An application area of increasing importance is creating agent-based simulations to model human societies. One component of developing these simulations is the ability to generate realistic human social networks. Online social networking websites, such as Facebook, Google+, and Twitter, have increased in popularity in the last decade. Despite the increase in online social networking tools and the importance of studying human behavior in these networks, collecting data directly from these networks is not always feasible due to privacy concerns. Previous work in this area has primarily been limited to 1) network generators that aim to duplicate a small subset of the original network's properties and 2) problem-specific generators for applications such as the evaluation of community detection algorithms. In this thesis, we extended two synthetic network generators to enable them to duplicate the properties of a specific dataset. In the first generator, we consider feature similarity and label homophily among individuals when forming links. The second generator is designed to handle multiplex networks that contain different link types. We evaluate the performance of both generators on existing real-world social network datasets, as well as comparing our methods with a related synthetic network generator. In this thesis, we demonstrate that the proposed synthetic network generators are both time efficient and require only limited parameter optimization.

With the emergence of the internet as a new business channel and its impact on the overall role of today¿s customers, existing models for the measurement of perceived quality, satisfaction and loyalty are worth revisiting. This is specifically important in light of the prominent progress of some of the new business concepts, particularly customer experience management, and the rising emphasis on customers¿ hedonic and emotional needs. This study attempts to bridge the gap in existing literature by examining the online customer experience in its entirety, attending within the study to both the utilitarian and hedonic needs of online customers and giving special attention to emerging aspects in the online environment, such as customer engagement in self-driven experiences. Therefore, the study includes a comprehensive review of a large body of knowledge, both in consumer behaviour and marketing literature as well as quality management literature, in addition to a scrutiny of 50 studies for different evaluation models in the online environment. This is in order to identify a list of attributes and factors that impact customer evaluations of online experiences. Upon the synthesis of the list of attributes and factors that impact customer evaluations of online experiences, an online blog was created as an environment for asynchronous focus groups. The online blog was beneficial in creating a deeper understanding of what online customers want and what impacts their experiences. Following, an online questionnaire was administered in two stages, once for measure purification purposes which received 90 pilot responses and once for mass data collection purposes which received 366 responses. As a result of this study, an integrated model for the measurement of online customer experience that emphasises the significance of the emotional component was proposed. The model consists of three components, each serve a specific measurement purpose. The XQual construct which consists of 7 attributes and 30 factors, is a performance measure of the experience in relation to specific aspects that address customers¿ utilitarian and hedonic needs. The satisfaction continuum consists of four factors and is an output measure for each experience or transaction with the online firm. The loyalty continuum consists of four factors and is an outcome measure that indicates customers¿ attitudinal commitment towards the online firm.

[pt] A interpretação sísmica é um processo fundamental para a exploração de hidrocarbonetos. Essa atividade consiste na identificação de informação geológica através do processamento e análise de dados sísmicos. Com o crescimento acentuado e a complexidade dos dados sísmicos, a análise manual de fácies sísmicas tornou-se um desafio significativo. O mapeamento de fácies sísmicas é um processo demorado e que requer profissionais especializados. O objetivo deste trabalho visa aplicar a classificação multiatributos usando uma rede neural encoder-decoder para mapear as fácies sísmicas e auxiliar no processo de interpretação. Um conjunto de atributos sísmicos, foram calculados utilizando o software Opendtect versão 6.6 a partir dos dados de amplitude contidos no Dataset Facies-Mark . Sendo eles: Energia, Pseudo Relevo, Fase instantânea e Textura, todos foram selecionados por um intérprete. A função de perda utilizada pela rede foi weighted categorical crossentropy, pelo fato das classes serem consideravelmente desbalanceadas. O treinamento foi realizado nas direções inlines e crosslines para as respectivas combinações: atributos, atributo + amplitude, e somente a amplitude. Os resultados baseado na métrica frequency weighted intersection over union (FWIU), mostraram que os atributos junto com a amplitude obtiveram o melhor resultado, 85,73 por cento, em comparação com as outras combinações citadas. Em comparação direta com o trabalho que inspirou essa dissertação, o multiatributos performou melhor. / [en] Seismic interpretation is a fundamental process for hydrocarbon exploration. This activity consists of identifying geological information through the processing and analysis of seismic data. With seismic data s rapid growth and complexity, manual seismic facies analysis has become a significant challenge. Mapping seismic facies is a time-consuming process that requires specialized professionals. The objective of this work is to apply multi-attribute classification using an encoder-decoder neural network to map the seismic facies and assist in the interpretation process. A set of seismic attributes were calculated using Opendtect version 6.6 software from the amplitude data contained in the Facies-Mark Dataset. These being: Energy, Pseudo Relief, Instant Phase, and Texture were all selected by an interpreter. The loss function used by the network was weighted categorical cross-entropy, because the classes are considerably unbalanced. The training was performed in the inlines and crosslines directions for the respective combinations: attributes, attribute + amplitude, and only the amplitude. The results based on the frequency weighted intersection over union (FWIU) metric showed that the attributes along with the amplitude obtained the best result, 85.73 percent, compared to the other combinations mentioned. In direct comparison with the work that inspired this dissertation, multi-attribute performed better.

