[Truncated abstract] Online games are an exciting new trend in the consumption of entertainment and provide the opportunity to examine selected antecedents of online game-playing based on studying the cognitive, experiential and habitual factors. This study was divided into two parts. The first part analysed the structural relations among research variables that might explain online game-playing using the Structural Equation Modeling (SEM) techniques. These analyses were conducted on a final sample of 218 online gamers. Specific issues examined were: If the variables of Perceived Game Performance, Satisfaction, Hedonic Responses, Flow and Habit Strength influence the Intention to Replay an online game. The importance of factors such as Hedonic Responses and Flow on Satisfaction in online game play. In addition to the SEM, analyses of the participants? reported past playing behaviour were conducted to test whether past game play was simply a matter of random frequency of past behaviour, or followed the specific pattern of the Negative Binomial Distribution (NBD). … The playing-time distribution was not significantly different to the Gamma distribution, in which the largest number of gamers plays for a short time (light gamers) and only a few gamers account for a large proportion of playing time (heavy gamers). Therefore, the reported time play followed a simple and predictable NBD pattern (Chisquare=. 390; p>.05). This study contributes to knowledge in the immediate field of online games and to the wider body of literature on consumer research. The findings demonstrate that gamers tend to act habitually in their playing behaviour. These findings support the argument that past behaviour (habit) is a better explanation of future behaviour than possible cognitive and affective explanations, especially for the apparent routinesed behaviour pattern on online games. The pattern of online game-playing is consistent with the finding of the NBD pattern in television viewing, in which the generalisability of the NBD model has been found in stable environments of repetitive behaviour. This supports the application of the NBD to areas beyond those of patterns in gambling and the purchase of consumer items. The findings have implications both for managerial and public policy decision-making.

Anaerobic digestion, which is the process by which bacteria breakdown organic matter to produce biogas (renewable energy source) and digestate (biofertiliser) in the absence of oxygen, proves to be the ideal concept not only for sustainable energy provision but also for effective organic waste management. However, the production amount of biogas to keep up with the global demand is limited by the underperformance in the system implementing the AD process. This underperformance is due to the difficulty in obtaining and maintaining the optimal operating parameters/states for anaerobic bacteria to thrive with regards to attaining a specific critical population number, which results in maximising the biogas production. This problem continues to exist as a result of insufficient knowledge of the interactions between the operating parameters and bacterial community. In addition, the lack of sufficient knowledge of the composition of bacterial groups that varies with changes in the operating parameters such as temperature, substrate and retention time. Without sufficient knowledge of the overall impact of the physico-environmental operating parameters on anaerobic bacterial growth and composition, significant improvement of biogas production may be difficult to attain. In order to mitigate this problem, this study has presented a nonlinear multi-parameter system modelling of mesophilic AD. It utilised raw data sets generated from laboratory experimentation of the influence of four operating parameters, temperature, pH, mixing speed and pressure on biogas and methane production, signifying that this is a multiple input single output (MISO) system. Due to the nonlinear characteristics of the data, the nonlinear black-box modelling technique is applied. The modelling is performed in MATLAB through System Identification approach. Two nonlinear model structures, autoregressive with exogenous input (NARX) and Hammerstein-Wiener (NLHW) with different nonlinearity estimators and model orders are chosen by trial and error and utilised to estimate the models. The performance of the models is determined by comparing the simulated outputs of the estimated models and the output in the validation data. The approach is used to validate the estimated models by checking how well the simulated output of the models fits the measured output. The best models for biogas and methane production are chosen by comparing the outputs of the best NARX and NLHW models (each for biogas and methane production), and the validation data, as well as utilising the Akaike information criterion to measure the quality of each model relative to each of the other models. The NLHW models mhw2 and mhws2 are chosen for biogas and methane production, respectively. The identified NLHW models mhw2 and mhws2 represent the behaviour of the production of biogas and methane, respectively, from mesophilic AD. Among all the candidate models studied, the nonlinear models provide a superior reproduction of the experimental data over the whole analysed period. Furthermore, the models constructed in this study cannot be used for scale-up purpose because they are not able to satisfy the rules and criteria for applying dimensional analysis to scale-up.

