); Xin Liu (Fuzhou

University & Zhicheng College, P.R. China); Dong Zhang (School of Computer Fuzhou University,

USA); Jingshan Huang (Fuzhou University, USA)

According to the American Academy of Sleep Medicine (AASM), patients with apnea of 10 seconds or

more , and more than 5 times per hour are Confirmed diagnosis with sleep disorders. The current

gold standard for detecting this person with sleep disorder is Polysomnography (PSG). But more than

80% Obstructive Sleep Apnea(OSA) patients of the Sleep Disorder(SD) have not been detected. The

reason is that the current configuration of PSG is insufficient in more than 2,500 sleep labs in the

United States , and that the lack of manpower of sleep professional technicians who analyze PSG

signal has caused many OSA patients to be diagnosed in a timely and effective manner. In China,

there has been no effective measures to reduce the risk even after OSA patients have been

diagnosed. Current medical treatments are either surgical or a lifelong Continuous positive dual

channel air pressure ventilator(CPAP). Another way to get patients with normal Body Mass

Index(BMI), but the patients is always not to return to the normal BMI index because the patient's

perseverance is insufficient , so the method can not achieve the goal of reducing SD. Domestic

research shows that OSA patients have poor sleep at night and sleepiness during the day. It often

results in inefficient work and causes many traffic accidents. Therefore, how to take effective

monitoring measures for these already diagnosed OSA patients has become an urgent problem to be

solved. This paper extracts an interactive monitoring system for patients with OSA based on the

Internet of Things(IoT) framework. It can reduce the timely rescue of OSA patients when they are in

danger in field operations. At the same time, through the interactive function of this indicator mark,

the anxiety during the waiting process can be reduced. It is also convenient for the peers to report

the progress of the patient in time. The specific method is to use the existing IoT framework. The IoT

data acquisition layer uses wearable sensors to collect vital signs of patients, with emphasis on ECG

and SpO2 signals. The network layer transmits the collected physiological signals to the Beidou

indicator using the Bluetooth Low Energy (BLE) protocol. The platform layer adopts the mature

rescue interaction platform of Beidou. The previous GPS indicator has no short message function,

and the patient can only passively wait for rescue. Positional standard is improved through Beidou

model, the short message interaction function has been added. Then the patient can report the

progress of the disease in time while waiting for the rescue. After our simulation test, the

effectiveness of the OSA patient rescue monitoring system based on the IoT framework has been

greatly improved, especially in outdoor work, when the mobile phone signal coverage is relatively

weak. The short message function added by the Beidou indicator can be used to provide timely

progress of the patient's condition, and provide a data support for the medical rescue team to

provide a more accurate rescue plan. After a comparative trial, the rescue rate of the OSA patients

with the detection device of this article increased by 10 percentage points compared with the rescue

rate with only GPS satellite phones.

Using Miniature Thermoelectric Generators for Wearable Energy Harvesting

Jaroslav Vondrak (VSB - Technical University of Ostrava, Czech Republic); Martin Schmidt (VSB –

Technical University of Ostrava, Czech Republic); Antonino Proto and Marek Penhaker (VSB -

Technical University of Ostrava, Czech Republic); Jan Jargus (VSB – Technical University of Ostrava,

Czech Republic); Lukas Peter (VSB-Technical University of Ostrava, Czech Republic)

Using thermal energy harvesting from human body has the potential to create wearable self-

powered devices for multitude of purposes. The focus of this work is to prepare a flexible

thermoelectric module prototype, consisting of 8 encapsulated miniature thermoelectric generators,

that can later be used for powering such a device. The first part of the work focuses on measuring

electrical parameters of the single mTEGs and the power output of the whole module while using

various series-parallel configurations. In the second part of the work a measurement on the forearm

is performed to measure typical power output of these configurations in room temperature. Average

power output at rest is 3 μW. The last part of this work is centered around testing two DC/DC step-up

converters, the LTC3108 and EM8900. Only the EM8900 is proven effective at powering an analog

accelerometer with the proposed TEM as the only power source.

S12: Energy-Photovoltaics and Applications I

Room: KORČULA

Innovative Technologies and the Human Factor: The Case of Building Integrated Photovoltaics

Daniel Attoye (United Arab Emirates University, United Arab Emirates); Kheira Anissa Tabet

Aoul (UAEU, United Arab Emirates); Ola Mosameh (United Arab Emirates University, United Arab

Emirates)

The integration of renewable energy in buildings and cities using innovative technologies significantly

addresses the limitations of conventional technologies, providing multiple benefits to users. These

may be environmental, economic, social, or design related. Cities and buildings with innovative

technologies however have a certain limitation: the human factor. Existing literature shows that

innovative technologies have an array of adoption barriers, and the public's perception, awareness

and knowledge of benefits is one of the most significant. This investigation focuses on Building

Integrated Photovoltaics (BIPV) as an example of innovative technology and addresses this specific

human dimension. The approach embodies the design and decision support process for the

integration of photovoltaics in building design. The research design involves a two-stage approach;

first a review of various innovative building structures and secondly a detailed case investigation on

decision and design for a BIPV prototype. This second stage uses a simplified Analytical Hierarchy

Process (AHP) to guide the user and researcher interaction during the design. The study makes three

novel contributions; firstly, it builds on the theoretical structure of 'diffusion of innovation" to design

an approach towards increased uptake. Secondly, it presents a structured approach for engaging

potential clients, facilitating awareness and promoting market diffusion. Thirdly, it presents

opportunities for further development towards a client -friendly interface adaptable for software

designs and mobile applications. The findings of this on-going investigation can be adopted by

designers, researchers, manufacturers and businesses; towards product development and market

diffusion of innovative technologies.

Study of the evaporation reduction in water basins with floating photovoltaic plants

Fausto Bontempo Scavo (Università degli studi di Catania, Italy); Giuseppe Marco Tina (University of

Catania, Italy); Antonio Gagliano (University of Catania & Italy, Italy); Sandro Nizetic (University of

Split, FESB, Croatia)

Under the general problem of the study about the interaction of floating PV systems (FPVs) in the

water basins where they can be installed, the present study aims to model and to analyze the

evaporative phenomenon of partially covered water basins. Some numerical models, taken from

literature, about water evaporation are implemented in such a way to quantify the level of daily

evaporation. The input of these models are the hourly environmental variables (global irradiance,

ambient temperature, wind speed) whereas the main parameter is the percentage of the water basin

covered by a FPV plant. The floating PV array can have different features (e.g. different floating

structures, different geometry of the deployment of the PV modules) that determine a different

impact on the water evaporation, especially on the energy balance of the covered part of the basin.

The results of the study show that by covering only 10% of water surface it is possible to reduce

evaporation from 6 to 18%.

Maximum power output performance modeling of solar photovoltaic modules

Bilal Taghezouit (Centre de Développement des Energies Renouvelables, Algeria)

The aim of this work is to present the results of maximum power performance measurements of PV

modules of the first grid-connected PV system installed at Centre de Développement des Energies

Renouvelables (CDER), working since June 2004. The analysis has shown that all the PV modules are

producing power, but less than rated value. In our case, two mathematical models have been used in

order to determine the maximum power output Pmax delivered by the PV module as functions of the

solar irradiance intensity and the PV-module temperature. Note that PVWATTS model is simpler than

the second one.

An Approach to Adaptive Protection Scheme for a PV Generator Based Microgrid

Manjeet Singh (Thapar Institute of Engineering and Technology, India); Satripleen Kaur (Siemens

Limited, India); Prasenjit Basak (Thapar Institute of Engineering and Technology, India)

This paper presents operation of photovoltaic (PV) generator based microgrid to analyze fault

characteristics under islanded and grid connected modes of operation. Line-Line-Line (LLL) faults are

simulated both in islanded and grid connected modes using Matlab/Simulink software. The

waveforms of fault current attributes in each mode are detected. The simulation results show that

different modes of microgrid operation contribute to the fault current with different levels. The

necessity to have adaptive protection schemes for PV based microgrid structures is revealed from the

attributes of the fault characteristics. Accordingly, a suitable protection scheme that capable of

sensing different modes of operation of PV based microgrid is proposed to facilitate adaptive

protection for the microgrid model.

S19: Engineering Modelling I

Room: BRAČ

RFID Sensing System Based on UHF Platform-Tolerant Antenna for Harsh Industrial Environments

Luca Catarinucci and Riccardo Colella (University of Salento, Italy); Neven Ruskovid (Spica Sustavi doo,

Croatia); Benedetta Chiffi (University of Salento, Italy)

In this paper, an UHF RFID sensor tag suitable for cold-chain applications is presented. The purpose

of this RFID tag, developed in the framework of a TETRAMAX technology transfer project, is to

provide both tracking and temperature monitoring of fresh and frozen fish. More in detail, the

temperature monitoring is based on a temperature sensor integrated into the used RFID chip, the

EM4325. When temperature exceeds a certain threshold, a LED turns on. In order to operate also

with the presence of ice, platform-tolerant tag antenna has been designed. The proposed device is a

semi-passive tag that includes a PIFA-type antenna matched with the EM4325 RFID chip, an

additional MCU and a LED. For the platform design and simulation, CST Microwave Studio is used.

