The objective of this study is to investigate the approaches utilised by external decision-makers in their evaluation of the different facets of performance of manufacturing organisations, operating as open systems. In process, important linkages which exist among relevant performance parameters are explored. The types and frequencies of performance measures used by the sampled Portuguese financial analysts are compared using factor analysis and multiple regression analysis. Results tend to underscore the significance of the collective performance of all subsystems of the manufacturing system. Based on the findings of this research, implications focusing on the management of organisational performance systems are identified.

The motivation for the thesis was to discover whether Finnish Red Cross Youth Shelters can be evaluated and developed from legal and moral standpoints, such as the Human Rights. A special focus is put on how the international law gets interpreted and practiced in a local (Youth Shelter) context. Findings from the collected data are based on the experiences of the Youth Shleter’s employees and volunteers through workshop discussions, surveys and interviews. This observational work done within the thesis is an initial mapping of how “things are at the moment”. Data is analysed with The New Legal Realism (NLR) theory, which main focus is to study law’s context-based interpretations and mobility ie. how international law creates meanings in a local setting. (Dagan & Kreitner, 2018; 534.) The value of the findings will increase through new ideas, support measures and a better identification of the needs of employees and volunteers arising from the findings. The observational work is inspired by the idea that if someone has an obligation to ensure rights, they are also entitled to get support with knowledge of how to implement them properly.

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for the prediction of intraday returns for various financial assets, including stock and commodity futures.

Magister Commercii - MCom / Over the 1ast eight years up to 1989, a new business phenomenon has manifested itself in South Africa. During this period, the so-ca 11ed "factory shop" concept has developed into one of the fastest growing industries in both the manufacturing and commercial sectors. In South Africa, factory shops have initially established in the Cape Peninsula.4,5. The nature of these shops is such that their creation may be attributed to the clothing industry itself ;" This trend originated in about 1980 at a few clothing manufacturers in Cape Town, inter alia, Desiree, Readywear, Atlantic Knitting Mills. Originally these factory shops were open for limited hours, I usually over lunch-time and on only one Saturday per month. They were strictly limited to and for the sole benefit of I the staff of those firms. Gradually, however, family and later friends and acquaintances of these staff members became aware of the so-called bargain prices at these stores. Both supply and demand played important roles in the development of factory shops. For example, increasing pressure on management to supply larger quantities of these merchandise items at bargain prices, as well as the fact that clothing factories had excess stock which was difficult to clear through the normal distribution channels. Factory owners recognized and seized this opportunity to reduce stock at little additional cost. From their inception, factory shops have had a significant influence on the turnover and profitability of the retail clothing industry. This trend is documented in reports by the organ i zed trade, 7 ,B where reference has been made to the influence of these factory shops and where independent clothing retailers have been calling for a plan of action for protect i on against the encroachment by these factory shops on their (the clothing retailers') markets. However, up to that stage, no in-depth study or formal research was done to justify such action for protection. The ref 0reitwa s felt that" An empirical stud y of the development of factory shops in the clothing industry in the Cape Peninsula" was needed to acquire an objective view of the state of affairs.

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Agile methods have been widely implemented in the industry while teaching these methods is a substantial part of Computer Science and Engineering program curricula. Evidencedriven data of agile practices, methods, and tools have been extracted based on empirical studies with students, however, there is an important need for more anecdotal evidence to confirm these findings. In order to fill this gap, this paper explores the perceptions and the applicability of the Scrum Framework in a student research team in an industrial context. Empirical data have been gathered through interviews with the case study participants combined with a survey. The analysis reveals that student experiences are mainly positive and that they can easily grasp the benefits of Scrum Framework. The challenges of implementing Scrum in such a setting mainly concern the balance between coach and self-organization, formulating accurate user stories when researching, finding the most suitable estimation method, as well as planning when conducting research. The empirical findings may potentially be extrapolated in student scrum teams or even in industrial settings. Finally, this research paper should encourage other researchers to investigate the adoption of Scrum in a student setting. / Agila metoder har implementerats i stor utsträckning inom branschen, medan undervisning i dessa metoder är en väsentlig del av utbildningarna för datavetenskap och teknik. Bevisdriven data om agila arbetssätt, metoder och verktyg har tagits fram från empiriska studier med studenter, men det finns ett viktigt behov av mer anekdotiska bevis för att bekräfta dessa resultat. För att fylla detta gap utforskar den här rapporten uppfattningarna och tillämpligheten av ramverket Scrum i ett studentforskningsteam i ett industriellt sammanhang. Empiriska data har samlats genom intervjuer med deltagarna i fallstudien i kombination med ett frågeformulär. Analysen visar att studentupplevelserna är främst positiva och att man lätt kan förstå fördelarna med Scrum. Utmaningarna med att implementera Scrum i en sådan miljö gäller främst balansen mellan coaching och självorganiserande, formulera exakta användarhistorier när man forskar, finner den mest lämpliga uppskattningsmetoden samt planerar forskningsrelaterat arbete. De empiriska fynden kan eventuellt extrapoleras i Scrumteam med studenter eller till och med i industriella miljöer. Slutligen bör detta forskningsarbete uppmuntra andra forskare att undersöka införandet av Scrum i ett studentkontext.

