hanze university of applied sciences, groningen€¦ · the graduate creates models for advanced...

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Teaching and Examination Regulations Full�time Master Sensor System Engineering

Hanze University of Applied Sciences, Groningen

Adopted by the Dean of the Institute of Engineering on 30 June 2016 These Regulations take effect from 1 September 2016

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Version history

Revision date Summary corrections By Version

10-06-2016 First concept J. Bruining 0.1

16-06-2016 Input Programme Committee inserted J. Bruining 0.2

30-06-2016 Version adjusted for 2016-2017 (approved by SPC and Dean)

J.Bruining 1.0

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Contents 1. Study Programme ....................................................................................................................................... 4

1.1 Examining Board and Assessment Committee.................................................................................. 4

1.2 Admission Committee ............................................................................................................................ 5

1.3 School Participation Council of the School/Academy/Institution ................................................ 5

1.4 Programme Committee .......................................................................................................................... 5

2. Learning Outcomes .................................................................................................................................... 5

2.1 General programme learning outcomes ............................................................................................. 5

2.2 Programme Learning outcomes for specialisation module Health: ............................................. 6

2.3 The Master’s level .................................................................................................................................... 7

3. Programme Outline ................................................................................................................................. 11

3.1 Mode of Study: Full-time, Part-time, Work-based ........................................................................ 11

3.2 Specialisations and Differentiations ................................................................................................... 11

3.3 Study Pathways ....................................................................................................................................... 11

3.4 Curriculum Overview ........................................................................................................................... 11

4. Curriculum ................................................................................................................................................ 12

5. Admission Requirements ........................................................................................................................ 31

5.1 Required Prior Learning ....................................................................................................................... 31

5.2 Language Requirements for Admission to Programmes taught in English ............................. 31

5.3 Foreign Students: Legal Residence Requirement ............................................................................ 31

6. Examinations ............................................................................................................................................. 31

6.1 Chronology of Examinations ............................................................................................................... 31

6.2 Number of Examination Resits (outside of written examinations) ............................................ 31

6.3 Anti-Plagiarism Rules ........................................................................................................................... 31

7. Placements and Excursions..................................................................................................................... 32

8. Compulsory Attendance .......................................................................................................................... 32

9. Foreign Languages used in the Programme ....................................................................................... 32

10. Cum Laude Regulations .......................................................................................................................... 32

11. Examination Regulations ....................................................................................................................... 33

NAMES and ABBREVIATIONS ....................................................................................................................... 42

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TEACHING REGULATIONS OF THE STUDY PROGRAMME MASTER SENSOR SYSTEM ENGINEERING

1. Study Programme

This document contains the teaching and examination regulations of the Master Sensor System Engineering. This programme is offered by the Institute of Engineering, based in Assen, and is part of the wider Institute of Engineering, one of the 17 schools of the Hanze University of Applied Sciences, Groningen (Hanze UAS). The teaching and examination regulations incorporate the general examination regulations of Master programmes at the Hanze UAS (Appendix I). The teaching and examination regulations apply to all students who are enrolled in the programme.

Programme Description

Graduates from the Master Sensor System Engineering are professional Engineers capable of conceiving, designing and managing end-to-end products and user level services in technical environments where the generation, management, analysis and application of (potentially large) data streams from sensors play a central role. They have the professional skills to carry projects beyond the proof-of-concept phase into prototypes and user applications. They can advise clients on conceptual solutions and on optimal ways to analyse complex systems and data flows. Their job-title will vary depending on the domain and specialisation, but has the common denominator of Sensor System Architect.

Educational principles

The educational basis of the Master Sensor System Engineering is provided by developments in the professional practice of Sensor Technology. Graduates have advanced technical knowledge of sensor technology with systems overview and a problem-oriented approach that allows them to take a user/service perspective. They have competences to design architectures for big-data sensor systems and data-centric sensor applications, including the modelling of complex data flows and analysis algorithms. They are aware of real-world limitations and constraints, both physical, societal and regulatory. They have the professional skills to work in intercultural and multidisciplinary teams, to excel in interaction with customers, colleagues and partners in the value chain. The programme’s main educational characteristics are: Competence based learning with focus on academic, technical and social and

communicative learning outcomes. Integrated learning of knowledge skills. Development of professional and personal competences Studying in an international environment

1.1 EXAMINING BOARD AND ASSESSMENT COMMITTEE

The Examining Board is responsible for assuring the quality of the programme by supervising the content, method and level of the examinations. It has the duty to determine whether graduates have achieved the learning outcomes described in the TER (Teaching and Examination Regulations). The members of the Examining Board are appointed by the Dean. The Assessment Committee is responsible for monitoring the quality of examinations and operates under the supervision of the Examining Board.

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The members of the Examining Board and the Assessment committee and how to contact them will be made available on MijnHanze.nl

1.2 ADMISSION COMMITTEE

The Admission Committee advises the Dean about the admission of students. The members of the committee are appointed by the Dean. The members of the admission committee and how to contact them will be made available on MijnHanze.nl

1.3 SCHOOL PARTICIPATION COUNCIL OF THE SCHOOL/ACADEMY/INSTITUTION

The representative council of a school, academy or institution is a democratically elected body. One half of the council is comprised of students and the other half of university staff. The members of the school participation council and how to contact them will be made available on MijnHanze.nl

1.4 PROGRAMME COMMITTEE

The Programme Committee gives advice about matters relating to teaching in the school, academy or institution. Half of its members are students. All the members are appointed by the Dean. The members of the programme committee and how to contact them will be made available on MijnHanze.nl

2. Learning Outcomes

The following programme learning outcomes have been defined for graduates of the Master Sensor System Engineering. These programme learning outcomes are thought to be essential for the future Sensor Technologist. These key competences agree with the Dublin Descriptors for a Master level programme (see below) and implement the EUR-ACE Programme Outcomes for a Professional Master of Engineering. These learning outcomes comprise:

2.1 GENERAL PROGRAMME LEARNING OUTCOMES

M1. Modelling Meaningful Data: The graduate creates models for advanced sensor systems that transform raw sensor data into meaningful data for a client or an automated system by applying complex analysis methods, taking into account state-of-the-art technologies and using model based reasoning from an multi-disciplinary perspective.

M2. Building Intelligent Architectures: The graduate independently designs the architecture of advanced sensor systems that process big data and use high performance processing. Within the architecture the graduate is able to make critical decisions on the location of system intelligence, by taking into account technical and financial specifications, as well as ethical and environmental considerations.

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M3. Creating Reliable Services: The graduate advises on or creates services for non-specialised clients that provide reliable decisions based on complex data from both advanced sensor systems and contextual information, using the data and data flow in a responsible way. To this end, the graduate takes the lead in gathering requirements and boundary conditions from the full range of stakeholders, in a potentially international environment.

M4. Designing Towards Prototype: The graduate extends upon a validated proof-of-concept to improve the robustness, reliability and usability of an advanced sensor system by user acceptance testing and/or system level field testing while utilising experts in the field of application when necessary. In doing so, the graduate assesses the effects of the system on the environment, as well as the acceptance factor and societal impact.

M5. Professional Skills: The graduate performs as a leader in a team that may be composed of different disciplines and nationalities by independently creating a network of stakeholders that can help in solving a problem in an interdisciplinary setting. The graduate acts as a proactive sparring partner for different stakeholders in the project by advising, asked and non-asked for, clients, on conceptual solutions and optimal ways to analyse complex systems and data flows, by judging end-user implications, using creativity and self reflection skills.

M6. Being Aware of Impact: The graduate optimizes the advice or design of an advanced sensor application through critical reflection on the impact on society and environment, based on ethical aspects, cradle-to-cradle, risk analysis, green engineering and unexpected information. In this process, the graduate proactively organises stakeholder groups and assessment meetings.

M7. Performing Responsible Research: The graduate independently gathers, selects and analyses relevant (new) information in an responsible way, formulating and critically verifying hypotheses through analysis or experiments, in order to validate and develop advanced sensor systems in unfamiliar contexts. By evaluation of the outcome of the experiments, the graduate contributes to the state of the art in the field of advanced sensor technology and finds original solutions to existing problems.

M8. Contributing to Innovation:

The graduate formulates new business cases by proactively collecting business data. The graduate identifies any intellectual property following from research and development activities. The graduate gains knowledge by continually critically judging insights originating from the forefront of advanced sensor technology and being aware of priorities of stakeholders.

2.2 PROGRAMME LEARNING OUTCOMES FOR SPECIALISATION MODULE HEALTH:

H1. Applying Sensor Technology in Health: The graduate applies the latest developments in advanced sensor technology and uses interdisciplinary knowledge in order to solve an unfamiliar, health-related problem in society by careful consideration of ethical implications.

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H2. Developing Health Applications: The graduate develops advanced sensor systems for health applications compliant with applicable regulations, health standards and financial models.

2.3 THE MASTER’S LEVEL

The Master’s level is characterised by the student’s expertise in their specialism. Students are (semi)autonomous, demonstrating independence in the negotiation of assessment tasks (including the Master thesis project) and the ability to evaluate, challenge, modify and develop theory and practice. Students are expected to demonstrate an ability to isolate and focus on the significant features of problems and to offer synthetic and coherent solutions, contribute to generizable knowledge, with some students producing original or innovative work in their specialism that is worthy of publication or public performance or display. From the point of view of the framework for Qualifications of the European Higher Education Area, the Master Sensor System Engineering is a second cycle programme. This means it should develop programme learning outcomes in line with Dublin Descriptors for the Master level. The table below describes the alignment of the Master Sensor System Engineering programme learning outcomes with these descriptors. The table below summarizes the qualifications that students need to comply with for being awarded Master level (“second cycle”).

