"One thing cannot be disputed: immigrants from all backgrounds and levels of cultural capital are drawn to noncredit ESL programs with high hopes of a brighter future and the attainment of the American dream" (Becker 2011). Adult ESL community learners are a fast-growing and diverse group of individuals. Previous studies demonstrate the many challenges this group faces in attending English classes (Tan, Nabb, Aagard, and Kim 2010; Tucker 2007) and the need for more online learning to better meet their needs (Eyring 2014; Reynard 2003). A survey was administered to 136 adult community ESL learners enrolled at the Provo, Utah Adult English Language Acquisition Program. Results of the survey detail their challenges, perceptions of online learning and whether they have the resources and skills needed to be successful in an online English class. Based on results from the survey, challenges to attending English classes still exist among adult community ESL learners. Although many of the participants had taken an online English class in the past, results indicate an overwhelming number of learners who want face-to-face instruction. There is also a need for hybrid and synchronous learning among primary care givers of children, participants with a bachelor's degree or higher, and participants 40 years old or younger. Many participants perceived themselves as having the skills needed to take an online class, yet participants still reported that online learning was difficult, and a computer class would be helpful. Further results indicate that many participants do not have all the resources needed to take an online class and some lack a quiet space to learn online.

A method for performing robust optimal design that combines the efficiency of experimental designs and the accuracy of nonlinear programming (NLP) has been developed, called Search-and-Zoom. Two case studies from the RF and communications industry, a high-frequency micro-strip band-pass filter (BPF) and a rectangular, directional patch antenna, were used to show that sensitivity optimization could be effectively performed in this industry and to compare the computational efficiency of traditional NLP methods (using fmincon solver in MATLAB R2013a) and they hybrid method Search-and-Zoom. The sensitivity of the BPF's S11 response was reduced from 0.06666 at the (non-robust) nominal optimum to 0.01862 at the sensitivity optimum. Feasibility in the design was improved by reducing the likelihood of violating constraints from 20% to nearly 0%, assuming RSS (i.e., normally-distributed) input tolerances and from 40% to nearly 0%, assuming WC (i.e., uniformly-distributed) input tolerances. The sensitivity of the patch antenna's S11 function was also improved from 0.02068 at the nominal optimum to 0.0116 at the sensitivity optimum. Feasibility at the sensitivity optimum was estimated to be 100%, and thus did not need to be improved. In both cases, the computation effort to reach the sensitivity optima, as well as the sensitivity optima with RSS and WC feasibility robustness, was reduced by more than 80% (average) by using Search-and-Zoom, compared to the NLP solver.

The interface with the real-world has proved to be extremely challenging throughout the past 70 years in which computer technology has been developing. The problem initially is assumed to be somewhat trivial, as humans are exceptionally skilled at interpreting real-world data, for example pictures and sounds. Traditional analytical methods have so far not provided the complete answer to what will be termed pattern recognition. Biological inspiration has motivated pattern recognition researchers since the early days of the subject, and the idea of a neural network which has self-evolving properties has always been seen to be a potential solution to this endeavour. Unlike the development of computer technology in which successive generations of improved devices have been developed, the neural network approach has been less successful, with major setbacks occurring in its development. However, the fact that natural processing in animals and humans is a voltage-based process, devoid of software, and self-evolving, provides an on-going motivation for pattern recognition in artificial neural networks. This thesis addresses the application of weightless neural networks using a ranking pre-processor to implement general pattern recognition with specific reference to face processing. The evaluation of the system will be carried out on open source databases in order to obtain a direct comparison of the efficacy of the method, in particular considerable use will be made of the MIT-CBCL face database. The methodology is cost effective in both software and hardware forms, offers real-time video processing, and can be implemented on all computer platforms. The results of this research show significant improvements over published results, and provide a viable commercial methodology for general pattern recognition.