Obtained results demonstrate the tag tolerance to the background material even in case of ice and

metal.

Control of Electric Power Steering System - OpenModelica Simulation

Damir Sedlar (University of Split, Croatia); Bruno Boban (FESB - Split, Croatia)

As the automotive industry is evolving, Electric Power Assisted Steering (EPAS) system presents a

great step forward in comparison to classical systems. Electric assist motor is the main part of an

EPAS. This paper discusses methods used for control improvement as seen through Pfeffer model.

Boost curve algorithm and PID controller influence the amount of current given to the assist motor.

The results have shown that additional tuning can be made using PID controller which is important

when optimizing settings for various conditions.

Steady state analysis and modeling of the gas metering and pressure reduction station using the

electrical analogy

Danko Vidovid (Energy Institute Hrvoje Požar, Croatia); Elis Sutlovid and Matislav Majstrovid (Faculty

of Electrical Engineering, Mechanical Engineering and Naval Architecture, Croatia)

The existing interdependencies between electric power and natural gas networks are getting

stronger with the increased penetration of renewable energy sources (RES), and should be

considered at both the operational and the planning stage. A powerful simulation model based on an

equivalent electrical model of the whole multi-energy system allows simultaneous analysis of these

two connected networks in one simulation environment. In this study, the behavior of an ideal, as

well as a real natural gas metering and pressure reduction station (MRS), has been analyzed and

electric analogy steady state models (i.e. models with electric circuit elements) are given. The

verification of the presented model is obtained by 24 examples carried out to cover a wide range of

input data, and the simulation results are compared with the results obtained by SIMONE - the

commercial software package for gas network simulation that is widely used in Europe. The results

have shown a very high precision of the presented model and confirmed the proposed modeling

principles, as well as the approach to modeling gas network elements in the electrical analogy.

Nonlinear dynamics quarter car model and response to road excitation

Antonio Vladislavic, Željan Lozina and Damir Sedlar (University of Split, Croatia)

In this paper a plane mechanism of double arm suspension is developed and implemented in order to

analyze road response. It is used for calibration of the corresponding OpenModelica suspension

model in energy harvesting potential evaluation.

Parameter identification for anisotropic Yld2000-2d stress function under non-associated flow rule

Maja Džoja (University of Split & The Faculty of Electrical Engineering, Mechanical Engineering and

Naval Architecture, Croatia); Vedrana Cvitanid (University of Split, Croatia)

In the present paper, widely used orthotropic Yld2000-2d stress function under non-associated flow

rule is applied to the aluminum alloy 5754-H22 sheet. Non-associated formulation based on Yld2000-

2d stress function contains sixteen anisotropy parameters that can be determined using selected

experimental data by an error minimization technique. Such formulation, with parameters calculated

by standard approach, might result in excellent predictions of uniaxial plastic material behavior, but

in unacceptable predictions of some complex sheet metal forming processes. Motivated by these

observations, in this paper, additional interventions are introduced into the parameter identification

procedure for the considered formulation applied to AA5754-H22 sheet.

Wednesday, June 19 10:00 - 11:00

PS: Poster session

An innovative approach to the damage mechanisms identification methodology for pressure

equipment

Vladimir Pilid (University of Novi Sad, Serbia); Daniel Baloš (Materialprüfungsanstalt,

Germany); Višnja Mihajlovid, Aleksandar Andjelkovic and Damir Đakovid (University of Novi Sad,

Serbia)

Implementation of the methodology for quantitative risk analysis, usually based on RBI (Risk Based

Inspection), is heavily influenced with the methods for damage mechanisms identification. Same

analysis may give various results depending on the adopted operating parameters in a given time.

The question arises as to whether such an analysis and the results of the analysis may represent

initial data for some subsequent analysis that can be carried out in the following period, regardless of

the reasons for the implementation. The aim of this paper is to demonstrate application of a

modified methodology for damage mechanism identification. The extension of well-known

methodology shown in ASME PCC 3 standard is in the manner in which the damage mechanisms are

identified: distinction will be made from active and passive (potential) damage mechanisms, and as

well as documentation of conditions under which passive damage mechanisms can become active.

Concept of barriers will also be presented.

Heating of domestic hot water in hotels using heat from grey wastewater

Aleksandar Andjelkovic (University of Novi Sad, Serbia); Danijel Todorovid (Energy Net,

Serbia); Mladen Tomid (University of Novi Sad, Faculty of Technical Sciences, Serbia)

In this paper it is described system and shown method for dimensioning of the system for heating

domestic hot water (DHW) in hotels using heat from grey wastewater as a heat source, that is

collected from hotel rooms and apartments, and rainwater. Water is heating using heat pumps. Also,

it was carried out techno-economic analysis between the mentioned system, a system that uses gas

boilers as only heat source and system with solar plate collectors supported by the gas boiler.

Biowaste management and potential for biomethane production through public involvement: A

case study City of Zagreb

Neven Voda (University of Zagreb Faculty of Agriculture, Croatia); Bojan Ribid (Zagreb Holding,

Croatia)

The improvement of waste management systems is one of the main challenges for most EU member

states, and it should be done in line with current legal obligations set in different EU directives. One

of the most important is decrease of landfilling and increase of separately collected waste fractions.

The implementation of sustainable waste management in the City of Zagreb should be performed

through the introduction of source-separation of biowaste, and its utilization as a feedstock for

biomethane production. Produced biomethane will be distributed by dedicated network of filling

stations within the City area. The main objective of this paper is presentation of environmental and

economic benefits of proposed approach and citizen's involvement in separate collection of biowaste

from households. In this sense, a survey has been conducted among residents in order to assess their

behaviours regarding the separate collection of waste fractions. The main motivation is the reduction

of waste fee, creation of new jobs, stimulation of local economy and biofuel production. Final result

of this analysis is the fact that citizens are motivated to participate in biowaste separation, and only

minor percentage are unwilling to participate due to the lack of space or potential odours.

Experimental Investigation of Dynamic Performance of PEM Fuel Cell using a Segmented Single-cell

Željko Penga (University of Split, Faculty of Elect. Eng., Mech. Eng. and Naval Arch); Gojmir

Radica (University of Split, FESB, Croatia); Ivan Tolj (University of Split, Faculty of Elect. Eng., Mech.

Eng. and Naval Arch., Croatia); Frano Barbir (University of Split, FESB, Croatia)

Dynamic testing of proton exchange membrane (PEM) fuel cells is gaining momentum due to

development of stacks for automotive applications and the requirement for reducing the size of the

battery packs in automobiles and the necessity to develop a robust control strategies. Start/stop

procedures and ramp-ups and downs are especially significant for the performance of the cell due to

the occurrence of undesirable phenomena resulting in exacerbated cell degradation. Five-segment

PEM fuel cell, single-cell, is used for experimental investigation of dynamic performance of the cell.

The cell is subjected to dynamic current and potential ramps and subjected to New European Drive

Cycle (NEDC) test protocol. The performance is investigated using dry/partially humidified and fully

humidified reactants. The results of the analyses indicate that the operation with dry and partially

humidified reactants is primarily influenced by the duration of the holds and consequently results in

different polarization curves and occurrence of pronounced hysteresis during forward and backward

polarization curve recording.

Wednesday, June 19 14:30 - 16:00

S13: Smart Cities-Communications and Coding

Room: HVAR

LBCN: Load Balancing based on Congestion Notification in CRAN Networks for 5G Transport

Man Zhang and Lingge Jiang (Shanghai Jiao Tong University, P.R. China); Chen He (Shanghai Jiaotong

University, P.R. China); Di He (Shanghai Jiao Tong University, P.R. China); Ping Li (Huawei

Technologies Co., Ltd., P.R. China)

The progress of modern smart cities has put more requirement on the development of mobile

communication, especially the fifth generation (5G) network. Cloud Radio Access Network (CRAN) is

an emerging network architecture designed to deal with the bursty and massive 5G traffic. In CRAN

networks, where multipath is often the case, an efficient load balancing algorithm is needed to

spread load among the links, to provide users promised quality of service (QoS). In the application of

5G communications such as smart cities, the delay of packets and flow completion time (FCT) are

highly concerned because QoS is closely allied to these metrics. We propose a load balancing

algorithm named LBCN, using two waterlines of buffer occupancy to detect congestion and taking

both local and neighbor buffer congestion information into consideration. We simulate LBCN in a 3-

tier Clos network. Simulation results shows that our algorithm achieves similar performance to

CONGA, shorten the FCT of large flows with low priority, which is a main data source in 5G traffic. It

also proves that LBCN balances the utilization of out ports better than ECMP and CONGA.

Improved Segmented SC-Flip Decoding of Polar Codes Based on Gaussian Approximation

Ying Fang, Jianping Li and Yansong Lv (Communication University of China, P.R. China)

Compared to Successive Cancellation (SC) decoding algorithm, Successive Cancellation Flip (SCF)

decoding algorithm keep the same average computational complexity at high SNR while improving

performance. To correct more errors, Partitioned Successive Cancellation Flip (PSCF) decoding

algorithm is subsequently proposed with lower computational complexity than SCF decoding

algorithm. In this paper, we propose an improved segmented SC-Flip (SSCF) decoding algorithm,

which divide the codeword through Gaussian approximation of calculating the error probability of

each bit channel. Simulation results show that this segmented approach can achieve 48.66% average

complexity reduction at SNR of 0.5 dB for (1024, 512) polar code, and better performance compared

to PSCF decoding algorithm.

