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Virtual Labs

This project was concerned with the preparation of teaching materials to assist in the teaching procedure of graduate programs in ICT and Energy Systems, School of Technology. The proposed project was necessary to supply several software platforms, which provided essential infrastructure for the teaching and research activities for the School of Technology.

The proposed Virtual Labs implemented a number of experiments using a graphical user interface on several key topics for the Master courses. The delivered software has provided an interactive opportunity for students to experiment and deepen their knowledge and understanding of the presented material. The delivered software must be scalable and expandable to cater for the future research and teaching needs. The following virtual labs are currently under implementation:

Wireless Telecommunication and Sensor Networks

Wireless Telecommunication and Sensor Networks

Research Assistant: Mr. Christos Liaskos
Academic Associate: Dr. George Koutitas
Courses covered: Mobile Communications & Sensor Networks

Under this virtual laboratory, several interactive exercises through Graphical User Interfaces (GUIs) were implemented, through which the students were able to practice some of the theoretical aspects taught in class. The aim was to introduce the student to common industrial problems and allow an in depth analysis and practice of the theory. This virtual laboratory has covered the following topics

 

Mobile Communication Networks

1. Virtual antenna simulation with applications. Empirical propagation models. Coverage estimations.

  • Antenna radiation pattern computation and visualization
  • Empirical propagation models
  • Coverage predictions
  • Antenna positioning effects
  • Point to point predictions
  • Predictions over measurement lines
  • Predictions over a plane
  • Link budget analysis

wtsn1

 

2. Narrowband and Wideband channel characteristics

  • Rayleigh Channels
  • Rice Channels
  • Statistical generation of wireless channels
  • First order fading statistics
  • Second order fading statistics
  • Narrowband channel modeling
  • Wideband channel modeling

wtsn2

3. Virtual drive test

  • Virtual drive test in a microcells urban environment
  • Virtual drive test in macrocell hilly environment

wtsn3

4. Applications for WLAN and Single Frequency Networks

  • Network Planning for an indoor WLAN system
  • Network Planning for a Single Frequency Network in a rural environment

 

wtsn4

Sensor Networks

1. Sensor battery lifetime simulations.

2. Spatial distribution of sensors over different area types. Network formation, routing.

3. Simplified simulations of communication protocols.

wtsn5

 

Multimedia Systems in Telecommunication, Medicine and Remote Sensing applications

Multimedia Systems in Telecommunication, Medicine and Remote Sensing applications

Research Assistant: Dr. Dimitrios Alexiadis
Academic Associate: Dr. Nikolaos Mitianoudis
Courses covered:

Multimedia Content Management

Medical Imaging

GIS and Remote Sensing

 

Under this virtual laboratory, several interactive exercises through Graphical User Interfaces (GUIs) were implemented, through which the students have been able to practice some of the theoretical aspects taught in class. This virtual laboratory covered the following topics:

 

1. Audio-Image-Video Encoding and Compression. More specifically, the students interacted with:

 

• The concept of transform coding, i.e. coding in transform domain, in which the energy-information tends to be concentrated in a few major coefficients.

 

• The concept of Scalar and Vector Quantization, which is the essential part of “lossy” encoders.

 

• Entropy coding (encoding Huffman, arithmetic coding, etc.), which is the last subsystem of modern codecs, which does not result in loss of information (lossless).

 

• Audio Coding : the compression standard MP3 (MPEG Audio Layer III). Attention was paid mainly on the lossy psychoacoustic masking, based on the limitations of the human hearing system.

 

• Still Image Coding: the compression formats JPEG and JPEG-2000 were visualized with special emphasis on the 2-D Discrete Cosine Transform (DCT) and the 2-D Discrete Wavelet Transform (DWT).

 

• Compression of moving pictures: The encoding standards MPEG1-MPEG2 and MPEG-4 have been presented. In the case of MPEG1-MPEG2, apart from a single frame coding (intra-frame coding), focused on motion estimation (motion vectors) between successive frames. In the case of MPEG-4, the focus was on the separation of moving objects, the encoding of shape and motion of which is the basic idea of the model.

 

mult_sys1

 

 
 

2. Streaming audio and video through communication channels are susceptible to noise and errors. This study examined the impact of transmission errors and packet loss on the quality of decoded signals and the bit-error rate. Forward Error Correction / Detection techniques that are 'hiding' the error in the decoder.

 

mult_sys2

 

 
 

3. Equalization - Noise Reduction - Registration - fusion of medical images. More specifically:

 

• Image Equalization: histogram equalization and local adaptive methods for image enhancement.

 

• Image Noise Reduction: Noise Reduction methods with simple filters (moving average, middle) and shrinkage methods using 2-D wavelet 2-D directional local bases (curvelets, contourlets) or 2D self-trained bases using Independent Component Analysis.

 

• Image Registration and Fusion: The concept of registration and fusion of images acquired from different modality sensors.