abstract: This dissertation proposes and presents two different passive sigma-delta modulator zoom Analog to Digital Converter (ADC) architectures. The first ADC is fullydifferential, synthesizable zoom-ADC architecture with a passive loop filter for lowfrequency Built in Self-Test (BIST) applications. The detailed ADC architecture and a step by step process designing the zoom-ADC along with a synthesis tool that can target various design specifications are presented. The design flow does not rely on extensive knowledge of an experienced ADC designer. Two example set of BIST ADCs have been synthesized with different performance requirements in 65nm CMOS process. The first ADC achieves 90.4dB Signal to Noise Ratio (SNR) in 512µs measurement time and consumes 17µW power. Another example achieves 78.2dB SNR in 31.25µs measurement time and consumes 63µW power. The second ADC architecture is a multi-mode, dynamically zooming passive sigma-delta modulator. The architecture is based on a 5b interpolating flash ADC as the zooming unit, and a passive discrete time sigma delta modulator as the fine conversion unit. The proposed ADC provides an Oversampling Ratio (OSR)- independent, dynamic zooming technique, employing an interpolating zooming front-end. The modulator covers between 0.1 MHz and 10 MHz signal bandwidth which makes it suitable for cellular applications including 4G radio systems. By reconfiguring the OSR, bias current, and component parameters, optimal power consumption can be achieved for every mode. The ADC is implemented in 0.13 µm CMOS technology and it achieves an SNDR of 82.2/77.1/74.2/68 dB for 0.1/1.92/5/10MHz bandwidth with 1.3/5.7/9.6/11.9mW power consumption from a 1.2 V supply. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

Dans de nombreux problèmes physiques, un modèle incertain peut être traduit par un ensemble d'équations aux dérivées partielles stochastiques. Nous nous intéressons ici à des problèmes présentant de nombreuses sources d'incertitudes localisées en espace. Dans le cadre des approches fonctionnelles pour la propagation d'incertitudes, ces problèmes présentent deux difficultés majeures. La première est que leurs solutions possèdent un caractère multi-échelle, ce qui nécessite des méthodes de réduction de modèle et des stratégies de calcul adaptées. La deuxième difficulté est associée à la représentation de fonctions de nombreux paramètres pour la prise en compte de nombreuses variabilités. Pour résoudre ces difficultés, nous proposons tout d'abord une méthode de décomposition de domaine multi-échelle qui exploite le caractère localisé des aléas. Un algorithme itératif est proposé, qui requiert une résolution alternée de problèmes globaux et de problèmes locaux, ces derniers étant définis sur des patchs contenant les variabilités localisées. Des méthodes d'approximation de tenseurs sont ensuite utilisées pour la gestion de la grande dimension paramétrique. La séparation multi-échelle améliore le conditionnement des problèmes à résoudre et la convergence des méthodes d'approximation de tenseurs qui est liée aux propriétés spectrales des fonctions à décomposer. Enfin, pour la prise en compte de variabilités géométriques localisées, des méthodes spécifiques basées sur les approches de domaines fictifs sont introduites.

