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An embedded HVDC system is a dc link with at least two ends being physically connected within a single synchronous ac network. The thesis reviews previous works on embedded HVDC, proposes a dynamic embedded HVDC model by PSCAD program, and compares the transient stability performance among AC, DC and embedded

An embedded HVDC system is a dc link with at least two ends being physically connected within a single synchronous ac network. The thesis reviews previous works on embedded HVDC, proposes a dynamic embedded HVDC model by PSCAD program, and compares the transient stability performance among AC, DC and embedded HVDC. The test results indicate that by installing the embedded HVDC, AC network transient stability performance has been largely improved. Therefore the thesis designs a novel frequency control topology for embedded HVDC. According to the dynamic performance test results, when the embedded HVDC system equipped with a frequency control, the system transient stability will be improved further.
ContributorsYu, Jicheng (Author) / Karady, George G. (Thesis advisor) / Hui, Yu (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2013
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Juvenile offenders suffer from substance use disorders at higher rates than adolescents in the general public. Substance use disorders also predict an increased risk for re-offending. Therefore, it is important that these juveniles, in particular, receive the appropriate substance use disorder treatment. The present study used logistic regression to test

Juvenile offenders suffer from substance use disorders at higher rates than adolescents in the general public. Substance use disorders also predict an increased risk for re-offending. Therefore, it is important that these juveniles, in particular, receive the appropriate substance use disorder treatment. The present study used logistic regression to test whether race/ethnicity would moderate the match between substance use disorder diagnosis and the receipt of a substance use disorder related service in a sample of male, serious juvenile offenders. Results showed that among those with a substance use disorder diagnosis, there were no race/ethnicity differences in the receipt of the appropriate service. However, among those without a substance use disorder diagnosis, non-Hispanic Caucasians were more likely to receive substance use service than were Hispanics or African-Americans. Post-hoc analyses revealed that when using a broader definition of substance use problems, significant differences by race/ethnicity in the prediction of service receipt were only observed at low levels of substance use problems. These findings shed light on how race/ethnicity may play a role in the recommendation of substance use disorder services in the juvenile justice system.
ContributorsMansion, Andre (Author) / Chassin, Laurie (Thesis advisor) / Dishion, Thomas (Committee member) / Knight, George (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters

The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters from human auditory models, such as auditory patterns and loudness, involves computationally intensive operations which can strain device resources. Hence, strategies for implementing computationally efficient human auditory models for loudness estimation have been studied in this thesis. Existing algorithms for reducing computations in auditory pattern and loudness estimation have been examined and improved algorithms have been proposed to overcome limitations of these methods. In addition, real-time applications such as perceptual loudness estimation and loudness equalization using auditory models have also been implemented. A software implementation of loudness estimation on iOS devices is also reported in this thesis. In addition to the loudness estimation algorithms and software, in this thesis project we also created new illustrations of speech and audio processing concepts for research and education. As a result, a new suite of speech/audio DSP functions was developed and integrated as part of the award-winning educational iOS App 'iJDSP." These functions are described in detail in this thesis. Several enhancements in the architecture of the application have also been introduced for providing the supporting framework for speech/audio processing. Frame-by-frame processing and visualization functionalities have been developed to facilitate speech/audio processing. In addition, facilities for easy sound recording, processing and audio rendering have also been developed to provide students, practitioners and researchers with an enriched DSP simulation tool. Simulations and assessments have been also developed for use in classes and training of practitioners and students.
ContributorsKalyanasundaram, Girish (Author) / Spanias, Andreas S (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis addresses the issue of making an economic case for energy storage in power systems. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load; store energy when it is inexpensive and discharge energy when it is expensive; potentially defer transmission