Scalable Code with Locality and Availability for Information Repair in Data Centres

Peter Farkaš (Slovak University of Technology & Pan-European University, Slovakia)

In this paper one new scalable code with locality and availability for information repair in cloud data

storage is presented. The construction of these codes is based on graph of [7, 3, 4] Simplex code. The

code could be prolonged indefinitely by adding a set of four nodes in each incrementation from

which one contains information and the three other contain redundancy. The computational

complexity and communications costs of each incrementation are constant and very modest.

SEDCA: Self-Error Detecting and Correcting Algorithm for Accurate Occupancy Tracking using a

Wireless Sensor Network

Changmin Lee and Duckhee Lee (Korea Railroad Research Institute, Korea)

For variety of smart building applications, the accurate occupancy counting is one of the most

important factors. This is because that becomes the basic information. Most of applications for

building have been operated based in their occupancy. So, many researchers have been trying to

discover reliable occupancy counting system. But, most of their studies are focused on the device

error caused by sensors and counting algorithm, like machine learning. But, we are focusing to the

accumulated errors of the system. According to the operating time, the accumulated error problem

becomes more serious continuously. To solve this problem, we propose a Self-Error Detecting and

Correcting Algorithm (SEDCA), consists of a Self-Error Detecting Algorithm (SEDA) and Self Error

Correcting algorithm (SECA). Using information sharing in wireless network, all of the devices

counting persons transfer the counting information to other neighbor devices and receive them.

Based on this property of wireless network, a SEDCA would detect end correct the counting error. In

order to poof our proposed algorithm, we consisted an experimental environment with Passive RFID

counters in our testbed. The results of a testbed experiment, we would reduce the accumulated

error problem of occupancy counting.

Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate

Jonatan Lerga (University of Rijeka & Faculty of Engineering, Croatia); Nicoletta Saulig (University of

Pula, Croatia); Martina Žuškin (University of Rijeka, Faculty of Maritime Studies, Croatia); Ante

Panjkota (University of Zadar, Croatia)

This paper presents study on denoising accuracy of adaptive temporal filtering methods based on the

intersection of confidence intervals (ICI) rule and relative intersection of confidence intervals (RICI)

rule with regards to signal sampling rate. The original ICI-based and the improved RICI-based method

were tested on four signal classes for a range of signal to noise ratios (SNRs). Denoising accuracy,

with respect to signal sampling rate, was measured in terms of the reductions in root mean squared

error (RMSE) and mean absolute error (MAE). Extensive simulations showed that the data-driven RICI

method outperformed the original ICI method reducing the RSME by up 79.6% and the MAE by up to

86.1%. It is important to note that both methods, especially the RICI method, exhibit significant

estimation accuracy improvement in case of signals with higher sampling rates.

S14: eHealth-Effectiveness Studies

Room: ŠOLTA

Gender differences in environment evaluation for office building

Tamara Bajc (University of Belgrade Faculty of Mechanical Engineering, Serbia); Stefan

Milanovid (Faculty of Mechanical Engineering University of Belgrade, Serbia)

Paper deals with an analysis of differences between the male and female responses regarding

thermal comfort, noise and lighting level and indoor air quality in offices. The research was done in

Belgrade, Serbia, for office building in a period from March to Jun 2018. Measurements for outdoor

and indoor air parameters were done, together with the statistical survey of occupants. The results

showed the significant differences in responses between male and women for the same state of the

environment. It is noticed that men were more sensitive to the higher temperatures, preferring

colder working environment, while women stated to feel more comfortable in slightly warmer

environment. Study also showed that men were more tolerant to noise, while women were more

sensitive to poor air quality.

Conventional vs. Digital dental impression: practitioner's and patient's perspective-a pilot study

Danijela Kalibovic Govorko and Benjamin Benzon (University of Split, School of Medicine,

Croatia); Antonija Jurela (Fiziodent Polyclinic, Zagreb, Croatia); Gordana Paid Karega, Ivna Vukovid

Kekez, Dora Mimica, Ivana Medvedec Mikid, Livia Cigid and Katarina Vukojevic (University of Split,

School of Medicine, Croatia)

Dental cast is an indispensable part of a routine diagnostic and therapeutic procedure. Conventional

impression materials, e.g. alginate and polyvinyl siloxane are used for capturing intraoral details and

subsequent dental casts pouring. Intraoral scanners (IOS) were introduced in dentistry in the early

1980s and became a valid alternative to those procedures. IOS are fast, accurate and more pleasant

for a patient than conventional impression techniques, making necessary introducing that technique

in Dental School's curriculum. Eighteen dental students and recent graduates performed both

techniques on each other and filled two two-part questionnaires (from patient's and practitioner's

perspective; before and after impression-taking) to reveal their preferences and expectations from

both techniques. The results showed a statistically significant difference in time needed for digital

and conventional impression, with digital being faster. After the scanning, all participants answered

that digital impression technique would spare more time in their office. Majority of participants

thought that digital techniques would completely replace conventional techniques during their

lifetime and that attitude hasn't changed afterwards. Results of this pilot study showed participants'

inclination towards new impression techniques and need for their implementation in Dental School's

curriculum.

Effect of Invisible Exertions on Computed Tomography Radiologists in Saudi Hospitals

Saad Aldoihi (ENSTA & King Abdulaziz City for Sciences and Technology (KACST), France); Omar

Hammami (ENSTA ParisTech, France)

Current radiology practices are extremely resources pressured and demanding multidimensional

requirements where the technicians are at the center of the constant notion of thriving optimal

productivity and optimization with minimal resources possible. The aim of this paper is to evaluate

invisible physical and mental exertions resulted from operating computed tomography scan. Fifty-

seven CT technicians were surveyed to examine and evaluate the impact of invisible physical and

mental exertion under current radiology practices. Demographic characteristics were examined to

evaluate differences across the study variables. The study deducts the difference among the study

variables based on gender, level of education, years of experience, and working sector.

User Experience Evaluation of the REEFOCUS ADHD Management Gaming System

Stelios C. A. Thomopoulos, Tasos Kanellos and Adam Doulgerakis (NCSR Demokritos, Greece); Eftichia

Georgiou (Institute of Informatics & Telecommunications, NCSR Demokritos, Greece); Maria

Bessa (NCSR Demokritos, Greece); Argiro Vatakis (CSRI Cognitive Systems Research Institute,

Greece); Andrea del Val-Guardiola (Hospital Sant Joan de Déu Barcelona, Spain); Jordi

Navarra (Fundació Sant Joan de Déu Institut de Recerca Sant Joan de Déu, Spain)

This paper reports on the findings concerning the user experience evaluation aspects of the

REEFOCUS gaming system based on experiments conducted with intended end-users. REEFOCUS has

been developed in the context of the FocusLocus H2020 project, whose objective was to provide an

innovative game-based intervention programme for assisting children to manage and overcome

ADHD (Attention Deficit and Hyperactivity Disorder) symptoms. The final prototype of the REEFOCUS

gaming system that resulted from research activities in FocusLocus has been deployed and tested in

operational conditions in the context of a pilot study organized by the Sant Joan de Déu Barcelona

Children's Hospital that involved 75 children diagnosed with ADHD, aged 8-14. 64 children used the

REEFOCUS game for a period of 8 weeks and, subsequently, participated in a survey on usability and

user satisfaction. The pilot study experiments indicate that REEFOCUS operated as intended and the

results of the user experience evaluation certify that the REEFOCUS game is acceptable by children,

parents, and clinicians and are encouraging in terms of future adoption of the proposed game-based

intervention.

Trancranial Direct Current Stimulation (tDCS) - The Effectiveness and Technical Parameters of The

Method

Joanna Karolina Budzisz (Wrocław University of Science and Technology, Poland)

The paper describes the tDCS method with regards to the effectiveness of its application, which

depends on the technical conditions adopted during a stimulation. Transcranial constant current

stimulation is a non-invasive, easy and exceptionally available method, however, this does not

transfer into it being effective. It turns out that although stimulation can be conducted quickly and

relatively simply, its effectiveness depends, to a large extent, on the technical parameters of

equipment and the skills of the person who qualifies for, as well as the person who performs the

stimulation. The correctness of using the method depends on the appropriately selected technical

parameters for each case. The work is based on available current literature.

S15: Energy-Photovoltaics and Applications II

Room: KORČULA

Low cost power recovery system for PV plant under partial shading condition

Mirco Muttillo, Tullio de Rubeis and Valeria Annibaldi (University of L'Aquila, Italy)

The spread of photovoltaic systems for clean energy improves the industrial and private sector.

