The intensifying idea that AI soon will be a part of our everyday life allows for dreams about the complex relationship we one day could have with non-biological social intelligence. However, establishing societal and individual acceptance of AI-powered autonomy in disciplines built upon to the reliance to human competence raises a number of pressing challenges. One of them being, what system components will engender respectively counteract cognitive trust in socially oriented AI-automated processes?   This masters thesis tackles the seemingly ambiguous concept of trust in automation by identifying and evaluating system components that affect trust in a confined and contextualised setting. Practically, we design, construct and test an AI-powered chatbot, Ava, that contains socially oriented questions and feedback about study- and vocational guidance. Through a comparative study of different system versions, including both quantitative and qualitative data, we contribute to the framework for identifying and evaluating human trust in AI-Automated service encounters. We show how targeted alterations to design choices constituting the system components transparency, unbiasses and system performance, identified to affect trust, has consequences on the perception of the cognitive trust concepts integrity, benevolence and ability. Our results display a way of conduct for practitioners looking to prioritise and develop trustworthy autonomy. More specifically, we account for how cognitive trust is decreased when system opacity is increased. Moreover, we display even more concerning effects on trust due to micking contextual bias in the conversation agent.

The object of this research is to optimize the overall power system performance using FACTS devices. Particularly, it is intended to improve the reliability, and the performance of the power system considering steady state operating condition as well as the system subjected to small and large disturbances. The methodology proposed to achieve this goal corresponds to an enhanced particle swarm optimizer (Enhanced-PSO) that is proven in this work to have several advantages, in terms of accuracy and computational effort, as compared with other existing methods. Once the performance of the Enhanced PSO is verified, a multi-stage PSO-based optimization framework is proposed for optimizing the power system reliability (N-1 contingency criterion). The algorithm finds optimal settings for present infrastructure (generator outputs, transformers tap ratios and capacitor banks settings) as well as optimal control references for distributed static series compensators (DSSC) and optimal locations, sizes and control settings for static compensator (STATCOM) units. Finally, a two-stage optimization algorithm is proposed to improve the power system performance in steady state conditions and when small and large perturbations are applied to the system. In this case, the algorithm provides optimal control references for DSSC modules, optimal location and sizes for capacitor banks, and optimal location, sizes and control parameters for STATCOM units (internal and external controllers), so that the loadability and the damping of the system are maximized at minimum cost. Simulation results throughout this research show a significant improvement of the power system reliability and performance after the system is optimized.

Made available in DSpace on 2016-06-02T19:51:46Z (GMT). No. of bitstreams: 1 3310.pdf: 3654714 bytes, checksum: 8f5412389b554170e561ec7fca521015 (MD5) Previous issue date: 2010-10-07 / This work assumes that to effectively manage business activities, a form of control and monitoring is necessary, whether by means of indicators, or in a more advanced situation, by means of a performance measurement process that is suitable to the company s reality. Thus, the objective of this study is to establish guidelines for develop a performance measurement system, capable of assisting the peculiarities and organizational needs of control and strategies for companies in the wood sector in the city of Sinop, in Mato Grosso, Brazil. Companies currently face several challenges, because they need to thrive in a highly competitive environment, concomitantly meeting the needs and expectations of multiple stakeholders. This paper addresses the importance of environmental and social variables, which are currently increasing and whose reflexes on the organization are no longer latent but obvious. The method used to achieve the goals was the multiple case study with a qualitative approach, which enabled to identify the companies selected, and from this reality, to establish guidelines for develop a performance measurement system for two scenarios, was first proposed for the method of Rouse e Putterill (2003) for companies without an adequate infrastructure to measure performance. The second applies the Performance Prism framework by Neely et al. (2002) for companies with more suitable infrastructure for the development of a system performance measurement more robust. In all the companies of the scenario, social and environmental issues can be included, hence representing the reality under study in a clearer manner. The contribution the academy is conducted to compare the characteristics of performance measurement and management infrastructure, already contributing to the logging companies was made to suggest ways to control and evaluation of activities that respect the maturity of the management and peculiarities of each. / Este trabalho parte da premissa que, para efetivamente haver gerenciamento das atividades do negócio, é necessária uma forma de controle e acompanhamento, seja por meio de indicadores ou, numa situação mais avançada, um sistema de medição de desempenho adequado à realidade da empresa. Assim, tem-se como objetivo estabelecer diretrizes para o desenvolvimento de um sistema de medição de desempenho, capaz de atender às peculiaridades e necessidades organizacionais de controle e estratégias das empresas do setor madeireiro na cidade de Sinop, no estado do Mato Grosso. Atualmente, há vários desafios para essas empresas, pois, num ambiente altamente competitivo, precisam prosperar, atendendo de forma concomitante, aos anseios dos mais diversos stakeholders. Este trabalho tem a preocupação de retratar a importância das variáveis ambientais e sociais que aumentam gradativamente e cujos reflexos na organização deixam de ser latentes e passam a ser evidentes. O método utilizado para atingir os objetivos foi o estudo de caso múltiplo com abordagem qualitativa, que permitiu conhecer as empresas selecionadas, para, a partir desta realidade, estabelecer as diretrizes para o desenvolvimento de formas de medição de desempenho para dois cenários: para o primeiro foi proposto o método de Rouse e Putterill (2003) para empresas sem uma infraestrutura adequada à medição de desempenho; para o segundo foi proposto o Performance Prism de Neely et al. (2002) para empresas com infraestrutura mais apropriada, sendo possível o desenvolvimento de um sistema de medição de desempenho mais robusto. Em ambos, a questão social e ambiental pode ser incluída, retratando melhor a realidade em estudo. A contribuição à academia é realizada ao relacionar as diretrizes características da medição de desempenho e a infraestrutura de gestão. Já a contribuição para as empresas madeireiras foi efetuada ao sugerir formas de controle e avaliação das atividades que respeitem a maturidade e peculiaridades da gestão de cada uma.

