Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item Design of a Quasi-Adiabatic Current-Mode Neurostimulator Integrated Circuit for Deep Brain Stimulation(2018) Mandal, Arindam; Newcomb, Robert W; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Electrical stimulation of neural tissues is a valuable tool in the retinal prosthesis, cardiac pacemakers, and Deep Brain Stimulation (DBS). DBS is being to treat a growing number of neurological disorders, such as movement disorder, epilepsy, and Parkinson’s disease. The role of the electronic stimulator is paramount in such application, and significant design challenges are to be met to enhance safety and reliability. A current-source based stimulator can accurately deliver a charge-balanced stimulus maintaining patient safety. In this thesis, a general-purpose current-mode neurostimulator (CMS) based upon a new quasi-adiabatic driving technique is proposed which can theoretically achieve more than 80% efficiency with the help of a dynamic high voltage supply (DHVS) as opposed to most conventional general-purpose CMS having less than 25% efficiency. The high-voltage supply is required to withstand the voltage seen across the electrodes (>10V) due to the time-varying impedance presented by the electrode-tissue interface. The overall efficiency of the designed CMS is limited by the efficiency of the DHVS. A HVDD of 15V is created by the DHVS from an input voltage (VDD) of 3V. The DHVS circuit is made by cascading five charge pump circuits using the AMI 0.5µm CMOS process. It can maintain more than 60% efficiency for a wide range of load current from 25µA to 1.4mA, with peak efficiency at 67% and this is comparable with existing specific-purpose state-of-the-art high-voltage supplies used in a current stimulator. The stimulator designed in this thesis employs a new efficient charge recycling mechanism to enhance the overall efficiency, compared to the existing state-of-the-art CMSs. Thus, the overall CMS efficiency is improved by 20% to 25%. A current source, programmable by 8-bit digital input, is also designed which has an output impedance greater than 2MΩ with a dropout voltage of only 120mV. Measurements show voltage compliance exceeding +/-15V when driving a biphasic current stimulus of 10µA to 2.5mA through a simplified R-C model of the electrode-tissue interface. The voltage compliance is defined as the maximum voltage a stimulator can apply across the electrodes to achieve neural stimulation.Item Essays in Personal Transportation Demand and Consumer Finance(2016) Evans, Jaclyn; Williams, Roberton C; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is composed of three essays covering two areas of interest. The first topic is personal transportation demand with a focus on price and fuel efficiency elasticities of mileage demand, challenging assumptions common in the rebound effect literature. The second topic is consumer finance with a focus on small loans. The first chapter creates separate variables for fuel prices during periods of increasing and decreasing prices as well as an observed fuel economy measure to empirically test the equivalence of these elasticities. Using a panel from Germany from 1997 to 2009 I find a fuel economy elasticity of mileage of 53.3%, which is significantly different from the gas price elasticity of mileage during periods of decreasing gas prices, 4.8%. I reject the null hypothesis or price symmetry, with the elasticity of mileage during period of increasing gas prices ranging from 26.2% and 28.9%. The second chapter explores the potential for the rebound effect to vary with income. Panel data from U.S. households from 1997 to 2003 is used to estimate the rebound effect in a median regression. The estimated rebound effect independent of income ranges from 17.8% to 23.6%. An interaction of income and fuel economy is negative and significant, indicating that the rebound effect may be much higher for low income individuals and decreases with income; the rebound effect for low income households ranged from 80.3% to 105.0%, indicating that such households may increase gasoline consumption given an improvement in fuel economy. The final chapter documents the costs of credit instruments found in major mail order catalogs throughout the 20th century. This study constructs a new dataset and finds that the cost of credit increased and became stickier as mail order retailers switched from an installment-style closed-end loan to a revolving-style credit card. This study argues that revolving credit's ability to decrease salience of credit costs in the price of goods is the best explanation for rate stickiness in the mail order industry as well as for the preference of revolving credit among retailers.Item ESSAYS ON ENERGY EFFICIENCY AND FOREST CONSERVATION(2015) Maher, Joseph Andrew; Just, Richard; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is composed of three essays in environmental economics related to residential energy efficiency and forest conservation. My first paper assesses the effectiveness of energy-efficient technologies in the setting of a utility rebate program. To date, the energy savings from energy-efficiency building retrofits are assessed using ex-ante engineering models. My analysis provides the first evaluation of engineering models that uses residential billing data, combined with data on observable characteristics of each residence, to assess the accuracy of engineering predictions across nine retrofit technologies used in Gainesville, Florida. My second essay presents the first causal evidence that trees have a major impact on consumer demand—with large shade trees reducing household electricity use by more than 20 percent. This work contributes to the existing literature on the energy saving potential of urban forests by implementing a quasi-experimental design to identify a causal