In traditional meta-analysis, a random-effects model is used to deal with heterogeneity and the random-effect is assumed to be normally distributed. However, this can be problematic in the presence of outliers. One solution involves using a heavy tailed distribution for the random-effect to more adequately model the excess variation due to the outliers. Failure to consider an alternative approach to the standard in the presence of unusual or outlying points can lead to inaccurate inference. A heavy tailed distribution is favoured because it has the ability to down-weight outlying studies appropriately, therefore the removal of a study does not need to be considered. In this thesis, the performance of the t-distribution and a finite mixture model are assessed as alternatives to the normal distribution through a comprehensive simulation study. The parameters varied are the average mean of the non-outlier studies, the number of studies, the proportion of outliers, the heterogeneity and the outlier shift distance from the average mean. The performance of the distributions is measured using bias, mean squared error, coverage probability, coverage width, Type I error and power. The methods are also compared through an empirical study of meta-analyses from The Cochrane Library (2008). The simulation showed that the performance of the alternative distributions is better than the normal distribution for a number of scenarios, particularly for extreme outliers and high heterogeneity. Generally, the mixture model performed quite well. The empirical study reveals that both alternative distributions are able to reduce the influence of the outlying studies on the overall mean estimate and thus produce more conservative p-values than the normal distribution. It is recommended that a practitioner consider the use of an alternative random-effects distribution in the presence of outliers because they are more likely to provide robust results. / Thesis / Master of Science (MSc)

In the modern computing landscape, the challenge of tuning software systems is exacerbated by the necessity to accommodate multiple divergent execution environments and stakeholders. Achieving optimal performance requires a different configuration for every combination of hardware setups and business requirements. In addition, the state of the art in system tuning can involve complex statistical models and tools which require deep expertise not commonly possessed by the average software engineer. As an alternative approach to performance tuning, this thesis puts forward the use of sonification-conveying information via non-speech audio-to aid software engineers in tuning complex systems. In particular, this thesis designs, develops, and evaluates a tuning system that interactively (i.e., in response to user actions) sonifies the performance metrics of a computer system. This thesis demonstrates that interactive sonification can effectively guide software engineers through performance tuning of a computer system. To that end, a scientific survey determined which sound characteristics (e.g., loudness, panning, pitch, tempo, etc.) are best suited to express information to the engineer. These characteristics were used to create a proof-of-concept tuning system that was applied to tune the parameters of a real world enterprise application server. Equipped with the tuning system, engineers-not experts in enterprise computing nor performance tuning-were able to tune the server, so that its resulting performance surpasses that exhibited under the standard configuration. The results indicate that sound-based tuning approaches can provide valuable solutions to the challenges of configuring complex computer systems. / Master of Science

Stroke is a leading cause of death and disability worldwide [8], underscoring the need for effective digital solutions for stroke patients, caregivers, and healthcare professionals. Given that, this thesis aims to evaluate quality aspects of usability, accessibility, and readability of stroke-related mobile health (mHealth) applications, with the primary objective of identifying strengths and weaknesses to enhance user experience and app quality. This study assessed sixteen stroke-related apps through a comprehensive methodology, including accessibility testing with the Google Accessibility Scanner, Mobile Application Rating Scale (MARS) evaluation, heuristic evaluation, and readability assessment. Key findings indicate significant issues with touch target sizes and text contrast, which are crucial for users with impaired visionand motor skills. MARS evaluations revealed that “Constant Therapy” excelled in engagement and functionality due to its interactive features and personalized schedules. At the same time, “Stroke Recovery Predictor” and “Conversation Therapy Lite” scored lower due to limited functionality and unclear interfaces. The heuristic evaluation highlighted frequent violations of the visibility of system status and insufficient error messaging. Readability assessments showed a range of reading difficulty levels, with some apps lacking privacy policies that could be found either within the application or on the developer’s website. The study provides actionable recommendations for developers, such as improving touch target sizes, improving text contrast, increasing functional variety, optimizing navigation, and ensuring privacy policy transparency. Addressing these areas can significantly improve the usability and accessibility of stroke-related mHealth apps, ultimately supporting better health outcomes and quality of life for stroke survivors. Future research should involve more evaluators, use multiple assessment tools, and focus on specific types of stroke apps to refine the evaluation process and provide more targeted insights.

Performance in software describes the efficiency with which a system or a component fulfills its intended tasks, considering factors such as execution speed, resource consumption, and accuracy. It is a quality that can determine whether a software system is a success or a failure and can bring both financial profits and losses to companies. Developers, however, do not fully utilize existing best practices to maximize performance or try to increase it by reducing other quality attributes. The performance issues they face are often more complex and require more effort to be solved than functional bugs. To provide more insight into the subject of such issues, a study is conducted on 54 real-life performance issues found in 7 C# projects, which are analyzed for root causes, affected quality (response time or memory allocation), and applied solutions. Issues are classified based on their root cause, and the taxonomy consisting of 12 categories used in the process is derived from different performance issue classifications proposed by related research through a literature review. Additionally, through another literature review, 11 patterns that can improve software performance are identified and described. Out of those 11 patterns, 4 are found to be commonly applied when solving performance issues in C#. The aim of this study is to provide insights into what kind of performance issues appear and how they are solved in the C# language.