Removing Oneself from the Shadows: A Heuristic Inquiry to Understand the Lived Experience of Epilepsy in Young Adult Women and their Epilepsy Disclosure

Epilepsy is a chronic neurological disorder characterized by recurrent seizures (Stein & Kanner, 2009). The purpose of this study was to understand the essence of being a young woman living with epilepsy using heuristic inquiry (Moustakas, 1990). The research was built upon the assumption that each experience is unique, yet commonalities exist. Five women aged 22 to 28 years living with epilepsy were interviewed. Additionally, the researcher described her life with epilepsy. Participants characterized life with epilepsy as a transformative journey. The act of meeting and interacting with another woman living with epilepsy provided an opportunity to remove themselves from the shadows and discuss epilepsy. Three major themes of seizures, medical treatment, and social relationships were developed revealing a complex view of an illness requiring engaged advocacy in the medical system. Respondents frequently make difficult adjustments to accommodate epilepsy. This study provides a complex in-depth view of life with epilepsy.

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 well-known interconnection networks, the hypercube and the Kautz graph. KCube links up multiple processors in a communication network with high density for a fixed degree. Since the KCube network is newly proposed, much study is required to demonstrate its potential properties and algorithms that can be designed to solve parallel computation problems. In this thesis we introduce a new methodology to construct the KCube graph. Also, with regard to this new approach, we will prove its Hamiltonicity in the general KC(m; k). Moreover, we will find its connectivity followed by an optimal broadcasting scheme in which a source node containing a message is to communicate it with all other processors. In addition to KCube networks, we have studied a version of the routing problem in the traditional hypercube, investigating this problem: whether there exists a shortest path in a Qn between two nodes 0n and 1n, when the network is experiencing failed components. We first conditionally discuss this problem when there is a constraint on the number of faulty nodes, and subsequently introduce an algorithm to tackle the problem without restrictions on the number of nodes.

A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization

Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.