Cutting Edge Research- Posters Event On Tuesday for those who can’t make Wednesday

Date: Tuesday 05 Mar 2013
Time: 19:00 – refreshments from 18:30
Speaker: Selected PhD students – Coventry and Warwick University
Location: Engineering and Computing building EC 1-29 Coventry University


As with last year, selected students from both Warwick and Coventry Universities will present their leading edge research. This is your chance to get up-to-date with the cutting edge in a number of fields in only one hour!

In no particular order: (well, actually in the order we received them!)

Entertaining Subnetting:
Mohammad Hijji, Coventry University
This research presents an educational game to support lecturers in ‘computer networking classes’ through make students to practice the concept of ‘Subnetting technique’ entertainingly. The game uses several application classes as ‘engines’ to train users on Subnetting technique. The design of game takes into account Human Computer Interaction (HCI), targeted audience and their pre-required knowledge. The UML and storyboard used to design the game. C# used to implement the designed framework for the game. The game constructed, and tested successfully, and evaluated through a process of primary data collection.
Key words: Subnetting Game, Converting Decimal to Binary Game, Converting Binary to Decimal Game, IP address classes Game, IP hosts Game, Subnet Game.

Agent Crowd Behaviour
Investigating links between the perceived realism and virtual realism of agent crowd behaviour within a simulated urban environment.
Stuart O’Connor, Coventry University
In this research, the implications of specific features discerned from a real-life scene and incorporated into an urban crowd simulation are discussed and evaluated with regards to both the virtual and perceived realism of agent crowd behaviour, highlighting links between the two types of realism. A cycle methodology consisting of the three elements, analysis, synthesis and perception was employed to enhance and test the simulations virtual and perceived realism over many generations in order to achieve a corpus of results from which to draw conclusions. The processed data from this research provides an in-depth insight into the quantity and type of features that are required to be incorporated into a crowd simulation in order to implement a single or combination of the two types of realism.

Stego-Image Creation
Creating Stego-Images through hiding single and multipile data using different steganographic tools
Ahd Al Jarf, Coventry University (Coventry Winner)
Recently, the concept of “Image Steganography” is became an important issue in the computer security world. Image steganography simply means hide some secret data into an object. The object can be a text, an image or a sound, but the most popular cover object used for hidden secret message is images.
On the other hand, to detect these hidden messages, many methods and techniques can be used as well. However, the procedures of detecting any hidden data, is called ‘Steganalysis’.
This research focuses on creating stego-images through hiding secret messages into clean images. It also reviews some image steganography methods and tools. In order to create a number of stego-images, three steganographic tools are used. They are: OpenStego, S-Tools and F5 algorithm. With respect to the hidden data, one and more hidden data file is embedded. In addition, testing for differentiating between stego-images created and the clean one is presented.

Cardiovascular Health and Air Pollution
Spatio-Temporal Analysis of the Effects of Air Pollution Hazards on Cardiovascular Health Outcomes in Bangalore, India
Anitha Chinnaswamy, Coventry University
The aim of this research is to provide a spatio-temporal study of the impact of air pollution on cardiovascular disease through the development of a Web-based Geographical Information System (GIS) application. The study will determine the general effects of air pollution on cardiac disorders and the possible links that may exist between various air contaminants and cardiovascular disease (CVD) in Bangalore. A Web-based GIS tool will be used to manage, store, analyse, and map disease information. This will be developed to assist cardiologists, healthcare providers and environmental stake holders in decision making and in the provision of optimal care to patients.

Energy Management for Hybrid Electric Vehicle (HEV).
Abdulazeez El-Ladan, Coventry University
Energy management for HEV centred on battery management system as is critical in nature for energy power train system application, this is because of high number of cells in the battery pack. Besides battery pack is design not only to provide long lasting energy but also deliver high power. The degradation of battery is characterized by capacity decrease due to repeated charge cycles, especially with the case of Li-ion which is now considered to be the most promising battery for EVs and HEVs .However temperature uniformity within cells of the battery packs is too important in achieving maximum life cycle of the pack.
The research here intends to use advance control approach aimed at optimizing the electric energy flow in HEV, with the hope of achieving the following optimal objective:
Minimize battery degradation, reduce gas emission, improve battery longevity, maintain the battery power flow and optimize vehicle range.