Qualifications that signify completion of the second cycle (= Master level) are awarded to students who: 1. Knowledge and

understanding have demonstrated knowledge and understanding that is founded upon and extends and/or enhances that typically associated with the first cycle, and that provides a basis or opportunity for originality in developing and/or applying ideas, often within a research context.

2. Applying knowledge and understanding

can apply their knowledge and understanding, and problem solving abilities in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.

3. Making judgments have the ability to integrate knowledge and handle complexity, and formulate judgements with incomplete or limited information, but that include reflecting on social and ethical responsibilities linked to the application of their knowledge and judgements.

4. Communication

can communicate their conclusions, and the knowledge and rationale underpinning these, to specialist and non specialist audiences clearly and unambiguously.

5. Learning skills

have the learning skills to allow them to continue to study in a manner that may be largely self-directed or autonomous.

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The table below shows how the Dublin descriptors are covered by the ProgrammeLearning Outcomes defined for the Master.

Dublin descriptors

1. K

now

ledge

and

under

stan

din

g

2. A

pply

ing

know

ledge

an

d u

nder

stan

din

g

3. M

akin

g ju

dgm

ents

4. C

omm

unicat

ion

5. L

earn

ing

skills

Professional competencies � Master Sensor System Engineering M1. Modelling Meaningful Data X X * M2. Building Intelligent Architectures X * X * M3. Creating Reliable Services X * X X *

M4. Designing Towards Prototype * * X X M5. Professional Skills * * * X X M6. Being Aware of Impact * X X X M7. Performing Responsible Research X * * X X M8. Contributing to Innovation * X * * *

Professional competencies – Master Sensor System Engineering, Specialisation ‘Health’ H1. Applying Sensor Technology in

Health * X X * X

H2. Developing Health Applications * * * * X = high contribution * = contribution

The EUR-ACE Programme Outcomes defines six programme outcomes for a Professional Master of Engineering.

1. Knowledge and understanding 2. Engineering analysis 3. Engineering design 4. Investigations 5. Engineering practice 6. Transferable skills

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These programme outcomes are summarised below with a description how they are implemented in the Master Sensor System Engineering.

1. Knowledge and Understanding The underpinning knowledge and understanding of science, mathematics and engineering fundamentals are essential to satisfying the other programme outcomes. Graduates should demonstrate their knowledge and understanding of their engineering specialisation, and also of the wider context of engineering. Second Cycle graduates should have:

• an in-depth knowledge and understanding of the principles of their branch of engineering

• a critical awareness of the forefront of their branch In-depth engineering knowledge and understanding is covered in the foundational programme learning outcomes: “Modelling Meaningful Data”, “Building Intelligent Architectures”, “Creating Reliable Services” and “Designing Towards Prototype”. As the titles imply, these programme learning outcomes go significantly beyond the average level, bringing students up to the front, and teaching them to assess critically the global technology base.

2. Engineering Analysis Graduates should be able to solve engineering problems consistent with their level of knowledge and understanding, and which may involve considerations from outside their field of specialisation. Analysis can include the identification of the problem, clarification of the specification, consideration of possible methods of solution, selection of the most appropriate method, and correct implementation. Graduates should be able to use a variety of methods, including mathematical analysis, computational modelling, or practical experiments, and should be able to recognise the importance of societal, health and safety, environmental and commercial constraints. Second Cycle graduates should have:

• the ability to solve problems that are unfamiliar, incompletely defined, and have competing specifications

• the ability to formulate and solve problems in new and emerging areas of their specialisation

• the ability to use their knowledge and understanding to conceptualise engineering models, systems and processes

• the ability to apply innovative methods in problem solving

Conceptualisation of models is an essential prerequisite for “Modelling Meaningful Data” and “Creating Reliable Services”. Engineering processes (including user specifications) are covered in depth in “Designing Towards Prototype”. Dealing with incomplete information is covered in all programme learning outcomes, but a formal process is covered in “Performing Responsible Research”. The field of Sensor System Engineering requires students to develop an acurate awareness of new and emerging technologies, in particular for the specialisation module.

3. Engineering Design Graduates should be able to realise engineering designs consistent with their level of knowledge and understanding, working in cooperation with engineers and non-engineers. The designs may be of devices, processes, methods or artefacts, and the specifications could be wider than technical, including an awareness of societal, health and safety, environmental and commercial considerations. Second Cycle graduates should have:

• an ability to use their knowledge and understanding to design solutions to unfamiliar problems, possibly involving other disciplines

• an ability to use creativity to develop new and original ideas and methods

• an ability to use their engineering judgement to work with complexity, technical uncertainty and incomplete information

“Modelling Meaningful Data”, “Creating Reliable Services”, “Designing Towards Prototype” and “Contributing to Innovation” address complex systems, requiring creativity in combination with engineering rigour. In both cases the bachelor level is exceeded by the introduction of modelling, client-interaction and field-testing, adding to complexity and

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uncertainty both in specifications, but also in verification.

4. Investigations Graduates should be able to use appropriate methods to pursue research or other detailed investigations of technical issues consistent with their level of knowledge and understanding. Investigations may involve literature searches, the design and execution of experiments, the interpretation of data, and computer simulation. They may require that data bases, codes of practice and safety regulations are consulted. Second Cycle graduates should have:

• the ability to identify, locate and obtain required data

• the ability to design and conduct analytic, modelling and experimental investigations

• the ability to critically evaluate data and draw conclusions

• the ability to investigate the application of new and emerging technologies in their branch of engineering

The handling and application of information in an international context is most directly addressed in “Performing Responsible Research” and “Contributing to Innovation”. Aspects of modelling and evaluation of emerging technologies are of course also covered in M1-M4, as well as in H1-H2.

5. Engineering Practice Graduates should be able to apply their knowledge and understanding to developing practical skills for solving problems, conducting investigations, and designing engineering devices and processes. These skills may include the knowledge, use and limitations of materials, computer modelling, engineering processes, equipment, workshop practice, and technical literature and information sources. They should also recognise the wider, non-technical implications of engineering practice, ethical, environmental, commercial and industrial. Second Cycle graduates should have:

• the ability to integrate knowledge from different branches, and handle complexity

• a comprehensive understanding of applicable techniques and methods, and of their limitations

• a knowledge of the non-technical implications of engineering practice

Non-technical implications are covered in “Being Aware of Impact”, inter-disciplinary research is an essential part of “Performing Responsible Research”, “Professional Skills” and “Applying Sensor Technology in Health”. The learning outcome “Modelling Meaningful Data” gives students the tools to assess the limitations of technology. Handling complex systems interdisciplinary is key to M2-M4 and H1-H2.

6. Transferable Skills The skills necessary for the practice of engineering, and which are applicable more widely, should be developed within the programme. Second Cycle graduates should be able to:

• fulfil all the Transferable Skill requirements of a First Cycle graduate at the more demanding level of Second Cycle

• function effectively as leader of a team that may be composed of different disciplines and levels

• work and communicate effectively in national and international contexts

Technical, research and professional skills are deepened with respect to the Bachelor level explicitly in “Professional Skills” and “Applying Sensor Technology in Health”. They are also covered by M1-M4 and H2, where an international context is implied throughout.

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3. Programme Outline

3.1 MODE OF STUDY: FULL�TIME, PART�TIME, WORK�BASED

The Master Sensor System Engineering is a fulltime programme.

3.2 SPECIALISATIONS AND DIFFERENTIATIONS

The Master Sensor System Engineering has only one specialisation, namely Health.

3.3 STUDY PATHWAYS

The Master Sensor System Engineering has only one study pathway.

3.4 CURRICULUM OVERVIEW

Master Semester 1

OC EC

1.1 Linear Algebra SEVM4LAL 4

1.2 Modelling and Simulation SEVM4MS 4

1.3 Advanced Data Analysis SEVM4ADA 4

1.4 Data Centric Architectures SEVM4DCA 4

1.5 Products and Services in Health SEVM4PSH 4

1.6 Sensor Applications in Health SEVM4SAH 3

1.7 Progress Test 1 SEVM16PT1 2


1.9 Professional Skills 1 SEVM4PFS1 2

1.10 Research and Ethics 1 1.11 Community Contribution 1

SEVM4RET1 SEVM4CC1

3 1

Total 35

Master Semester 2

OC EC

Master Thesis

2.1 Master Thesis SEVM4MT 30

2.2 Professional Skills 2 SEVM4PFS2 1

2.3 Research & Ethics 2 SEVM4RET2 2


Total 35

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4. Curriculum

Heading Description Title Linear Algebra

English Title Linear Algebra

Code SEVM4LAL

Academic Year 2016/2017

Workload 4 ECTS

Competencies M1 – Modelling Meaningful data M2 – Building Intelligent Architectures

Target group/type of course

Compulsory for students taking the study programme/major: Master Sensor System Engineering

Prerequisites Mathematics 2 of Bachelor Advanced Sensor Applications Statistics 2 of Bachelor Advanced Sensor Applications

Level O Introductory X Deepening O Advanced

Content The course covers the following linear algebra topics: linear systems, matrix algebra, determinants, vector spaces, Eigenvalues, Eigenvectors, orthogonality, least squares, symmetric matrices and quadratic forms. Next to this it sketches some applications in the field of engineering. The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

- The student can manipulate matrices to solve a linear system of equations.

