Seamless interconnection of smart mobile devices and cloud services is a key goal in modern mobile computing. Mobile Cloud Computing is the holistic integration of contextually-rich mobile devices with computationally-powerful cloud services to create high value products for end users, such as Apple's Siri and Google's Google Now product. This coupling has enabled new paradigms and fields of research, such as crowdsourced data collection, and has helped spur substantial changes in research fields such as vehicular ad hoc networking. However, the growth of Mobile Cloud Computing has resulted in a number of new challenges, such as testing large-scale Mobile Cloud Computing systems, and increased the importance of established challenges, such as ensuring that a user's privacy is not compromised when interacting with a location-aware service. Moreover, the concurrent development of the Infrastructure as a Service paradigm has created inefficiency in how Mobile Cloud Computing systems are executed on cloud platforms. To address these gaps in the existing research, this dissertation presents a number of software and algorithmic solutions to 1) preserve user locational privacy, 2) improve the speed and effectiveness of deploying and executing Mobile Cloud Computing systems on modern cloud infrastructure, and 3) enable large-scale research on Mobile Cloud Computing systems without requiring substantial domain expertise. / Ph. D.

Since the beginning of the Global War on Terror, almost three million children, spouses, and adult dependents have been directly affected by the deployment experiences of more than two million service members. This study examined the applicability of the Contextual Model of Family Stress (Boss, 2002) to a reintegrating military family sample (N = 228) by assessing the effects of external, military-related contextual factors (i.e., rank, component, combat exposure, length of time home post-deployment, and cumulative length of deployments) and internal contextual factors of boundary ambiguity and family and deployment-related ambivalence on family functioning. Quantitative data were taken from a national survey of service members from multiple branches of the United States military. A hierarchical regression analysis revealed that, as a whole, the addition of the military-related contextual factors, boundary ambiguity, and the ambivalence variables made a significant contribution to the prediction of family functioning, controlling for all previously entered variables. Service members from lower ranks and those who had been home for longer periods of time reported poorer family functioning. Higher degrees of boundary ambiguity and family ambivalence were also associated with poorer family functioning. The results from this study extend existing theoretical applications of the Contextual Model (Boss, 2002) to military families through the incorporation of boundary ambiguity and ambivalence. Findings will also inform interventions aimed at promoting family resilience in the military population during the post-deployment period. / Ph. D.

Research investigating how same-sex military couples conjointly experience the deployment process is absent. This study employed transcendental phenomenological methods (Moustakas, 1994) to explore the lived experiences of same-sex military couples and the deployment process. In-depth, conjoint interviews were conducted with eighteen individuals: five female couples and four male couples, representing four military branches, Army, Navy, Air Force, and Marine Corps. Three thematic categories emerged that revealed the essence of the couples' experiences of deployment: deployment experience is context-dependent, challenges associated with sexual minority status, and learned resilience. Though couples experienced a host of unique challenges related to their minority status and restrictive policies, couples developed adaptive coping strategies that served to mediate the impact of distinctive barriers and restrictions. Findings demonstrate the vulnerability and resilience of same-sex military couples during deployment. Political, clinical, and research implications are discussed. / Master of Science

While extensive research has been done examining stress in families using the Double ABCX model and examining stress management using attachment theory, there is no research combining the model to understand how they might be integrated in understanding stress and coping. The current study uses the Double ABCX model and research on attachment to suggest that attachment relationships will be the primary resource to adjust for military families during deployment. Two extreme case studies were selected to explore the interplay of these two models. The in-depth interviews of the women with a deployed spouse and with children in the home were examined. Exploration of the experiences of the two women informed a model in understanding the synthesis of stress and attachment and understanding the influence of meaning making and adjustment. Therapeutic implications and suggestions for future research are also discussed. / Master of Science

Effective weed control is crucial, especially for herbicide-resistant species. Machine vision technology, through weed detection and localization, can facilitate precise, species-specific treatments. Despite the challenges posed by unstructured field conditions and weed variability, deep learning (DL) algorithms show promise. This study evaluated thirteen DL-based weed detection models, including YOLOv5, RetinaNet, EfficientDet, Fast RCNN, and Faster RCNN, using pre-trained object detectors. RetinaNet (R101-FPN) achieved the highest accuracy with a mean average precision (mAP@0.50) of 79.98%, though it had longer inference times. YOLOv5n, with the fastest inference (17 ms on Google Colab) and only 1.8 million parameters, achieved a comparable 76.58% mAP@0.50, making it suitable for real-time use in resource-limited devices. A prototype using YOLOv5 was tested on two datasets, showing good real-time accuracy on In-season data and comparable results on Cross-season data, despite some accuracy challenges due to dataset distribution shifts.