This thesis addresses the issue of making an economic case for energy storage in power systems. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load; store energy when it is inexpensive and discharge energy when it is expensive; potentially defer transmission and generation expansion; and provide for generation reserve margins. As renewable energy resource penetration increases, the uncertainty and variability of wind and solar may be alleviated by bulk energy storage technologies. The quadratic programming function in MATLAB is used to simulate an economic dispatch that includes energy storage. A program is created that utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona transmission system, part of the Western Electricity Coordinating Council (WECC). The MATLAB program is used first to test the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization out-puts such as the system wide operating costs. Very high levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand.
ContributorsRuggiero, John (Author) / Heydt, Gerald T (Thesis advisor) / Datta, Rajib (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The purpose of this research study provided observational techniques and Applied Behavior Analysis (ABA) prompts and fading procedures to analyze music therapist-child interaction for child with autism spectrum disorder. Impaired social interaction is the primary symptom of a child with autism spectrum disorder. However, social interaction exists everywhere and throughout

The purpose of this research study provided observational techniques and Applied Behavior Analysis (ABA) prompts and fading procedures to analyze music therapist-child interaction for child with autism spectrum disorder. Impaired social interaction is the primary symptom of a child with autism spectrum disorder. However, social interaction exists everywhere and throughout human life. Therefore, to improve interaction is the primary and significant goal in music therapy treatment for a child with autism spectrum disorder. The music therapist designs a series of music therapy activity interventions in order to create a therapeutic environment, based on a child's interests and favorite activities. Additionally, the music therapist utilizes the music to build the quality of relationship and interaction with child and support child practicing interaction with the therapist. Then music therapist utilizes the process of interaction to improve child's social interaction. Once the child achieves at desired behavior, he/she has ability to apply the music therapy techniques independently in the real world situations, such as family and schools that the child has learned throughout the process of interaction with therapist. The participants were three children with autism spectrum disorder and two certified music therapists (MT-BC). The researcher calculated the number of prompts and cues which the therapists provided, and the number of appropriate responses by each child in each activity intervention. Then the researcher utilized Applied Behavior Analysis (ABA), prompt and fading procedure in order to analyze the progress of therapist-child interactions during the sessions. The result showed that the children had improvement in the interactions with their therapist.
ContributorsLiao, Yin-chun (Author) / Crowe, Barbara J. (Thesis advisor) / Rio, Robin (Committee member) / Dishion, Thomas J. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can

Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can be achieved through the use of dynamic loading. A benefit of dynamic loading is that it allows better utilization of the transformer capacity, thus increasing the flexibility and reliability of the power system. This document presents the progress on a software application which can estimate the maximum time-varying loading capability of transformers. This information can be used to load devices closer to their limits without exceeding the manufacturer specified operating limits. The maximally efficient dynamic loading of transformers requires a model that can accurately predict both top-oil temperatures (TOTs) and hottest-spot temperatures (HSTs). In the previous work, two kinds of thermal TOT and HST models have been studied and used in the application: the IEEE TOT/HST models and the ASU TOT/HST models. And, several metrics have been applied to evaluate the model acceptability and determine the most appropriate models for using in the dynamic loading calculations. In this work, an investigation to improve the existing transformer thermal models performance is presented. Some factors that may affect the model performance such as improper fan status and the error caused by the poor performance of IEEE models are discussed. Additional methods to determine the reliability of transformer thermal models using metrics such as time constant and the model parameters are also provided. A new production grade application for real-time dynamic loading operating purpose is introduced. This application is developed by using an existing planning application, TTeMP, as a start point, which is designed for the dispatchers and load specialists. To overcome the limitations of TTeMP, the new application can perform dynamic loading under emergency conditions, such as loss-of transformer loading. It also has the capability to determine the emergency rating of the transformers for a real-time estimation.
ContributorsZhang, Ming (Author) / Tylavsky, Daniel J (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
ABSTRACT Developing new non-traditional device models is gaining popularity as the silicon-based electrical device approaches its limitation when it scales down. Membrane systems, also called P systems, are a new class of biological computation model inspired by the way cells process chemical signals. Spiking Neural P systems (SNP systems), a