Operating Systems use fast, CPU-addressable main memory to maintain an application’s temporary data as anonymous data and to cache copies of persistent data stored in slower block-based storage devices. However, the use of this faster memory comes at a high cost. Therefore, several techniques have been implemented to use main memory more efficiently in the literature. In this dissertation we introduce three distinct approaches to improve overall system performance by optimizing main memory usage. First, DRAM and host-side caching of file system data are used for speeding up virtual machine performance in today’s virtualized data centers. The clustering of VM images that share identical pages, coupled with data deduplication, has the potential to optimize main memory usage, since it provides more opportunity for sharing resources across processes and across different VMs. In our first approach, we study the use of content and semantic similarity metrics and a new algorithm to cluster VM images and place them in hosts where through deduplication we improve main memory usage. Second, while careful VM placement can improve memory usage by eliminating duplicate data, caches in current systems employ complex machinery to manage the cached data. Writing data to a page not present in the file system page cache causes the operating system to synchronously fetch the page into memory, blocking the writing process. In this thesis, we address this limitation with a new approach to managing page writes involving buffering the written data elsewhere in memory and unblocking the writing process immediately. This buffering allows the system to service file writes faster and with less memory resources. In our last approach, we investigate the use of emerging byte-addressable persistent memory technology to extend main memory as a less costly alternative to exclusively using expensive DRAM. We motivate and build a tiered memory system wherein persistent memory and DRAM co-exist and provide improved application performance at lower cost and power consumption with the goal of placing the right data in the right memory tier at the right time. The proposed approach seamlessly performs page migration across memory tiers as access patterns change and/or to handle tier memory pressure.

The aim of this thesis is to compare and evaluate pension system of the Czech Republic and Switzerland and the pension funds operating at the level of II. and III. pillar. In many aspects Switzerland is claimed to have the right and healthy pension system. This thesis tries to answer if it is true and in what way could be Switzerland inspiring for the Czech Republic. At first, the study focuses on present pension systems in both countries, characterizes them and after it describes their economic environment. Using method of quantitative analysis the paper compares pension funds in the Czech Republic and Switzerland according chosen factors. As the conclusion the paper is devoted to final comparison of pension systems of both countries and evaluates them.

