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This thesis proposes a computationally effective analytical approach to automated material handling system (AMHS) performance modeling for a simple closed loop AMHS, such as is typical in supporting a 300mm wafer fab bay. Discrete-event simulation can produce accurate assessments of the production performance, including the contribution by the AMHS. However, the corresponding simulation models are both expensive and time-consuming to construct, and require long execution times to produce statistically valid estimates. These attributes render simulation ineffective as a decision support tool in the early phase of system design, where requirements and configurations are likely to change often. We propose an alternative model that estimates the AMHS performance considering the possibility of vehicle-blocking. A probabilistic model is developed, based on a detailed description of AMHS operations, and the system is analyzed as an extended Markov chain. The model tracks the operations of all the vehicles on the closed-loop considering the possibility of vehicle-blocking. The resulting large-scale model provided reasonably accurate performance estimates; however, it presented some computational challenges. These computational challenges motivated the development of a second model that also analyzes the system as an extended Markov chain but with a much reduced state space because the model tracks the movement of a single vehicle in the system with additional assumptions on vehicle-blocking. Neither model is a conventional Markov Chain because they combine the conventional Markov Chain analysis of the AMHS operations with additional constraints on AMHS stability and vehicle-blocking that are necessary to provide a unique solution to the steady-state behavior of the AMHS. Based on the throughput capacity model, an approach is developed to approximate the expected response time of the AMHS to move requests. The expected response times are important to measure the performance of the AMHS and for estimating the required queue capacity at each pick-up station. The derivation is not straightforward and especially complicated for multi-vehicle systems. The approximation relies on the assumption that the response time is a function of the distribution of the vehicles along the tracks and the expected length of the path from every possible location to the move request location.

Blocking artifact, characterized by visually noticeable changes in pixel values along block boundaries, is a common problem in block-based image/video compression, especially at low bitrate coding. Various post-processing techniques have been proposed to reduce blocking artifacts, but they usually introduce excessive blurring or ringing effects. This paper proposes a self-learning-based image/ video deblocking framework via properly formulating deblocking as an MCA (morphological component analysis)-based image decomposition problem via sparse representation. The proposed method first decomposes an image/video frame into the low-frequency and high-frequency parts by applying BM3D (block-matching and 3D filtering) algorithm. The high-frequency part is then decomposed into a ¡§blocking component¡¨ and a ¡§non-blocking component¡¨ by performing dictionary learning and sparse coding based on MCA. As a result, the blocking component can be removed from the image/video frame successfully while preserving most original image/video details. Experimental results demonstrate the efficacy of the proposed algorithm.

In the near future, the integration of GSM and GPRS services will bring the wireless personal communication networks into a new era. With the extreme growth in the number of users for contending limited resources, an efficient channel allocation scheme for GSM/GPRS users become very important. Currently, existing channel allocation schemes do not consider the various characteristics of traffic classes. Consequently, users can not obtain their optimal channel resources in delivering different types of traffic. In this thesis, a preemptive channel allocation mechanism is introduced for GSM/GPRS cellular networks. Based on the call requests, for different types of services, we classify the traffic into GSM, real-time GPRS and non-real-time GPRS. Two channel thresholds are defined. TGSM/GPRS is used to separate the channels between GSM and GPRS users, while TGPRS_rt is used to separate the channels between real-time and non-real-time GPRS users. Since the two thresholds can be dynamically adjusted based on the number of call requests, the channel utilization is increased and less resources are wasted. Note that in our proposed scheme, high-priority users¡]i.e., GSM handoff calls¡^can preempt the channels being used by low-priority users¡]i.e., non-real-time GPRS calls¡^. Hence, the call blocking probability of high-priority calls can be significantly reduced and their quality of services can be guaranteed as well. We build a 3-D Markov Chain mathematical model to analyze our proposed channel allocation schemes. The parameters of our interests include the call blocking probability, the average number of active calls, the average call completion rate and the overall channel utilization. To verify our mathematical results, we employ OPNET simulator to simulate the proposed schemes. Through the mathematical and simulation results, we have observed that with the preemptive channel allocation, the high-priority calls¡]i.e., GSM and real-time GPRS¡^can achieve relatively low blocking probability while slightly increasing the blocking probability of non-real-time GPRS calls. Besides, the overall channel utilization is greatly improved due to the appropriate channel allocation.