<p> Historically, pneumatology has had little influence on the Christian doctrine of God. In particular, although Christians throughout the ages have defended the deity of the Spirit, they have not adequately taken the economic activity of the Spirit into consideration when formulating the doctrine of the divine attributes. In an effort to correct the historical lack of influence that pneumatology has had on the doctrine of the divine attributes, this book advocates and explores the potential of a pneumatological approach to the doctrine of the divine attributes by presenting pneumatological revisions to classical theism. The thesis of this book is that a pneumatological approach to the doctrine of God recovers an emphasis on divine immanence, which has been marginalized by classical theism's imbalance toward divine transcendence. After the introductory chapter, chapter two illustrates how classical theism neglects the doctrine of the Trinity (and pneumatology in particular) in its formulation of the doctrine of the divine attributes and how classical theism privileges divine transcendence. Chapter three provides a review of how process theologians, evangelical theologians, and trinitarian theologians critique and revise classical theism and displays how contemporary theologians have only begun to develop a pneumatological approach to the doctrine of the divine attributes. Chapter four continues by recommending a pneumatological approach to the divine attributes. The remainder of the book illustrates how pneumatology provides a way to revise the classical accounts of divine impassibility, immutability, and omnipotence. In contrast to classical conclusions regarding these doctrines, pneumatological perspectives on the doctrine of the divine attributes portray God as suffering, changing his presence, and exercising his omnipotence kenotically.</p> / Thesis / Doctor of Philosophy (PhD)

Software quality attributes are properties that reflect the quality of a software system, and Non-functional requirements (NFRs) are the specifications that define how a software system should perform to reach a desired level of goals of the quality attributes.The evaluation of quality attributes is important to show the effectiveness of a system in meeting customers' NFRs. Continuous integration (CI) environments have emerged as powerful platforms for organizations to improve software quality through automated software verification and validation.Despite this, there is a growing need for evaluating quality attributes that is often met by in-house development of metrics and tools.This highlights the importance of quality attributes for software product quality. This thesis investigates the association between quality attributes and components of a CI environment, as well as how to utilize these components for evaluating software quality attributes.The focus is on improving the knowledge of the evaluation and providing specific recommendations for companies to enhance their CI environments for higher demands of quality evaluation.The contributions of this thesis include a better understanding of the relationship between quality attributes and CI components, and a set of practical guidelines for companies to effectively leverage CI for quality attribute evaluation. The studies in this thesis utilized mixed methodologies, including a systematic literature review, a multi-case study conducted in four software development companies, and an synthesis of the collected data.The multi-case study provided a comprehensive overview of practices for quality attribute evaluation and how CI components can generate data to support the evaluation of specific attributes.The synthesis study presents a maturity model based on the collected data from both academia and industry, and the model can aid organizations in assessing their current level of maturity in utilizing CI environments to identify potential improvements.The results in these studies show the capabilities of different components of a CI environment and how these components can be used to support the evaluation of quality attributes.While the use of CI environments for the thesis topic offers benefits, it also presents several challenges, for example, the challenge to identify effective quality metrics. In conclusion, this thesis contributes to the understanding of the use of CI environments for evaluating software quality attributes.The results suggest that CI environments can be an effective approach for quality attribute evaluation, but suitable metrics need to be considered to ensure accurate and meaningful evaluation results. Furthermore, the thesis presents areas for future research, such as the use of machine learning techniques to improve the accuracy of quality assessment using CI environments.

