[pt] Os últimos anos mostraram um interesse crescente no uso do controle háptico compartilhado (HSC) em sistemas teleoperados. No HSC, a aplicação de forças orientadoras virtuais, diminui o esforço de controle do usuário e melhora o tempo de execução em várias tarefas, apresentando uma boa alternativa em comparação com a teleoperação direta. O HSC, apesar de demonstrar bom desempenho, abre uma nova lacuna: como disenhar as forças orientadoras. Por esse motivo, o verdadeiro desafio está no desenvolvimento de controladores para fornecer as forças orientadoras virtuais, capazes de lidar com novas situações que aparecem enquanto uma tarefa está sendo executada. Este trabalho aborda esse desafio, projetando um controlador baseado no algoritmo Deep Deterministic Policy Gradient (DDPG) para fornecer assistência, e uma rede neural convolucional (CNN) para executar a detecção da tarefa. O agente aprende a minimizar o tempo que o ser humano leva para executar a tarefa desejada, minimizando simultaneamente sua resistência ao feedback fornecido. Essa resistência fornece ao algoritmo de aprendizado informações sobre a direção que o humano está tentando seguir, neste caso na tarefa pick-and-place. Diversos resultados demonstram a aplicação bem-sucedida da abordagem proposta, aprendendo políticas personalizadas para cada usuário que foi solicitado a testar o sistema. Ele exibe convergência estável e ajuda o usuário a concluir a tarefa com o menor número possível de etapas. / [en] Recent years have shown a growing interest in using haptic share control (HSC) in teleoperated systems. In HSC, the application of virtual guiding forces decreases the user’s control effort and improves execution time in various tasks, presenting a good alternative in comparison with direct teleoperation. HSC, despite demonstrating good performance, opens a new gap: how to design the guiding forces. For this reason, the real challenge lies in developing controllers to provide the virtual guiding forces, able to deal with new situations that appear while a task is being performed. This work addresses this challenge by designing a controller based on the deep deterministic policy gradient (DDPG) algorithm to provide the assistance, and a convolutional neural network (CNN) to perform the task detection. The agent learns to minimize the time it takes the human to execute the desired task, while simultaneously minimizing their resistance to the provided feedback. This resistance thus provides the learning algorithm with information about which direction the human is trying to follow, in this case, the pick-and-place task. Diverse results demonstrate the successful application of the proposed approach by learning custom policies for each user who was asked to test the system. It exhibits stable convergence and aids the user in completing the task with the least amount of steps possible.

There is a housing shortage in attractive urban areas in Europe and Sweden. The waiting lists for affordable rental housing are increasing and that in turn creates pressure on owner-occupied housing. Inflated asset prices and household debt have become a major concern for policy makers. Shared ownership is a mixture of equity and debt, therefore, a mixture of owner-occupation and rental accommodation. In the UK it´s used by the non-profit sector to help households to buy their own home. In this research a shared ownership model is developed for the Swedish property market. The model is commercially viable and used to extend traditional mortgage finance. The findings suggest that the proposed model can increase household affordability and lower their exposure to the financial markets. An investor will gain a market rate of return and access a market segment different from rental housing, shared ownership is an investment in owner-occupational housing. The major drawback of the model is the relationship between the bank and the investor. The bank will require priority to the collateral which results in a complicated and inflexible model. Further research should investigate the possibility of sharing collateral which would result in a simpler and more flexible model. / Bostadsbristen i europeiska och svenska storstadsregioner har resulterat i långa köer till rimliga hyresrätter. Detta har ökar pressen på bostadsrätter och ökat hushållens skuldsättning, vilket ses som ett potentiellt hot mot ekonomin. Hybridköp av bostäder innebär att bostadskonsumenten hyr en del av bostaden och köper den andra. I Storbritannien subventioneras detta av staten för att hjälpa hushåll att köpa sin bostad. Målet med denna studie är att skapa en modell för hybridköp i Sverige. Modellen kommer att komplimentera bostadslån och drivas på kommersiella grunder. Resultatet av studien visar att konsumenten kan ökar sin köpkraft och minska exponeringen mot den finansiella marknaden. Investeringen har en marknadsmässig avkastning och ger en möjlighet att investera i bostadsrätter och småhus, ett segment som skiljer sig från hyresrätter. Den största nackdelen är att banken kommer att kräva prioritet till säkerheten som ligger i bostaden vilket resulterar i en komplicerad modell. Fortsatta studier borde utforska möjligheten att dela säkerheten mellan investeraren och banken.