- The student can analyse a dynamical system using determinants to find eigenvalues and eigenvectors.

- The student can solve least squares problems.

- The student can apply singular value decomposition to problems in data analysis and signal Processing.

Teaching method □ Action Learning x Practical/training

□ Thesis □ Problem-Based Learning (PBL)

□ International thesis □ Project learning

□ Guest lecture □ International placement

x Lecture □ Placement/work-based learning (WBL)

□ Individual tutoring □ Supervised learning

□ Peer coaching x Tutorial

Assessment □ Attendance □ Professionalism

□ Oral examination □ Professional product x Assignment x Written examination

□ Other □ Skills assessment

□ Portfolio assessment □ Report

□ Presentation □ Work discussion

Costs -

Study materials

Title Author ISBN Compulsory/recommended Comment

Linear Algebra and Its Applications, 4th Edition

David Lay 978-1-29202-055-6

Compulsory

Introduction to Linear Algebra, 4th edition

Gilbert Strang

978-0980232714 Recommended Accompanying video lectures: http://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011

Language of instruction

O Dutch | x English | O German

Particulars -

Contact Corina Vogt, [email protected], telephone: 050-5957379, location: Assen, room: 1.13.

Curriculum year x 1

Period x 1 | □ 2 | □ 3 | □ 4

Year/Period in the curriculum

x 1.1 | O 1.2 | O 1.3 | O 1.4

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Heading Description

Title Modelling and Simulation

English Title Modelling and Simulation

Code SEVM4MS


Workload 4 ECTS

Competencies M1 – Modelling Meaningful Data



Prerequisites Project theme 5 of Bachelor Advanced Sensor Applications Digital Signal Processing of Bachelor Advanced Sensor Applications Data Analysis of Bachelor Advanced Sensor Applications Intelligent Sensors of Bachelor Advanced Sensor Applications Sensor Data of Bachelor Advanced Sensor Applications

Level O Introductory O Deepening X Advanced

Content The course covers the following topics: stationary discrete-time stochastical processes and models, linear and non-linear dynamical system models, (normalized) Least-Mean-Square adaptive filters, Recursive Least Squares Adaptive Filters and Kalman filtering, model simulation tools, model-based reasoning. The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

- Model and simulate (sensor) systems using tools such as Modelica and pySimulator.

- Describe systems in the time-domain and/or frequency domain using stationary discrete-time stochastical processes and models, such as autoregressive and moving-average models.

- Describe systems using linear and nonlinear dynamical system models by applying techniques such as state space, phase portrait, linearization and bifurcations.

- Clean data using advanced filter techniques, such as (normalized) Least-Mean-Square adaptive filters, Recursive Least Squares Adaptive Filters and Kalman filtering.

- Analyse sensor systems using model-based reasoning

- Represent data in a meaningful way.

Teaching method □ Action Learning □ Practical/training








□ Oral examination □ Professional product

x Assignment □ Written examination




Costs -

Study materials


Adaptive Filter Theory, 5th edition

S. Haykin 9780273764083 Compulsory International Edition



Particulars -

Contact Dr. Berend-Jan van der Zwaag, Email: [email protected] Telephone: 050 595 6193

Curriculum year x 1

Period x 1 | □ 2 | □ 3 | □ 4


O 1.1 | x 1.2 | O 1.3 | O 1.4

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Heading Description

Title Advanced Data Analysis

English Title Advanced Data Analysis

Code SEVM4ADA


Workload 4 ECTS

Competencies M1 – Modelling Meaningful Data M2 – Building Intelligent Architectures



Prerequisites Statistics 1 of Bachelor Advanced Sensor Applications Digital Signal Processing of Bachelor Advanced Sensor Applications Statistics 2 of Bachelor Advanced Sensor Applications Intelligent Sensors of Bachelor Advanced Sensor Applications Sensor Data of Bachelor Advanced Sensor Applications Programming Java 2 of Bachelor Advanced Sensor Applications or similar experience with an OO language


Content The course covers the following topics: computer algebra systems (Python based), sensor fusion architectures, common representational format, temporal and spatial alignment, error propagation analysis, principal component analysis, independent component analysis, support vector machines, k-means clustering. The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

- The student can manipulate numerical data using Python with the linear algebra package Numpy and the plotting package MatPlotlib.

- The student can analyse system requirements to identify applicable sensor fusion architectures.

- The student can analyse data acquisition by a sensor system to construct a common representational format.

- The student can adapt sensor system design to create correct temporal and spatial alignment of multi-sensor data.

- The student can create a sensor system which combines multi-sensor data into correct interpretations.

- The student can analyse a data analysis task and compare features to evaluate their fitness for the task at hand.

- The student can evaluate whether a data analysis task requires dimensionality reduction, blind source separation, cluster analysis or classification.

- The student can interpret high dimensional data using dimensionality reduction techniques such as principal component analysis.

- The student can interpret multi-sensor data: o using blind source separation techniques like independent component analysis. o using cluster analysis techniques. o using classification algorithms like support vector machines.



□ International thesis x Project learning







□ Assignment □ Written examination


x Portfolio assessment □ Report


Costs -

Study materials

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Title Author ISBN Compulsory/recommended

Comment

Multi-Sensor Data Fusion: An Introduction, Part I: Basics and Part II: Representation

H.B. Mitchell 978-3-540-71463-7 Recommended

Machine Learning: The Art and Science of Algorithms that Make Sense of Data

Peter A. Flach 9781107422223 Compulsory Students need to buy this book.

An Introduction to Variable and Feature Selection

I. Gyuon and A. Elisseeff

Journal of Machine Learning Research 3, (2003) p. 1157-1182

Compulsory Article: available electronically from Hanze mediatheek.

Neural Networks, Vol. 13, No 4, pages 411-430

A. Hyvärinen and E. Oja

Compulsory Article: made available by authors through http://cis.legacy.ics.tkk.fi/aapo/papers/IJCNN99_tutorialweb

An Efficient k-Means Clustering Algorithm: Analysis and Implementation

T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu

IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 7, 2002

Compulsory Article: available electronically from Hanze mediatheek.

A Tutorial on Principal Component Analysis

Jonathon Shlens Compulsory Article: available from the author website through http://www.snl.salk.edu/~shlens/pca.pdf

SVMs—a practical consequence of learning theory’

Bernhard Scholkopf

IEEE Intelligent Systems, pages 18-21, July/Aug 1998

Compulsory Article: available from the author website http://www.is.tuebingen.mpg.de/nc/employee/details/bs

Lectures on python and numpy from version 4 of the software carpentry

Compulsory http://software-carpentry.org/

Matplotlib gallery Compulsory http://matplotlib.org/gallery.html

Multi-Sensor Fusion

Ghuang-Zhong Yang and Xiaopeng Hu

1-84628-272-1 Recommended

Surface-Based and Probabilistic Atlases of Primate Cerebral Cortex

David C. Van Essen and Donna L. Dierker

(2007), Neuron Recommended

Support Vector Machines and other kernel-based learning methods

John Shawe-Taylor &NelloCristianini

Cambridge University Press, 2000

Recommended



Particulars -

Contact Ronald van Elburg, [email protected], telephone: 050-5952431, location: Assen, room: 1.06

Curriculum year x 1

Period x 1 | □ 2 | □ 3 | □ 4


x 1.1 | O 1.2 | O 1.3 | O 1.4

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Heading Description

Title Data Centric Architectures

English Title Data Centric Architectures

Code SEVM4DCA


Workload 4 ECTS

Competencies M2 – Building Intelligent Architectures M5 – Professional Skills M6 – Being Aware of Impact



Prerequisites Sensor Networks 1 of Bachelor Advanced Sensor Applications Intelligent Sensors of Bachelor Advanced Sensor Applications


Content In this module students are trained in architectural design at two conceptual levels. At the level of System Architectures for “big data” applications they learn about top-level trade-offs, e.g. between measured data rates and required processing power. They get introduced to high-performance computing and streaming database technology. At the level of Digital Signal Processing Architectures, they learn key concepts (fixed point, floating point) and technologies (FPGA, GPU, Mixed signal chips). Linear and Functional programming as well as Parallel processing are covered. The theoretical part of this module is assessed during the progress test At the end of this module the student is able to:

- Design and/or implement a Digital Signal Processing Architecture based on fixed point core, floating point core, PLD, FPGA, GPU or mixed signal systems

- Implement algorithms by means of sequential (i.e. linear) programming.