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Cette thèse s’inscrit dans le cadre d’un projet industriel multi-partenaires ayant pour objectif le développement d’un robot mobile collaboratif (un cobot), autonome dans ses mouvements au sol, capable de réaliser l’inspection visuelle d’un aéronef, à la fois en phase de petite ou grande maintenance dans un hangar ou en phase de pré-vol sur le tarmac d’un aéroport. Le cobot est équipé de capteurs lui permettant d’effectuer ses tâches de navigation autonome, mais également d’un ensemble de capteurs optiques constituant la tête d’inspection : une caméra orientable Pan-Tilt-Zoom et un scanner 3D qui délivrent respectivement des données sous forme d’images 2D et de nuages de points 3D. L’objectif de la thèse est de développer des algorithmes d’analyse d’images 2D et de nuages de points 3D, afin d’établir un diagnostic sur l’état de l’avion et son aptitude à voler. Nous avons développé des algorithmes pour vérifier certains éléments de l’appareil, tels que valves, portes, capteurs, pneus ou moteurs, et également pour détecter et caractériser des dommages 3D sur le fuselage (impacts, rayures, etc.). Nous avons exploité dans nos algorithmes les connaissances a priori disponibles, en particulier le modèle 3D CAO de l’avion (un AIRBUS A320 dans le cadre de nos essais). Durant ces travaux de la thèse, nous avons pu répondre à deux besoins (parfois antagonistes) : développer des algorithmes d’inspection rapides et robustes, mais également répondre aux exigences spécifiques d’un projet industriel qui visait à développer un prototype opérationnel. Nous nous sommes attachés à développer des algorithmes les plus génériques possibles, de manière à ce qu’ils puissent être utilisés pour d’autres types d’inspection, tels que l’inspection de bâtiments ou de navires par exemple. Nous avons aussi contribué au développement du prototype (robot mobile équipé de capteurs) en développant le module de contrôle des capteurs d’inspection et en intégrant nos codes sur le robot avec les autres modules développés par les partenaires. Le prototype a fait l’objet de nombreux essais en hangar de maintenance ou sur tarmac. / This thesis makes part of an industry oriented multi-partners project aimed at developing a mobile collaborative robot (a cobot), autonomous in its movements on the ground, capable of performing visual inspection of an aircraft during short or long maintenance procedures in the hangar or in the pre-flight phase on the tarmac. The cobot is equipped with sensors for realizing its navigation tasks as well as with a set of optical sensors which constitute the inspection head: an orientable Pan-Tilt-Zoom visible light camera and a three-dimensional scanner, delivering data in the format of two-dimensional images and three-dimensional point clouds, respectively. The goal of the thesis is to propose original approaches for processing 2D images and 3D clouds, with intention to make a decision with respect to the flight readiness of the airplane. We developed algorithms for verification of the aircraft items such as vents, doors, sensors, tires or engine as well as for detection and characterization of three-dimensional damages on the fuselage. We integrated a-priori knowledge on the airplane structure, notably numerical three-dimensional CAD model of the Airbus-A320. We argue that with investing effort to develop robust enough algorithms and with the help of existing optical sensors to acquire suitable data, we can come up with non-invasive, accurate, and time-efficient system for automatic airplane exterior inspection. The thesis work was placed in between two main requirements: develop inspection algorithms which could be as general as possible and also meet the specific requirements of an industry oriented project. Often, these two goals do not go along and the balance had to be made. On one side, we were aiming to design and assess the approaches that can be employed on other large structures, for ex. buildings, ships. On the other hand, writing source code for controlling sensors as well as integrating our whole developed source code with other modules on the real-time robotic system, were necessary in order to demonstrate the feasibility of our robotic prototype.

The thesis deals with the design and optimization of varifocal lens for projection illuminating purposes, its mechanical design and manufacturing drawings. It was proceed in the cooperation with Robe Lighting s.r.o., which defined requirement for a new projective objective lens. Lighting fixtures development is a very specific industry with a number of unusual conditions for design and methods of using of the optical systems. In this paper conditions for imaging quality will be defined and a new design of the lens with corrected distortion will be created based on the definition of the conditions.

The ongoing Covid-19 pandemic has led to society being forced to switch to a digital presence, where physical meetings have been replaced by digital ones. For universities, this has meant that teaching and examinations have taken place through a special installation of the video conferencing service Zoom. Zoom is offered in a so-called on-premises installation which largely runs on private servers or instance, in Denmark. NORDUnet and Sunet are the providers of the special installation which has been given the “Sunet E-meeting”. For the service to work, personal data is processed. This data includes names and e-mail addresses, but also meeting data, gathered by the camera and audio feed, and IP-addresses. All personal data should be processed on the private instance according to the service description. To connect to the service, various options are provided, including installing a client provided by Zoom on a computer or smartphone. Another way to connect that does not require any installation is through a web client, also provided by Zoom.  One of Sweden’s universities recently discovered that a student who joined the meeting via the web client was connected to a public Zoom data center in the United States. Through network analyzes and the study below, it turns out that the web client is a form of exception in the service where traffic does not go directly to the private cloud. Instead, the traffic goes via Zoom's public cloud where traffic is at risk of going to various data centers both outside and within the European Union. This study of the service is based on the data protection legislation. Questions concerning the division of roles and responsibilities between the data controller and the processor, security concerns, the use personal data, processing, and third-country transfers has been done.  Following the Schrems II judgment, where the European Court of Justice ruled that the United States does not have an adequate level of protection regarding the protection of individuals' personal data, the possibilities of transferring personal data to the country were limited. Determining whether the usage of the cloud service means that personal data is transferred to the United States or not is therefore of great importance. This study concludes that a third country transfer has occurred at least once, which is not compatible within the data protection regulation. The study also shows the importance of knowledge of the service being used both by the controller and processor to ensure correct processing of the data.

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