 

 

4. Fusion Applications on remote sensing images.

 

With the help of the corresponding interactive graphical display (GUI), students have been able to experiment with the parameters and observe the effect of these on the performance of remote sensing imaging fusion algorithms (pansharpening).

Decision Support Systems and Knowledge Management

Decision Support Systems & Knowledge Management

A. Decision Support Systems

Academic Associate: Dr. Christos Berberidis
Research Assistants:

Dr. Fotios Kokkoras

Mr. Konstantinos Paraskevopoulos

Courses Covered: Decision Support Systems

 

The purpose of this virtual lab was to develop interactive training material on Decision Support Systems. The educational material was developed in the form of training workshops/ experiments based on specialized software that allowed the learner:

 
  • understand in a practical manner the relevant theoretical knowledge through analytical solved problems that highlighted the current issues of theory
  • to check the degree of theory understanding, by solving problems and exercises
 

The above activities were conducted using specialized software that was either developed by the scientific team or free, open source popular software tools and platforms that were evaluated and selected to be used.

In particular, the delivered software provided an interactive opportunity for students to experiment and to deepen in a supervisory manner to topics that deal with. In addition, it allowed the teacher to create additional teaching material to meet possible future needs.

 

The thematic contents of the deliverable software to create training workshops are:

 

1. Simple decisions under certainty: Multicriteria Methods

Software and training workshops that were developed to allow students to interact with the following multicriteria methods:

  • Weighted Average Sum (WAS),
  • ELECTRE methodology
  • Analytic Hierarchy Process (AHP)

 

DSS1

 

2. Simple Decisions under ignorance

Software and training workshops were be delivered for the following decision rules:

  • MaxiMax / MiniMin,
  • MiniMax / MaxiMin the Wald,
  • Hurwicz rule,
  • MiniMax Regret Savage rule

 

3. Simple Decisions under uncertainty

Delivered software and training workshops on:

  • Bayesian Networks
  • Decision Trees (Trees sequential decisions)
  • Game Theory

 

DSS2

 

4. Decision making through data analysis

Software and training workshops covered:

  • Classification trees
  • Neural Networks
  • Genetic Algorithms
  • Clustering
  • Association Rules

 

DSS3

DSS4

 

B. Knowledge Management

Academic Associate: Dr. Christos Berberidis
Research Assistants:

Mr. Efstratios Kontopoulos

Ms. Kalliopi Kravari

Courses Covered: Knowledge Management, Decision Support Systems (partial), Web Information Systems (partial)

 

This virtual laboratory involves a wide variety of task-oriented exercises grouped by escalating difficulty levels. Students progressively proceeded through the material with the help of popular free third-party software tools as well as rich Graphical User Interfaces (GUIs) that were implemented for the purposes of the course.

The aim was to allow the students to get acquainted with modern (web) Knowledge Management (KM) technologies, practice the theoretical aspects taught in class and progressively develop a practical, real-life Web application (e.g. “Amazon-like” e-commerce web site).

 

DSS5

 

The following topics were covered:

  • XML (Extensible Markup Language), which is a set of rules for encoding documents electronically. More specifically, students practiced with: (a) The XML Syntax and the three main XML building blocks, (b) DTD and XML Schema, (c) XML namespaces, (d) XML querying via XPATH and (e) XML processing via XSLT.
  • RDF (Resource Description Framework), a standard model for data interchange on the Web. More specifically, students focused on: (a) The RDF triple-based model of statements, (b) RDF Schema (RDF/S), (c) RDF querying via SPARQL, and (d) RDF processing/parsing via Jena, a Java library for processing RDF and RDF/S documents.
  • OWL (Web Ontology Language), a family of knowledge representation languages for authoring ontologies. Users got familiarized with: (a) The OWL syntax, which heavily builds on RDF and XML, (b) The three increasingly expressive OWL sublanguages (OWL Lite, OWL DL, OWL Full), (c) The basic notions of ontologies and ontology engineering, the main methodologies for manually and (semi)automatically constructing ontologies as well as reusing existing ontologies and the most widely-used software tools for these tasks.

DSS6

 

 

 

  • Logic & Inference, the study of reasoning and the process of drawing a conclusion by applying logical clues. Users got familiarized with: (a) Deductive rules, (b) Production rules, (c) Monotonic rules, (d) Non-monotonic rules.

 

  • Knowledge and Ontology Engineering. Users got familiarized with: (a) Knowledge-based systems, especially with their development cycle and architecture, (b) knowledge elicitation, (c) manually constructing ontologies, (d) re-using existing ontologies, (e) using relevant methodologies, semi-automatic methods and popular tools.
  • Knowledge search. Users got familiarized with semantic search and knowledge portals by using popular SW Search Engines, such as Semantic Web Search Engine (SWSE), Sindise, Watson, Yahoo! Microsearch, Falcons, Swoogle, Semantic Web Search and Zitgist Search.

 

DSS7

For more details please visit http://rad.ihu.edu.gr/index.php?id=10