- implement algorithms by means of parallel processing

- Design and implement a system architecture using streaming database technology

- Design and implement an architecture for a given sensor system algorithm capable of big data streams and high performance processing

- Design based on top-down approach an appropriate architecture for an advanced sensor system














Costs -

Study materials


Embedded Systems Architecture, Second Edition: A Comprehensive Guide for Engineers and Programmers

Tammy Noergaard 978-0123821966 Compulsory

Software Mark W. Maier, David IEEE Computing, April Compulsory Downloadable article

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Architecture: Introducing IEEE Standard 1471

Emery, Rich Hilliard 2001, pp. 107-109

From Microprocessors to Nanostores: Rethinking Data-Centric Systems

Parthasarathy Ranganathan

IEEE Computer, January 2011 (vol. 44 no. 1), pp. 39-48

Compulsory Downloadable article

Gordon: An Improved Architecture for Data-Intensive Applications

Adrian M. Caulfield, Laura M. Grupp& Steven Swanson

IEEE Micro, January/February 2010 (vol. 30 no. 1), pp. 121-130

Compulsory Downloadable article



Particulars -

Contact Ir. J.W. Knobbe PDEng., Email: [email protected], Telephone: 050 595 7658

Curriculum year x 1

Period x 1 | □ 2 | □ 3 | □ 4


x 1.1 | O 1.2 | O 1.3 | O 1.4

Heading Description Title Products and Services in Health

English Title Products and Services in Health

Code SEVM4PSH


Workload 4 ECTS

Competencies M2 – Building Intelligent Architectures M4 – Designing Towards Prototype M5 – Professional Skills M8 – Contributing to Innovation H1 – Applying Sensor Technology in Health H2 – Developing Health Applications



Prerequisites Part of Reliability Engineering 1 and 2 (technology assessment, CPK/PPK, Gage R&R, Design of Experiments , Tolerance Design, Validation) of Bachelor Advanced Sensor Applications Methodical Design of Bachelor Advanced Sensor Applications


Content A majority of the course material covers the following 5 areas of designing medical products and services:

- Case analysis: Formulating business cases in the health domain; problem definitions, design goals and subgoals and identify stakeholders.

- Business case formulation: Investigate and assess possible and existing business models, stakeholders and associated regulations and systems.

- Requirements engineering: Translating business cases, user cases and user requirements into product/service requirements and technical specifications.

- Ideation for innovation: generating ideas and applying advanced technologies and algorithms. Looking for state of the art, but out of context applications.

- System architecture: distributing functionality over (sensor)hardware, transport, service software etc, taking into account the full lifecycle.

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The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

- Methodically and systematicaly analyse a problem case in the health domain and present a convincing analysis of the problem, possible goals and current solutions and their short comings in multiple presentations and a report.

- Methodically design a product, from case to concept, at top-level system architecture, including use scenarios, visualisations and specification and present it as a business case in both a report and presentation.

- Understand product development in the health domain; business models, the regulatory landscape and stakeholders.

- Present and communicate, purposeful and convincingly, ideas, business cases, needs and questions for co-operation.


□ Thesis x Problem-Based Learning (PBL)


x Guest lecture □ International placement


□ Individual tutoring x Supervised learning

x Peer coaching □ Tutorial

Assessment x active participation (1 ECTS) □ Professionalism □ Oral examination □ Professional product □ Assignment □ Written examination x Progress Test (1 ECTS) □ Skills assessment □ Portfolio assessment x Report (2 ECTS)

x Presentation (1 ECTS) □ Work discussion

Costs -

Study materials


Common mistakes in medical device development

Anney Majewski Infographic, August 2nd, 2015

Compulsory namsa.com/infographic-common-mistakes-in-the-medical-device-development-continuum-2/

Requirements – What’s the Big Deal?

Lou Wheatcraft - (blog post 13 August 2012)

Compulsory reqexperts.com/blog/2012/08/requirements-importance

When Should You Start Managing Requirements?

Lou Wheatcraft - (blog post 27 September 2012)

Compulsory reqexperts.com/blog/2013/09/when-should-you-start-managing-requirements

Using V Models for Testing

Donald Firesmith - (SEI blog post 11 November 2013)

Compulsory blog.sei.cmu.edu/post.cfm/using-v-models-testing-315



Particulars -

Contact Ward van der Houwen [email protected] 0628578101

Curriculum year x 1

Period □ 1 | x 2 | □ 3 | □ 4


O 1.1 | x 1.2 | O 1.3 | O 1.4

19

Heading Description

Title Sensor Applications in Health

English Title Sensor Applications in Health

Code SEVM4SAH


Workload 3 ECTS

Competencies M6 – Being Aware of Impact H1 – Applying Sensor Technology in Health H2 – Developing Health Applications



Prerequisites Biology 1 of Bachelor Advanced Sensor Applications Biochemistry of Bachelor Advanced Sensor Applications Biology 3 of Bachelor Advanced Sensor Applications Sensor Data of Bachelor Advanced Sensor Applications

Level O Introductory x Deepening O Advanced

Content During this module a number of topics related to sensor applications in health will be covered: - Human physiology - Principles and applications of biochemical sensor technology. - Diagnostics - Hospital and home care and monitoring - The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

-

- Explain the physical, chemical or biological principles of a given sensor that is able to detect a specific biological signal

- Based on a current scientific literature choose the best type of sensor suitable for detection and analysis of a given biological signal and justify their choice

- Describe basic human physiological (and pathological) functions and systems like circulation, respiration, digestion, excretion, reproduction, metabolism, immunity, locomotion, control systems (endocrine and nervous) and ageing.

- Measure given basic human physiological functions using sensors and interpret the results of the measurements.

- Design innovative solutions for home care monitoring taking into account ethical issues




x Guest lecture □ International placement




Assessment x Attendance - 0% □ Professionalism


x Assignment - 17% □ Written examination


□ Portfolio assessment x Report - 66%

x Presentation – 17% □ Work discussion

Costs -

Study materials


Roos and Wilson Anatomy and Physiology in Health and Illness

Waugh and Grant 978-0-7020-5326-9 Compulsory Including on-line access

Handbook of J. Fraden 978-1-4419-6465-6 Compulsory Available online

20

Modern Sensors through HanzeMediatheek

Textbook of Medical Physiology, 12th edition

Guyton and Hall 978-1-4160-4574-8 Recommended

Body Sensor Networks

Yang 978-1-4471-6373-2

Recommended

Healthcare Sensors Networks

D.T. Huei Lai, R. Begg, M. Palaniswami

978-1-4398-2181-7 Recommended



Particulars -

Contact Dr. M. A. Kozielska-Reid, E-mail: [email protected], Phone: 050 595 7636

Curriculum year x 1

Period □ 1 | x 2 | □ 3 | □ 4


O 1.1 | x 1.2 | O 1.3 | O 1.4

Heading Description Title Progress Test 1

English Title Progress Test 1

Code SEVM4PT1


Workload 2 ECTS

Competencies M1 – Modelling Meaningful Data M2 – Building Intelligent Architectures M3 – Creating Reliable Services M4 – Designing Towards Prototype M5 – Professional Skills M6 – Being Aware of Impact M7 – Performing Responsible Research M8 – Contributing to Innovation H1 – Applying Sensor Technology to Health H2 – Developing Health Applications



Prerequisites Linear Algebra of Master Sensor System Engineering Modelling and Simulation of Master Sensor System Engineering Advanced Data Analysis of Master Sensor System Engineering Data Centric Architectures of Master Sensor System Engineering Products and Services in Health of Master Sensor System Engineering Sensor Applications in Health of Master Sensor System Engineering Community Contribution of Master Sensor System Engineering


Content Throughout the year, the student is tested at least 3 times on the theoretical knowledge of all the modules of the Master Sensor System Engineering. Each progress test takes 3 hours. The first test takes place 10 weeks after the start of the academic year. If a student has at least 30% of answers correct, this will earn him the 2 ECTS for progress test 1.. The second test takes place 20 weeks after the start of the academic year. If a student has at least 60% of correct answers on this test, he/she will earn the 4 ECTS for progress test 2 (and the 2 ECTS for progress test 1, if the first test was failed). The test will consist of the topics covered by the following study units: 1 part Linear Algebra 1 part Modelling and Simulation 1 part Advanced Data Analysis

21

1 part Data Centric Architectures 1 part Products and Services in Health 2 parts Sensor Applications in Health 1 part Community Contribution




□Guest lecture □ International placement

□ Lecture □ Placement/work-based learning (WBL)


□ Peer coaching □ Tutorial



□ Assignment x Written examination




Costs -

Study materials


-



Particulars The theoretical knowledge of all the modules of the Master is tested.

Contact Dr. Esther Vertelman, [email protected], 050 595 7611

Curriculum year x 1

Period x 1 | □ 2 | □ 3 | □ 4


x 1.1 | □ 1.2 | □ 1.3 | □ 1.4

Heading Description

Title Progress Test 2


Code SEVM4PT2


Workload 4 ECTS





Level O Introductory O Deepening

22

X Advanced

Content Throughout the year, the student is tested at least 3 times on the theoretical knowledge of all the modules of the Master Sensor System Engineering. Each progress test takes 3 hours. In order to gain the credits for this particular study unit, the student needs to answer at least 60% correct on the progress test that takes place 20 weeks after the start of the academic year, this will also give a pass for the study unit Progress Test 1. If a student fails progress test 2, 60% of correct answers on progress test 3 will be a pass for progress test 2 as well. The test will consist of the topics covered by the following study units: 1 part Linear Algebra 1 part Modelling and Simulation 1 part Advanced Data Analysis 1 part Data Centric Architectures 1 part Products and Services in Health 2 parts Sensor Applications in Health 1 part Community Contribution














Costs -

Study materials






Curriculum year x 1

Period □1 | x 2 | □ 3 | □ 4


□ 1.1 | x 1.2 | □ 1.3 | □ 1.4

Heading Description

Title Professional Skills 1

English Title Professional Skills 1

Code SEVM4PFS1


Workload 2 ECTS

Competencies M3 – Creating Reliable Services M5 – Professional Skills



Prerequisites Professional Skills courses from premaster SSE

Level O Introductory O Deepening x Advanced

Content The topics of the Professional Skills module will be:

23

- Negotiation skills You will learn about the different types of negotiation styles you can use and practice developing effective arguments. We will also see how questions should and should not be used in a negotiation context and the type of conventions that apply in intercultural negotiations.