Literature Duplication Detection
An Approach to Literature Duplication Detection and Investigation in Medical Domain Using Latent Semantic Indexing
Muna Alsallal, Coventry University
Research suggests that there are an increasing number of duplicate publications within the medical domain (Nayak, 2009). This is worrying not only because it violates the copyright law of journals but also because it artificially extends authors’ biodata and misleads readers into thinking that what they are reading consists of original research. This paper focuses on analysing the way in which latent semantic indexing (LSI) is being used to detect duplicate publications within this domain and argues that its semantic categorisation of different documents means that it is more effective at detecting similarities between different documents when compared to alternative algorithms. However, empirical research suggests that it is also associated with a lower degree of precision, with a large number of false positives. It is suggested that this may be due to the failure to identify an optimal set of noise reduction parameters although it is clear that further empirical research needs to be conducted before this can be fully ascertained.

Empirical Mode Decomposition for feature extraction in Motor Imagery responses for BCI.
Simon Davies from WMG, University of Warwick
Presenting a novel method, based on multi-channel Empirical Mode Decomposition (EMD), of classifying the electroencephalogram (EEG) recordings of imagined movement by a subject within a brain-computer interfacing (BCI) framework. EMD is a technique that divides any non-linear or non-stationary signal into groups of frequency harmonics, called Intrinsic Mode Functions (IMFs). As frequency is a key component of both IMFs and the µ rhythm (8-13 Hz brain activity generated during motor imagery), IMFs are then grouped by frequency. EMD is applied to the recordings from two electrodes for each trial and the resulting IMFs are grouped according to peak-frequency band via Hierarchical Clustering Analysis (HCA). The cluster containing the frequency band of the µ rhythm (8-13 Hz) is then selected and the sum-total of the IMFs from each electrode are summed together. A simple linear classifier is then sufficient to classify the motor-imagery with 89% sensitivity from a separate test set.

Developing Communication-aware Service Placement Frameworks in the Cloud Economy
Chao Chen, Department of Computer Science, University of Warwick
In a Cloud system, a number of services are often deployed with each service hosted by a collection of Virtual Machines (VM), and the services may interact with each other. In this paper, we present a method to determine the sufficient number of VMs for the interacting Cloud services in a Cloud. The proposed method borrows the ideas from the Leontief Open Production Model in economy. Further, this paper develops a communication-aware strategy to place the VMs to Physical Machines (PM), aiming to minimize the communication costs incurred by the service interactions. A genetic algorithm is developed to find a VM-to-PM placement with low communication costs. Simulation experiments have been conducted to evaluate the performance of the developed communication-aware placement framework. The results show that compared with the placement framework aiming to use the minimal number of PMs to host VMs, the proposed communication-aware framework is able to reduce the communication cost significantly with only a very little increase in the PM usage.

Quality in Closed-loop Lifecycle Management (QCLM)- Methodology & Implementation
Avishek Pal, WMG, University of Warwick
Quality in Closed-loop Lifecycle Management (QCLM) is a novel methodology of conducting root cause analysis and correction of product failures in service such as warranty and No-Fault-Found issues. It integrates heterogeneous data from service, manufacturing and design phases of product lifecycle on a common computing platform to apply machine learning algorithms that mine fault patterns from service data. These fault patterns are then correlated using statistical methods with manufactured dimensions and design specifications to root cause the failure. This is followed by multi-objective optimization to find the optimal corrective action. An IT architecture, leveraging in-database analytics, is also suggested for implementation of the methodology.

RLW Navigator
Software Architecture and Multidisciplinary Optimisation for Embedding New Production Processes
Abhishek Das, Digital Lifecycle Management Group, WMG, University of Warwick (Warwick winner)
Remote Laser Welding (RLW) Navigator aims to develop an innovative Process Navigator to configure, integrate, test and validate applications of Remote Laser Welding (RLW) in automotive assembly addressing today�s critical needs for frequently changing operating conditions and product-mix provisions. Thus, RLW Navigator will crucially serve as an enabler for future energy efficient smart factories. Currently, RLW systems are limited in their applicability due to an acute lack of systematic ICT-based simulation methodologies to navigate their efficient application in automotive manufacturing processes. RLW Navigator aims to develop a Process Navigator simulation system that will deal with the key challenges thereby allowing manufacturers to utilise the advantages of the RLW system.

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