Under det senaste århundrandet har möbeldesign utvecklats och designats för att bli mer ekonomiskt tillgänligt. Majoriteten av möblerna under de senaste årtiondet är designade för att underlätta fövaring och transport för att minimera kostnaden för företaget. Företaget kan låta kunden montera det själva i hemmet för att reducera priset ytterligare. För att kunderna ska bli nöjda behövs det en snabb och intuitiv monteringslösning. Detta projektets syfte är att förbättra monteringen för rambaserade möbler med fokus på FAMILJ A från IKEA. För insamling av information gällande de problem som kan komma upp när kunden monterar ihop möbler används olika metoder så som intern benchmarking och konsultering av experter. En behovs- och egenskaps matris upprättas som hjälp och riktlije för vad de nya koncepten bör upfylla. För att generera idéer för nya koncept som kan förbättra designen, används metoder så som extern benchmarking, patentsökning och brainstorming. 19 olika koncept och idéer som förbättrar och löser olika problem togs fram. Genom att konsultera experter på IKEA i en fokusgrupp väljs ett koncept ut som kallas för "Indented frame". Konceptet vidareutvecklas och en 3-dimensionel modell genereras för att visualisera det nya konceptet. Indented frame modifieras och anpassas efter dagens infästningsanordning. Baserat på den 3-dimensionella modellen skapas ritningar för tillverkning av prototyper. Prototypens monteringstid mäts och ett belastningstest utförst för att mäta hållfastheten. Resultatet är att den nya designen har en enklare monteringsprocess, snabbare monteringstid och belastningstestet visar ingen större skillnad i hållfasthet. Efter belastningstestet utvärderas det nya konceptet med dagens produkt som referens. Detta görs utifrån form, funktion, kvalité, hållbarhet och lågt pris. Slutsatsen är att det nya konceptet är en förbättrad design. / During the last century, furniture design has developed to become more financially accessible. Most furniture during the past decades is designed to facilitate the storage and transport of the product to minimise costs for the company. The company can let the customer assemble the furniture themselves at home to reduce the price even more. For customers' to be satisfied, the assembly of the furniture needs to go quickly and easily. The objective of this thesis is to improve today's assembling process of frame-based furniture with a focus on series of FAMILY A at IKEA. To gather information about what problems a customer may encounter today when assembling the furniture different methods are used such as consulting experts and internal benchmarking. A requirement and characteristics matrix is made as a guideline for what the new concepts should fulfil. To get ideas on new concepts that can improve the design, methods such as external benchmarking, patent search and brainstorming are used. The result is 19 different concepts that will improve several different problems. By consulting experts from IKEA in a focus group, one of the concepts named the Indented frame is chosen for further development. A 3-dimensional model is made to visualise the new concept and the Indented frame is adapted to existing components for wall hanging for the previous model of FAMILY A. Based on the 3-dimensional model, drawings are produced for the first prototypes. The prototypes assembly time are measured and a load test is carried out to measure the durability for the new concept. The result is that the new design has a decreased assembly time and the load test shows that there is no significant difference in durability. After the tests, the new concept is evaluated compared to the old design in view of form, function, quality, sustainability and low price. The conclusion is that the new concept would improve the furniture and the customers' experience when assembling.

Speech processing systems have been developed for many years but the integration into devices had started with the deployment of the modern powerful computational systems. This dissertation thesis deals with development of the keyword detection system in speech data. The proposed detection system is based on the Large Margin and Kernel methods and the key part of the system is phoneme classifier. Two hierarchical frame-based classifiers have been proposed -- linear and non-linear. An efficient training algorithm for each of the proposed classifier have been introduced. Simultaneously, classifier based on the Gaussian Mixture Models with the implementation of the hierarchical structure have been proposed. An important part of the detection system is feature extraction and therefor all algorithms were evaluated on the current most common feature techniques. A part of the thesis technical solution was implementation of the keyword detection system in MATLAB and design of the hierarchical phoneme structure for Czech language. All of the proposed algorithms were evaluated for Czech and English language over the DBRS and TIMIT speech corpus.

Partial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip resources. Operations are partitioned into Logic, Translation, and Reconfiguration layers along with a standardized set of Application Programming Interfaces (APIs). At each level, resource details are encapsulated and managed for efficiency and portability during operation. An MRRA mapping theory is developed to link the general logic function and area allocation information to the device related physical configuration level data by using mathematical data structure and physical constraints. In certain scenarios, configuration bit stream data can be read and modified directly for fast operations, relying on the use of similar logic functions and common interconnection resources for communication. A corresponding logic control flow is also developed to make the entire process autonomous. Several prototype MRRA systems are developed on a Xilinx Virtex II Pro platform. The Virtex II Pro on-chip PowerPC core and block RAM are employed to manage control operations while multiple physical interfaces establish and supplement autonomous reconfiguration capabilities. Area, speed and power optimization techniques are developed based on the developed Xilinx prototype. Evaluations and analysis of these prototype and techniques are performed on a number of benchmark and hashing algorithm case studies. The results indicate that based on a variety of test benches, up to 70% reduction in the resource utilization, up to 50% improvement in power consumption, and up to 10 times increase in run-time performance are achieved using the developed architecture and approaches compared with Xilinx baseline reconfiguration flow. Finally, a Genetic Algorithm (GA) for a FPGA fault tolerance case study is evaluated as a ultimate high-level application running on this architecture. It demonstrated that this is a hardware and software infrastructure that enables an FPGA to dynamically reconfigure itself efficiently under the control of a soft microprocessor core that is instantiated within the FPGA fabric. Such a system contributes to the observed benefits of intelligent control, fast reconfiguration, and low overhead.