- Developing your career You will learn to use the main sources of information in your professional field. You will access scientific journals and professional magazines to figure out where the field is heading so you can stay one step ahead in your search for job, research and funding opportunities. In addition, you will learn basic skills to facilitate job-hunting after your studies.

At the end of this module the student is able to:

- Identify the differences between distributive and integrative bargaining and identify them in an applied setting.

- Explain the main issues that affect intercultural negotiations.

- Plan the way to reach goals for future career by reflecting and adjusting actions where necessary.

- Identify the main steps and actions required to become a consultant engineer.










x Assignment 50% □ Written examination



x Presentation 50% □ Work discussion

Costs -

Study materials


The engineer’s career guide

Hoschette, J. A. 9780470503508 Recommended



Particulars -

Contact Dr. F. J. Guzmán Muñoz, E-mail: [email protected]

Curriculum year x 1

Period x 1 | x 2 | □ 3 | □ 4


x 1.1 | x 1.2 | O 1.3 | O 1.4

Heading Description Title Research and Ethics 1

English Title Research and Ethics 1

Code SEVM4RET1


Workload 3 ECTS

Competencies M5 – Professional Skills M6 – Being Aware of Impact M7 – Performing Responsible Research M8 – Contributing to Innovation



Prerequisites - Project theme 5 of Bachelor Advanced Sensor Applications

24

- Research Skills of Bachelor Advanced Sensor Applications OR

- Professional Skills of pre-master Sensor System Engineering - Project of pre-master Sensor System Engineering


Content The study unit Research & Ethics is centred around two major pillars. In the research part the student will work with the creative action methodology to learn about research skills. The research skills include evaluating scientific articles, hypothesis formulation and verification and reasoning about references. The students are expected to be critical of their research as well as that of others. At every step during the research the students have to be aware of the impact of their solutions on people and the environment, analyse the risks that are accompanied to the research and reflect on how to improve these implications. The results should be communicated to an audience of both experts and non-experts. In order to gain the credits for research and ethics 1, the student should write a report on research on a predefined ethical problem, which will give 2 out of 3 credits. Also a presentation on the same predefined ethical problem is part of this study unit, which will give the last credit for this study unit. At the end of this module the student is able to:

- Independently gather, select and analyse relevant new information in a responsible way by using scientific databases, correct search terms and evaluating the source of the information

- Formulate and critically verify a hypothesis through analysis or experiments

- Identify intellectual property following from research and development activities

- Gain knowledge by continuously critically judging insights originating from the forefront of advanced sensor technology

- Optimize the advice or design of an advanced sensor application through critical reflection on the impact on society, environment, and end-user implications, based on ethical aspects, risk analysis and unexpected information

- Communicate the results of research to a public of experts and non-experts by presenting the outcomes of the research in a way that is understandable for the audience in any case.












□ Portfolio assessment x Report – 2 EC

x Presentation – 1 EC □ Work discussion

Costs -

Study materials


All literature will be made available on blackboard



Particulars -

Contact Dr. E.J.M. Vertelman, E-mail: [email protected], Phone: 050 595 7611

Curriculum year x 1

Period x 1 | x 2 | □ 3 | □ 4


x 1.1 | x 1.2 | O 1.3 | O 1.4

25

Heading Description

Title Community Contribution

English Title Community Contribution

Code SEVM4CC1


Workload 1 ECTS

Competencies M5 – Professional Skills M6 – Being Aware of Impact M8 – Contributing to Innovation



Prerequisites Professional Skills courses from pre-master SSE


Content The topics of the Community Contribution module will be:

- Developing a professional network You will learn how to develop and maintain a professional network and how to use your network to

further your professional career. This topic will be closely related to communication skills because when using your network you will sometimes have to act as an expert, sometimes as a mere translator of the requirements of a client and sometimes you will be a sparring partner for clients or experts.

- The engineer and the community. You will learn about different ways to understand the social responsibility of companies and how the

concept of corporate social responsibility has evolved during the last decades. We will discuss in class about the role and responsibility of the engineer within the community. You will also be introduced to relevant concepts as Green Engineering and Cradle2Cradle.

The theoretical part of this module is assessed during the progress test. At the end of this module the student is able to:

- Describe the principles behind cradle2cradle and green engineering using examples of real-world applications.

- Identify factors that contribute to the development of a network and apply them in a networking situation.

- Explain the arguments that constitute the business case for corporate social responsibility.







□Peer coaching x Tutorial







Costs -

Study materials


The engineer’s career guide

Hoschete, J. A. 9780470503508 Recommended



Particulars -


Curriculum year x 1

Period x 1 | x 2 | □ 3 | □ 4


x 1.1 | x 1.2 | O 1.3 | O 1.4

26

Heading Description

Title Master Thesis

English Title Master Thesis

Code SEVM4MT


Workload 30 ECTS



Compulsory for students taking the study programme: Master Sensor System Engineering



Content Each Master thesis project must comply with the following: 1 The project must be related to sensor technology 2 The project must be related to modelling and/or data analysis 3 The project must solve a problem in the context of health 4 The project has sufficient scope for discussion (the final outcome has not yet been

decided) and ethical considerations 5 The student is responsible for gathering knowledge from literature as well as from

experts which is needed for the completion of the assignment 6 The project has sufficient possibilities for conducting research. 7 There is sufficient capacity to offer good technical support to the students within

the company or the institution (or an agreement with the study institution is in place in order to safeguard this support).

8 Sufficient facilities have been made available by the assignment provider in order to realise the assignment agreed within the planned period of time.

9 The assignment can be completed within the time frame of 20 weeks. 10 The assignment has been approved by the Master Thesis Coordinator.


x Thesis □ Problem-Based Learning (PBL)


□Guest lecture x International placement

□ Lecture x Placement/work-based learning (WBL)





□ Assignment □Written examination


□ Portfolio assessment x Report – 70%

x Presentation – 30% □ Work discussion

Costs -

27

Study materials


Master Thesis Rules Sensor System Engineering

E. Vertelman Available on Blackboard



Particulars


Curriculum year x 1

Period □1 | □ 2 | x 3 | x 4


O 1.1 | O 1.2 | x 1.3 | x 1.4

Heading Description Title Professional Skills 2

English Title Professional Skills 2

Code SEVM4PFS2


Workload 1 ECTS

Competencies M3 – Creating Reliable Services M5 – Professional Skills



Prerequisites Professional Skills 1 of Master Sensor System Engineering


Content This is a practical module based on the performance of the student during the work on his/her Master thesis. The assessment is based on a performance review filled by the company supervisor. At the end of this module the student is able to:

- Reflect on his engineering, social and personal skills based on his/her performance during the master thesis phase and the feedback by the company supervisor.






x Individual tutoring □ Supervised learning








Costs …….

Study materials




Particulars -


Curriculum year x 1

Period □ 1 | □ 2 | x 3 | x 4

Year/Period in cur. O 1.1 | O 1.2 | x 1.3 | x 1.4

28

Heading Description Title Research and Ethics 2

English Title Research and Ethics 2

Code SEVM4RET2


Workload 2 ECTS

Competencies M5 – Professional Skills M6 – Being Aware of Impact M7 – Performing Responsible Research M8 – Contributing to Innovation



Prerequisites Research and Ethics 1 of Master Sensor System Engineering


Content The study unit Research & Ethics is centred around two major pillars. In the research part the student will work with the creative action methodology to learn about research skills. The research skills include evaluating scientific articles, hypothesis formulation and verification and reasoning about references. The students are expected to be critical of their research as well as that of others. At every step during the research the students have to be aware of the impact of their solutions on people and the environment, analyse the risks that are accompanied to the research and reflect on how to improve these implications. The results should be communicated to an audience of both experts and non-experts. In order to gain the credits for research and ethics 2, the student should have an approved proposal for their master thesis, which will give 1 credit. Also the student should have an approved graduation definition and plan in order to gain the last credit. At the end of this module the student is able to:

- Independently gather, select and analyse relevant new information in a responsible way by using scientific databases, correct search terms and evaluating the source of the information

- Formulate and critically verify a hypothesis through analysis or experiments

- Identify intellectual property following from research and development activities

- Gain knowledge by continuously critically judging insights originating from the forefront of advanced sensor technology

- Optimize the advice or design of an advanced sensor application through critical reflection on the impact on society, environment, and end-user implications, based on ethical aspects, risk analysis and unexpected information

- Communicate the results of research to a public of experts and non-experts by presenting the outcomes of the research in a way that is understandable for the audience in any case.






