Browsing M.Sc. Computer Science by Title
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A Centrality Based MultiObjective DiseaseGene Association Approach Using Genetic Algorithms
The Disease Gene Association Problem (DGAP) is a bioinformatics problem in which genes are ranked with respect to how involved they are in the presentation of a particular disease. Previous approaches have shown the strength ... 
Characterizing Dynamic Optimization Benchmarks for the Comparison of MultiModal Tracking Algorithms
Populationbased metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many realworld optimization problems. Although it is of ten sufficient to find a single solution to these problems, ... 
Comparison of classification ability of hyperball algorithms to neural network and knearest neighbour algorithms
(20120403)The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, ... 
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 ... 
Construction of IDeletionCorrecting Ternary Codes
(20130408)Finding large deletion correcting codes is an important issue in coding theory. Many researchers have studied this topic over the years. Varshamov and Tenegolts constructed the VarshamovTenengolts codes (VT codes) and ... 
Data mining using Lfuzzy concept analysis.
Association rules in data mining are implications between attributes of objects that hold in all instances of the given data. These rules are very useful to determine the properties of the data such as essential features ... 
Decoding algorithms using sideeffect machines
(Brock University, 20100309)Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems ... 
Deep Learning Concepts for Evolutionary Art
A deep convolutional neural network (CNN) trained on millions of images forms a very highlevel abstract overview of any given target image. Our primary goal is to use this highlevel content information of a given target ... 
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 ... 
DiseaseGene Association Using a Genetic Algorithm
(Brock University, 20141009)Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of highthroughput experiments ... 
DiseaseGene Association Using Genetic Programming
As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme ... 
Effect of the Side Effect Machines in Edit Metric Decoding
The development of general edit metric decoders is a challenging problem, especially with the inclusion of additional biological restrictions that can occur in DNA error correcting codes. Side effect machines (SEMs), an ... 
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 ... 
Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture
(Brock University, 20121107)As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as treebased ... 
Equational Reasoning about ObjectOriented Programs
(20130408)Formal verification of software can be an enormous task. This fact brought some software engineers to claim that formal verification is not feasible in practice. One possible method of supporting the verification process ... 
Evolution of architectural floor plans
(Brock University, 20111013)Layout planning is a process of sizing and placing rooms (e.g. in a house) while a t t empt ing to optimize various criteria. Often the r e are conflicting c r i t e r i a such as construction ... 
Evolutionary synthesis of stochastic gene network models using featurebased search spaces
(Brock University, 20090128)A featurebased fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, ... 
Extending relAPS to first order logic
(Brock University, 20110308)RelAPS is an interactive system assisting in proving relationalgebraic theorems. The aim of the system is to provide an environment where a user can perform a relationalgebraic proof similar to doing it using pencil ... 
Eﬃcient Merging and Decomposition Variants of Cooperative Particle Swarm Optimization for Large Scale Problems
For largescale optimization problems (LSOPs), an increased problem size reduces performance by both increasing the landscape complexity, as well as exponentially increasing the search space size. These contributing factors ... 
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 ...