In this dissertation, we study the single machine scheduling problem with an objective of minimizing the total completion time subject to release dates. The problem, denoted 1|rj £UCj ,was known to be strongly NP-hard and both theoretically and practically important. The focus of the research in this dissertation is to develop the efficient algorithms for solving the 1|rj|£UCj problem. This thesis contains two parts. In the first part, the theme concerns the approximation approach. We derive a necessary and sufficient condition for local optimality, which can be implemented as a priority rule and be used to construct three heuristic algorithms with running times of O(n log n). By ¡¨local optimality¡¨, we mean the optimality of all candidates whenever a job is selected in a schedule, without considering the other jobs preceding or following. This is the most broadly considered concepts of locally optimal rule. We also identify a dominant subset which is strictly contained in each of all known dominant subsets, where a dominant subset is a set of solutions containing all optimal schedules. In the second part, we develop our optimality algorithms for the 1|rj |£UCj problem. First, we present a lemma for estimating the sum of delay times of the rest jobs, if the starting time is delayed a period of time in a schedule. Then, using the lemma, partially, we proceed to develop a new partition property and three dominance theorems, that will be used and have improved the branch-and-bound algorithms for our optimization approach. By exploiting the insights gained from our heuristics as a branching scheme and by exploiting our heuristics as an upper bounding procedure, we propose three branch-and-bound algorithms. Our algorithms can optimally solve the problem up to 120 jobs, which is known to be the best till now.

This dissertation evaluates the following thesis statement: Program analysis techniques can enable and support the debugging of failures in widely-used applications by (1) capturing, replaying, and, as much as possible, anonymizing failing executions and (2) highlighting subsets of failure-inducing inputs that are likely to be helpful for debugging such failures. To investigate this thesis, I developed techniques for recording, minimizing, and replaying executions captured from users' machines, anonymizing execution recordings, and automatically identifying failure-relevant inputs. I then performed experiments to evaluate the techniques in realistic scenarios using real applications and real failures. The results of these experiments demonstrate that the techniques can reduce the cost and difficulty of debugging.

The implementation of sustainable solvents and processes is critical to new developments in reducing environmental impact, improving net efficiency, and securing economic profitability in the chemical and pharmaceutical industries. In order to address the challenge of sustainability, researchers have used switchable solvents for both reaction and separation by utilizing a built-in switch to undergo a step change in chemical and physical properties. This allows us to facilitate reactions in the solvent then activate the switch to enable separation and facile product recovery. Subsequently, we can recover the solvent for reuse and avoid energy- or waste-intensive separation processes; thus we are developing and using these switchable solvents as sustainable and environmentally benign alternatives to traditional processes. In this research, we enable the sustainable scale-up of a switchable solvent - piperylene sulfone - a "volatile" and recyclable DMSO replacement. In the development of this process, we improved the reaction performances and developed a green purification method. Furthermore, we enable and demonstrate the implementation of a Meerwein-Ponndorf-Verley (MPV) reduction, a pharmaceutically relevant reaction, into a continuous flow platform. The innovation of continuous flow processes can replace traditional batch reaction technology, and is indeed a key research area that has been acknowledged by the pharmaceutical industry. Additionally, we utilize the switchable sulfone solvents, piperylene and butadiene sulfone, for reaction and separation of HMF produced from monosaccharides as an alternative to a process which has been limited by an inefficient separation step.