This talk discusses optimized collective algorithms and the benefits of leveraging independent hardware entities in a pipelined manner. The resulting approach uses overlap of computation and communication to reach this task. Different examples are given.

Considering biocompatibility, the Dye Sensitized Solar Cell (DSC) based on titanium dioxide should play a major role in the future of solar energy. In this ongoing study, different components and ambient process conditions for the fabrication of were investigated. Titanium dioxide substrate thickness and morphology was found to have a direct impact on the cell efficiency. Scanning Electron Microscopy (SEM) was used to investigate the TiO2 nanostructure. Different chemical treatments and electrolytes were also explored towards optimizing the cell performance. A group of porphyrin based organic dyes were synthesized and evaluated. Standard solar cell characterization techniques such as current-voltage and spectral response measurements were employed to evaluate the cell performance.

Distributed data storage is a building block for many distributed systems such as mobile file systems, web service replication systems, enterprise file systems, etc. New distributed data storage systems are frequently built as new environment, requirements or workloads emerge. The goal of this dissertation is to develop the science of distributed storage systems by making it easier to build new systems. In order to achieve this goal, it proposes a new policy architecture, PADS, that is based on two key ideas: first, by providing a set of common mechanisms in an underlying layer, new systems can be implemented by defining policies that orchestrate these mechanisms; second, policy can be separated into routing and blocking policy, each addresses different parts of the system design. Routing policy specifies how data flow among nodes in order to meet performance, availability, and resource usage goals, whereas blocking policy specifies when it is safe to access data in order to meet consistency and durability goals. This dissertation presents a PADS prototype that defines a set of distributed storage mechanisms that are sufficiently flexible and general to support a large range of systems, a small policy API that is easy to use and captures the right abstractions for distributed storage, and a declarative language for specifying policy that enables quick, concise implementations of complex systems. We demonstrate that PADS is able to significantly reduce development effort by constructing a dozen significant distributed storage systems spanning a large portion of the design space over the prototype. We find that each system required only a couple of weeks of implementation effort and required a few dozen lines of policy code. / text

Numerous advancements made in the field of computational sciences have made CFD a viable solution to the modern day fluid dynamics problems. Progress in computer performance allows us to solve a complex flow field in practical CPU time. Commodity clusters are also gaining popularity as computational research platform for various CFD communities. This research focuses on evaluating and enhancing the performance of an in-house, unstructured, 3D CFD code on modern commodity clusters. The fundamental idea is to tune the codes to optimize the cache behavior of the node on commodity clusters to achieve enhanced code performance. Accordingly, this work presents discussion of various available techniques for data access optimization and detailed description of those which yielded improved code performance. These techniques were tested on various steady, unsteady, laminar, and turbulent test cases and the results are presented. The critical hardware parameters which influenced the code performance were identified. A detailed study investigating the effect of these parameters on the code performance was conducted and the results are presented. The successful single node improvements were also efficiently tested on parallel platform. The modified version of the code was also ported to different hardware architectures with successful results. Loop blocking is established as a predictor of code performance.

Mathematical models displaying travelling waves appear in a variety of domains. These waves are often faced with different kinds of perturbations. In some cases, these perturbations result in propagation failure, also known as wave-blocking. Wave-blocking has been studied in the case of several specific models, often with the help of numerical tools. In this thesis, we will display a technique that uses symmetry and a center manifold reduction to find a criterion which defines regions in parameter space where a wave will be blocked. We focus on waves with low velocity and small symmetry-breaking perturbations, which is where the blocking initiates; the organising center. The range of the tools used makes the technique easily generalizable to higher dimensions. In order to demonstrate this technique, we apply it to the bistable equation. This allows us to do calculations explicitly. As a result, we show that wave-blocking occurs inside a wedge originating from the organising center and derive an expression for this wedge to leading order. We verify our results with some numerical simulations.

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