Heterogeneous computing is increasingly used in today's datacenters to meet the increasing computational demands of applications. Heterogeneous hardware typically includes CPUs, GPUs, ASICs, and FPGAs, among others. An important emerging trend is instructionset- architecture (ISA)-heterogeneity: high-end x86 servers with attached SmartNICs and SmartSSDs that incorporate general-purpose CPUs, typically of the RISC ISA family (e.g., ARM, RISC-V). To alleviate resource congestion on server computing nodes, application workloads can be scaled-out across server x86 CPUs and SmartNIC ARM CPUs using the distributed shared memory (DSM) abstraction. We present SNIC-DSM, a SmartNIC-based DSM infrastructure for heterogeneous ISA machines. SNIC-DSM implements a low-latency messaging layer, which enables inter-node communication across multi-ISA CPUs, and a DSM protocol processor that provides memory coherency among these nodes, both implemented in SmartNIC's FPGA logic. SNIC-DSM is reconfigurable and allows the implementation of different memory consistency protocols. Our experimental studies using compute-intensive benchmarks reveal that SNIC-DSM outperforms the state-of-the-art DSM - Popcorn Linux's software DSM - when server resource congestion is high. / Master of Science / The availability of heterogeneous computing architectures has led to the development of distributed shared memory systems, which allows compute-intensive applications to run in a distributed manner on different types of computing devices such as graphics processors, reconfigurable logic devices, and custom integrated circuits. Adopting such a heterogeneous computing strategy yields better performance and improves power consumption. Generally, these DSM systems use a software-based approach, which offers great flexibility but suffers from software overheads. Hardware-based approaches are used to overcome these limitations but they generally do not offer flexibility. This thesis presents, SNIC-DSM, which is a reconfigurable implementation of the DSM framework. SNIC-DSM provides a platform for the host and smart networking devices such as SmartNICs to communicate with each other and enables application execution in a distributed manner by providing memory coherency. Our experimental evaluation using High-Performance Computing benchmarks reveals that SNIC-DSM improves performance when compared with software-based DSM.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24803号 / 医博第4995号 / 新制||医||1067(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 金子 新, 教授 伊藤 能永, 教授 上野 英樹 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Sweden is often identified as one of the countries where implementation of Agenda 2030 and the Sustainable Development goals (SDGs) is high. There is still, however, considerable room for improvements, especially considering the mitigation of climate change, and in addition, the reinterpretation of Agenda 2030 and the SDGs have been proven challenging in Swedish sustainability governance. Infrastructure, responsible for approximately 80%, has been identified as an area where strategies for climate change mitigation are likely to have a significant impact. Simultaneously, infrastructure development has been identified as key in driving human development and fulfilling Agenda 2030 and the SDGs. As sustainable infrastructure is becoming increasingly important, understanding what constitutes sustainable infrastructure is essential. Using a case study approach, this study explores the conceptualization and integration of sustainability in Sweden, explicitly focusing on road culvert replacements in northern Sweden. The findings reveal a lack of a shared understanding of what constitutes sustainable transport infrastructure but show a partially shared understanding of what constitutes sustainable road culvert replacement practices. The analysis highlights challenges faced by public organizations in implementing sustainability and emphasizes the importance of stakeholder collaboration and knowledge exchange. This research provides insights into strategies for integrating sustainability into road culvert replacements and highlights the importance of stakeholder collaboration for sustainable outcomes, contributing to future sustainable infrastructure development.

Elever som hamnar i matematiksvårigheter ska, utöver ledning och stimulans, genom extra anpassningar och/eller särskilt stöd få det stöd som krävs för att de ska kunna nå utbildningens mål. Elever erbjuds i en del fall, utöver stöd från ämneslärare i helklass, särskilt stöd av speciallärare, specialpedagoger eller lärare med specialpedagogisk kompetens. Det stödet kan ges i särskild undervisningsgrupp till skillnad från stöd från lärare som ges i den ordinarie undervisningen. Elever får därför undervisning av olika lärare och i den här studien undersöks lärarsamarbete kring undervisning av dessa elever. Syftet är att undersöka hur några ämneslärare, speciallärare/specialpedagog och lärare med specialpedagogisk kompetens i matematik samarbetar i det dagliga arbetet kring elever i behov av särskilt stöd. I den småskaliga studien undersöks lärarnas samarbete kring elever som delar sin undervisning och går mellan en klassrumssituation och en särskild undervisningsgrupp. Det är en kvalitativ studie där data har samlats in via semistrukturerade intervjuer. Elva lärare har deltagit i studien. Lärare avser här ämneslärare, speciallärare/specialpedagog och lärare med specialpedagogisk kompetens. Studiens resultat visar att skolorna oftast har en ”studio” eller motsvarande dit eleverna går vissa lektioner men att det verkar saknas ett systematiskt samarbete kring elever som får stöd i särskild undervisningsgrupp. I ”studion” finns större tillgång till laborativt och konkret material jämfört med i det vanliga klassrummet samt att fler uppgifter görs muntligen där. När eleven deltar i helklassundervisning ges eleven extra anpassningar i form av att läraren väljer vilka uppgifter eleven ska göra, möjlighet till paus under lektion och eleven arbetar oftast tyst för sig själv. De faktorer som påverkar samarbetet mellan lärarna upplevs vara organisation, kommunikation och relation.