link between tree shade and energy use. Results suggest that the energy savings from tree shade are an order of magnitude greater than other energy-efficiency policy measures, providing new evidence that tree ordinances may serve as effective demand-side management policies. My third essay assesses the effectiveness of forest conservation policies in reducing carbon emissions from deforestation. To date, the effectiveness of protected areas has been assessed using cross-sectional methods. In this essay, new quasi-experimental models using panel data on annual deforestation are used to reveal new insights into the importance of government oversight of protected areas with findings that counter economists’ prior notions of the avoided deforestation of new parks. I extend the analysis to estimate avoided carbon emissions, a key policy metric that varies considerably from deforestation trends.Item Energy Efficiency and Privacy Protection in Cellular Networks(2014) Ta, Tuan Minh; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Smartphones have become an essential part of our society. The benefits of having an always present, highly capable device cannot be overstated. As more aspects of our life depend on our smartphones, it is more important than ever to ensure the availability of those devices. However, their big advantages also come with big risks. The fact that we have our smartphones with us all the time means that it is easier than ever to collect our information, sometimes without our consent. In this dissertation, we study the two pressing concerns in cellular communications: energy efficiency and privacy protection. We focus on LTE networks, the current most advanced global standard for cellular communications. In the first part of the dissertation, we study the energy efficiency problem from both device and network perspectives. From the device point of view, we introduce a new angle to address the battery life concern. We recognize that the value of battery for the users is not always the same, and that it depends on the user usage. We also identify, and show in real network, diversity of usage, the phenomenon that at any instant, there is a diverse distribution of smartphone usage among cellular users. We propose ``Battery Deposit Service'' (BDS), a cooperative system which makes use of device-to-device (D2D) communications underlaying cellular networks to provide energy sharing in the form of load sharing. We design BDS to take advantage of diversity of usage to maximize the utility of smartphone battery. We show that our system increases battery life of cellular users, at almost no cost to the rest of the network. BDS is designed to be compatible to LTE architecture. From the network point of view, we design an energy efficient D2D relay system underlaying LTE networks. We minimize transmission power of smartphones by considering relay selection, resource allocation and power control. The overall problem is prohibited due to its exponential search space. We develop a divide-and-conquer strategy which splits the overall problem into small sub-problems. We relate these sub-problems to well-studied graph theoretic problems, and take advantage of existing fast algorithms. We show that our algorithms meet the runtime requirement of real-time LTE operations. In the second part of the dissertation, we address a privacy concern in LTE networks. In particular, we show that user location can be leaked in current LTE paging architecture. We propose a mechanism based on signal processing to remedy this vulnerability. Our method makes use of physical layer identification, which are low-power tags embedded on the wireless waveform, to signal paging messages to user devices. We show that our method is stealthy and robust, and that it mitigates the aforementioned privacy issue.Item GUARANTEE DESIGN ON ENERGY PERFORMANCE CONTRACTS UNDER UNCERTAINTY(2011) Deng, Qianli; Cui, Qingbin; Jiang, Xianglin; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Due to the growing concerns with climate change and energy supply, Energy Performance Contracting (EPC), which uses the guaranteed future utility savings to repay the initial renovation investments, becomes increasingly popular. However, most Energy Service Companies (ESCOs) set the savings guarantee roughly based on their previous experience, which leads to inaccurate estimates in practice. This paper has built the stochastic models for the savings risks both from the energy price volatility and the facility performance instability, which follow the Geometric Brownian Motions (GBM) and Ito's lemma. Then, a flexible guarantee designing method for ESCOs is developed to minimize the financial risks and a case study has been conducted to show the application. Finally, suggestions have been made for how ESCOs set the guarantee and the extra profit sharing proportion in contracts based on the existing information. This method will help them appropriately allocate risks with successful contract negotiation.Item Modeling Household Energy Consumption and Adoption of Energy-efficient Technology Using Recent Micro-data(2011) Li, Jia; Just, Richard E; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study develops a unified technology choice and energy consumption model (a "discrete/continuous model") that can be applied to study household energy use behavior. The model, stemming from consumer theory, ensures modeling of consumer short-run energy demand and long-run capital investment decisions in a mutually consistent manner. The model adopts a second-order translog flexible functional form that allows considerable flexibility in the structure of consumer preferences and in the exploration of interplays among energy uses and between energy demand and appliance choices. This study extends the discrete/continuous model developed by Dubin and McFadden (1984) and