Skolan; ett monument Några av de ursprungliga byggnaderna i Slakthusområdet, ritade av Gustaf Wickman, ska i programmet omvandlas till gymnasieskolor och få ett kompletterande och samlande tillägg i form av ett lärocenter. Ett lärocenter som blandar läromiljöer med mer publikt inriktade funktioner så som bibliotek, servering och en blackbox för de omkringliggande gymnasieskolorna och området.  I mitt projekt har min utgångspunkt varit skolans status och funktion i samhället. En status som under skolans historia har präglats av dess funktion av att vara en viktig grundpelare och förutsättning för ett fungerande demokratiskt samhälle. Själva skolbyggnaden har i en historisk kontext ofta varit en materiell manifestation för att tydliggöra och i viss mån reproducera den status som var/är kopplad till skolan som institution. Skolbyggnaden tilläts ta plats fungerade och fungerar på flera sätt som ett monument. Skolbyggnaden tilläts ta plats i fysiskt bemärkelse men också i en aspekt av tid genom att i sin gestaltning och materialval bli en beständig del i sin kontext. Med begreppet status och kopplingen till skolan som utgångspunkt har jag valt att låta mitt projekt förhålla sig till sammanhängande och sammankopplade begrepp så som makt, hierarki, kunskap, monument (minnesmärke), landmärke, objekt och centrum mfl. Syftet med begreppen har varit att undersöka hur de kan hjälpa mig att skapa en byggnad som manifesterar sitt egna tänka värde och som tydligt avläses som en huvudbyggnad som hierarkiskt överordnar sig de omkringliggande gymnasieskolorna.  Jag har i min process låtit symboler, bilder och arkitekturhistoriska referenser påverka utformningen och gestaltningen av mitt lärocenter. Det har handlat om att låta en del av programmets funktioner referera på ett mer eller mindre tydligt sätt till klassiska element som bland annat amfiteatern, agoran och monumentet. Det har också handlat om att låta sig styras och påverkas av resultaten från bildsökningar av de begrepp som jag har valt att förhålla mig till. Mitt lärocenter är en byggnad som präglas av en monolitisk karaktär och placerar sig som en huvudbyggnad runt parken Fållan. Genom att plocka upp material och former från den ursprungliga byggnationen i området blir min byggnad ett med platsen. / The School Building; a Monument Some of the original buildings in the so called Slakthusområdet south of Stockholm, designed by Gustaf Wickman, will be transformed into upper secondary schools and receive a complementary and collective supplement in the form of a learning center. A learning center that mixes learning environments with more publicly oriented functions such as library, dining and a black box for the surrounding upper secondary schools and the area. In my project, my starting point has been the school’s status and function in society. A status that historically has been high due to the schools function of being an important pillar for a functioning democratic society. The school building itself has in a historical context often been a material manifestation to clarify and to some extent reproduce the status that was/is linked to the school as an institution. The school building was allowed to take up space and in the same time function and serve as a monument. The school building was allowed to take up space in a physical sense but also in an aspect of time by becoming a permanent part of its context in its form and choice of material. With the concept of status and connection to school as a starting point, I have chosen to let my project relate to coherent and interlinked concepts such as power, hierarchy, knowledge, monument, landmark, object and center, etc. The purpose of the concepts has been to explore how they can help me create a building that manifests its own perceptual value and is clearly read as a main building that is hierarchically superior to the surrounding schools. I have in my process let symbols, pictures and architectural references affect the design and the shape of my learning center. I have let some of the features of the program refer more or less obviously to classical elements such as the amphitheater, the agora and the monument. I have also allowed myself of being guided and influenced by the results of image searches of the concepts I have chosen to relate to. My learning center is a building of a monolithic character and places itself as a main building around the park called Fållan. By using materials and shapes that refers to the original buildings in the area, my building becomes one with its location.

Made available in DSpace on 2014-06-12T15:57:23Z (GMT). No. of bitstreams: 2 arquivo3187_1.pdf: 2434276 bytes, checksum: df6b126c4802eed8524aba0d3cb25af9 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Boudox Peres, Glaucia; Cabral Mota, Alexandre. A black-box testing technique for the detection of crashes based on automated test scenarios. 2009. Dissertação (Mestrado). Programa de Pós-Graduação em Ciência da Computação, Universidade Federal de Pernambuco, Recife, 2009.