Today, thanks to the cost reduction, photovoltaic systems are becoming widespread. However,

producing the maximum possible power with changing irradiation is a problem, mostly in the partial

shading condition. The aim of this work is to create a low-cost power recovery system for

photovoltaic arrays under partial shading condition using an MPPT search algorithm and balancing

for the photovoltaic system using the "Variable Interleaving DC-DC Converter" (VICDC). Indeed, due

the partial shading which affects and lowers the performance of the photovoltaic system, the output

power is moved to load decreases. Model of a series of photovoltaic panels under partial shading

conditions was implemented on the SIMULINK environment to study its behaviour. The I-V and P-V

characteristics of the simulated system under partial shading conditions are then compared with

those of regular operation. As a second step in the simulation, a boost converter connected to each

panel of the same string has been inserted, as required by the VICDC technique. The results showed

an increase in performance both in efficiency and on the power of the PV system: additionally, the

benefits from an economic, environmental and social point of view, are quantified. Finally, starting

from the data obtained by the simulations, the design of a low cost system for partial shading is

proposed. The device, mounted on each panel, uses wireless protocol to communicate with a

datalogger whose task is the management and storage of data. In particular, the proposed device

monitors the presence of partial shading conditions on the panels for the possible activation of the

VICDC compensation system. The results showed how the use of the proposed system in partial

shading conditions increases the maximum power point by 10.91%.

Updating Algerian Solar Atlas Using MEERA-2 Data Source

Kamel Abdeladim (Centre de Développement des Energies Renouvelables, Algeria)

Knowledge of the potential solar of the region is crucial for sizing different solar systems before their

installation at a particular location. Furthermore, in order to assess solar potential, it is necessary to

have a large network of stations ensuring the measurement of solar radiation. Moreover, this

assessment must take into account the daily and seasonal variations, solar radiation and load profile.

According to its geographical location, Algeria holds one of the highest solar potential in the

Mediterranean basin, as indicated in many studies. Unfortunately, an important lack of data of the

solar global radiation is observed. With a huge area of 2 381 741 km2, it is necessary to have

numerous stations performing radiation measurement in order to quantify in an objective way the

solar potential. Previously, several studies have been conducted dealing solar potential evaluation.

Two solar atlases, based on a statistical approach have been published. In this study, an update of

the Algerian solar atlas is presented. Thus, a solar mapping on the national territory was carried out

based this time on data measured over a period of almost 37 years. In fact MEERA-2 "The Modern-

Era Retrospective Analysis for Research and Applications, Version 2, NASA", were used in this study.

Therefore, solar maps for solar radiation on different tilting planes were plotted thanks to the use of

SURFER® software, through Kriging interpolation method. Furthermore, measured data for five (05)

locations across the country were used in order to make comparison to those given by MERRA-2.

Computational fluid dynamics analysis and design exploration of water-cooled photovoltaics

subjected to various operating conditions

Domagoj Priegl and Mišo Jurčevid (University of Split, FESB, Croatia); Željko Penga (University of Split,

Faculty of FESB, Croatia); Sandro Nizetic (University of Split, FESB, Croatia); Maro Jelid (University of

Dubrovnik, Croatia)

In recent years, investments in the development of renewable energy sources are increasing due to

long-term unsustainability of fossil fuels and their negative impact on the environment. In this

respect, the Sun is the most prominent renewable energy source, while photovoltaics (PV) are the

most popular solar energy harvesting product, i.e. PV-cell absorbs sun arrays as a source of energy to

generate electricity. A small part of solar radiation is converted to electrical energy, with the rest

reflected, transmitted and converted to heat, respectively resulting in heat generation in the PV-

cells. The efficiency of the photovoltaic module decreases due to higher operating temperatures, i.e.

the efficiency can drop up to 0.5% for the one-degree temperature rise in the photovoltaic module.

In order to increase the overall efficiency of the PV module, the active cooling technique is

incorporated. On the back of the photovoltaic, there is a fixed tank through which the water coolant

flows. Three-dimensional computational fluid dynamics (CFD) model for steady-state heat transfer is

developed and tested. This numerical analysis deals with the heat transfer through the PV module

and provides insight into the intensity of heat extraction from the module thanks to the active

cooling system. The developed numerical model predicts output parameters based on three input

parameters that can be varied as desired without triggering CFD simulation. The heat source, the

coolant inlet velocity, and the ambient temperature are the input parameters that are varied while

the coolant inlet temperature is fixed at 290 K. The average PV-cell temperature, the pressure drop

in the tank and the coolant outlet temperature are output parameters. To create a Response Surface,

30 design points are created, each point representing a unique combination of the input parameters.

The predictions of the output parameters are made from the generated Response Surface and

compared to the simulation results for 36 design points. The average deviation of the predictions,

generated from the Response Surface, is less than 1% when compared to the simulation results for

the design points.

An Online Novel Two-Layered Photovoltaic Fault Monitoring Technique Based Upon The Hybrid

Parameters

Qamar Navid (United Arab Emirates University, United Arab Emirates); Ahmad Hassan (UAE

University, United Arab Emirates); Abbas Fardoun (Al Maaref University, Lebanon); Rashad

Ramzan (United Arab Emirates University, United Arab Emirates)

The utility-scale photovoltaic power plants are facing unique challenges compared to the traditional

fossil fuel-based power plant in terms of faults localization, diversity, and frequency. The complex

nature of faults raises serious concerns about grid-connectivity of photovoltaic plants in terms of

operability, power quality, grid stability, and breakdown vulnerability. One of the predominant

problems concerning utility-scale photovoltaic power plants remains in the variety, frequency, and

nature of faults occurring during operation. In this research work, an online novel cost-effective two-

layered fault monitoring scheme is introduced based upon the thermal and electrical signatures. The

proposed scheme is implemented on a 1.6 kW photovoltaic array and various faults (short circuit,

open circuit, and ground fault) are induced in the photovoltaic modules. The scheme shows

promising results in fault monitoring and classification without making any hardware modifications in

the solar module. The proposed scheme is compared and validated through thermography and

results indicates that the proposed fault monitoring scheme can monitor and characterize the faults

effectively compared to traditional means through thermography.

S20: Engineering Modelling II

Room: BRAČ

Simulation of thermal trigger design for crashworthiness structures

Nuno Peixinho (University of Minho, Portugal); Bruno Azevedo (Universidade do Minho, Portugal)

This study presents an alternative approach for the improvement of crash energy absorption in

representative automobile crashworthiness structures. It is studied the introduction of configurable

crush initiators through localized heating in tubular structures. The main objective is to improve the

ability to absorb impact energy in a progressive and controlled manner by a local modification of

material properties. In this manner, associated with the softening of the aluminum alloy, the

deformation can be introduced precisely, forcing the tubular structure to deform in a mode of high

energy absorption and reducing the maximum load in a controlled manner. The application is studied

on a representative geometry using numerical simulation.

Dynamic material properties for numerical modelling of impact behaviour of light-alloy structures

Nuno Peixinho (University of Minho, Portugal); Bruno Azevedo (Universidade do Minho, Portugal)

This study presents tensile testing results for ZE10 magnesium and 6111-T4 aluminum alloys at

different strain rates. For crashworthiness applications an understanding of material behavior at

relevant strain rates is needed as well as constitutive equations suitable for use with numerical

simulation tools. The mechanical properties were determined from tensile test using flat sheet

specimens and recurring to different test techniques: servo-hydraulic machine and a tensile-loading

Hopkinson bar. The results were used to compare different mechanical properties and to validate

constitutive equations intended to provide a mathematical description of strain rate dependence.

The Cowper-Symonds equation was examined.

On the incident power density calculation at 5G frequencies

Dragan Poljak (University of Split, FESB, Croatia); Mario Cvetkovid (University of Split, Croatia)

The 5th generation (5G) mobile communication systems require the use of millimeter-waves, i.e.

these devices communicate in GHz frequency range. Frequency at 3 GHz in IEEEC95.1 standard, same

as frequency at 10 GHz, respectively, represents the transition frequency for local exposure. Instead

of specific absorption rate (SAR) averaged over tissue volume one is supposed to use incident power

density (IPD) averaged over specific area. This paper deals with the analysis of the averaged area for

IPD calculation by using a rather simple geometry of Hertz dipole. A dependence of IPD on the

incident radiated wave angle is studied. An illustrative example is presented at frequency of 3 GHz.

Wave structure functions and spatial coherence radiuses of optical waves propagating in

anisotropic turbulence

Bing Guan and Jaeho Choi (Chonbuk National University, Korea)

Based on the weak fluctuation theory, the new analytic expressions of wave structure function for

plane and spherical waves propagation through anisotropic non-Kolmogorov turbulence in a

horizontal path are derived. Moreover, using the Rytov approximation method, the new expressions

for spatial coherence radius are obtained. Using the new obtained expressions for the spatial

coherent radius, the effects of the power law exponent, and the anisotropic factor are analyzed. The

analytical simulation results show that the wave structure functions are greatly influenced by the

power law exponent α, the anisotropic factor ζ, and the turbulence strength σ~R2 . Moreover, the

spatial coherence radiuses are also significantly affected by the anisotropic factor ζ and the

turbulence strength σ~R2 , while they are gently influenced by the power law exponent α.