Title from PDF of title page. / Document formatted into pages; contains 124 pages. / Thesis (Ph.D.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: As technology scales down and CMOS circuits are powered by lower supply voltages, standby leakage current becomes significant. A behavioral level framework for the synthesis of data-paths with low leakage power is presented. There has been minimal work done on the behavioral synthesis of low leakage datapaths. We present a fast architectural simulator for leakage (FASL) to estimate the leakage power dissipated by a system described hierarchically in VHDL. FASL uses a leakage power model embedded into VHDL leafcells. These leafcells are characterized for leakage accurately using HSPICE. We present results which show that FASL measures leakage power significantly faster than HSPICE, with less than a 5% loss in accuracy, compared to HSPICE. We present a comprehensive framework for synthesizing low leakage power data-paths using a parameterized Multi-threshold CMOS (MTCMOS) component library. / ABSTRACT: The component library has been characterized for leakage power and delay as a function of sleep transistor width. We propose four techniques for minimization of leakage power during behavioral synthesis: (1) leakage power management using MTCMOS modules; (2) an allocation and binding algorithm for low leakage based on clique partitioning; (3) selective binding to MTCMOS technology, allowing the designer to have control over the area overhead; and (4) a performance recovery technique based on multi-cycling and introduction of slack, to alleviate the loss in performance attributed to the introduction of MTCMOS modules in the data-path. Finally, we propose two iterative search based techniques, based on Tabu search, to synthesize low leakage data-paths. The first technique searches for low leakage scheduling options. The second technique simultaneously searches for a low leakage schedule and binding. It is shown that the latter technique of unified search is more robust. / ABSTRACT: The quality of results generated bytabu-based technique are superior to those generated by simulated annealing (SA) search technique. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

The thermoelectric effect was discovered well over a century ago, yet performance has not shown improvement until recent years. Prior work has shown that the thermoelectric effect can be enhanced by the use of microscale pieces of thermoelectric material. Conventional assembly techniques are inadequate to deal with parts of this size, making it necessary to find a suitable alternative before these devices can be made economically. Capillary self-assembly is a promising alternative to conventional techniques. This method employs the use of preparing substrates with areas of favorable surface tension to place and align parts. Still, many obstacles have to be overcome to adapt this process for use of constructing thermoelectric coolers. The goal of this work is to overcome these obstacles and assess the viability of self-assembly for fabricating these devices. In effort to make the method more effective a process for creating more uniform deposits of solder is also assessed. This work shows that microscale thermoelectric elements can be assembled into functional thermoelectric devices using self-assembly techniques through the assembly of coolers in experimental work.

The continuous scaling down of the metal-oxide-semiconductor field-effect transistor (MOSFET) has improved the performance of electronic appliances. Unfortunately, it has come to a stage where further scaling of the MOSFET is no longer possible due to the physical and the fabrication limitations. This has motivated researchers towards designing and fabricating novel devices that can replace MOSFET technology. Carbon Nanotube Field-Effect Transistors, Single Electron Tunneling Junctions, Nano-Magnetic Devices, and Spin Field-Effect Transistors are some prospective candidates that could replace MOSFET devices. In this dissertation, we have studied the computational performance of Nano−Magnetic Devices due to their attractive features such as room temperature operation, high density, robustness towards thermal noise, radiation hardened nature and low static power dissipation. In this work, we have established that data can be propagated in a causal fashion from a driver cell to the driven cells. We have fabricated a ferromagnetic wire architecture and used a magnetic force microscopy (MFM) tip to provide localized magnetic inputs. This experiment validated two important phenomena; (1) a clocking field is essential to propagate data and (2) upon removal of the clocking field data can be propagated according to the input data. Next, we have fabricated and captured MFM images of a nano-magnetic logic architecture that has computed the majority of seven binary variables. The architecture was designed by interconnecting three three-input majority logic gates with ferromagnetic and antiferromagnetic wire architectures. This seven input majority logic architecture can potentially implement eight different logic functions that could be configured in real-time. All eight functions could be configured by three control parameters in real-time (by writing logic one or zero to them). Even though we observed error-free operations in nano-magnetic logic architectures, it became clear that we needed better control (write/read/clock) over individual single layer nano-magnetic devices for successful long-term operation. To address the write/clock/read problems, we designed and fabricated amultilayer nano-magnetic device. We fabricated and performed a set of experiments with patterned multilayer stacks of Co/Cu/Ni80Fe20 with a bottom layer having a perpendicular magnetization to realize neighbor interactions between adjacent top layers of devices. Based on the MFM images, we conclude that dipolar coupling between the top layers of the neighboring devices can be exploited to construct three-input majority logic gates, antiferromagnetic and ferromagnetic wire architectures. Finally, we have experimentally demonstrated a magnetic system that could be used to solve quadratic optimization problems that arise in computer vision applications. We have harnessed the energy minimization nature of a magnetic system to directly solve a quadratic optimization process. We have fabricated a magnetic system corresponding to a real world image and have identified salient features with true positive rate more than 85%. These experimental results feature the potentiality of this unconventional computing method to develop a magnetic processor which solves such complex problems in few clock cycles.