Java applications consume energy, which has become a controversial topic since it limits the number of machines and increases the cost of data centers. This paper investigates the potential relationship between energy consumption and some quality attributes for Java Collections and Sorting algorithms in order to raise awareness about using energy-efficient programs. In addition, introduce to the developers the most and least efficient Java Collection and Sorting algorithm in terms of energy consumption, memory, and CPU usage. This was achieved by conducting a controlled experiment to measure these terms. The data obtained for the results was used to acquire Statistical and Efficiency Analysis to answer the research questions.

Maintaining and increasing customer loyalty has become a crucial strategic objective for businesses due to cross-shopping and intensified competition across many industries. In the realm of grocery retailing, the necessity for retailers to invest resources towards fostering customer loyalty has reached unprecedented levels, primarily due to the proliferation of shopping formats accessible to customers. Hard discounters are among those store formats. They are stores that offer basic goods and daily necessities at the lowest prices possible while maintaining high-quality standards. Due to the tough economic times, consumers are becoming more price-oriented which makes them switch some of their shopping to hard discounters and when they do, they learn that quality, assortment, and service are actually better than expected which leads to them remaining loyal to the store when good economic times return. However, to be able to achieve and maintain loyalty, stores must first create store satisfaction. And that store satisfaction is in turn based on other factors, such as store attributes and the store's physical environment. Nevertheless, existing marketing research offers limited assistance to retail managers when it comes to maintaining loyalty for hard discounters. Therefore, the purpose of this thesis is to analyze which store image attributes can create store loyalty in a store environment for hard discounters within the Swedish grocery market. This study intends to explore the relationship between store attributes, store image, store satisfaction, and store loyalty within hard discounters. Towards filling this gap, a conceptual model considering the effects of store image attributes on store satisfaction and store loyalty is proposed. Data was collected from a survey of 151 Swedish shoppers at hard discounters. The data was then analyzed using IBM SPSS. when analyzing the data, the results show that the store attributes atmosphere and price had the biggest impact on store satisfaction, followed by assortment and personnel which exerts a moderately positive impact on store satisfaction. However, service did not exert a positive influence on store satisfaction. Ultimately, store satisfaction exerts a strong positive effect on store loyalty to hard discounters. In conclusion, the results indicate that there is a relationship between store image attributes, store satisfaction, and store loyalty for hard discounters in the Swedish grocery market.

Between 1994 and 2003, two related concerns were in the educational spotlight. The first concern was participation rates of low income students in higher education. The second was the apparent disparity in Internet usage by low income and other disadvantaged individuals, highlighted in the report Falling Through The Net (United States Department of Commerce, 2000). The purpose of this study is to identify the economic factors and demographic attributes that influence participation of low income students in online distance learning courses offered by a Mississippi community college. This study centers on the hypothesis that there is no statistically significant difference between low income and non low income student participation rates in online distance education courses and that the economic factors, other than income, between low income participates and non low income participants will be statistically similar. Survey data collected from analyzed through the use of logistical regression to determine the relationship of demographic and economic factors to the decision to enroll in future online courses. It was found that students who are older and married are less likely to choose to enroll in future online distance learning courses. Students with higher numbers of courses completed and who paid for college with personal funds are more likely to enroll in future online distance learning courses than those with fewer numbers of distance learning hours completed and those who experience less difficulty traveling to campus are less likely to choose to enroll in future distance learning courses.

A greater emphasis is being placed on hardwood management, yet there has been relatively little effort to develop growth and yield information for hardwood forest types. Measurements on permanent growth and yield plots collected in 1981, 1988, 1994, and 2006 in minor stream bottoms in Mississippi and Alabama were used to construct a stand level growth and yield model for red oak/sweetgum stands. The model predicts arithmetic mean diameter, quadratic mean diameter, trees per acre, basal area, total tree height, and cubic foot volume per acre for the total stand and by species. Different sets of equations were constructed depending on the amount of information known about a hardwood stand. Models were chosen based on significance of variables, coefficient of determination, index of fit, and biological trends. Predicted stand development patterns are discussed. These models will be base models for a complete diameter distribution growth and yield model.

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