In this dissertation, we investigate the use of lot streaming in a two-stage assembly system and a two-stage hybrid flow shop in order to improve system performance. Lot streaming accelerates the flow of a production lot through a production process by splitting it into sublots, and then, processing these sublots in an overlapping fashion over the machines, thereby reducing work-in-process and cycle-time. Traditionally, lot streaming has been applied to problems in various flow shop machine configurations. It has also been applied to machine environments of job shop, open shop, and parallel machines. Its application to assembly system is relatively new. The two-stage assembly system that we consider consists of multiple suppliers at Stage 1 with each supplier producing one type of a subassembly (or a component), and one or more assembly locations at Stage 2, where the subassemblies are then put together. Lot-attached and sublot-attached setup time and cost are encountered on the machines at both the stages, and sublot-attached time and cost are encountered for the transfer of sublots from Stage 1 to Stage 2. Mass customization is an example of such a system in which the final assembly of a product is postponed to capture specific customer demands. Dell Computer constitutes a real-life example of this system. A customer picks his/her computer processor, memory, storage, and other equipment, on Dell's web site. Dell's supply chain is configured to obtain subassemblies from suppliers (stage 1), and then, to assemble the requisite systems in different market areas (stage 2). This enables a reduction in operating cost while improving responsiveness to customers. The problem that we address is as follows: Given a maximum number of sublots of each lot, determine the number of sublots to use (assuming equal sublot sizes), and also, the sequence in which to process the lots, in order to minimize two criteria, namely, makespan, total cost. We propose two column generation-based methods that rely on different decomposition schemes. The results of our computational investigation conducted by using randomly generated data sets reveal that the proposed column generation methods obtain solutions in a few seconds of CPU time while the direct solution by CPLEX of a mixed integer programming model of the problem requires much larger CPU times. For the hybrid flow shop lot streaming problem, the machine configuration that we consider consists of one machine at Stage 1 and two machines at Stage 2 (designated as 1+2 system). A single lot is to be processed in the system, and the objective is to minimize the makespan. A removal time is associated with each sublot at Stage 1. We present a mixed integer programming model for this problem to determine optimal number of sublots and sublot sizes. First, we consider the case of a given number of sublots for which we develop closed-form expressions to obtain optimal, continuous sublot sizes. Then, we consider determination of optimal number of sublots in addition to their sizes. We develop an upper bound on optimal number of sublots, and use a simple search procedure in conjunction with the closed-form expressions for sublot sizes to obtain an optimal solution. We also consider the problem of determining integer sublot sizes, and propose a heuristic method that directly solves the mixed integer programming model after having fixed values of appropriate variables. The results of our numerical experimentation reveal the efficacy of the proposed method to obtain optimal, continuous sublot sizes, and also, that of the proposed heuristic method to obtain integer sublot sizes, which are within 0.2% of optimal solutions for the testbed of data used, each obtained within a few seconds of CPU time. The last problem that we address is an extension of the single-lot lot streaming problem for a $1+2$ hybrid flow shop considered above to the case of multiple lots, where each lot contains items of a unique product type. We consider two objectives: minimize makespan, and minimize the sum of the completion times for all the lots. The consideration of multiple lots introduces a complicating issue of sequencing the lots. We use the results derived for the single-lot problem and develop effective heuristic methods for this problem. The results of our computational investigation on the use of different heuristic methods reveal their efficacy in solving this problem. / Ph. D.

Digital signal processing systems demand higher computational performance and more operations per second than ever before, and this trend is not expected to end any time soon. Processing architectures must adapt in order to meet these demands. The two techniques most prevalent for achieving throughput constraints are parallel processing and stream processing. By combining these techniques, significant throughput improvements have been achieved. These preliminary results apply to specific applications, and general tools for automation are in their infancy. In this dissertation techniques are developed to automatically generate efficient parallel streaming hardware architectures. / Ph. D.

Increasing computing power has been helping researchers understand many complex scientific problems. Scientific computing helps to model and visualize complex processes such as molecular modelling, medical imaging, astrophysics and space exploration by processing large set of data streams collected through sensors or cameras. This produces a massive amount of data which consume a large amount of processing and storage resources. Monitoring the data streams and filtering unwanted information will enable efficient use of the available resources. This thesis proposes a data-centric system that can monitor high-speed data streams in real-time. The proposed system provides a flexible environment where users can plug-in application-specific data monitoring algorithms. The Long Wavelength Array telescope (LWA) is an astronomical apparatus that works with high speed data streams, and the proposed data-centric platform is developed to evaluate FPGAs to implement data monitoring algorithms in LWA. The throughput of the data-centric system has been modeled and it is observed that the developed data-centric system can deliver a maximum throughput of 164 MB/s. / Master of Science