x Individual tutoring □ Supervised learning






□ Portfolio assessment x Report – 1 EC: proposal; 1 EC: definition + plan

□Presentation □ Work discussion

Costs -

Study materials


All literature will

29

be made available on blackboard



Particulars -

Contact Dr. E.J.M. Vertelman, E-mail: [email protected], Phone: 050 595 7611

Curriculum year x 1

Period □ 1 | □ 2 | x 3 | x 4


O 1.1 | O 1.2 | x 1.3 | x 1.4

Heading Description

Title Progress Test 3


Code SEVM16PT3


Workload 2 ECTS






Content Throughout the year, the student is tested at least 3 times on the theoretical knowledge of all the modules of the Master Sensor System Engineering. Each progress test takes 3 hours. In order to gain the credits for this particular study unit, the student needs to answer at least 60% correct on the progress test that takes place 40 weeks after the start of the academic year, this will also give a pass for the study unit Progress Test 2. If a student fails the last exam, a resit will be offered shortly before the start of the new academic year. The test will consist of the topics covered by the following study units: 1 part Linear Algebra 1 part Modelling and Simulation 1 part Advanced Data Analysis 1 part Data Centric Architectures 1 part Products and Services in Health 2 parts Sensor Applications in Health 1 part Community Contribution

-




30











Costs -

Study materials






Curriculum year x 1

Period □1 | □ 2 | x 3 | x 4


O 1.1 | O 1.2 | x 1.3 | x 1.4

31

5. Admission Requirements

5.1 REQUIRED PRIOR LEARNING

A BEng in Advanced Sensor Applications from Hanze University of Applied Sciences gives automatic entrance to the programme. In general, holders of a different technical degree will have to prove the contents of their previous education by means of a portfolio. The portfolio will be considered carefully by the admission committee. The admission committee has 3 options:

1. The student can be asked to do a special bridging programme before they can be admitted; the precise content will be decided on by the admissions committee.

2. The student can start with the Master Sensor System Engineering without additional courses.

3. The student is not accepted.

5.2 LANGUAGE REQUIREMENTS FOR ADMISSION TO PROGRAMMES TAUGHT IN ENGLISH

The programme has the following prerequisites with respect to the English level of students: By means of an internationally used test, the student has demonstrated the required command of the English language (a minimum score of two B2s and two C1s according to the Common European Framework) or comparable IELTS score of 6.5, with no subscores below 5.5, or an equivalent score on the TOEFL test.

Students who can prove that their prior education for which they obtained a diploma was full time English-taught will be exempt from submitting an extra language proficiency test. A statement by Nuffic (Netherlands Organisation for International Cooperation in Higher Education), confirming that the student took an English-taught programme, may be required. Students who have a qualification from the United States, Canada (English speaking part), Australia, New Zealand, United Kingdom or Ireland are exempted from the language requirement.

5.3 FOREIGN STUDENTS: LEGAL RESIDENCE REQUIREMENT

The student must have valid residency status which enables them to study in the Netherlands. Students can contact the International Student Office for further information.

6. Examinations

6.1 CHRONOLOGY OF EXAMINATIONS

Progress assessments take place four times a year: one week before the start of the academic year and after 10, 20 and 40 weeks.

6.2 NUMBER OF EXAMINATION RESITS (OUTSIDE OF WRITTEN EXAMINATIONS)

If a student did not obtain a sufficient score for the last progress assessment, an additional test can be requested from the Examination Board.

6.3 ANTI�PLAGIARISM RULES

All academic work, written or otherwise, submitted by students to their lecturers, is expected to be the result of their own thought, research, or self-expression. In cases where students feel unsure about a question of plagiarism involving their work, they are obliged to consult their lecturers on the matter before submission.

32

When students submit work claiming to be their own, but which in any way borrows ideas, wording or anything else from another source without appropriate referencing/attribution/ acknowledgement, the students are guilty of plagiarism. Plagiarism includes reproducing someone else's work, whether it be published article, chapter of a book, a paper from a friend or some file. Plagiarism also includes the practice of employing or allowing another person to alter or revise the work which a student submits as his/her own, whoever that other person may be. Students may discuss assignments among themselves or with an instructor or tutor, but when the actual work is done, it must be done by the student, and the student alone. When a student's assignment involves research in outside sources or information, the student must carefully acknowledge exactly what, where and how he/she has employed them. If the words of someone else are used, the student must put quotation marks around the passage in question and add an appropriate indication of its origin.

7. Placements and Excursions

Apart from the Master thesis project no special placements take place. The rules for the Master thesis project can be found in the Master thesis Rules.

8. Compulsory Attendance

Attendance at lectures, workshops and other educational activities is strongly advised but never strictly required, with the exeption of Research and Ethics I & 2 – attendance for these is compulsory.

9. Foreign Languages used in the Programme

The Master Sensor System Engineering is an international Master and therefore the complete programme is taught in English

10. Cum Laude Regulations

Students can graduate ‘Cum Laude’ if he/she meets the following requirements: a. examinations of units of study to which the pass/fail system is applied must

have been passed within the normal time set for completing the study programme;

b. where a marking scheme is applied, the average of all results must be at least 8.0, no mark may be below 7.0 and the student must have completed his/her studies within the normal length of study.

c. The Master Thesis has to be awarded with at least an 8.0.

33

_____________________________________________________________________________

11. Examination Regulations

Chapter 4a Student Charter: Examination Regulations for Master’s Degree Programmes at Hanze University of Applied Sciences Groningen Article 4a.1 General Provisions 4a.1.1 These Examination Regulations in conjunction with the Teaching Regulations form the Teaching and Examination Regulations for the Master’s degree programmes taught at Hanze UAS. 4a.1.2 In these Examination Regulations, ‘examination’ means an assessment of a student’s knowledge, understanding and/or skills. An examination can be in the form of a written, oral or computer examination, a practical, a practice-based examination or competence assessment, an individual or group (project) assignment or any other form of assessment approved by the Examining Board. Students are assessed individually, also where it concerns group assignments. Examinations may also be referred to as tests. 4a.1.3 For the purposes of these Regulations, a written request or a written communication has the same status as a request or communication made by electronic means. 4a.1.4 Where these Examination Regulations refer to credits, European Credits are meant. One European Credit (ECTS) is equivalent to 28 hours of study. 4a.1.5 If any serious inequity arises in the application of these Examination Regulations, the Examining Board may depart from these regulations as it sees fit. 4a.1.6 In cases which are not covered by the Examination Regulations or the Examination Protocol, the Examining Board decides. Article 4a.2 Educational Programme 4a.2.1 The academic programme, the organisation of teaching and the annual planning of the master’s degree programme is set out in the Teaching Regulations. 4a.2.2 Curricula are divided into units of study. The workload of a unit of study is expressed as credits/ECTS in whole numbers. The workload of the entire master’s degree programme is specified in the Teaching Regulations. 4a.2.3 The units of study comprised in the master’s degree programme are stated in a curriculum overview which forms part of the Teaching Regulations. The number of credits assigned to the various units of study in the curriculum overview correspond to the workload established for the units of study. 4a.2.4 Any prerequisites that may apply to a unit of study are specified in the Teaching Regulations. Article 4a.3 Teaching Regulations 4a.3.1 The Teaching Regulations describe the contents of the master’s degree programme and the units of study which it is comprised of. The Teaching Regulations also include a description of the competencies relating to knowledge, understanding and skills that the student must have achieved on completion of the master’s degree programme. 4a.3.2 The Teaching Regulations describe any practical assignments that are part of the programme. 4a.3.3 The Teaching Regulations state the number and the order in time of examinations, and at what times they can be taken. They also state whether examinations will be taken orally, in writing or in another way, and whether oral examinations are open to public attendance, all subject to the Examining Board’s power to determine otherwise in special cases.

34

4a.3.4 The Teaching Regulations describe how students with a physical or sensory disability can reasonably be given the opportunity to sit examinations. Article 4a.4 Final Examinations A student has passed the final examination if he/she has passed all the particular examinations of the units of study belonging to the master’s degree programme. Article 4a.5 Examinations 4a.5.1 Each unit of study has one or more examinations attached to it. For each study period the Teaching Regulations stipulate the maximum number of examinations that may be administered in that period. 4a.5.2 After a student has passed an examination, the examination result is recorded and credits are awarded. No compensation between examination results is possible. If a unit of study has more than one examination attached to it, the student must pass all the examinations to complete the unit successfully. The Dean may lay down in the Teaching Regulations that students forfeit their examination results if they do not pass all the examinations attached to the unit by the end of the academic year. The Dean will give an explanation of the educational reasons. 4a.5.3 The Teaching Regulations may stipulate that students have to sign up for examinations. Article 4a.6 Term of validity 4a.6.1 Final examinations and the results of individual examinations remain valid indefinitely. 4a.6.2 In respect of students who have been enrolled in a master’s degree programme without interruption, no limitations can be set to the term of validity of credits awarded or exemptions granted, unless the student’s period of enrolment exceeds the nominal length of study plus one year. 4a.6.3 Notwithstanding the provisions of the preceding paragraph, with respect to students who have been enrolled in the Architecture master’s degree programme without interruption, no limitations can be set to the term of validity of credits awarded or exemptions granted unless their period of enrolment exceeds the nominal length of study plus two years. Article 4a.7 Examination results 4a.7.1 Examinations are graded by the examiner(s) who administered the examination. If an examination is graded by more than one examiner, the examiners decide on the grade in consultation. The Examining Board shall draw up guidelines for grading if two or more examiners are involved; these guidelines may include rules for the appointment of a third examiner (why/when and how). 4a.7.2 Examinations are graded and the results announced to students as soon as possible, but no later than twenty days after the examination was held, and no later than five working days before any resit examination. The result of an oral examination is announced on the same day as the examination was held, unless the Examining Board stipulates otherwise. 4a.7.3 Examination results may be announced by electronic means. 4a.7.4 The result of an examination is expressed as a number between 1 and 10 with no more than one decimal after the point, or as a ‘pass’ or ‘fail’. A grade of 5.5 or higher is deemed a pass; a grade below 5.5 is deemed a fail. Participation in an examination is awarded a minimum grade of a 1 or a fail. Article 4a.8 Viewing Examination Papers 4a.8.1 The Examining Board ensures that students have the opportunity of viewing their examination papers within twenty-five working days of the last day of the study period, or no