is the first known application of the second-order translog flexible functional form in joint discrete/continuous modeling of consumer energy demand and appliance choice. Using a unique household-level dataset of 2,408 households served by the Pacific Gas and Electric Company in California, the model is applied to examine the roles of income, prices, household characteristics, and energy and environmental policy in household short-run energy use and long-run technology choices. The empirical analysis estimates a system of short-run household demand equations for electricity and natural gas and long-run technology choices with respect to clothes washing, water heating, space heating, and clothes drying. The results demonstrate the modeling framework is appropriate and robust in studying household energy use behavior. Findings from the empirical analysis have important implications for policy design. This study confirms two important market failures with respect to household energy technology choice behavior: the principal/agent problem and information imperfection. In the case of clothes washer choices, the voluntary, information-based Energy Star program emerges as the most significant factor influencing the adoption of energy-efficient front-loading clothes washers, followed by energy efficiency standards. Surprisingly, financial incentives, such as the popular rebate programs used to lower the initial capital cost of energy-efficient appliances, are found to be far less effective in influencing adoption of energy-efficient appliances. Furthermore, the study finds at the household level that the incentive for new technology adoption is greater under direct regulation than under market-based instruments, such as a carbon cap-and-trade program or emission taxes.Item DELAY MINIMIZATION IN ENERGY CONSTRAINED WIRELESS COMMUNICATIONS(2010) Yang, Jing; Ulukus, Sennur; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In wireless communications and networks, especially for many real-time applications, the average delay packets experience is an important quality of service criterion. Therefore, it is imperative to design advanced transmission schemes to jointly address the goals of reliability, high rates and low delay. Achieving these objectives often requires careful allocation of given resources, such as energy, power, rate, among users. It also requires a close collaboration between physical layer, medium access control layer, and upper layers, and yields cross-layer solutions. We first investigate the problem of minimizing the overall transmission delay of packets in a multiple access wireless communication system, where the transmitters have average power constraints. We formulate the problem as a constrained optimization problem, and then transform it into a linear programming problem. We show that the optimal policy has a threshold structure: when the sum of the queue lengths is larger than a threshold, both users should transmit a packet during the current slot; when the sum of the queue lengths is smaller than a threshold, only one of the users, the one with the longer queue, should transmit a packet during the current slot. Then, we study the delay-optimal rate allocation in a multiple access wireless communication system. Our goal is to allocate rates to users, from the multiple access capacity region, based on their current queue lengths, in order to minimize the average delay of the system. We formulate the problem as a Markov decision problem (MDP) with an average cost criterion. We first show that the value function is increasing, symmetric and convex in the queue length vector. Taking advantage of these properties, we show that the optimal rate allocation policy is one which tries to equalize the queue lengths as much as possible in each slot, while working on the dominant face of the capacity region. Next, we extend the delay-optimal rate allocation problem to a communication channel with two transmitters and one receiver, where the underlying rate region is approximated as a general pentagon. We show that the delay-optimal policy has a switch curve structure. For the discounted-cost problem, we prove that the switch curve has a limit along one of the dimensions. The existence of a limit in the switch curve along one of the dimensions implies that, once the queue state is beyond the limit, the system always operates at one of the corner points, implying that the queues can be operated partially distributedly. Next, we shift our focus from the average delay minimization problem to transmission completion time minimization problem in energy harvesting communication systems. We first consider the optimal packet scheduling problem in a single-user energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we develop an optimal off-line scheduling policy which minimizes the transmission completion time, under causality constraints on both data and energy arrivals. Then, we investigate the transmission completion time minimization problem in a two-user additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature. We first analyze the structural properties of the optimal transmission policy. We prove that the optimal total transmit power has the same structure as the optimal single-user transmit power. We also prove that there exists a cut-off power level for the stronger user. If the optimal total transmit power is lower than this level, all transmit power is allocated to the stronger user, and when the optimal total transmit power is larger than this level, all transmit power above this level is allocated to the weaker user. Based on these structural properties of the optimal policy, we propose an algorithm that yields the globally optimal off-line scheduling policy. Next, we investigate the transmission completion time minimization problem in a two-user AWGN multiple access