long uglytestingdeck

Challenging the Internet of the Challenging the Internet of the Future with Future with Urban Computing Urban Computing

Lecturer: Emanuele Della Valle

emanuele.dellavalle@cefriel.ithttp://swa.cefriel.it

http://emanueledellavalle.org

Authors:Emanuele Della Valle, Irene Celino, Kono Kim, Zhisheng Huang,

Volker Tresp, Werner Hauptmann, and Yi Huang

Seven Framework Programme Information Society Technologies (IST)

Specific Targeted Research ProjectFor more information visit http://wiki.larkc.eu/UrbanComputing

Cities born, grow, evolve like living beings.

The state of a city changes continuously, influenced by a lot of factors, human ones: people

moving in the city or extending it

natural ones: precipitations or climate changes

Cities are aliveCities are alive

[source http://www.citysense.com]

OneSpace

Urban Computing as a Way to Address themUrban Computing as a Way to Address them

3 OneSpace

[source IEEE Pervasive Computing,July-September 2007 (Vol. 6, No. 3)]

Availability of DataAvailability of Data

Some years ago, due to the lack of data, solving Urban Computing problems with ICT looked like a Sci-Fi idea.

Nowadays, a large amount of the required information can be made available on the Internet at almost no cost: maps with the commercial activities and meeting places, events scheduled in the city and their locations, average speed in highways, but also normal streets positions and speed of public transportation vehicles parking availabilities in specific parking areas, and so on.

We are running a survey (please contribute), see http://wiki.larkc.eu/UrbanComputing/ShowUsABetterWay http://wiki.larkc.eu/UrbanComputing/OtherDataSources

4 OneSpace

The LarKC projectThe LarKC project

5 OneSpace

[Source: Fensel, D., van Harmelen, F.: Unifying reasoning and search to web scale. IEEE Internet Computing 11(2) (2007)]

Visit http://www.larkc.eu !Visit http://www.larkc.eu !

Actors: Carlo: a citizen

living in Varese. The day after, he has to go to Lombardy Region premises in Milano at 11.00.

UCS: a fictitious Urban Computing System of Milano area

Ways to Milano

Private Car

FS railways

Le Nord railways

A Challenging Use Case 1/5A Challenging Use Case 1/5

6 OneSpace

Varese

Milano

Vision for Urban ComputingVision for Urban Computing

7 OneSpace

Mobility

Tourism

City Planning Culture

Thank you for paying attentionThank you for paying attention

Any Questions?

8 OneSpace

Challenging the Internet of the Challenging the Internet of the Future with Future with Urban Computing Urban Computing

Lecturer: Emanuele Della Valle

emanuele.dellavalle@cefriel.ithttp://swa.cefriel.it

http://emanueledellavalle.org

Authors:Emanuele Della Valle, Irene Celino, Kono Kim, Zhisheng Huang,

Volker Tresp, Werner Hauptmann, and Yi Huang

When Big Data and Predictive Analytics Collide:

Visual Magic Happens

Insights – Analysis – Content Engineering

The Problem: Massive data explosion (mobile, social,

wearable, cloud, m2m etc.) and brands are struggling to make use of this data.

Predictive AnalyticsPredictive Analytics

Predictive Analytics enables decision makers to predict future events and proactively act on that

insight to drive better business.

Predictive AnalyticsPredictive Analytics

Then, Now & Where We’re goingThen, Now & Where We’re going

Most Common Predictive Models

• Clustering – finding groups and predicting themes

• Classification – most popular “Decision tree”

• Association – multi assurance connected buckets

• Link Analysis – relationships

• Text Mining – unstructured data to meaning

• Time Series – predicting a continuous value

• Graph Structure – structure predicts behavior

Where We’re Going – Pattern predictionWhere We’re Going – Pattern prediction

Where to goWhere to go

KDD-Nuggets http://kdnuggets.comRapidMiner http://rapid-i.comR Statistical Computing http://www.r-project.orgRevolution Analytics http://www.revolutionanalytics.com Teradata http://www.teradata.comTableau http://tableausoftware.comSpotfire http://spotfire.tibco.comSAS http://www.sas.comIBM SPSS http://www.ib.com/software/analytics/spssMahout https://cwiki.apahce.org/confluence/display/MAHOUT/AlgorithsWeka Open Source Data mining http://www.cs.waikato.ac.nz/ml/weka Pajek and (large) network analysis and visualization.http://webdatacommons.org/hyperlinkgraph

Tableau DemoTableau Demo http://public.tableausoftware.com/views/PredictiveDataVisualizationwithSSASDataMining/Classification#1

Content Marketing Flow = data Content Marketing Flow = data

Visual Content HubVisual Content Hub

We’re Here to Help YouWe’re Here to Help You

@chasemcmichael sales@infinigraph.com@infinigraph

http://smo.infinigraph.comhttp://www.infinigraph.com

YouTube /infinigraphSlideshare /infinigraph

Great Social Engagement Is About Knowing what drives engagement

Graphs Part-IIGraphs Part-II

DegreeDegree The degree of vertex in an undirected graph is the

number of

edges incident to that vertex. A vertex with degree one is called pendent vertex or

vertex. A vertex with degree zero and hence has no incident

edges is

called an isolated vertex.

In the undirected graph vertex v3 has the degree 3And vertex v2 has the degree 2

Pendent vertexIsolated vertex

Verifying Isomorphic graph

Vertices(A) : a b c d e

Vertices(B): q p r s t

Degree of vertices:

2 3 3 3 1

Edges(A): e1 e2 e3 e4 e5 e6

Edges(B): e’1 e’4 e’3 e’2 e’5 e’6

Graph A

Graph B

Do you think that only one specie can live in a habitat?

NO - many species can live in the same habitat

What are species ?

Species are often defined as a group of organisms capable of interbreeding and producing fertile offspring.

What is a population?

Group of organisms of the same specie

C o m m u n i t C o m m u n i t yyIt is a group of populations living together and

interacting with each other - sharing the same food, places, shelter, water resources, etc, etc . . .

R e e F Forest

> That is an Ecosystem <

YEAHYEAH!!

Limiting FactorsLimiting Factors

A factor or limiting resource is a factor that controls a process, such as organism growth or species population, size or distribution. The availability of food, predation pressure, hard temperatures or availability of shelter are examples of factors that could be limiting for an organism. An example of a limiting factor is sunlight, which is crucial in rainforests.

Another example is rain, which can bust an ecosystem in two ways. One way is rain can destroy an ecosystem is flood. Flooding can wash away shelter, food, and even parts of the life-form's population itself. The other way rain can destroy an ecosystem is drought. The main way it can destroy an ecosystem is the depletion of food sources.

Episode 01

LIVING THINGS AND THELIVING THINGS AND THE ENVIRONMENTENVIRONMENT

OBJECTIVE :OBJECTIVE : In this unit we will In this unit we will study the different rolls and study the different rolls and impact that the living things impact that the living things

have on the environment. There have on the environment. There will be a strong focus in the will be a strong focus in the

interaction that organisms have interaction that organisms have among themselves and the among themselves and the

environmentenvironment

How is a cat similar and different from a fish besides the physical appearance ?

Organisms that live in different habitats

el “ Gato volador ”el “ Gato volador ”

What is an Organism ?

It’s a Living thing that has (or can develop) the ability to act or function independently

Where do organisms live?

They live in their habitats

What is a habitat?

It is the physical space that has all the propped conditions for an organism to live,

and reproduce. It has to provide the necessary food and water needed to

survive

The Dow’s 5 Most Loved Stocks

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required information

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specific parking areas

urban computing lecturer

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ieee internet computing

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