In this study, the initial hydrostatic stability, the hydrostatic stability and the structure realibility of three different barge-shaped vessels is simulated and evaluated in order to see which of the vessels would be the most optimal to use for deployment of wave energy converters, WECs. The vessels differ in their hull type: Bulbous-bow hull vessel, Barge hull vessel and Modified-barge hull vessel. In order to do the evaluation, the hull of each vessel is designed in DELFTship and further design is proceeded in SolidWorks 2014. Structural strength analysis is performed in SolidWorks 2014 and hydrostatic properties are simualted in Ansys Aqwa 16.0. The collected results are pointing at that the Modified-barge hull vessel is slightly superior to the others in terms of hydrostatic stability, while the structure stability is equal. The results of this study will provide a foundation for further evaluation of vessels capable of deploying wave energy converters.

Mobile Learning (M-learning) refers to any kind of learning which takes place within and beyond the traditional learning environment via wireless mobile devices. These devices are able to move with the learner to allow learning anytime, anywhere. M-learning is considered as the next step beyond electronic learning (E-learning) and distance learning (D-learning) by using mobile wireless devices with internet connectivity to facilitate formal and informal learning. Over the past decade M-learning has become gradually popular in university settings by providing mobile access to learning resources, collaborative learning and to exchange formative evaluation and feedback between students and instructors. Therefore, M-learning involves learning activities that are not restricted to a specific time or place. Despite the familiarity with M-learning as a new paradigm in modern education, there has been a shortage of research concerning how to deploy this technology in a successful way. The integration of M-learning in a university environment needs to involve some aspects in terms of the readiness of users and institutions, users‟ acceptance and engagement, and the sustainability of the system. There are some initial models that investigate the implementation of M-learning which provide some guidelines that work as starting point for the future of M-learning deployment. However, there is no theoretical model that provides guidelines for staged deployment of M-learning. In addition, there was no clear definition of sustainability factors that will assure continues evaluation and upgrade of M-learning systems after deployment. The aims of this research work are to study students‟ readiness for M-learning, investigate the factors that affect students‟ acceptance and analyse M-learning literature in order to propose and evaluate a model which can be used to foster the sustainable deployment of M-learning within teaching and learning strategies in higher education institutions. The research was conducted in Brunel University, West London. Data were collected from School of Information, Computing and Mathematical Science students using three surveys: the first studied students‟ readiness for M-learning, the second investigated factors that affect students‟ acceptance of M-learning and the last one developed and evaluated a sustainable M-learning deployment model. The outcome of this research lead to a conceptual model that gives a wide overview of all elements that need to be addressed in the M-learning environment and bridges the gap between the pre- and post-implementation phases in order to ensure sustainability. Furthermore, the model provides university educators with a planned approach to incorporate M-learning in higher education curriculums with the aim of improving teaching and learning.

The currently emerging trend of building more complex web applications to solve increasingly more involved software problems has led to the the need for a more automated and practical means for deploying resources required by these advanced web applications. As web based applications become more complex and involve more developers, greater system redundancy, and a larger number of components, traditional means of resource deployment become painfully inadequate as they fail to scale sufficiently. The purpose of this research is to provide evidence that a more sound and scalable test and deployment process can be employed and that many of the components of this improved process can be automated and/or delegated to various system actors to provide a more usable, reliable, stable, and efficient deployment process. The deployable resources that have been included for their commonality in web based applications are versioned resources (both ASCII based and binary files), database resources, cron files, and scripting commands. In order to achieve an improved test and deployment process and test its effectiveness, a web-based code deployment tool was developed and deployed in a production environment where its effects could be accurately measured. This deployment tool heavily leverages the use of Subversion to provide the management of versioned resources because of its extensive ability to manage the creation and merging of branches.