35

later than five days before the resit, if a resit is offered. Students may only view their examination papers in the presence of the examiner or their deputy. Students are also given the opportunity to take cognizance of the exam questions and the assessment standards. 4a.8.2 The provisions of the preceding paragraph do not apply if the way in which the course is organised makes it impossible to follow the normal procedure. In such a case, the Examining Board shall offer an alternative arrangement for viewing the papers, such that the student can view the examination papers no later than five working days before the resit, if a resit is offered. This procedure must be included in the Teaching Regulations. 4a.8.3 Viewing or taking cognizance of examination papers takes place at a predetermined place and time. 4a.8.4 The Examining Board may set further rules such as a prohibition to carry switched-on photographic or recording equipment during the viewing. Violation of these rules will be considered an irregularity as referred to in Article 5.6. Article 4a.9 Resit Examinations 4a.9.1 If a student retakes an examination, the highest result achieved is recorded. 4a.9.2 Written examinations can be retaken at least once in any academic year. 4a.9.3 Examinations other than those referred to in paragraph 10.2 can be resat in the manner described in the Teaching Regulations for the relevant unit of study. 4a.9.4 If it is decided during an academic year that a certain unit of study, or part of it, will no longer be offered in the following years or will be substantially revised, then the students concerned will be given at least one extra opportunity to take the relevant examination(s) before the end of the academic year after which the new arrangement comes into force. Such resit opportunities are announced at least three months before the resit. Article 4a.10 Exemptions 4a10.1 The Examining Board may, on a student’s written application, grant the student exemption from one or more examinations on the grounds of a competence assessment or because the student possesses a certificate, diploma or other document which proves that they have complied with the requirements of the examination(s) in question. The application may also be submitted electronically. The Teaching Regulations may include regulations regarding procedures for applying for exemptions. 4a10.2 If an Examining Board grants the exemption requested, it sends the applicant a certificate of exemption within four weeks of the day that the application was received. This certificate must state the date on which the exemption was granted and the examination(s) which the exemption applies to. It must be signed by the Chair of the Examining Board. 4a10.3 The Examining Board has the power to grant exemption from the obligation to participate in practical exercises and may impose other requirements instead. 4a10.4 The Teaching Regulations may stipulate that, with regard to the units of study referred to in the regulations, no exemption can be granted for taking the examinations in these units of study. Article 4a.10a Provision of Degrees 4a.10a.1 Students who have successfully passed the final examination of a Master’s degree programme are granted the degree of Master by the Dean. The Executive Board may authorise an officer other than the Dean to award the degree. 4a.10a.2 A student to whom a degree has been granted pursuant to Article 4a.10a.1 is entitled to add the title associated with the degree to their name.

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Article 4a.11 Diplomas 4a11.1 When a student has passed all the examinations of the units of study of a master’s degree programme, the Examining Board confirms that the student has successfully passed the final examination. It awards the associated diploma as soon as the Dean has declared that all the procedural requirements for awarding the diploma have been complied with. The diploma is drawn up in the language in which the course was taught, as determined by the Executive Board. 4a11.2 The diploma awarded for passing the final examination must always state: - the name of the degree programme; - the examination subjects; - the qualifications attached to the diploma, if applicable; - the degree awarded; - the latest accreditation period of the study programme; - if applicable: the successful completion of an Honours Talent Programme; - if applicable: the designation ‘cum laude’, as referred to in article 4a.12 below. 4a11.3 The diploma is accompanied by a list of grades and a diploma supplement. The diploma supplement is drawn up in the English language. 4a11.4 At the student’s request for a charge, the Student Administration provides extra copies of the diploma supplement including a transcript of records, and a certified copy of the diploma. Article 4a.12 Cum laude 4a.12.1 The Examining Board may award a student the classification ‘cum laude’ if the student’s overall achievement meets the following requirements: a. No more than one-third of the total number of the examination credits have been obtained in the form of exemptions; b. All units of study have been completed within the nominal length of time; c. The student has made no more than two attempts at any examination; d. Where a numerical scheme is applied, the average of all results is at least 8.0, no grade is below 7.0 and the student has completed their studies within the normal length of time. The average referred to in the preceding paragraph under (d) is calculated according to a Weighted Grade Average system, where the weighting factor used in calculating the weighted average is the number of ECTS credits which the unit of study represents. 4a.12.2 Without prejudice to the provisions of the preceding paragraph, the Teaching Regulations may stipulate that the result achieved for a certain unit of study must be at least an 8.0. 4a.12.3 A student against whom the Examining Board has taken a measure which deprived him or her of the right to take one or more examinations at Hanze UAS, is not entitled to the classification ‘cum laude’. 4a.12.4 In special cases, the Examining Board may grant exemption from the provisions of the first paragraph under (b) and/or (c). Article 4a.13 Legal protection (See also Chapter 10, Legal Protection) Students can appeal decisions regarding the implementation of the Examinations Protocol to the Student Appeals Board.

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Chapter 5 Student Charter: Examination Protocol for Students Article 5.1 General 5.1.1 This chapter contains rules for the proper conduct of examinations as referred to in Section 7.12 of the WHW Act.

5.1.2 The examiner determines: - the time available for taking the examination or the latest date at which assignments to be assessed must be handed in;

- any aids and materials students may use during examinations. 5.1.3 The examiner prepares the assignments and question papers, draws up assessment criteria, administers the examination and determines the result.

5.1.4 In principle, no more than five per cent of a text excluding any appendices may consist of quotations, unless otherwise provided in the assignment. Quotations and paraphrases must be clearly recognizable as such and the source must be referenced correctly.

5.1.5 Oral examinations are open to public attendance. However, the examiner or the Examining Board may, in exceptional circumstances, decide that an oral examination must be held behind closed doors. The Examining Board can also decide that a second examiner be present at an oral examination. Students can request a second examiner to be present at the oral examination as well and, if this request cannot be met, the examination will be recorded on tape. The student must submit such a request to the Examining Board, no later than five working days before the oral examination will be held. Article 5.2 Examination Sign�up Procedure 5.2.1 For examinations such as those referred to in the second and third paragraphs of article 3.8, students must sign up via Osiris. The sign-up period is announced on the University intranet.

5.2.2 The dates of examinations that are held in the first and second study periods of the academic year are announced at the beginning of the year. The dates of examinations held in the third study period are announced at the beginning of the second period, and those of the fourth period at the beginning of the third period. For the ‘Dance’ and ‘Dance in Education’ bachelor programmes and the ‘Dance’ associate degree programme, the dates of examinations held in the fifth study period are announced at the start of the fifth period. 5.2.3 The timetable stating the start and finish times and the location of each individual examination is announced by the Dean, no later than ten working days before the examinations begin. A term of at least five working days applies to resits held during a study period. 5.2.4 If a student was unable to register for an examination within the time limit because of circumstances beyond their control, they can ask the Examining Board of their study programme to be placed on the sign-up list stating the circumstances.

5.2.5 A student who has not signed up for an examination in accordance with the provisions of this article is excluded from participating. 5.2.6 If signing up via Osiris is not possible for technical reasons, the student must contact their programme with due observance of the time limits stated in article 5.2.2. 5.2.7 After signing up for an examination, the student may cancel their registration via Osiris up to two days before the examination date. Article 5.3 Inability to Attend 5.3.1 A student who has the right to take an examination but is unable to attend due to circumstances outside their control, is entitled to an additional opportunity to take the examination, which they must apply for, if it would be clearly unfair to reject their application.

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5.3.2 To retain this right, the student must submit a written application to the Examining Board, accompanied by evidence if possible. The Examining Board will decide on the application and inform the student of its decision in writing, giving reasons in case of refusal and stating the date, time and place of the examination if the application is granted.

5.3.3 The application referred to in the preceding paragraph must be submitted no later than two weeks after the student was unable to take the original examination because of circumstances outside their control. If these circumstances persist beyond the period stated in the previous sentence, the term of two weeks takes effect from the day that the circumstances no longer apply. Article 5.4 Procedure 5.4.1 Students are required to be present five minutes before the start of the examination in the examination room and to take their seats. If necessary the invigilator will conduct the student to a seat.

5.4.2 Students are required to follow the instructions of the Examining Board, the examiner or the invigilator, which are made known before the start of the examination, and any other instructions given during or immediately after the examination.

