M.Sc. Computer Science
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A Deep Learning Pipeline for Classifying Different Stages of Alzheimer's Disease from fMRI Data.
Abstract Alzheimer’s disease (AD) is an irreversible, progressive neurological disorder that causes memory and thinking skill loss. Many different methods and algorithms have been applied to extract patterns from ... 
Properties and Algorithms of the (n,k)Arrangement Graphs and Augmented Cubes
The (n, k)arrangement graph was first introduced in 1992 as a generalization of the star graph topology. Choosing an arrangement topology is more efficient in comparison with a star graph as we can have a closer number ... 
Complete computational sequence characterization of mobile element variations in the human genome using metapersonal genome data
While a large number of methods have been developed to detect such types of genome sequence variations as single nucleotide polymorphisms (SNPs) and small indels, comparatively fewer methods have been developed for finding ... 
Learning Strategies for Evolved Cooperating MultiAgent Teams in Pursuit Domain
This study investigates how genetic programming (GP) can be effectively used in a multiagent system to allow agents to learn to communicate. Using the predatorprey scenario and a cooperative learning strategy, ... 
Nonphotorealistic Rendering with Cartesian Genetic Programming using Graphic Processing Units
Nonphotorealistic rendering (NPR) is concerned with the algorithm generation of images having unrealistic characteristics, for example, oil paintings or watercolour. Using genetic programming to evolve aesthetically ... 
Approximation Algorithms using Allegories and Coq
In this thesis, we implement several approximation algorithms for solving optimization problems on graphs. The result computed by the algorithm may or may not be optimal. The approximation factor of an algorithm indicates ... 
Elliptic Curve Cryptography using Computational Intelligence
Publickey cryptography is a fundamental component of modern electronic communication that can be constructed with many different mathematical processes. Presently, cryptosystems based on elliptic curves are becoming popular ... 
Multiobjective Genetic Algorithms for Multidepot VRP with Time Windows
Efficient routing and scheduling has significant economic implications for many realworld situations arising in transportation logistics, scheduling, and distribution systems, among others. This work considers both the ... 
Lossy Compression of Quality Values in NextGeneration Sequencing Data
In this work we address the compression of SAM files which is the standard output file for DNA assembly. We specifically study lossy compression techniques used for quality values reported in the SAM file and we analyse ... 
Shortest Path Routing on the Hypercube with Faulty Nodes
Interconnection networks are widely used in parallel computers. There are many topologies for interconnection networks and the hypercube is one of the most popular networks. There are a variety of different routing paradigms ... 
Statistical Image Analysis for Image Evolution
This thesis is focused on using genetic programming to evolve images based on lightweight features extracted from a given target image. The main motivation of this thesis is research by Lombardi et al. in which an image ... 
Generic Matrix Manipulator System
In this thesis we describe in detail a generic matrix manipulator system that performs operations on matrices in a flexible way, using a graphical user interface. A user defines allowable data entries called a coefficient ... 
Using Age Layered Population Structure for the MultiDepot Vehicle Routing Problem
This thesis studies the NPhard multidepot vehicle routing problem (MDVRP) which is an extension of the classical VRP with the exception that vehicles based at one of several depots should service every customer assigned ... 
A Scalability Study and New Algorithms for LargeScale ManyObjective Optimization
Many realworld optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multiobjective problems (MOPs). Over the past few decades, a plethora of multiobjective ... 
Properties and Algorithms of the KCube Interconnection Networks
The KCube interconnection network was first introduced in 2010 in order to exploit the good characteristics of two wellknown interconnection networks, the hypercube and the Kautz graph. KCube links up multiple processors ... 
GA approach for finding Rough Set decision rules based on bireducts
Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct  the minimal discerning set of attributes  is an important area. ... 
Feature Selection and Classification Using Age Layered Population Structure Genetic Programming
The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is ... 
LFuzzy Structured Query Language
Lattice valued fuzziness is more general than crispness or fuzziness based on the unit interval. In this work, we present a query language for a lattice based fuzzy database. We define a Lattice Fuzzy Structured Query ... 
An Abstract Algebraic Theory of LFuzzy Relations for Relational Databases
Classical relational databases lack proper ways to manage certain realworld situations including imprecise or uncertain data. Fuzzy databases overcome this limitation by allowing each entry in the table to be a fuzzy set ... 
Inverse Illumination Design with Genetic Programming
Interior illumination is a complex problem involving numerous interacting factors. This research applies genetic programming towards problems in illumination design. The Radiance system is used for performing accurate ...