Stochastic Boundary-Domain Integral Method for heat transfer simulations

Jure Ravnik (University of Maribor, Faculty of Mechanical Engineering, Slovenia); Anna

Susnjara (University of Split, Croatia); Jan Tibaut (University of Maribor, Slovenia); Dragan

Poljak and Mario Cvetkovid (University of Split, Croatia)

In this paper we couple a numerical method aimed at simulation of flow and heat transfer of

nanofluids with stochastic modelling of input and material parameters. A fast Boundary-Domain

Integral Method has been developed to solve the governing equations and set up the deterministic

flow and heat transfer solver. Furthermore, the Stochastic Collocation Method is used in combination

with the deterministic flow simulation code in order to propagate the uncertainty from input to

output parameters. The developed algorithm is used to simulate natural convection of a nanofluid in

a closed cavity. By simulation of a very large number of cases and by applying the stochastic analysis,

we were able to identify the relative impact of different input parameters. The results reveal that the

uncertainty of input parameters results in more stronger influence in the convection dominated flow

regimes.

S21: Energy-Grids and Machine Learning I

Room: MEET ROOM

PMU Placement with Power Grid Partitioning for Line Outage Detection

Rana Alhalaseh, Halil Alper Tokel, Subhodeep Chakraborty, Gholamreza Alirezaei and Rudolf

Mathar (RWTH Aachen University, Germany)

Fault location detection is an important functionality in distribution power systems. For this matter,

the deployment of sensors and measurement units in power systems play an important role.

Therefore, in our previous work in [1], data- driven approach has been considered for this matter,

where mutual information (MI) based feature selection method has been implemented for phasor

measurement units (PMUs) placement. In [1], the location of a minimum number of PMUs is

optimally identified to achieve a desired fault detection accuracy via a decision tree (DT) based fault

location detector. Using the concept of graph theory, this work presents a splitting method to

virtually partition a grid into several child grids to create sub-zones, and optimally place a PMU in

each sub-zone. Different from other approaches, neither reconfiguring the grid topology, nor

removing lines to perform splitting, which contribute to system faults, are required.

Convolutional Neural Network Based Fault Location Detector for Power Grids

Rana Alhalaseh and Robert Kämmer (RWTH Aachen University, Germany); Nayan Chandra Nath (MS

Student at The Sirindhorn International Thai-German Graduate School of Engineering (TGGS) &

Exchange Master's Thesis Student at RWTH Aachen University, Germany); Halil Alper

Tokel and Rudolf Mathar (RWTH Aachen University, Germany)

Monitoring of power distribution networks for the purpose of identifying system faults has become

more important due to the continuous demands for reliable and sustainable power supply. Several

works are found in literature which focus on optimal placement of sensor units to achieve full

monitoring and observability of power grids. In our previous work [1], a data driven approach has

been introduced to determine the location of measurement units to achieve a desired fault location

detection accuracy. In [1], the location of phasor measurement units (PMUs) has been identified via

several feature selection based measures, and the performance of several machine learning based

detectors has been evaluated. Simulation results have shown that the mutual information (MI)

measure is capable of placing minimum number of PMUs for sufficient grid observability to achieve a

desired detection accuracy using a decision tree (DT) based detector. In this work however, a new

approach in the form of a convolutional neural network (CNN) based detector is introduced, and its

performance is compared to the detectors in [1]. Several benchmark distribution systems are used in

this work in order to evaluate the performance of the fault location detectors.

DSM in Hybrid AC/DC Rooftop PV Integrated Smart Nano Grid

Ali Raza Kalair (Comsats University, Pakistan); Shoaib Rauf and Naeem Abas (University of Gujrat,

Pakistan); Anam Kalair and Qadeer ul Hasan (Comsats University, Pakistan); Nasrullah Khan (Comsats

University & Park Road Islamabad, Pakistan)

Normal time and load slabs based revolving load shedding techniques affect equally all small and

large consumers. Small homes have simple light and fan loads in summer compared to fully air

conditioned posh bungalows. Utility blanket load shedding techniques affect equally low and high

load customers equally. In summer, April to September, domestic air conditioner loads are 46 to 47%

of domestic loads. Utilities certainly want to reduce load on 11kV feeders during peak hours without

punishing small consumers by blanket load shedding. There is no technology in market that can

selectively disconnect large loads and permit small loads. Luxurious suburbs are responsible for large

loads, not the poor consumers. Introduction of smart devices into consumer premises can facilitate

them shutdown themselves by detecting system health conditions. Voltage and frequency of power

system tell the system health condition as temperature and pulse rate tell the health condition of a

patient. Priority based load management is a good alternative to incorporate renewable energy but

not good for live load management. Utility wants to control consumer loads through local smart

circuit breakers or AMI under bottom up approach. Intelligent circuit breakers controlling luxurious,

auxiliary and essential loads can be prioritized to implement the smart grid option yet in an

unsustainable forced manner. A smart load controller may automatically detect system overloading

and use standard HEC-12/ZigBee wireless technologies to switch off luxury loads in multiple story

buildings. If the same idea is implemented by all consumers then demand side load management can

become a living reality. Demand side live line load management can also be accomplished by

advance metering infrastructures (AMI) if manufactured using smart load management functions

inside it that are not available in common AMI meters in market. Presence of live line load controller

in all homes adapt the load according to available utility supply capacities that might need utility

level arrangement.

Stacked Generalization Concept for Electrical Load Prediction

Rania Alhalaseh (Mutah University, Jordan); Khaleel Alhalaseh (American University of Madaba,

Jordan)

Short-term power load forecasting has been widely investigated, as it provides crucial and on-

demand information for power planning and operation. In literature, different statistical and

mathematical methods along with machine learning and data-driven based approaches have been

employed and considered for this matter. In terms of the latter approaches, various benchmark

models are found in literature for electrical load forecasting, such as support vector regression (SVR)

and artificial neural network (ANN). Further steps has been already taken by combining such models

in the form of ensemble learning schemes, in particular bagging and AdaBoost ensembles. Different

from other methods, this paper investigates the stacked generalization ensemble concept where the

electrical load has been analyzed in a time series fashion. The results have been compared with the

individual underlying benchmark models, which have shown that the ensemble scheme outperforms

the individual models. Furthermore, the introduced scheme is rather robust against error

propagation, as the estimated load at a certain future time slot is also utilized to estimate further

slots.

Electric Vehicle Range Anxiety: An Obstacle for the Personal Transportation (R)evolution?

Dario Pevec (University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia); Jurica

Babic (University of Zagreb & Faculty of Electrical Engineering and Computing, Croatia); Arthur

Carvalho (Miami University, Farmer School of Business, USA); Yashar Ghiassi-Farrokhfal (Erasmus

University, Rotterdam School of Management, Canada); Wolfgang Ketter (RSM Erasmus University,

The Netherlands); Vedran Podobnik (University of Zagreb, Faculty of Electrical Engineering and

Computing, Croatia)

Trends in the electromobility industry, increasing research efforts related to alternative fueled

vehicles, as well as growing environmental concerns are suggesting that the transition from the

internal combustion engine technology to electric vehicles (EV) is necessary and inevitable. To ensure

and enable rapid market penetration of EVs, one major obstacle needs to be addressed - range

anxiety, a fear of running out of electricity before reaching another available charging station. This

research employs a survey methodology to assess potential EV owners' perception of range anxiety

with the goal of quantifying and explaining it through key EV parameters: state of charge (i.e., a

relative measure comparing the remaining amount of energy in the EV battery with the maximum

capacity) and remaining range (i.e., how much distance the EV can still reach without re-charging).

Through the survey analysis, we answered two relevant research questions that fall into the range

anxiety research agenda: (i) how potential EV owners perceive the optimal distance between

charging stations in comparison to traditional, well-developed gas station infrastructure; and (ii) how

key EV parameters influence the decision to charge as well as the distance one is willing to travel to

reach another charging station that may or may not be occupied. This research is beneficial for

business makers as the knowledge about range anxiety is very important for making decisions about

charging station placement, as well as for the research community since range anxiety is a variable

that could and should be included in various research areas centered around EVs. Besides business

makers and researchers, this work is beneficial to the society in general as it may potentially have a

positive impact on raising awareness about the necessity of electrification in the transportation

industry.

Thursday, June 20

Thursday, June 20 8:30 - 10:00

S16: Energy-Grids and Machine Learning II

Room: HVAR

Perfomance Evaluation of Institutional Load with Photovoltaic and Battery to Operate it as Micro-

Grid

Arvind Sharma (University of Agder & TERI, Norway); Mohan Kolhe and Nils Ulltveit-Moe (University

of Agder, Norway)

Building integrated solar photovoltaic (PV) can be integrated into a Micro-grid along with other

distributed energy resources. The load analysis with available PV capacity is necessitated for

developing a micro grid system with appropriate sizing of other distributed energy resource. In this

work, a typical institution has been selected, where the PV system and energy storage has been

operating for supplying local demand in coordination with the grid. The institutional load profile has

been analyzed with essential and non-essential loads for understanding the operation and

contributions from the PV and battery energy storage in addition from the grid. Annual institutional

hourly load variations and PV system outputs are analyzed for evaluating the installed battery

performance intended at assessing the charging - discharging patterns, lifetime throughput and

percentage energy contents (EC). The month-wise hourly analysis is also carried out and the two

months scenarios based on PV output with load demand ratio (maximum and minimum) are used for

reporting the battery performance. It is observed that essential loads are fulfilled during grid outage

through batteries, and may affect the institutional load reliability, if the outage hours are higher. It is

noticed that the installed battery energy throughput must be maximized for effective PV utilization.