5.4.3 If a student ignores any instructions referred to in the second paragraph of this article, the Examining Board, the examiner or the invigilator may exclude him/her from further participation in the examination. Exclusion entails that no grade is given for the examination. Before a decision to exclude a student is taken, the student will be given the opportunity to be heard by the Examining Board. 5.4.4 In urgent cases the Examining Board may take a provisional decision to exclude a student on the basis of an oral report by the examiner or the invigilator. If possible, the student is heard before the provisional decision to exclude him or her is taken. The Board will ensure that this report is put into writing immediately after the examination and that a copy is sent to the student. 5.4.5 Students are required to display their (valid) Hanze UAS student cards on their desks for inspection by the invigilator. If a student is unable to produce their student card, identification may also take place on the basis of a valid driving licence, passport, identity card, residence permit or personal public transport chip card (OV�chipkaart). A student who is not able to identify him/herself in one of these ways must leave the examination room and is barred from participation in the examination. The invigilator shall note such events in the examination record. If the student refuses to leave the examination room, this will also be recorded by the invigilator. The record is sent to the Examining Board of the study programme in which the student in question is enrolled. 5.4.6 If a student is not in possession of a valid identity card because of circumstances beyond his or her control, a police report of fire, theft or loss of the identity card will suffice. 5.4.7 Students are required to sign the attendance roll.

5.4.8 When taking a written examination students should check the question paper to see if the copy they have received is correct and complete. 5.4.9 In written examinations, students are required to write the following details on their examination papers: - their name,

- their student number,

- the code of the unit of study (subject),

- the name of the lecturer teaching the subject being examined,

- the date of participation in the examination.

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5.4.10 A student who has received the questions of the written examination or computer examination or has signed the attendance roll is considered to have participated in the examination.

5.4.11 Students are not allowed to leave the examination room during the first thirty minutes of the examination.

5.4.12 Students arriving not more than fifteen minutes after the start of the examination are allowed to participate.

5.4.13 Students must hand in their papers to the invigilator before they leave the examination room. Question papers and rough work must also be handed in before leaving the room if this is stated on the question paper.

5.4.14 At the end of the examination students may only leave the examination room after the invigilators have collected all papers.

5.4.15 For arrangements concerning extra time or extra facilities during examinations, see article 5.8. Article 5.5 Prohibitions and Disturbances 5.5.1 In written examinations it is prohibited to make the examination on paper other than that supplied by the invigilator. Students requiring extra paper should make this known to the invigilator by raising their hands. Students are not allowed to fetch extra paper themselves. 5.5.2 Written examinations written in pencil do not qualify for assessment, excepting answer forms for optical readers, which do have to be filled in pencil. 5.5.3 All forms of communication between students are prohibited during examinations. Students are also not permitted to see each other’s work or to talk. Telephone use is not allowed. Mobile telephones must be switched off and kept in a closed bag or case. The ringing of a mobile telephone is regarded as a disturbance and will lead to expulsion from the examination room. Wearing a watch may be forbidden. 5.5.4 Students are not allowed to borrow books or calculators from each other during examinations. They are allowed to exchange other items but only after consulting the invigilator, whose attention they should attract by raising their hands. 5.5.5 The use of textbooks, law codes, dictionaries, diskettes, electronic calculators, graphic calculators, mini PCs, translation aids, smartwatches, etc., is not permitted in the examination room except as stated on the examination question paper. Students may if they wish inquire, well before the examination, which aids or materials are permitted. 5.5.6 Items not mentioned as aids as referred to in the preceding paragraph, may not lie on the table during the examination, with due observance of the provisions of article 5.8. 5.5.7 A student who causes a disturbance during an examination or is caught cheating, as referred to in article 5.6, will be removed from the examination room. A student who is removed within 15 minutes of the start of the examination will be escorted by the invigilator to a location designated by the Student Administration Department. The invigilator shall note such incidents in the examination record. If a student refuses to leave the examination room, this will also be recorded by the invigilator. The record is sent to the Examining Board of the student’s study programme. 5.5.8 A student who is removed from the examination room will have their completed work collected. The Examining Board may take action and will also take a decision about the collected work. The provisions of articles 5.6.4 up to and including 5.6.9 apply by analogy in such cases. Article 5.6 Academic fraud 5.6.1 Academic fraud is defined as any act or omission on the part of a student (or external student) which is intended to wholly or partly obstruct the proper assessment of the student’s knowledge, understanding or skills; this includes cheating at an examination. It is also

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considered fraud for a student to act, or desist from acting, with the purpose of partially or wholly obstructing the proper assessment of another student’s knowledge, understanding or skills. A specific form of academic fraud is plagiarism.

5.6.2 Plagiarism is the copying of another person’s work and passing it off as one’s own. In all cases where academic fraud is suspected, the Examining Board is notified.

5.6.3 The Examining Board may take appropriate measures against students who commit academic fraud, including exclusion of the student from participation in examinations at Hanze UAS or any of its departments for a period not exceeding one year. 5.6.4 In the event of repeated cheating or other acts of academic fraud, the Examining Board may take a more severe measure with due observance of the maximum term mentioned in the preceding paragraph.

5.6.5 In serious cases of academic fraud, the Executive Board can terminate the student’s enrolment permanently on the recommendation of the Examining Board.

5.6.6 The Examining Board will give the student the opportunity to be heard before it takes a decision as referred to in the third paragraph of this article.

5.6.7 In urgent cases, the Examining Board may take a provisional decision to exclude a student on the basis of the oral account of the examiner or the invigilator. If possible, the student will be heard before the provisional decision to exclude him or her is taken. The Board will ensure that this account is put down in writing immediately following the examination and that a copy is sent to the student. 5.6.8 If an irregularity is discovered after the end of an examination, the Examining Board may withhold the student’s diploma or decide that the diploma may only be awarded after the student has taken one or more resit examinations, in which case the Examining Board will determine what examinations must be resat and how they will be administered. Article 5.7 Examination Room Facilities 5.7.1 Students are allowed to go to the toilet during examinations after notifying an invigilator who will escort them. No more than one student at a time may be outside the examination room. Visits to the toilet are not permitted during the first sixty minutes and the last thirty minutes of the examination.

5.7.2 The lateral distance between desks used at examinations shall be at least 75 cm. 5.7.3 Eating and drinking are allowed during written examinations provided that the student does not cause any nuisance. 5.7.4 Any bags or cases brought by a student must remain closed and must be stored at a place indicated by the invigilator. Article 5.8 Studying with a Language Deficiency or a Functional Disability 5.8.1 The regulations for written examinations apply in the first place. 5.8.2 Students whose native language is not Dutch, but who meet the NT2 (Dutch as a second language) admission requirement, have the right to extra time at examinations during their first year of enrolment. Requests for additional time are decided on by the Examining Board, which will send a copy of its written decision to the Examinations Unit of the Student Administration Department. 5.8.3 Students whose native language is not Dutch, but who meet the NT2 (Dutch as a second language) admission requirement, have the right to use translation dictionaries during examinations. Requests to use translation dictionaries are decided on by the Examining Board, which will send a copy of its written decision to the Examinations Unit of the Student Administration Department.

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5.8.4 Students who believe they are entitled to extra examination time or other special facilities at an examination because of a (temporary) functional limitation need to make an appointment with one of the student counsellors. 5.8.5 The student should bring the following document(s) to the appointment: - in case of dyslexia, an official certificate of dyslexia;

- in the case of other functional limitations, a medical certificate. 5.8.6 Students with a functional limitation who desire extra time or other special facilities at an examination should send their application to the Examining Board of their study programme no later than 4 weeks before the start of the examination. The Examining Board decides on the application with due observance of the advice given by the student counsellor. Students with chronic functional limitations need to submit an application only once during their studies.

5.8.7 If the student’s application is granted by the Examining Board of his/her study programme, the student will receive a letter from the Examining Board stating his/her right to extra facilities. The Examining Board will send a copy of its decision to the Examinations Unit of the Student Administration Department.

5.8.8 The student must indicate before the start of the examination period, via Osiris, which examinations he/she wants to take.

5.8.9 The registration referred to in the preceding paragraph must be made no later than ten working days before the start of the examination. Article 5.9 Legal Protection (See also Chapter 10) Students can appeal decisions regarding the implementation of the Examinations Protocol to the Student Appeals Board.

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NAMES and ABBREVIATIONS

English Dutch

C/R Compulsory/Recommended V/A Verplicht/Aanbevolen DOP (Digital Course Planner) DOP Digitale Onderwijsplanner E Examination T tentamen Educational Framework Expert Group Expertisegroep Onderwijskader HAVO senior secondary general education HAVO hoger algemeen voortgezet onderwijs HBO higher professional education HBO hoger beroepsonderwijs MBO senior secondary vocational education MBO middelbaar beroepsonderwijs O&O Teaching and Research Department O&O Stafbureau Onderwijs en Onderzoek Programme Committee Opleidingscommissie (OC) SMR School Representative Council SMR Schoolmedezeggenschapsraad STAD Student Administration STAD Studentenadministratie TER Teaching and Examination Regulations OER Onderwijs� en Examenregeling VWO pre-university education VWO voorbereidend wetenschappelijk onderwijs W/O Written/Other S/O schriftelijk/overig WBL Work-Based Learning � duaal onderwijs

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