With the advent of high throughput sequencing technologies over the past decade there has been a surge in the amount of genomic data that needs to be analyzed and interpreted. Despite the availability of software frameworks such as the Genome Analysis Toolkit, data interpretation and analysis still requires human intervention and refinement. Genome browsers enable developers and users of sequence analysis tools to visualize, compare, and better interpret genomic data such as gene expression and functional annotations. We developed a next generation cross platform web-based genome browser, NextBrowse, for visualizing General Feature Format and Binary Alignment Map files. NextBrowse uses advanced visualization techniques such as 3D feature selection and transparency based on mapping quality, and improved Graphical User Interface elements such as individual track searching and textual and graphical reference location. NextBrowse is the first genome browser to allow BAM files to be streamed and visualized, the first genome browser to employ security measures, and the first to use only client side rendering. NextBrowse takes advantage of the open-source community, allowing developers and users to extend the project to fit their needs. NextBrowse along with all documentation is available for use at http://www.nextbrowse.vbi.vt.edu. / Master of Science

Data volume is growing for each day as more and more is digitalized which puts the data management on test. The smart tools developed by Atlas Copco saves and transmits data to the cloud as a service to find errors in tightening's for their customers to review. A problem is the amount of data that is lost in this process. A tightening cycle usually contains thousands of data points and the storage space for it is too great for the tool's hardware. Today many of the data points are deleted and a small portion of scattered data of the cycle is saved and transmitted. To avoid overfilling the storage space the data need to be minimized. This study is focus on comparing data compression algorithms that could solve this problem.   In a literature study in the beginning, numerous data compression algorithms were found with their advantages and disadvantages. Two different types of compression algorithms are also defined as lossy compression, where data is compressed by losing data points or precision, and lossless compression, where no data is lost throughout the compression. Two lossy and two lossless algorithms are selected to be avaluated with respect to their compression ratio, speed and error tolerance. Poor Man's Compression - Midrange (PMC-MR) and SWING-filter are the lossy algorithms while Gorilla and Fixed-Point Compression (FPC) are the lossless ones.   The reached compression ratios, in percentage, could range from 39\% to 99\%. As combinations of a lossy and a lossless algorithm yields best compression ratios with lower error tolerance, PMC-MR with Gorilla is suggested to be the best suited for Atlas Copco's needs.

Varför sitter människor i flera timmar och tittar på när någon annan spelar ett dator/tv-spel? Idag har spelstreaming vuxit sig stort och flera miljoner väljer att titta på spelandet. I vår undersökning kommer vi att svara på vad som motiverar vissa människor att titta på spelstreams genom en kvalitativ intervjustudie. Från den data som vi samlar in från intervjuer tar vi ut de motivationsfaktorer som nämns och delar in dem i fem behovskategorier: cognitive, affective, personal integrative, social integrative samt tension release. Genom vår studie så blev det klart att samma person kan titta på spelstreams vid olika tillfällen, med olika motiv. De två absolutvanligaste motiven till att se på spelstreams var underhållning och att lära sig något. / Why do people sit for hours to watch someone else play a videogame? Today gamingstreaming has grown large and millions of people choose to watch others play games. In our study we will answer what motivates people to watch gamingstreams through a qualitative interview study. From the data that we collect through interviews we will extract the motivationsfactors mentioned and sort them by five need-categories: cognitive, affective, personal integrative, social integrative and tension release. Our study showed that the same person can watch gamingstreams with different motives at different times. The two most common motives for watching thestreams was entertainment and learning something new.

This thesis focuses on the phenomenon of live-streaming of computer games in the Czech Republic. This thesis is based on an approach of online ethnography and tries to describe what meaning do the producers of content (who are labeled as performers in this thesis) ascribe to streaming, what are their motivations to stream, how they present themselves on the streams and what is the content of those streams. The live-streaming of computer games in this thesis is put into context of user-generated content. The main part of this thesis is a qualitative research realized through an online observations of streams and through interviews with the performers, who stream on the streaming service Twitch. The findings show that streaming is entertaining and time passing activity for the performers, but also a form of a social contact. Some motivations of the performers include the satisfaction of their viewers and recurring contact with them. There were no financial motivations involved among the performers. Performers mostly do not stylize themselves into any specific role, however some of them do take on themselves the roles of teachers, who teach their viewers to be a better gamer, or the roles of entertainers. During the stream the performers mostly put their attention to only a single game and also to an...

The purpose of this essay is to study whether streaming services has made a difference in the act of viewing linear TV together with others. The methods used in the research are: a focus group performed with six people, an email-interview with an expert in TV and a general survey used to define the user groups. The results shows that streaming services has had an impact on viewing patterns and also contributed with new ones. The Swedish consumer is more likely to use streaming services everyday except for Fridays, which can be attributed to a tradition called Fredagsmys (friday cosiness), co-viewing primetime TV on Fridays. Co-viewing TV is also affected by streaming services according to our studies, but not nearly as much as the viewing behaviours. We’re using a theory called Diffusion of Innovation to explain the usage of streaming services and why it has not been adopted by everyone as their main platform for viewing media.