Unsupervised models can provide supplementary soft constraints to help classify new, "target" data since similar instances in the target set are more likely to share the same class label. Such models can also help detect possible differences between training and target distributions, which is useful in applications where concept drift may take place, as in transfer learning settings. This contribution describes two general frameworks that take as input class membership estimates from existing classifiers learnt on previously encountered "source" data, as well as a set of cluster labels from a cluster ensemble operating solely on the target data to be classified, and yield a consensus labeling of the target data. One of the proposed frameworks admits a wide range of loss functions and classification/clustering methods and exploits properties of Bregman divergences in conjunction with Legendre duality to yield a principled and scalable approach. The other approach is built on probabilistic mixture models and provides additional flexibility of distributed computation that is useful when the target data cannot be gathered in a single place for privacy or security concerns. A variety of experiments show that the proposed frameworks can yield results substantially superior to those provided by popular transductive learning techniques or by naively applying classifiers learnt on the original task to the target data. / text

This study investigates “how is the Pay As You Throw (PAYT) principle viewed by housing estates in HK and how are they preparing for its possible implementation”. A multiple case study approach is adopted. The research findings are based on five case studies with in-depth interviews with the respective property managers and site visits to the housing estates. Based on the data analysis of the research, four findings are highlighted. First, Environmental management system is the trend for property management companies to adopt in order to upgrade their quality of service in Hong Kong. Second, Hong Kong housing estates are willing to join the programmes related to waste recovery and reduction which are organized by EPD and charitable organizations. Third, the quantity-based charging system is regarded as the fairest system; however, the property managers have the greatest reservation on its implementation. Finally, there is a dilemma of role conflict between the enforcement of law and the provision of customer service. Four recommendations are suggested to be put in place alongside the future waste charging policy. Mandatory participation with comprehensive recycling scheme should be adopted. Measures against illegal dumpling and environmental education for the public should be simultaneously worked out to complement the waste charging policies as well. / published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

published_or_final_version / Architecture / Master / Master of Landscape Architecture

Scientific evidence of human impact on the natural environment, such as global warming, continues to mount. Green manufacturing systems that focus on minimizing environmental impact of manufacturing processes and products are ever more important to our sustainable future. Green manufacturing systems are slow to gain acceptance as manufacturers are focused on implementing Lean manufacturing systems, generally considered the most competitive manufacturing systems in the world. In recent years, researchers and the US Environmental Protection Agency (EPA) have sought to "build a bridge" between Lean and Green manufacturing systems, in hopes that the rapid expanse of Lean can serve as a catalyst to the implementation of Green manufacturing systems.This study contributes to this growing body of knowledge by determining if leading Lean manufacturers are transcending beyond the traditional limits of Lean and implementing Green manufacturing systems as part of their overallwaste reduction strategy. In this work Lean manufacturing plants that have been evaluated by a panel of experts from the Shingo Prize for Excellence in Manufacturing are surveyed on the diffusion of Green manufacturing system practices throughout their operation. A full system correlation analysis is performed utilizing forty-eight measures of Lean and Green manufacturing systems under the categories of management system, waste reducing techniques, and results. Data analysis indicates that known Lean manufacturers are significantly Greener than the general population of manufacturers in twenty-five of twenty-six measures of Green manufacturing. Lean manufacturers who implement Green manufacturing systems have the strongest results in both Lean and Green result areas, particularly cost reduction, indicating synergy between Lean and Green manufacturing systems. Manufacturing plants that choose to vertically integrate versus horizontally integrate their Lean systems transcend to Green manufacturing. Mexican plants in the study practice significantly higher levels of material resource efficiency and are more inclined to develop industrial partnerships to resolve environmental issues. The study also identifies a critical need for integrating Lean and Green management systems to drive synergistic waste reducing techniques throughout the operation. An integrated Lean and Green manufacturing system model, dubbed "Zero Waste Manufacturing", is proposed as a solution for economically and environmentally sustainable manufacturing.