Results from this work are going to contribute for functioning this institutional installed PV and

battery system with appropriated distributed energy resources to operate it is as a micro-grid.

Load Demand Analysis of Nordic Rural Area with Holiday Resorts for Network Capacity Planning

Nils Jakob Johannesen, Mohan Kolhe and Morten Goodwin (University of Agder, Norway)

Most of the Nordic holiday resorts are in rural area with low capacity distributed network. The rural

area network is weak and needs capacity expansion planning as the load demand of this area are

going to increase due to penetration of electric vehicles and heat pumps. Such type of rural network

can be operated as micro-grid, and for appropriate operation, load analysis is required. The load

analysis will also be useful for finding proper sizing of distributed energy resources including energy

storage. In this work, load demand analysis of a typical Nordic holiday resorts, connected in rural

grid, is presented to find out the load variation during the usage periods. The load analysis is targeted

for demand prediction. In this work the demand forecasting has been considered through integrating

Regression Tools with Artificial Neural Networks for the low amount of data especially characterizing

the Holiday Resorts. Collected data is from a rural area in Norway consisting of 125 holiday cabins,

with maximum load of 478 kW in the period of 2014 to 2018. This work is presenting the analysis on

the total electric load consumption of cabins during typical short and long term holidays. It is

observed, during the longer time holiday period, the loads are significantly higher compared to

shorter time holiday period. Prediction analysis shows the MAPE is relatively higher compare to

prediction results in higher load area. Through analysis, it is observed that the curvature of the

maximum peak demand is unfitting the predictive outcome. To overcome this problem the finite

gradient by autoregression, has been used in this work.

Wide & Deep Machine Learning Model for Transformer Health Analysis

Petar Sarajcev (University of Split, Croatia); Damir Jakus (University of Split & Faculty of Electrical

Engineering, Mechanical Engineering and Naval Architecture, Croatia); Matej Nikolic (University of

Split, Croatia)

Transformer health index (HI) is a powerful tool for quantifying the overall health of a power

transformer, due to the fact that it appraises its condition based on different criteria that are related

(often in complex ways) to the long-term degradation factors that cumulatively lead to its end-of-life.

Several authors have proposed different approaches to the HI calculation, e.g., analytical

expressions, binary logistic regression, fuzzy logic models, support vector machines, and artificial

neural networks. This paper proposes using Bayesian "Wide & Deep" machine learning model for the

HI calculation, where the wide model part is the Bayesian ordered robust "probit" regression, while

the deep part is the Bayesian artificial neural network. Both model parts are trained simultaneously

within the Bayesian setting, using the so-called "joint learning" process with a Markov-chain Monte

Carlo algorithm. Model is demonstrated using the actual transformer data.

Impact of Stray Load and Iron Losses on Vector Control of Small Induction Generators

Matija Bubalo (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,

Split, Croatia); Mateo Bašid (University of Split, FESB, Croatia); Dinko Vukadinovid (Faculty of Electrical

Engineering, Mechanical Engineering and Naval Architecture, Croatia); Ivan Grgid (University of Split,

Croatia)

This paper presents the analysis of detuning induced by the stray load and iron losses in vector-

controlled self-excited induction generators (SEIGs). Previously, the stray load loss impact has been

examined only for induction motors. Detuning in vector-controlled induction machines (IMs) is

caused by a mismatch between the actual IM and the corresponding mathematical model. This

usually implies disagreement between the actual and assumed values of IM parameters or between

the actual and modeled phenomena. The detuning is characterized by a misalignment between the

actual and reference flux vector (i.e., flux angle error) or by a non-unity ratio of actual to reference

flux vector magnitudes (i.e., flux magnitude error). The presented analysis encompasses load torques

up to the rated value and rotor flux values down to 50% of the rated value. For this purpose, an IM

model is utilized in which the stray load and iron losses are modeled as variable with respect to the

operating frequency, flux, and torque. The simulation model of the considered system is built in the

MATLAB-Simulink. Three small IMs (1.5 kW) of different efficiency and rotor material have been

considered.

S17: Energy- Engineering Applications and Modelling

Room: ŠOLTA

Comparison of evaporation models for free water basins surfaces

Giuseppe Marco Tina (University of Catania, Italy); Antonio Gagliano (University of Catania & Italy,

Italy); Fausto Bontempo Scavo (Università degli studi di Catania, Italy)

The assessment of the water evaporation rate (E) is worth of interest in a wide range of frameworks,

such as hydrology, agronomy, forestry and land resources planning. in recent time there is a growing

interest in evaluating the interactions with floating photovoltaic systems. The main objective of this

study is to develop novel numerical models, which allow calculating the E starting from known

environmental variables (e.g. global irradiance, ambient temperature, wind speed, relative humidity).

Thus four distinct numerical models, which are based on 2, 3 or 4 of the above-mentioned variables,

have been obtained through the use of both the (Design of Experiments) DoE and linear regression

method. The daily evaporation calculated by the novel numerical models has been compared to

several existing literature model, as well as with experimental data for evaluating the accuracy of the

proposed model. These comparisons, performed through statistical indices, highlight that the

prediction of the proposed model has an accuracy better than many existing literature models. In the

light of the obtained results, the proposed model could represent useful tools that require a simple

implementation to quantify rather quickly the evaporation rate of a basin in which PV floating

systems are installed.

Investigation of Effect of Window-to-Wall Ratio on the Indoor Air Temperature by Lumped

Capacitance Approach

Ahmet Yuksel (Yalova University, Turkey); Muslum Arici and Hasan Karabay (Kocaeli University,

Turkey)

In this study, the effect of window-to-wall ratio of a residential building is evaluated for different

internal volumes of a by lumped capacitance approach. The computations are carried out for

different window-to-wall ratios varying from 0% to 100%, internal volumes (namely, 45m3, 75m3 and

105m3) and insulation material thicknesses varying from 10mm to 30mm. The influence of the

considered parameters on the indoor temperature of the room having a double-pane window is

evaluated together with time lag and decrement factor. Computed results show that the window-to-

wall ratio has a very significant effect on the considered parameters. Time lag increases and

decrement factor decreases with the increase in insulation layer and indoor volume. However, the

most significant parameter is window-to-wall ratio. As the window-to-wall ratio increases, time lag

decreases and decrement factor increases considerably. The effect of insulation layer thickness on

the considered parameters is more profound particularly for low window-to-wall ratio values.

Phase Change Materials to increase the storage potential of solar thermal systems

Elli Kyriaki, Stefanos Stergiopoulos and Agis M. Papadopoulos (Aristotle University of Thessaloniki,

Greece)

Thermal energy storage, is a key issue for the use of solar thermal systems in buildings so that

autonomy of the system is increased and therefore solar thermal systems become a more attractive

solution for buildings. It has therefore been in the focus of research over the past few decades, as it

is an important technology in order to solve the problem of temporal deviation between the

availability of solar energy and the utilization of the heat generated. Thermal storage is crucial in

order to bridge this gap, especially in regions where prolonged periods of reduced sunshine are

common and as a result solar systems are inefficient. Traditionally thermal storage is achieved by

using water, which has been proven to be practical and cost effective, especially when fairly small

storage capacities are required. There are however limits, mainly due to space limitations and

increasing losses, as soon as bigger volumina are needed to extend the storage period. The use of

Phase Change Materials (PCMs), is an upcoming, promising technology, which has drawn the

scientific community's attention for quite some years now. The main idea is to substitute water as a

storage medium, with PCMs, which have larger specific energy storage capacity compared to other

materials. In this paper, a solar thermal system for Domestic Hot Water production and space

heating with either water storage or PCM storage is studied, for two different climate conditions in

Greece.

Influence of TIG shielding gas composition on weld geometry and corrosion properties of titanium

weld joints

Maja Jurica, Ivica Garašid and Zoran Kožuh (Faculty of Mechanical Engineering and Naval

Architecture, Croatia)

This paper presents an experimental study of influence of shielding gas composition on TIG produced

weld bead geometry and its corrosion resistance. Short overview of properties and application of

Titanium was provided in the introduction of the paper. Within the framework of the experimental

work, four bead on plate welds were produced using two different shielding gases and two welding

speeds. Influence of shielding gases was investigated by analysing weld bead geometry and corrosion

resistance testing. Weld bead geometry analysis showed that shielding gas has a significant influence

on the penetration and width. Corrosion testing implicates that higher heat input results in a lower

corrosion resistance of the welded joint.

Measurement of vehicle exhaust gas pollutant emissions according to real driving emissions (RDE)

testing procedure

Ante Kozina (University of Split, FESB, Croatia); Gojmir Radica (University of Split, Croatia); Frano

Barbir and Sandro Nizetic (University of Split, FESB, Croatia)

An overview of the present state in the field of measurement and homologation of passenger cars,

light commercial vehicles and trucks with regard to exhaust gas pollutant emissions is presented. The

issue of non-compliance with the amount of harmful emissions in everyday use conditions has been

elaborated, resulting in the need for introducing additional homologation procedures to measure

their amount in the form of the new real driving emissions (RDE) testing procedure. The Power

Binning Testing Method was described and the measurement on the vehicle was carried out using

this method, which included adaptation, manufacturing and installation of measuring equipment. On

board measurement of unit emission of CO2, NOx and CO were conducted, recorded and calculated

for passenger car, euro 5 compliant. Based on the analysis of the obtained results, conclusions on the

justification of the method used as well as the verification of emissions in realistic conditions were

made. The biggest drawbacks as well as the proposed solutions are explained for some of them.

