This degree project was made in collaboration with Nordicstation. The project task was to develop a testing application for a self-developed telephone survey service, which uses third party software. This third party software showed to be unreliable at higher loads. The purpose of the application is to analyse the speech quality of clients connected to the service. This report gives an introduction to the speech quality algorithms Perceptual Evaluation of Speech Quality (PESQ) and Single Sided Speech Quality Measure (3SQM). It also gives descriptions of the methods used to develop the application. The final chapters in this report are about the testing of the telephone service. The primary result of the testing was that the telephone service is unable to acceptably handle 80+ clients and recommendations to Nordicstation is to set a maximum of parallel connected clients to 80 or find an alternative to the third party software currently in use. / Detta examensarbete har gjorts i samarbete med Nordicstation. Projektets uppgift var att utveckla ett test program för at testa en egenutvecklad telefonundersökning-tjänst, baserad på tredjeparts mjukvara. Denna tredjeparts mjukvara visade sig vara opålitlig vid högre belastning. Syftet med programmet är att analysera samtals kvalitéten på de klienter som är anslutna till tjänsten. Denna rapport ger en introduktion till ljudkvalitetsalgoritmer så som Perceptual Evaluation of Speech Quality (PESQ) och Single Sided Speech Quality Measure (3SQM). Rapporten går även igenom de metoder som använts för att utvecklat programmet. De sista kapitlen i denna rapport är om själva testningen av telefonitjänsten. Det primära resultatet av testningen var att telefontjänsten inte kan hantera 80+ klienter acceptabelt och rekommendationer till Nordicstation är att sätta ett tak på maximalt parallellt anslutna klienter till 80 eller hitta ett alternativ till den tredjeparts mjukvara som nu används.

The rapid improvement of hardware and internet speed in modern societies has contributed to more vibrant websites with lots of motion, which often has a correlation to a better user experience, but not always. Scroll-hijacked websites are one of the more controversial techniques, a questionable action where one modifies the default scroll behaviour, which affects the preconceived notions about how to navigate a website. But the effect can be beneficial when one wants to draw attention to crucial call-to-action (CTA) elements.  This thesis resulted in creating a scroll-hijacked prototype based on an already deployed event website with lots of vital CTA elements. The developed prototype was then evaluated against the old website through A/B testing with SUS- and NASA-TLX-surveys. These tests and evaluations were performed by a user study with 44 participants. During the thesis, it was found that there are areas of use where it can be favourable to use scroll-hijacking to increase attention for CTA elements, and thereby increase the conversion, but it requires a thoughtful application.

This research concerns exploiting knowledge of the user's environment (i.e., context information) to enrich a user's communication making it more personal, by ensuring that the user receives only relevant messages and calls in his/her current context, and to facilitate more opportunities for communication interactions with people that are in the same context and that share the same interests as this user. We describe in this licentiate thesis the concepts of context-addressed messaging and context-aware session control that enable users to: (1) send messages to others based on their context, rather than their network address and (2) to initiate, adapt, and terminate user's communication sessions based on this user's current context, respectively. These concepts address questions such as: how to discover, select, and switch to an optimal communication means to meet varying user, contextual, communication, and device resource requirements and preferences. A key to solving these problems is to create a representation of the user's context-dependent preferences and to process the user's context-dependent preferences which are part of context triggers. These context triggers can initiate a communication event upon a particular context update. Additionally, in order to provide the described context-aware communication functions, these mechanisms need timely access to the acquired (desired) context information. This in turn raises a plethora of other questions, such as how to discover sensors that provide the desired context information; how to acquire raw context data from these sensors; how to abstract, process, and model this data to become "understandable" to applications and system components; and how to distribute this context to applications that are running on different nodes.   This research is split into three different parts. The first part concerns investigating and implementing context management functions. As part of this research we propose a novel approach for context synthesis using context operators. We also propose a design architecture for context-aware middleware that mediates between the sensors and applications, and that is able to share and retrieve context from other nodes in the network. The second part of our research concerns our proposed mechanism for context-addressed messaging. To implement this mechanism we designed our own message format, called the Common Profile for Context-Addressed Messaging (CPCAM) that is able to use any high level context to compose a context-based address. Additionally, we proposed to use context-based filtering to find the correct message recipients and determine if this message is relevant to these potential message recipients in their current context, as well as to deliver this message to the recipients' preferred device that is adapted using their preferred communication means. At the end of this second part we design context-addressed messaging system operations on top of a SIP and SIMPLE-based network infrastructure. The third part of our research describes context-aware session control mechanisms using context switch and context trigger constructs. A context-switch selects an action from a set of context-dependent actions upon an incoming communication event based on the receiver's current context. In contrast, a context trigger initiates an action based on a context update and the user's preferences that are specified in this updated context. This part illustrates in several examples the context-aware session control mechanisms, i.e. the initiation of a communication session based on the match of a user's preferences and current context, as well as adaptation and (if necessary) termination of an ongoing communication session based upon the user's context-dependent preferences.   The research leading to this licentiate has created network and system level models necessary for implementation of a context-addressed communication system that would enable users to easily design their own personalized, context-aware communication services. The necessary constructs and properties of these models are designed and analyzed in the thesis, as well as in conference papers and other documents published in the process of doing the research for this thesis. A number of remaining open issues and challenges have been outlined as part of the future work. / EU FP6 MIDAS (Middleware Platform for Developing and Deploying Advanced Mobile Services) / EU FP6 MUSIC (Self-adapting Applications for Mobile Users In Ubiquitous Computing Environments)