ABSTRACT Developing new non-traditional device models is gaining popularity as the silicon-based electrical device approaches its limitation when it scales down. Membrane systems, also called P systems, are a new class of biological computation model inspired by the way cells process chemical signals. Spiking Neural P systems (SNP systems), a certain kind of membrane systems, is inspired by the way the neurons in brain interact using electrical spikes. Compared to the traditional Boolean logic, SNP systems not only perform similar functions but also provide a more promising solution for reliable computation. Two basic neuron types, Low Pass (LP) neurons and High Pass (HP) neurons, are introduced. These two basic types of neurons are capable to build an arbitrary SNP neuron. This leads to the conclusion that these two basic neuron types are Turing complete since SNP systems has been proved Turing complete. These two basic types of neurons are further used as the elements to construct general-purpose arithmetic circuits, such as adder, subtractor and comparator. In this thesis, erroneous behaviors of neurons are discussed. Transmission error (spike loss) is proved to be equivalent to threshold error, which makes threshold error discussion more universal. To improve the reliability, a new structure called motif is proposed. Compared to Triple Modular Redundancy improvement, motif design presents its efficiency and effectiveness in both single neuron and arithmetic circuit analysis. DRAM-based CMOS circuits are used to implement the two basic types of neurons. Functionality of basic type neurons is proved using the SPICE simulations. The motif improved adder and the comparator, as compared to conventional Boolean logic design, are much more reliable with lower leakage, and smaller silicon area. This leads to the conclusion that SNP system could provide a more promising solution for reliable computation than the conventional Boolean logic.
ContributorsAn, Pei (Author) / Cao, Yu (Thesis advisor) / Barnaby, Hugh (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Fluxgate sensors are magnetic field sensors that can measure DC and low frequency AC magnetic fields. They can measure much lower magnetic fields than other magnetic sensors like Hall effect sensors, magnetoresistive sensors etc. They also have high linearity, high sensitivity and low noise. The major application of fluxgate sensors

Fluxgate sensors are magnetic field sensors that can measure DC and low frequency AC magnetic fields. They can measure much lower magnetic fields than other magnetic sensors like Hall effect sensors, magnetoresistive sensors etc. They also have high linearity, high sensitivity and low noise. The major application of fluxgate sensors is in magnetometers for the measurement of earth's magnetic field. Magnetometers are used in navigation systems and electronic compasses. Fluxgate sensors can also be used to measure high DC currents. Integrated micro-fluxgate sensors have been developed in recent years. These sensors have much lower power consumption and area compared to their PCB counterparts. The output voltage of micro-fluxgate sensors is very low which makes the analog front end more complex and results in an increase in power consumption of the system. In this thesis a new analog front-end circuit for micro-fluxgate sensors is developed. This analog front-end circuit uses charge pump based excitation circuit and phase delay based read-out chain. With these two features the power consumption of analog front-end is reduced. The output is digital and it is immune to amplitude noise at the output of the sensor. Digital output is produced without using an ADC. A SPICE model of micro-fluxgate sensor is used to verify the operation of the analog front-end and the simulation results show very good linearity.
ContributorsPappu, Karthik (Author) / Bakkaloglu, Bertan (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog

The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Recent research has identified affirmation of transcendence and exposure to violent Bible verses as being related to greater prejudice toward value-violating out-groups (Blogowska & Saroglou, 2012; Shen et al., 2013). Effects of exposure to specific Bible verses on attitudes toward out-groups have not been measured in combination with the Post-Critical

Recent research has identified affirmation of transcendence and exposure to violent Bible verses as being related to greater prejudice toward value-violating out-groups (Blogowska & Saroglou, 2012; Shen et al., 2013). Effects of exposure to specific Bible verses on attitudes toward out-groups have not been measured in combination with the Post-Critical Belief Scale developed by Hutsebaut (1996). The relationships between exposure to scriptural endorsements of prejudice, affirmation vs. disaffirmation of transcendence, literal vs. symbolic processing of religious content, and prejudice toward value-violating out-groups were examined using an online survey administered to a sample of U.S. adults (N=283). Greater affirmation of transcendence scores were linked to greater prejudice toward atheists and homosexuals and more favorable ratings of Christians and highly religious people. Lower affirmation of transcendence scores were linked to less favorable ratings of Christians and highly religious people and more favorable ratings of atheists. Exposure to scriptural endorsements of prejudice did not have a significant effect on levels of prejudice in this study.
ContributorsGrove, Richard (Author) / Robles, Elías (Thesis advisor) / Hall, Deborah (Committee member) / Schweitzer, Nicholas (Committee member) / Arizona State University (Publisher)
Created2013