Measured carbon monoxide emissions are within permitted limits, CO2 emissions and fuel

consumption are 13.4% more than factory declared, while NOx emissions exceed 3.5 times the

permissible emissions

Numerical Calculation and Experimental Measurement of Temperature and Deflections in a T-joint

Buried Arc Welded Structure

Mato Perid (Bestprojekt Ltd., Zagreb, Croatia); Sandro Nizetic (University of Split, FESB, Croatia); Ivica

Garašid (Faculty of Mechanical Engineering and Naval Architecture, Croatia); Zdenko

Tonkovid (Faculty of Mechanical Engineering and Naval Architecture, Zagreb, Croatia)

In this paper, a numerical simulation of buried-arc welding is conducted on a T-joint fillet sample to

investigate temperature fields and plate deflections. In the numerical simulation, a sequential

method is applied where a thermal analysis is done by using the element birth and death method to

simulate the addition of weld filler while a mechanical analysis is done in one step to reduce

simulation time. The obtained temperature-time histories and plate deflections are verified

experimentally.

S18: Energy-Energy Systems I

Room: KORČULA

A Methodology for Detection of Power Quality Disturbances in the Context of Demand Side

Management

Wilson Rodrigues (Federal University of Piauí (UFPI), Brazil); Fabbio Borges (USP, Brazil); Ricardo

Rabelo (Federal University of Piaui (UFPI), Brazil); Joel J. P. C. Rodrigues(National Institute of

Telecommunications (Inatel), Brazil & Instituto de Telecomunicações, Portugal)

With the wide use of non-linear loads and the integration of multiple power systems, there is an

increased risk of damaging power quality. Automatic detection of disturbance is the first step in

dealing with power quality problems. Most of the related works founded in the literature, to detect

power quality disturbances, use high computational cost techniques, making difficult to board in

hardware. Thus, this work proposes a methodology with a low computational cost for disturbances

detection in electrical power quality aiming embedded in hardware. In this way, the pre-processing

stage employed a sliding window, with a one-point step, and for each window, two features are

calculated: the root mean square and the harmonic distortion, to be used in the disturbance

detection. From the results obtained through synthetic data, it was possible to observe that the

proposed methodology can efficiently and rapidly detect the presence of disturbances with an

accuracy rate greater than 90% for signals with more than 25 points of disturbance. The observed

results can also be considered relevant for power quality analysis in Smart Grids because it can be

shipped in a low-cost smart meter.

Design of a Supercritical CO2 15 MW Power Group for a Recompression Cycle

Ambra Giovannelli (Roma Tre University, Italy); Coriolano Salvini (Università degli Studi ROMA TRE,

Italy); Erika Maria Archilei and Muhammad Anser Bashir (University of Roma Tre, Italy); Giuseppe

Messina (ENEA Casaccia, Italy)

Recently, several power cycles which consider supercritical CO2 as working fluid have been analyzed

in detail. Due to their potential thermodynamic efficiency, their compactness and their expected

operational flexibility if compared with conventional Rankine cycles, they are attracting the R&D

Community interests worldwide. The paper deals with the layout arrangement and machinery design

of a 15 MW power group for a supercritical recompression cycle. Such a group is, finally, made of a

two-stage Main Compressor a two-stage Recompressor and two one-stage Expanders. The final

layout arranged on three shafts at different speed is discussed in detail and justified from the

aerodynamic and mechanical point of view. Moreover, all the components have been iteratively

designed using preliminary 1-D and 2-D models and, then, designed and modelled in detail by means

of the commercial Ansys-CFX software. The main critical aspects related to the design of the main

compressor are presented as well as the proposed solutions.

Thermodynamic Performance Assessment of Solar Based Closed Brayton Cycle for Different

Supercritical Fluids

Anil Erdoğan (Dokuz Eylül University, Turkey); Önder Kizilkan (Isparta University of Applied Sciences,

Turkey); Ozgur Colpan (Dokuz Eylül University, Turkey)

In this study, a comprehensive analysis for solar based closed Brayton cycle is carried out for

different supercritical working fluids. For this aim, a mathematical model is developed in order to

investigate the performance of the closed Brayton cycle. Then, a parametric study is performed to

identify the effect of compression ratio, working fluid type, and solar irradiation on the performance

of the system. A mathematical model is also used for parabolic trough solar collector. The designing

and modeling equations are solved in the Engineering Equation Solver environment. The results show

that R744 is most suitable working fluid for increasing the performance among the other types of

cycle working fluids. The results of this study are intended to guide researchers who work on

thermodynamic analysis of Brayton cycles to design these systems more efficiently.

An optimization tool for the energy management of remote insular communities

Maria Symeonidou and Spyridoula Trakaki (Aristotle University Thessaloniki, Greece); Agis M.

Papadopoulos (Aristotle University of Thessaloniki, Greece)

Within this paper, an optimization framework will be presented that deals with the optimized energy

production and planning for a small insular community, like it can be found in Greek and

Mediterranean islands in general. The problem is analyzed by means of a mathematical model, based

on the system's energy production units such as heat pumps, micro Combined Heat and Power

(micro-CHP) units, conventional oil-fired burners, photovoltaic panels (PVs), wind generations and

batteries for storage. Co-generation is gaining much of attention lately, especially when integrated to

micro-grid communities that may use the energy produced in a more flexible and hence way.

Additionally, heat pumps are used extensively, as they seem to achieve greater efficiencies and cost

reduction compared to the conventional energy production. For that reason, the objective function

of the system is designed so as to minimize the total cost of the system and support the selection of

the most effective energy production combination. The problem is solved based on a mixed integer

linear programming (MILP). Additionally, a graphical user interface (GUI) is created and used for the

representative input and output presentation of the optimization results in a comprehensive and

attractive way. Three representative studies are presented, that underline the importance of

choosing the appropriate scope for the problem in question, and demonstrate the possibilities of the

tool developed.

S22: Energy-Green Cities and Sustainability

Room: BRAČ

Forecasting Air Pollution by Adaptive Neuro Fuzzy Inference System

Masoomeh Zeinalnezhad (Tehran West Branch, Islamic Azad University, Iran); Abdoulmohammad

Gholamzadeh Chofreh (Brno University of Technology - VUT Brno, Czech Republic); Feybi Ariani

Goni (Universiti Kebangsaan Malaysia, Malaysia); Jiří Klemeš (Brno University of Technology, Czech

Republic); Ardalan Mohammadi Darvishvand(Masjed Soleyman Branch, Islamic Azad University, Iran)

Air pollution causes a variety of adverse effects on humans such as illness or even death and

damages the living organisms and the natural environment. This environmental issue needs to be

controlled using various application and technology to estimate the composition of multiple

pollutants in the atmosphere for a specified time and location. The present study aims to develop a

system for air pollution forecasting using an adaptive neuro-fuzzy inference system. This method is a

type of artificial neural network that integrates both neural networks and fuzzy logic principles. The

adaptive neuro-fuzzy inference system calculations include four phases including implement fuzzy

system, enter parameters, start the learning process, and verify the processed data. As a sample, the

concentrations of atmospheric pollutant data recorded by sensors. The adaptive neuro-fuzzy

inference system method predicts four air pollution indicator levels including carbon monoxide,

sulfur dioxide, nitrogen oxides, and trioxygen. The analysis results reveal that the mean absolute

error of the adaptive neuro-fuzzy inference system method results is less than 15 %.

Internet of Things for Green Cities Transformation: Benefits and Challenges

Jiří Klemeš and Yee Van Fan (Brno University of Technology, Czech Republic)

This contribution provides an overview of IoT embedded in the cities, its contributions and the

challenges, from the environmental perspective. Energy, which is the essential lifeline of smart cities,

can be a crucial sector benefiting from IoT implementation. However, there is still a research gap on

the offset/saving versus the footprint of the IT sector. The overall reduction of energy consumptions

through the integration of IoT is yet to be verified. The end of life management remains an issue.

Continuous research and development, as well as assessment, could bring the sustainable smart

concept into its real-life implementation in the foreseeable future. The presentation stems to provide

a platform for the discussion of future research directions and priorities.

Emission Pinch Analysis for Regional Transportation Planning: Stagewise Approach

Yee Van Fan and Jiří Klemeš (Brno University of Technology, Czech Republic)

The transportation sector is one of the main contributors to air emissions, both GHG and air

pollutants. There have been various assessment approaches being proposed to support decision

making. However, it still remains a challenge due to its dynamic nature. There has always been still a

gap between the identified strategies and the readiness for implementation. The study aims to

propose a modified stagewise graphical approach (Emission Pinch Analysis) to facilitate the planning

of an environmentally sustainable transportation system in meeting the defined emission targets.

The steps by steps framework are presented. The non-GHG emission, entire life cycle and temporal

dimension are suggested to be included in accounting environmental sustainability. Strategies

considered are the modal shift, increase of average occupants, alternative fuels/energy and

technologies, and weight reduction. A case study on passenger transportation is presented to

demonstrate the applicability. This study presents the novel idea in utilising Pinch Analysis

methodology for regional transportation planning.