Data lineage forms an important aspect of today's enterprise environment. MANTA Flow is a data lineage analysis platform that already has basic support for analysis of Java programs, provided by one of its components called Bytecode Scanner. Neverthe- less, there are very few applications in today's enterprise environment that do not use dependency injection at least in a very limited way. Therefore, we present an extension of Bytecode Scanner in the MANTA Flow platform to support data lineage analysis of dependency injection frameworks as well. The extension is able to process even complex definitions of standard dependency injection containers. Since the dependency injec- tion influences a selection of method call targets, we also provide a description of call graph structure and its modification to support dependency injection. Last, we use this infrastructure to design and implement a plugin into Bytecode Scanner for the Spring Framework, a popular dependency injection framework targeting Java Platform. The plugin has been successfully tested on a small but realistic software system that can read data from a file, transform them, and write them into a database. 1

No description available.

Despite initiatives and management efforts to minimize exacerbation and adverse outcomes, asthma remains a leading cause of childhood chronic disease in the United States. Environmental, personal, and social factors have been associated with an increase of asthma morbidity. However, little is known about how they cumulatively affect children's quality of life. This study applied a multifactorial conceptual model grounded by the ecological systems theory framework to ascertain which environmental, personal, and social factors were cumulatively associated with adverse health-related quality of life (HRQoL) in children with asthma ages 5-17 years. A national, cross-sectional survey, the Behavioral Risk Factor Surveillance System Asthma Call-back Survey, of 2,968 (unweighted) participants were used to identify the association between the factors and HRQoL outcomes, symptom-free days, missed school, and activity limitations. Multiple linear regression and cumulative regression models for complex survey data were used to assess the associations. Factors associated with the HRQoL outcomes included cost barriers to asthma medications and primary care physicians, insurance status, having an insurance gap, the type of health insurance, the presence of mold in the school, the guardian's diminished mental health, and environmental tobacco smoke. Understanding which factors influence asthma HRQoL may foster positive social change by enlightening and empowering the child, caregivers, health care professionals, and other stakeholders to become active participants in the asthma management process. Therefore, quality of life is optimized by all participants taking an active role in the asthma management process through conversations and developing synergistic strategies.