Cross-Eye (CE) jamming is a technique aimed at inducing false target angles in radar measurements. The potential to deceive monopulse radar, a radar type commonly used due to its angular accuracy and resilience against jamming, has captured the interest of Electronic Warfare (EW) system manufacturers. CE jamming may increase the capability of self-defense against radar guided missiles. In this thesis, a CE jammer, based on the retrodirective channel design, for use in an EW systems is modeled and analyzed. The focus of the analysis is on the non-reciprocal Active Electronically Scanned Arrays (AESA). An electrical model of the jammer system and the AESA, including variations in the electrical properties, together with three different system correction methods are used. A simulation procedure, using single frequency (CW) signals, is defined and used for estimating total level of reciprocity, which is a primary contributor to jammer performance. Reciprocity error sensitivity for variations in model parameters is simulated to indicate which AESA aspects are essential for performance. Further, the influence of characterization and calibration noise is investigated. The usability of the model is demonstrated in different types of simulations, which highlights the differences between the system correction methods. Simulations show that a relatively high level of reciprocity can be achieved when using system correction, if measurement noise and model limitations are disregarded. The expected degradation in reciprocity from differences in electrical properties between the reception and transmission branch of the AESA has been confirmed. The effect of characterization and calibration noise, for realistic levels of noise, seems to be a dominating factor in the total reciprocity error. A significant increase in reciprocity error can likely be expected when non-CW signals are used and when realistic levels of noise and non-linear effects are added. / Cross-eye (CE) är en störprincip som har potential att inducera vinkelmätfel i radar. Dess möjlighet att störa monopulsradar, en vanligt förekommande typ av radar som är motståndskraftig mot många störformer, har skapat ett intresse för metoden hos tillverkare av system för elektronisk krigföring (EW-system). Användning av CE störning i ett EW-system skulle kunna öka möjligheten till självskydd vid attack från en monopulsradarstyrd robot. Avhandlingen analyserar en modell av en retrodirektiv CE störare som är avsedd för integration i ett multifunktionellt EW-system. Fokus i analysen är på de aktiva gruppantennerna (AESA) som används i systemet. En elektrisk modell av systemet används, vilken inkluderar variationer i parametrar hos AESA samt tre olika systemkorrektionsmetoder. En simuleringsprocedur som ger möjlighet att uppskatta reciprocitetsfel och känslighet för parametervariationer i AESA är definierad. Vidare undersöks inverkan av karaktäriserings och kalibreringsbrus. Modellens användningsområden visas i olika typer av prestandasimulering där effekter av de olika systemkorrektionsmetoderna tydliggörs. Simuleringsresultat för enkelfrekvens (CW) signaler visar en relativt hög nivå av reciprocitet om brus och olinjäriteter ignoreras. Det förväntade resultatet, att elektriska skillnader mellan mottagar- och sändargrenarna orsakar en försämring i reciprocitet, bekräftas. Inverkan av karaktäriserings och kalibreringsbrus verkar vara en dominerande faktor i det totala reciprocitetsfelet då rimliga brusnivåer används. En signifikant höjning av reciprocitetsfelet kan sannolikt förväntas då signaler med en viss bandbredd används och då rimliga nivåer av brus samt olinjäriteter inkluderas. / <p>QC 20171102</p>

<p>The 2020 pandemic emphasized the need for accessible and accurate point-of-care diagnostic tests. With the continued development of isothermal nucleic acid amplification tests, this can be achieved. A requirement of these tests includes heating and holding a specific temperature, in this case, 65C for 30 minutes, for amplification to occur. To achieve this, heaters often require external feedback to control the temperature; bringing up the device’s cost. Several self-regulating heaters have been made with materials having a positive thermal coefficient of resistance eliminating the need for complex circuitry. With this property, point-of-care diagnostic tests can be simplified and made more accessible. In this study, ink-based positive thermal coefficient of resistance heaters are developed and characterized using the scalable method of screen printing to achieve 65C and aid in the detection of SARS-CoV-2. Various curing methods and screen-printing parameters were evaluated to improve the stability and understanding of the reproducibility of the heaters. The longevity of the heaters was evaluated with oxidation studies and a COMSOL model was created to study the heat transfer within the device. Furthermore, the heaters were successfully implemented into a second-generation electronic point-of-care diagnostic device. Detection of SARS-CoV-2 using a self-regulating heater removes the need for complex circuitry, improving the accessibility of point-of-care tests with the potential to be expanded to a wide range of pathogen detection. </p>