The use of biosensors in predicting occupant's thermal comfort in office building during heating

season

Nikolina Pivac (FESB University of Split, Croatia); Sandro Nizetic (University of Split, FESB,

Croatia); Vlasta Zanki (Director at HEP ESCO, Croatia)

The improvement of life quality and the work environment arise the need for innovations in

predicting real-time thermal comfort that consequently benefits to occupants' well-being and

productivity along with the more rational use of energy in the building. The discrepancy between

energy usage and office thermal comfort highlights the call for reliable control mechanisms. One way

to mitigate excessively dissipation of energy is to re-evaluate what actually makes occupants

comfortable focusing on their individualism. Human parameters such as the metabolic equivalent of

task (MET) and occupant's activity level are unfairly and improperly reduced on simple activity diary

method in BS EN ISO and ANSI /ASHRAE Standards. In this paper, the occupants' role is recognized as

double, a sensor and an indicator of preferences. Therefore, the biosensors are deployed to provide

real-time MET information during the heating season, together with the sensors for collecting the

environmental conditions such as air temperature, relative humidity and a level of carbon dioxide

(CO2). Moreover, a survey questionnaire is used to evaluate occupants' thermal comfort. All

measurements were conducted in-situ. In total, eight subjects participated in the investigation. The

conclusions of this study can be useful to set possible standards for regulation of the air-conditioning

systems in office buildings as well as operating parameters for achieving an indoor environment that

is most preferred.

S23: Engineering Modelling III

Room: VIS

High order RBF-FD approximations with application to a scattering problem

Jure Slak (Jožef Stefan Institute & University of Ljubljana, Slovenia); Blaž Stojanovič (Jozef Stefan

Institute & University of Ljubljana, Slovenia); Gregor Kosec (Jožef Stefan Institute, Slovenia)

A recently suggested technique for high order meshless approximations is described and analyzed in

this paper. It involves constructing ordinary Radial Basis Function-generated finite difference

approximations augmented with monomials up to a given order to ensure higher convergence rates.

These approximations are used to solve the Poisson's equation on an annulus to demonstrate the

predicted convergence rates. The presented methodology is then applied to a scattering problem,

which is described by a coupled system of two complex-valued PDEs on two domains, sharing a

common boundary.

Transient numerical analysis and experimental validation of Archimedes screw hydro turbine

Hrvoje Dedid-Jandrek (University of Split & Faculty of Electrical Engineering, Mechanical Engineering

and Naval Architecture, Croatia); Željko Penga (University of Split, Faculty of FESB, Croatia); Sandro

Nizetic (University of Split, FESB, Croatia)

Archimedes turbine (AT) power output and efficiency are investigated in this work via interactive

combination of experimental testing and numerical analysis. The experimental approach considers

different configurations of the AT inclination angle (21°, 25° and 30°) coupled with different angular

velocities (from 60 to 120 rpm) and water flow rates (10 l s-1 and 12.81 l s-1), while the numerical

model considers single flow rate with other variable parameters. The numerical analysis is conducted

using Computational Fluid Dynamics (CFD) modeling. The transient three-dimensional multiphase

model incorporating Volume of Fluid (VoF) method was developed for simulation of the two distinct

phases, air and water and their interface, i.e. free surface of water. Sliding mesh methodology was

employed to simulate the rotational movement of the AT to ensure the most accurate and realistic

simulation environment as possible, when compared to the experimental readings. Transient

numerical results are compared with experimental data with reasonable agreement and outlined the

influence of inclination angle and rotational speed of the Archimedes screw on the net performance

of the hydro turbine. The numerical results also gave insights for further possibility focused on

optimisation of the hydro turbine design parameters as well as operating conditions.

Numerical and analytical investigation of vertical axis wind turbine for different parameters

Ozgun Korukcu (Bursa Uludag University & Faculty of Engineering, Turkey)

Most of the wind turbine studies are focused on performance prediction. This study investigates

aerodynamic performance of a straight-bladed vertical axis wind turbine for different solidity values

and for different airfoil types. For numerical calculations unsteady Navier-Stokes (URANS) equations

were solved and for analytical calculations Double Multiple Stream Tube (DMST) model was solved

by using MATLAB software. Both the numerical and analytical calculation results are compared with

experimental data, and the results show that the calculations are valid. Effect of chord length and

rotor radius on maximum power coefficient (Cp) point were obtained. According to the

Computational Fluid Dynamics (CFD) results maximum moment coefficient (Cm) were obtained at

70°-190°-310°.

Modeling and optimization of slow speed two stroke marine Diesel engine using Multi zone

combustion model

Ante Muše (Marine Engineer, Croatia); Gojmir Radica (University of Split, Croatia); Nikola

Račid (University of Split, Faculty of Maritime Studies, Croatia); Zdeslav Jurid(University of Split,

Faculty of Maritime Studies, Croatia)

This paper presents the process calculation and modeling of a slow speed two stroke marine Diesel

engine using AVL Boost software. Unlike the previous models based on Vibe's calculation process,

where the pressure and temperature are calculated only inside the engine cylinder, here is Multi

zone combustion model applied. The losses in the intake and exhaust system and other processes of

changing the condition and composition of the gas are calculated in the whole engine. The influence

of three-dimensional geometry is taken into account by means of flow coefficient, which represent

the ratio of an actual flow. The calibration and validation of the model was performed with the

experimental data obtained at 75% load.

S24: Energy-Energy Systems II

Room: MEET ROOM

Circularity in production process as a tool to reduce energy, environmental impacts and operational

cost: The case of insulation materials

Effrosyni Giama, Michail Mamaloukakis and Agis M. Papadopoulos (Aristotle University of

Thessaloniki, Greece)

The production of construction materials accounts for significant quantities of raw materials and

respectively big amounts of energy. The fact that construction materials contribute in a most decisive

way to sustainable building management has been proven by many studies; they are therefore

rightly considered as important elements for the energy conscious and bioclimatic design and

construction of new buildings. Their exact environmental features, however, have to be determined

on a product specific base, as they depend on the raw materials used, the manufacturing process

applied and the energy sources consumed. Furthermore, the determination of the materials'

environmental impact can be carried out in many methodological ways. The ongoing challenges in

economy and environment lead to new methodologies in order to evaluate and improve the global

competitiveness towards sustainability. In that sense, in 2015, the European Commission adopted an

ambitious Circular Economy Action Plan. Circular economy is a methodology aiming at efficient

resources management, as well as waste management at the end of products' life. Therefore, circular

economy targets to minimizing waste, environmental impacts, resources use towards sustainability

and economic efficiency.

Hybrid photovoltaic-wind system for the electricity production in isolated sites

Samir Mouhadjer (Renewable Energy Research Unit in the Saharan Region, URERMS /, Algeria)

The main framework studied in this work is to design and fabricate an electronic charge regulator for

a hybrid generation system (photovoltaic/wind) of low and medium power, with accumulator battery

for different applications in isolated sites. The purposed charge controller must be able to charge,

using a hybrid generator, a lead-acid battery that is constantly concerned about the power supply for

12 or 24v DC current. The principle of operation of the system is to receive the power, obviously

variable and fluctuating depending on atmospheric conditions, to optimize it properly before using it

totally or partially for charging the battery. Finally, the proposed system helps to reduce the

complexity and cost of the hybrid systems and also ensures the largest operating region of the PV

and Wind generators.

Techno-economic analysis of PV/wind turbine stand-alone energy system

Jakov Šimunovid (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture,

Croatia); Frano Barbir (University of Split, FESB, Croatia); Gojmir Radica(University of Split,

Croatia); Branko Klarin (University of Split, FESB, Croatia)

Techno-economic analysis of various stand-alone photovoltaic wind turbine energy systems is made.

Three different energy storage options were compared namely (i) battery, (ii) hydrogen system and

(iii) combined battery and hydrogen system. Each of the three energy storage options was simulated

with five different system configurations. Overall, 15 different hour by hour simulation were

performed using Matlab. The hourly wind speed and solar insolation input data, location Split

Croatia, were acquired from the national meteorological service. The techno-economic analysis

consists of annual life cycle analysis, levelized cost of energy analysis and overall system efficiency.

The results show that using both solar and wind for energy production and using both battery and

hydrogen for energy storage is the economically more viable solution than using only one energy

source and one form of energy storage.Techno-economic analysis of various stand-alone

photovoltaic wind turbine energy systems is made. Three different energy storage options were

compared namely (i) battery, (ii) hydrogen system and (iii) combined battery and hydrogen system.

Each of the three energy storage options was simulated with five different system configurations.

Overall, 15 different hour by hour simulation were performed using Matlab. The hourly wind speed

and solar insolation input data, location Split Croatia, were acquired from the national

meteorological service. The techno-economic analysis consists of annual life cycle analysis, levelized

cost of energy analysis and overall system efficiency. The results show that using both solar and wind

for energy production and using both battery and hydrogen for energy storage is the economically

more viable solution than using only one energy source and one form of energy storage.

Solar/wind/battery/hydrogen system configuration resulted in 0.509 €/kWh, while solar/battery and

wind/battery resulted in 0.945 €/kWh and 2.496 €/kWh levelized cost of energy, respectively.