<p>  </p> <p>The transportation sector has emerged as one of the largest contributors to energy consumption and greenhouse gas emissions within the U.S. economy. As a consequence, transportation sustainability faces great challenges in automobile traffic congestion alleviation, air pollution reduction, and climate change adaptation. Emerging technologies bring new chances to resolve these issues. However, existing literature focusing on the sustainability assessment of emerging technologies often relies on the analysis of isolated systems using historical data. These studies neglected the complex interactions across different systems and failed to consider the potential impacts of future technology adoption. The sustainability performance of emerging transportation technologies is heavily dependent on competing and complementary relationships with existing transportation systems. Furthermore, the dynamics of system interactions can change with the diffusion of future technologies, as user behavior becomes more heterogeneous. Consequently, the future adoption of emerging technologies may lead to an uncertain urban sustainability outlook. Therefore, sustainability assessment and prospective system planning for emerging technologies necessitate a comprehensive examination of their interactions with urban transportation systems and the evolving landscape. </p> <p>The primary objective of this dissertation is to demonstrate the necessity and benefits of incorporating system interactions into sustainability assessments. To achieve this goal, this dissertation conducts four case studies, using various models inspired by machine learning, statistics, econometrics, and agent-based approaches, and applies them to two emerging technologies: shared mobility (including bike-sharing, shared e-scooters, and ride-hailing) and e-commerce. First, the interaction classification analysis shows that the current shared mobility primarily competes with public transit rather than complementing it, resulting in a significant bus ridership decline. Second, to enhance sustainability, it is crucial for shared mobility to substitute private car trips and integrate effectively with public transit. Understanding why current users do not sustainably use the system is the key. Results from the traveler mode choice behavior show that the travel cost and out-of-vehicle travel time (e.g., time spent on walking connection, waiting) of shared mobility are the major barriers for travelers to substitute car trips and use multimodal systems. Third, future system planning should improve the pricing mechanisms and fleet management to encourage travelers to use shared mobility in a sustainable way. Optimal pricing and fleet management strategies are sought through an agent-based simulation. Transit-oriented-development is proven to be the best fleet siting strategy and an optimal combination of fleet size and pricing for each shared mobility system is also solved for minimizing vehicle miles traveled (VMT) from urban transportation. Fourth, the penetration of e-commerce also reshapes urban mobility from personal travel demand changes, mode choice shifts, and goods delivery inclusion. We integrated the market segmentation and penetration of e-commerce into transportation simulation to comprehensively estimate its impact on urban mobility and transportation sustainability. </p> <p>Case studies from this dissertation demonstrate that the existing adoption of emerging technologies requires further actions in system design, user guidance, and operation management to obtain sustainability benefits. Knowledge from this dissertation supports decision-makers in their efforts to design and plan future emerging technologies toward a sustainable pathway. The findings and insights presented in the dissertation offer valuable guidance for policymakers, urban planners, and stakeholders involved in shaping the trajectory of these technologies.</p>

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The purpose of this study was to examine the relationships between family downhill skiing patterns and family functioning. The Family Adaptability and Cohesion Evaluation Scale (FACES II), was used to measure family functioning. Questions created by the researcher were used to measure the average number of family ski experiences per year (frequency) and how many years the family has skied together (duration). Satisfaction with family ski experiences was measured using the Satisfaction with Family Skiing Scale. The sample consisted of 110 family units from throughout the United States. The findings from this study found that frequency and duration of family ski experiences were not significant predictors of family functioning. The data did determine that satisfaction with family ski experiences was a significant predictor of family functioning from the youth, parent, and family perspectives.