To produce high quality software both software developers and testers need continuous improvement in their work methodologies and processes. So, far much work has been done in the effective ways of eliciting and documenting the requirements. However important aspect is to make sure that whatever is documented in specifications actually works correctly in the developed software. Software testing is done to ensure this phenomenon. Aim of this thesis is to develop a software test case work flow strategy that helps in identification and selection of suitable test paths that can be used as an input to acceptance testing and as a pre-requisite to start actual testing of the system. This thesis focuses on organizing system test artifacts by closely specifying them with system requirements and use cases. In this perspective focus of this thesis is on requirement writing by use cases, requirements traceability, test case prioritization and application acceptance criteria. A structured way to design test cases is proposed with the help of use cases. Some work is done to trace user needs to system requirements and use cases and benefits of using use case modeling approach in structuring the relationships among test cases is analyzed. As test cases are subject to changes in future so, challenges imposed due to traceability among requirements, use cases and test cases are main subjects of this work along with the challenges faced by software testers to perform application acceptance testing. A green path scheme is proposed to help testers define application acceptance criteria and weight assignment approach is used to prioritize the test cases and to determine the percentage of application running successfully.

Pour atteindre les objectifs de réduction de consommation et augmenter la flexibilité de la demande des bâtiments, il est nécessaire de disposer de modèles de prévision de charge de climatisation facilement diffusables sur site et performants qui permettent la mise en place de stratégies d’optimisation énergétique et d’effacement. Cette thèse compare plusieurs architectures de modèles inverses (« boite noire », « boite grise »). Un modèle semi-physique d’ordre 2 (R6C2) a été retenu pour prévoir la puissance de climatisation et la température intérieure moyenne en chauffage et en refroidissement. Il permet aussi d’interpréter des situations inédites (effacement), absentes de la phase d’apprentissage. Trois stratégies d’optimisation énergétique et d’effacement adaptées aux contraintes d’exploitation sont étudiées. La première permet d’optimiser la relance en chauffage afin de réduire la consommation et d’atteindre effectivement la température de confort le matin. La seconde stratégie optimise les températures de consigne sur une journée dans un contexte de prix variable de l’énergie, ceci afin de réduire la facture énergétique. Enfin, la troisième stratégie permet au bâtiment de s’effacer en limitant la charge tout en respectant des critères de confort spécifiés. Le modèle R6C2 et les stratégies ont été confrontés à un bâtiment réel (une école élémentaire). L’étude montre qu’il est possible de prévoir la puissance électrique et la température moyenne d’un bâtiment complexe avec un modèle mono-zone ; elle permet d’évaluer les stratégies développées et d’identifier les limites du modèle. / To reach the objectives of reducing the energy consumption and increasing the flexibility of buildings energy demand, it is necessary to have load forecast models easy to adapt on site and efficient for the implementation of energy optimization and load shedding strategies. This thesis compares several inverse model architectures ("black box", "grey box"). A 2nd order semi-physical model (R6C2) has been selected to forecast load curves and the average indoor temperature for heating and cooling. It is also able to simulate unknown situations (load shedding), absent from the learning phase. Three energy optimization and load shedding strategies adapted to operational constraints are studied. The first one optimizes the night set-back to reduce consumption and to reach the comfort temperature in the morning. The second strategy optimizes the set-point temperatures during a day in the context of variable energy prices, thus reducing the energy bill. The third strategy allows load curtailment in buildings by limiting load while meeting specified comfort criteria. The R6C2 model and strategies have been faced with a real building (elementary school). The study shows that it is possible to forecast the electrical power and the average temperature of a complex building with a single-zone model; the developed strategies are assessed and the limitations of the model are identified.

Black box testing techniques are important to test the functionality of the system without knowing its inner detail which makes sure correct, consistent, complete and accurate behavior or function of a system. Black box testing strategies are used to test logical, data or behavioral dependencies, to generate test data and quality of test cases which have potential to guess more defects. Black box testing strategies play pivotal role to detect possible defects in system and can help in successful completion of system according to functionality. The studies of five companies regarding important black box testing strategies are presented in this thesis. This study explores the black box testing techniques which are present in literature and practiced in industry as well. Interview studies are conducted in companies of Pakistan providing solutions to finance industry, which is an attempt to find the usage of these techniques. The advantages and disadvantages of identified Black box testing strategies are discussed, along with it; the comparison of different techniques with respect to most defect guessing, dependencies, sophistication, effort, and cost is presented as well.