The main objective of this thesis is to provide a smooth video playout on the mobile device over wireless networks. The parameters that specify the wireless channel include: bandwidth variation, frame losses, and outage time. These parameters may affect the quality of the video negatively, and the mobile users may notice sudden stops during the playout video, i.e., the picture is momentarily frozen, followed by a jump from one scene to a different one. This thesis focuses on eliminating frozen pictures and reducing the amount of video data that need to be transmitted. In order to eliminate frozen scenes on the mobile screen, we propose three different techniques. In the first technique, the video frames are split into sub-frames; these sub-frames are streamed over different channels. In the second technique the sub-frames will be “crossed” and sent together with other sub-frames that are from different positions in the streaming video sequence. If some sub-frames are lost during the transmission a reconstruction mechanism will be applied on the mobile device to recreate the missing sub-frames. In the third technique, we propose a Time Interleaving Robust Streaming (TIRS) technique to stream the video frames in different order. The benefit of that is to avoid losing a sequence of neighbouring frames. A missing frame from the streaming video will be reconstructed based on the surrounding frames on the mobile device. In order to reduce the amount of video data that are streamed over limited bandwidth channels, we propose two different techniques. These two techniques are based on identifying and extracting a high motion region of the video frames. We call this the Region Of Interest (ROI); the other parts of the video frames are called the non-Region Of Interest (non-ROI). The ROI is transmitted with high quality, whereas the non-ROI is interpolated from a number of references frames. In the first technique the ROI is a fixed size region; we considered four different types of ROI and three different scenarios. The scenarios are based on the position of the reference frames in the streaming frame sequence. In the second technique the ROI is identified based on the motion in the video frames, therefore the size, position, and shape of the ROI will be different from one video to another according to the video characteristic. The videos are coded using ffmpeg to study the effect of the proposed techniques on the encoding size. Subjective and objective metrics are used to measure the quality level of the reconstructed videos that are obtained from the proposed techniques. Mean Opinion Score (MOS) measurements are used as a subjective metric based on human opinions, while for objective metric the Structural Similarity (SSIM) index is used to compare the similarity between the original frames and the reconstructed frames.

Atualmente existe uma grande variedade de serviços de telecomunicações focados na transmissão de voz, vídeo e dados através de redes complexas, embora, em muitos casos, o usuário final não seja atendido com um nível de qualidade aceitável. Neste trabalho, se avalia como o serviço de streaming de vídeo em uma rede com protocolo Internet (IP) pode ser afetado por uma condição adversa da rede, tal como a variação de atraso (jitter). São mostrados os resultados de avaliações objetivas e subjetivas de streaming de vídeo que indicam que a qualidade de vídeo é diretamente afetada por fatores de degradação da rede IP como a variação de atraso de pacotes. Além disso, se verifica que cenas de maior movimento também são mais afetadas pela variação de atraso. Para a realização dos testes, utiliza-se um cenário de emulação de rede isolado, no qual são parametrizadas diferentes condições de rede. Assim, no canal de transmissão são configurados diversos valores de variação de atraso, obtendo-se uma Base de Dados de vídeos com diferentes graus de degradação de qualidade. Estes vídeos são avaliados utilizando métodos subjetivos: Índice por Categorias Absolutas (ACR - Absolute Category Rating) e Índice por Categorias de Degradação (DCR - Degradation Category Rating) e métricas objetivas: Relação Sinal-Ruído de Pico (PSNR - Peak Signal to Noise Ratio), Índice de Similaridade Estrutural (SSIM - Structural Similarity Index) e Medição de Qualidade de Vídeo (VQM - Video Quality Metric). Com a finalidade de mostrar o desempenho das métricas objetivas em relação às subjetivas são empregados os coeficientes de correlação, além do erro de predição e quadrático médio. Adicionalmente, é importante destacar que a partir dos resultados obtidos são estabelecidos intervalos de valores de variação de atraso para os quais a qualidade do vídeo é considerada aceitável ou não para o usuário final. Finalmente, obtém-se uma Base de Dados de vídeos com diferentes graus de degradação da qualidade e que pode ser utilizada em futuras pesquisas. / Nowadays, there is a wide range of telecommunications services focused on the transmission of voice, video and data across complex networks, although, in many cases, the end user is not satisfied with an acceptable quality level. In this work it is assessed how the video streaming service over an IP network can be affected by adverse conditions on the network, such as packet delay variation (jitter). Results from objective and subjective video streaming assessments are shown and indicate that the video quality is directly affected by IP network degradation factors such as packet delay variation. Beyond that, it is also verified that scenes with great movement content are also more sensitive to packet delay variation. For experimental tests, a network emulation totally isolated is considered, for which different network conditions are parameterized. Then, to the transmission channel, different values of packet delay variation are configured and videos are assessed, using subjective metrics: Absolute Category Rating (ACR) and Degradation Category Rating (DCR), and objective metrics: Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) and Video Quality Metric (VQM). In order to show the performance of objective metrics in relation to subjective ones correlation coefficients are employed as well as the prediction error and the mean square error. Finally, it is important to note that, from the results obtained, it can be established a range of delay variation values in which the video quality is acceptable or not at the end user. Additionally, a Video Data Base is obtained with different degrees of quality degradation and which can be used for future researches.