Queueing theory has often been applied to study communication and service queueing systems such as call centers, hospital emergency departments and ride-sharing platforms. Unfortunately, it is complicated to analyze queueing systems. That is largely because the arrival and service processes that mainly determine a queueing system are uncertain and must be represented as stochastic processes that are difficult to analyze. In response, service providers might be able to partially capture the main characteristics of systems given partial data information and limited domain knowledge. An effective engineering response is to develop tractable approximations to approximate queueing characteristics of interest that depend on critical partial information. In this thesis, we contribute to developing high-quality approximations by studying tight bounds for the transient and the steady-state mean waiting time given partial information. We focus on single-server queues and multi-server queues with the unlimited waiting room, the first-come-first-served service discipline, and independent sequences of independent and identically distributed sequences of interarrival times and service times. We assume some partial information is known, e.g., the first two moments of inter-arrival and service time distributions. For the single-server GI/GI/1 model, we first study the tight upper bounds for the mean and higher moments of the steady-state waiting time given the first two moments of the inter-arrival time and service-time distributions. We apply the theory of Tchebycheff systems to obtain sufficient conditions for classical two-point distributions to yield the extreme values. For the tight upper bound of the transient mean waiting time, we formulate the problem as a non-convex non-linear program, derive the gradient of the transient mean waiting time over distributions with finite support, and apply classical non-linear programming theory to characterize stationary points. We then develop and apply a stochastic variant of the conditional gradient algorithm to find a stationary point for any given service-time distribution. We also establish necessary conditions and sufficient conditions for stationary points to be three-point distributions or special two-point distributions. Our studies indicate that the tight upper bound for the steady-state mean waiting time is attained asymptotically by two-point distributions as the upper mass point of the service-time distribution increases and the probability decreases, while one mass of the inter-arrival time distribution is fixed at 0. We then develop effective numerical and simulation algorithms to compute the tight upper bound. The algorithms are aided by reductions of the special queues with extremal inter-arrival time and extremal service-time distributions to D/GI/1 and GI/D/1 models. Combining these reductions yields an overall representation in terms of a D/RS(D)/1 discrete-time model involving a geometric random sum of deterministic random variables, where the two deterministic random variables have different values, so that the extremal waiting times need not have a lattice distribution. We finally evaluate the tight upper bound to show that it offers a significant improvement over established bounds. In order to understand queueing performance given only partial information, we propose determining intervals of likely performance measures given that limited information. We illustrate this approach for the steady-state waiting time distribution in the GI/GI/K queue given the first two moments of the inter-arrival time and service time distributions plus additional information about these underlying distributions, including support bounds, higher moments, and Laplace transform values. As a theoretical basis, we apply the theory of Tchebycheff systems to determine extremal models (yielding tight upper and lower bounds) on the asymptotic decay rate of the steady-state waiting-time tail probability, as in the Kingman-Lundberg bound and large deviations asymptotics. We then can use these extremal models to indicate likely intervals of other performance measures. We illustrate by constructing such intervals of likely mean waiting times. Without extra information, the extremal models involve two-point distributions, which yield a wide range for the mean. Adding constraints on the third moment and a transform value produces three-point extremal distributions, which significantly reduce the range, yielding practical levels of accuracy.

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This report aimed to develop algorithms for solving the optimization problem of matchingbuy and sell orders in call auctions while minimizing the number of transactions. The developed algorithms were evaluated based on their execution time and solution accuracy.The study found that the problem was more difficult to solve than initially anticipated, and commercial solvers were inadequate for the task. The data’s characteristics werecritical to the algorithms’ performance, and the lack of specifications for instruments andexchange posed a challenge. The algorithms were tested on a broad range of datasets with different characteristics, as well as real trades of stocks from the Stockholm Stock Exchange. Evaluating the best-performing algorithm became a trade-off between time and accuracy, where the quickest algorithm did not have the highest solution accuracy. Therefore, the importance of these factors should be considered before deciding which algorithm to implement. Eight algorithms were evaluated: four greedy algorithms and four clusteralgorithms capable of identifying 2-1 and 3-1 matches. If execution time is the single most crucial factor, the Unsorted Greedy Algorithm should be considered. However, if accuracyi s a priority, the Cluster 3-1 & 1-3 Algorithm should be considered, even though it takes longer to find a solution. Ultimately, the report concluded that while no single algorithm can be definitively la-beled as the best, the Cluster 2-1 Algorithm strikes the most effective balance between execution time and solution accuracy, while also remaining relatively stable in perfor-mance for all test cases. The recommendation was based on the fact that the Cluster 2-1 Algorithm proved to be the quickest of the developed cluster algorithms, and that cluster algorithms were able to find the best solutions for all tested data sets. This study successfully addressed its purpose by developing eight algorithms that solved the given problem and suggested an appropriate algorithm that strikes a balance between execution time and solution quality.

In an effort to better understand the mental processing connected to different kinds of CALL activities, this study collected data on time subjects spent, as well as buttons subjects clicked while doing 10 different CALL activities accompanying a beginning French text book. In addition, a group of subjects thought out loud as they completed the same activities. These subjects were recorded on video, their thinking out loud was transcribed and the transcriptions were coded according to how they indicated they were dealing with the language input. The frequencies of coded categories were compared to see if there were connections between certain activity types and the kind of mental processing that should lead to language acquisition. It found that activities which required language production at least at the sentence level had higher occurrences of the kind of processing that one expects to lead to acquisition. The study also found that activities which required the learners to click as a response were connected to what could be considered shallower processing, or processing that is less likely to lead to language acquisition. It found similar results concerning True/False activities. In investigating the connection between behavior and mental processing in the CALL setting, the study found that button-use does seem to be connected to more effective processing, but that time spent on an activity is something that is perhaps too ambiguous to draw conclusions from.