The purpose of this thesis work was to develop a Hardware-in-the-Loop imaging setup that enables experimenting with an event-based and frame-based camera under simulated space conditions. The generated data sets were used to compare visual navigation algorithms in terms of an event-based and frame-based feature detection and tracking algorithm. The comparative analyses of the feature detection and tracking algorithms were used to get insights into the feasibility of event-based vision near-space space objects. Event-based cameras differ from frame-based cameras by how they produce an asynchronous and independent stream of events caused by brightness changes at each pixel instead of capturing images at a fixed rate. The setup design is based on a theoretical framework incorporating optical calculations. These calculations indicating the asteroid model needed to be scaled down by a factor of 3192 to fit inside the camera depth-of-view. This resulted in a scaled Bennu asteroid with a size of 16.44 centimeters.The cameras under testing conducted three experiments to generate data sets. The utilization of a feature detection and tracking algorithm on both camera data sets revealed that the absolute number of tracked features, computation time, and robustness in various scenarios of the frame-based camera algorithm outperforms the event-based camera algorithm. However, when considering the percentages of tracked features relative to the total detected features, the event-based algorithm tracks a significantly higher percentage of features for at least one key frame than the frame-based algorithm.  The comparative analysis of the experiments performed in space-simulated conditions during this project showed that the feasibility of an event-based camera using solely events is low compared to the frame-based camera.

過往對於情緒分析的研究顯少聚焦在讀者情緒，往往著眼於筆者情緒之研究。讀者情緒是指讀者閱讀文章後產生之情緒感受。然而相同一篇文章可能會引起讀者多種情緒反應，甚至產生與筆者迥異之情緒感受，也突顯其讀者情緒分析存在更複雜的問題。本研究之目的在於辨識讀者閱讀文章後之切確情緒，而文件分類的方法能有效地應用於讀者情緒偵測的研究，除了能辨識出正確的讀者情緒之外，並且能保留讀者情緒文件之相關內容。然而，目前的資訊檢索系統仍缺乏對隱含情緒之文件有效的辨識能力，特別是對於讀者情緒的辨識。除此之外，基於機器學習的方法難以讓人類理解，也很難查明辨識失敗的原因，進而無法了解何種文章引發讀者切確的情緒感受。有鑑於此，本研究提出一套基於語意框架(frame-based approach, FBA)之讀者情緒偵測研究的方法，FBA能模擬人類閱讀文章的方式外，並且可以有效地建構讀者情緒之基礎知識，以形成讀者情緒的知識庫。FBA具備高自動化抽取語意概念的基礎知識，除了利用語法結構的特徵，我們進一步考量周邊語境和語義關聯，將相似的知識整合成具有鑑別力之語意框架，並且透過序列比對(sequence alignment)的方式進行讀者情緒文件之匹配。經實驗結果顯示證明，本研究方法能有效地運用於讀者情緒偵測之相關研究。 / Previous studies on emotion classification mainly focus on the writer's emotional state. By contrast, this research emphasizes emotion detection from the readers' perspective. The classification of documents into reader-emotion categories can be applied in several ways, and one of the applications is to retain only the documents that cause desired emotions for enabling users to retrieve documents that contain relevant contents and at the same time instill proper emotions. However, current IR systems lack of ability to discern emotion within texts, reader-emotion has yet to achieve comparable performance. Moreover, the pervious machine learning-based approaches are generally not human understandable, thereby, it is difficult to pinpoint the reason for recognition failures and understand what emotions do articles trigger in their readers. We propose a flexible semantic frame-based approach (FBA) for reader's emotion detection that simulates such process in human perception. FBA is a highly automated process that incorporates various knowledge sources to learn semantic frames that characterize an emotion and is comprehensible for humans from raw text. Generated frames are adopted to predict readers' emotion through an alignment-based matching algorithm that allows a semantic frame to be partially matched through a statistical scoring scheme. Experiment results demonstrate that our approach can effectively detect readers' emotion by exploiting the syntactic structures and semantic associations in the context as well as outperforms currently well-known statistical text classification methods and the stat-of-the-art reader-emotion detection method.

Tato diplomová práce představuje model a prototyp kooperativního distributivního systému zálohování dat založeném na P2P komunikační síti. Návrh systému umožňuje uživatelům přispět svým lokálním volným místem na disku do systému výměnou za spolehlivé úložiště jejich dat u jiných uživatelů. Představené řešení se snaží splnit požadavky uživatelů na ukládání dat, zároveň však také řeší, jak se vypořádat s mírou nepředvídatelnosti uživatelů  ohledně poskytování volného místa. To je prováděno dvěma způsoby - využitím Reed - Solomon kódů a zároveň také tím, že poskytuje možnost nastavení parametrů dostupnosti. Jedním z těchto parametrů je časový rozvrh, který značí, kdy uživatel může nabídnout předvídatelný přínos do systému. Druhý parametr se týká spolehlivosti konkrétního uživatele v rámci jeho slíbeného časového úseku. Systém je schopen najít synchronizaci ukládaných dat na základě těchto parametrů. Práce se zaměřuje rovněž na řešení zabezpečení systému proti širšímu spektru možných útoků. Hlavním cílem je publikovat koncept a prototyp. Jelikož se jedná o relativně nové řešení, je důležitá také zpětná vazba od široké veřejnosti, která může produkt používat. Právě jejich komentáře a připomínky jsou podnětem pro další vývoj systému.