channel. We first develop a generalized iterative backward waterfilling algorithm to characterize the maximum departure region of the transmitters for any given deadline. Then, based on the sequence of maximum departure regions at energy arrival epochs, we decompose the transmission completion time minimization problem into a convex optimization problem and solve it efficiently. Finally, we investigate the average delay minimization problem in a single-user communication channel with an energy harvesting transmitter. We consider three different cases. In the first case, both the data packets and the energy to be used to transmit them are assumed to be available at the transmitter at the beginning. In the second case, while the energy is available at the transmitter at the beginning, packets arrive during the transmissions. In the third case, the packets are available at the transmitter at the beginning and the energy arrives during the transmissions, as a result of energy harvesting. In each scenario, we find the structural properties of the optimal solution, and develop iterative algorithms to obtain the solution.Item SELF ORGANIZING WIRELESS SENSOR NETWORKS(2007-10-26) Kordari, Kamiar; Blankenship, Gilmer L; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is concerned with the properties of self-organizing network systems, where a large number of distributed sensor nodes with limited sensing, processing and communication capability organize themselves into a cooperative network without any centralized control or management. Due to the distributed nature of the management and lack of global information for in-node decision making, sensor management in such networks is a complicated task. The dynamics of such networks are characterized by constraints and uncertainty, and the presence of disturbances that significantly affect aggregate system behavior. In this dissertation we examine several important topics in the management of self-organizing wireless sensor networks. The first topic is a statistical analysis to determine the minimum requirements for the deployment phase of a random sensor network to achieve a desired degree of coverage and connectivity. The second topic focuses on the development of a viable online sensor management methodology in the absence of global information. We consider consensus based sensor data fusion as a motivating problem to demonstrate the capability of the sensor management algorithms. The approach that has been widely investigated in the literature for this problem is the fusion of information from all the sensors. It does not involve active control of the sensors as part of the algorithm. Our approach is to control the operations of the nodes involved in the consensus process by associating costs with each node to emphasize those with highest payoff. This approach provides a practical, low complexity algorithm that allows the nodes to optimize their operations despite the lack of global information. In the third topic we have studied sensor networks that include "leaders," "followers," and "disrupters." The diffusion of information in a network where there are conflicting strategies is investigated through simulations. These results can be used to develop algorithms to manage the roles in the network in order to optimize the diffusion of information as well as protect the network against disruption.Item The effect of life-cycle cost disclosure on consumer behavior(2007-04-25) Deutsch, Matthias; Ruth, Matthias; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)For more than 20 years, analysts have reported on the so-called "energy paradox" or the "energy efficiency gap", referring to the fact that economic agents could in principle lower their total cost at current prices by using more energy-efficient technology but, nevertheless, often decide not to do so. Theory suggests that providing information in a simplified way could potentially reduce this "efficiency gap". Such simplification may be achieved by providing the estimated monetary operating cost and life-cycle cost (LCC) of a given appliance--which has been a recurring theme within the energy policy and efficiency labeling community. Yet, little is known so far about the causal effects of LCC disclosure on consumer action because of the gap between the acquisition of efficiency information and consumer purchasing behavior in the real marketplace. This dissertation bridges the gap by experimentally integrating LCC disclosure into two major German commercial websites--a price comparison engine for cooling appliances, and an online shop for washing machines. Internet users arriving on these websites were randomly assigned to two experimental groups, and the groups were exposed to different visual stimuli. The control group received regular product price information, whereas the treatment group was, in addition, offered information about operating cost and total LCC. Click-stream data of consumers' shopping behavior was evaluated with multiple regression analysis by controlling for several product characteristics. This dissertation finds that LCC disclosure reduces the mean energy use of chosen cooling appliances by 2.5% (p<0.01), and the energy use of chosen washing machines by 0.8% (p<0.001). For the latter, it also reduces the mean water use by 0.7% (p<0.05). These effects suggest a potential role for public policy in promoting LCC disclosure. While I do not attempt to estimate the costs of such a policy, a simple quantification shows that the benefits amount to 100 to 200 thousand Euros per year for Germany, given current predictions regarding the price of tradable permits for CO2, and not counting other potential benefits. Future research should strive for increasing external validity, using better instruments, and evaluating the effectiveness of different information formats for LCC disclosure.