This thesis focuses on the lower bounds for generic algorithms for discrete logarithms problem and Diffie-Hellman's problems. This thesis introduces two diffrent models of Black-Box for that purpose. On these models thesis approxi- mates and compares success probability of generic algorithms for given problems including Maurer's reduction. This reduction solves discrete logarithms problem using a appropriate elliptic curve and a Diffie-Hellman's oracle. This thesis also researches generic algorithm for identifiaction schemes, that are based on discrete logarithms problem. 1

[pt] Diversos estudos apontam que desenvolvimento orientado a serviços terá, em alguns anos, grande influência sobre o desenvolvimento de sistemas. Esta dissertação discute o que realmente o desenvolvimento orientado a serviços apresenta como novidade tecnológica, através da discussão de todas suas características consideradas relevantes para construção de uma aplicação baseada no conceito de serviços. Características como reuso caixa-preta, distribuição e suporte a heterogeneidade ambiental, entre outras, são discutidas no intuito de identificar suas vantagens e funcionalidades, e principalmente, sua importância para o desenvolvimento orientado a serviços. É discutido, também, o conceito representado pelo termo serviço, que possui interpretações distintas na indústria e em publicações acadêmicas. São apresentados também alguns frameworks que dão suporte ao desenvolvimento orientado a serviços, como Vinci, Jini e os XML Web Services. Finalmente, é apresentada uma proposta para um novo framework que oferece suporte ao desenvolvimento orientado a serviços, e que tem como diferencial a opção de se basear na extensão da infra-estrutura de um servidor de aplicações J2EE. / [en] Several studies point that service-oriented development will have, in some years, great influence on the development of systems. This work shows what service- oriented development actually presents as technological innovation, through the discussion of all its relevant characteristics for construction of an application based on the concept of services. Characteristics as black-box reuse, distribution and environment heterogeneity support, among others, are discussed in intention to identify its advantages and features, and mainly, its importance for the service-oriented development. It is also discussed the concept represented for the term service, that have distinct interpretations in the industry and academic publications. In addition some frameworks are presented that support derviceoriented Development, such as Vinci, Jini and the XML Web Services. Finally, a proposal for a new framework is presented which offers support for Service- Oriented Development. Unlike the others frameworks previously mentioned, this is based on the extension of J2EE application server infrastructure.

Enterprising technologies and policies that focus on energy reduction in buildings are paramount to achieving global carbon emissions targets. Energy retrofits, building stock modelling, heating, ventilation, and air conditioning (HVAC) upgrades and demand side management all present high leverage opportunities in this regard. Advances in computing, data science and machine learning can be leveraged to enhance these methods and thus to expedite energy reduction in buildings but challenges such as lack of data, limited model generalizability and reliability and un-reproducible studies have resulted in restricted industry adoption. In this thesis, rigorous and reproducible studies are designed to evaluate the benefits and limitations of state-of-the-art machine learning and statistical techniques for high-impact applications, with an emphasis on addressing the challenges listed above. The scope of this work includes calibration of physics-based building models and supervised deep learning, both of which are used to estimate building properties from real and synthetic data. • Original grey-box methods are developed to characterize physical thermal properties (RC and RK)from real-world measurement data. • The novel application of supervised deep learning for thermal property estimation and HVAC systems identification is shown to achieve state-of-the-art performance (root mean squared error of 0.089 and 87% validation accuracy, respectively). • A rigorous empirical review is conducted to assess which types of gray and black box models are most suitable for practical application. The scope of the review is wider than previous studies, and the conclusions suggest a re-framing of research priorities for future work. • Modern interpretability techniques are used to provide unique insight into the learning behaviour of the black box methods. Overall, this body of work provides a critical appraisal of new and existing data-driven approaches for thermal property estimation in buildings. It provides valuable and novel insight into barriers to widespread adoption of these techniques and suggests pathways forward. Performance benchmarks, open-source model code and a parametrically generated, synthetic dataset are provided to support further research and to encourage industry adoption of the approaches. This lays the necessary groundwork for the accelerated adoption of data-driven models for thermal property identification in buildings. / Graduate