The market is developing and a growing competition increases pressure on companies to maintain their competitive advantage. Working with cost savings is a way to enhance earnings in a short term but also in a longer perspective. Volvo Powertrain Production Köping has an overall goal; to reduce costs by nine percentages in three years. To achieve the goal, Volvo Powertrain Production Köping works with World Class Manufacturing where the Department of Processing Technology constitutes an important part. Volvo Powertrain Production Köping lacks a standard for how savings within the metal cutting tool area are to be calculated. This makes it difficult to control and monitor their business outcome but it also causes difficulties in controlling the tool suppliers’ outcome. The suppliers’ outcome is later used as the basis in price negotiations which means that Volvo Powertrain Production Köping lacks information that can improve their outcome of a negotiation. The aim of the project is to increase understanding of how activities of processing technology affect productivity through a spreadsheet model. Starting with a current status report and a literature review revealed that many companies are missing an hourly rate designed at machine level. There are theories saying that the machine hourly rate should be allocated for both producing state and downtime, which in subsequent interviews with other companies proves to be far from being reality. Collected information was analyzed and a model was developed. The model has been tested in two improvement projects and the outcome has been compared with existing calculations from tool vendors. The result of the thesis is a standardized savings model with a machine specific hourly rate, taking into account both producing and downtime states. The savings model is based on the currently used Cost Deployment system. The proposed spreadsheet will monitor the outcome of tool suppliers which will result in a better control of cost savings and price negotiations. The savings model is not solely for savings calculations; the model also helps the user to understand how different parameters affect the cost of manufacturing. The expectation is to increase cost awareness and reduce the risk of sub-optimization in Volvo Powertrain Production Köping´s operations. The developed hourly rate is not specific to processing technology but the entire company can benefit from the spreadsheet. From a wider viewpoint, the model is applicable to manufacturing companies that have a detailed loss monitoring system similar to Cost Deployment. / Marknaden utvecklas och konkurrensen ökar vilket medför ett ökat tryck på företagen att behålla sin konkurrensfördel. Att arbeta med kostnadsbesparingar är det säkraste sättet för att öka förtjänsten på kort sikt men även i ett längre perspektiv. Volvo Powertrain Production Köping har ett övergripande mål som innebär att kostnaderna ska reduceras med nio procent på tre år. För att uppnå målet arbetar Volvo Powertrain Production Köping med World Class Manufacturing där bearbetningsteknik utgör en viktig del. Volvo Powertrain Production Köping saknar en standard för hur besparingar inom bearbetningsteknik ska beräknas. Detta medför svårigheter att kontrollera och följa upp den egna verksamhetens utfall men också svårigheter att kontrollera verktygsleverantörernas utfall som ligger till grund för inköpsförhandlingar. Syftet med examensarbetet är att öka förståelsen för hur aktiviteter inom det bearbetningstekniska området påverkar produktiviteten genom en kalkylmodell. Arbetet började med en nulägesbeskrivning och en litteraturgenomgång som visade att många företag saknade en timkostnad framtagen på maskinnivå. Det finns teori som säger att maskintimkostnaden bör finnas både för producerande tillstånd och stillestånd vilket i efterföljande kvalitativa intervjuer med andra företag visar sig vara långt ifrån verkligheten. Insamlad information analyserades och en modell utvecklades. Modellen har testats i två förbättringsprojekt och utfallet har jämförts med befintliga kalkyler från verktygsförsäljare. Resultatet av examensarbetet är en standardiserad besparingskalkyl med en maskinspecifik timkostnad där hänsyn tas till om maskinen producerar eller om maskinen har oplanerat stillestånd. Besparingskalkylen är baserad på Cost Deployment som redan används inom Volvo Powertrain Production Köping. Besparingsmodellen är inte enbart till för att beräkna besparingar utan modellen kan också hjälpa användaren att förstå hur olika parametrar påverkar tillverkningskostnaden i hopp om att öka kostnadsmedvetenheten och minska risken för suboptimering i den egna verksamheten. Den framtagna timkostnaden är inte specifik för bearbetningsteknik utan hela företaget har nytta av kalkylen vid besparingsberäkningar. I ett större perspektiv är modellen applicerbar på tillverkningsföretag som har en noggrann förlustuppföljning liknande Cost Deployment.

Znížená efektivita spôsobená robením repetitívnych a manuálnych prác je častým problémom v IT. Vývojári často testujú a nasadzujú svoj software manuálne, čo je nielen náročné na čas, nezáživné a náchylné k chybám. Táto práca sa snaží v rámci jedného DevOps tímu, vyriešiť tento problém pomocou zjednotenia vývojárskych a testovacích nástrojov, a pomocou aplikovania pricípov CI a CD do produkčného prostredia. Zároveň sa sústredí na software využívajúci Python, Jenkins a kontajnery. Hlavnými použitými nástrojmi sú GitLab CI, OpenShift a Tox. Vďaka tejto práci sa podarilo zvýšit počet projektov, ktoré používajú CI/CD zo 7 na 50 percent, zvrátiť rastúci trend v počte porušení štýlu v jazyku Python, opatriť kontajnery metadátami, zautomatizovať proces tvorby kontajnerov, ušetriť čas nerobením repetitívnych úloh a pod.