Currently, there are various training machines that can support training of the muscles while the muscles are lengthened, also known as eccentric training. Training machines that are widely used to train the muscles eccentrically utilize a flywheel to generate load to the user. When training the muscles eccentrically with such a machine, there is a desire to accomplish eccentric overload, which is achieved when the muscles under training are exposed to a very high load during eccentric training of these muscles. To achieve this, the user needs to activate other muscles that are not in the focus of the training or be assisted by another person. In this study, a novel, smart flywheel training machine was developed by implementing electric motor and sensors, which could identify the exercise pattern of the user and help achieve desired eccentric overload. This study focused on how the system performance of such training machine interacting with human beings was affected by various grade of sensor feedback. With an increased resolution of the sensors and a lower sample time, the cost of the system is increased, and it was therefore of interest to study what grade of sensor feedback was required. More exactly, this study evaluated how the system performance was improved when sensor resolution was improved, what resolution and sample time were required for the system to perform correct and safely and last, how noise and disturbances affected the system. The study was conducted in a simulated environment in Matlab and Simulink, and some real tests and experiments were also performed on the existing flywheel training machine. An incremental encoder was implemented in the system and resolution of the encoder, as well as sample time, were tweaked in the simulation to test different combinations of these. The results showed that both resolution and sample time had an impact on the system performance. A higher resolution resulted in a smaller tracking error to some extent, but after a certain value the system became unstable if the sample time was not small enough. Noise and disturbances had a minor impact on the system performance. It was concluded that the best choice of encoder resolution was 0.0314 radians with a sample time of 0.01 ms. Even lower resolution such as 0.628 rad, 0.126 rad or 0.0571 rad with a sample time of 0.1 ms could be allowed and should be considered safe. However, the system might not perform as desired if these alternatives are chosen, although the alternatives might decrease the cost of the system. / I nuläget finns det olika träningsmaskiner som kan stödja träning av muskler där musklerna förlängs, även känt som excentrisk träning. Träningsmaskiner som idag används i stor utsträckning för att träna musklerna excentriskt använder ett svänghjul för att generera träningsmotstånd till användaren. När musklerna tränas excentriskt med en sådan maskin finns det en önskan att åstadkomma excentrisk överbelastning; detta uppnås när musklerna som tränas utsätts för en mycket hög belastning under den excentriska träningsfasen. För att uppnå detta måste användaren aktivera andra muskler som inte står i träningens fokus eller få hjälp av en annan person. I den här studien har en ny, smart, svänghjulsträningsmaskin utvecklats genom att implementera elmotor och sensorer som kan identifiera användarens träningsmönster och hjälpa till att uppnå önskvärd excentrisk överbelastning. Denna studie fokuserade på hur systemprestanda för en sådan träningsmaskin som interagerar med människor påverkades av olika grader av sensoråterkoppling. Med en ökad upplösning av sensorerna och en lägre samplingstid ökar kostnaden för systemet och det var därför av intresse att studera vilken grad av sensoråterkoppling som krävdes. Mer exakt utvärderar denna studie hur systemets prestanda förbättrades när sensorupplösningen var högre och vilken upplösning och samplingstid som krävdes för att systemet skulle fungera korrekt och säkert. Påverkan av brus och störningar på systemet utvärderades också. Studien genomfördes i simuleringsmiljö i Matlab och Simulink och verkliga tester och experiment utfördes på den befintliga svänghjulsträningsmaskinen. En inkrementell pulsgivare (incremental encoder) implementerades i systemet och dess upplösning, såväl som samplingstid, justerades i simuleringen för att testa olika kombinationer av dessa. Resultat visade att både upplösningen och samplingstiden påverkade systemets prestanda. En högre upplösning resulterade i ett mindre reglerfel till en viss del, men efter en viss ökad upplösning blev systemet instabilt om samplingstiden inte var tillräckligt liten. Brus och störningar hade en mindre inverkan på systemprestandan. Slutsatsen var att det bästa valet av pulsgivarupplösning var 0,0314 radianer med en samplingstid på 0,01 ms. Även lägre upplösning såsom 0,628 rad, 0,126 rad eller 0,0571 rad med en samplingstid på 0,1 ms kan tillåtas och bör betraktas som säkert. Systemet kan dock komma att inte fungera som önskat om dessa alternativ väljs, dock kan alternativen sänka kostnaden för systemet.

This research explores an innovative approach to managing extensive rulesets in Host Intrusion Detection Systems (HIDS) through segmentation and dynamic expansion. Drawing upon the MITRE ATT&amp;CK framework, the methodology categorizes rulesets into initial detection, choke point detection, and advanced detection, streamlines threat detection, and optimizes resource utilization. The segmentation allows for targeted detection of potential threats, while dynamic expansion enables the addition of advanced detection rules based on attacker actions. The study evaluates the effectiveness of this approach in reducing performance overhead and improving threat detection capabilities. Test cases validate the approach for detecting multi-stage attacks and optimizing system performance. Results indicate that while the segmentation and dynamic expansion technique offers structured threat detection, challenges such as missed detections and complexity in rule management exist. Future research directions include refining segmentation processes and enhancing rule categorization logic. Overall, this research contributes to the advancement of HIDS methodologies and underscores the importance of ongoing refinement and validation in cybersecurity strategies.

Made available in DSpace on 2015-03-05T17:05:27Z (GMT). No. of bitstreams: 0 Previous issue date: 27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação apresenta uma proposta de método para elaboração de um sistema de indicadores industriais. O método é proposto visando estabelecer um alinhamento entre as dimensões competitivas oriundas da estratégia de produção e de sistemas de produção baseados nos conceitos, métodos e técnicas do Sistema Toyota de Produção e da Teoria das Restrições. A pesquisa tem como base metodológica o design research, estruturado em cinco fases: conscientização do problema, sugestão, desenvolvimento do artefato, avaliação e conclusão. O método sugerido para a elaboração do sistema de indicadores consiste em oito etapas: análise do ambiente industrial; identificação das práticas de gestão da produção utilizadas na empresa; análise do desdobramento da estratégia de negócios da empresa nos objetivos específicos da área industrial; elaboração de uma proposta inicial do conjunto de indicadores a ser adotado; detalhamento dos indicadores; validação do conjunto de indicadores proposta final do conjunto de indicadores e; mon