Browsing by Author "Dr. Mark White, Committee Member"

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An Approach to Develop Knowledge Representation for Expert System to Diagnose Faults in Domestic Systems using Qualitative Modeling.
(2006-06-01) Kotcher, Pratik C; Dr. Wesley Snyder, Committee Member; Dr. Mark White, Committee Member; Dr. Edward Grant, Committee Chair
Faults, if remained undetected lead to huge financial losses. Troubleshooting faults requires analytical skills and knowledge of the system. Elementary skills help in solving common faults but faults that are infrequent or those which cannot be debugged by a consumer or even a field technician due to lack of in-depth knowledge of the system requires an expert's intervention. Experts are not always available in the field and lack of knowledge on the field technician's part may lead to huge financial losses and inconvenience on the part of the consumer. To avoid such situations an approach to make available expert's knowledge and capability to the field technicians is demonstrated through this research. A qualitative modeling approach to develop a knowledge representation is outlined here. A qualitative knowledge of the system from expert's point of view is modeled for a Bosch dishwasher for whom knowledge is extracted to generate a rule base, which reasons the characteristics of the system like an expert. Further it has been explored that using the rule base one can develop a questionnaire using the concept of model based diagnosis for troubleshooting. A qualitative model is useful for this kind of system because it resembles the analytical thinking capability of an expert and in general for any human being making it easier to communicate and interpret. Thus providing such a system to the field technician or even the consumer will simplify the troubleshooting process and will help in reducing downtime and financial losses.
The Development of a Low-Cost and Robust Autonomous Robot Colony Using LEGO Mindstorms
(2003-04-15) Braly, J. Chris; Dr. Edward Grant, Committee Chair; Dr. John F. Muth, Committee Member; Dr. H. Troy Nagle, Committee Member; Dr. Mark White, Committee Member
The late twentieth century marked the birth of urban search and rescue robots. The act of rescuing victims from collapsed or damaged buildings is extremely dangerous for the humans involved. After the attacks on the World Trade Center, researchers recognized the need for small robots with limited capabilities to be used in conjunction with more advanced robots for urban search and rescue. This research has developed a low-cost, autonomous robot colony with limited sensor capabilities using the LEGO® Mindstorms™ development platform. The study of this colony will provide insight into the group behavior of a marsupial robot colony used for urban search and rescue. A microphone sensor was developed to facilitate communication among the robot agents that comprise the colony. The incoming analog signal was amplified using a standard non-inverting operational amplifier configuration. This amplified signal was input into a tone detection circuit. This circuit was designed to provide a digital output to the LEGO® robot if a single tone of a specific frequency was detected. Other frequency tones have no effect on the circuit. Using this sensor, the robots could be controlled with different frequency tones. The task undertaken by the robots was a shepherding mission. The goal of the sheepdog robot was to herd the sheep robot into a pen located at a fixed location. A helper dog robot was added to assist the sheepdog when needed. The interaction, as well as communication, between the sheepdog and helper dog was studied.
The EvBot II: An Enhanced Evolutionary Robotics Platform Equipped with Integrated Sensing for Control
(2003-04-09) Mattos, Leonardo Serra; Dr. Troy Nagle, Committee Member; Dr. John Muth, Committee Member; Dr. Edward Grant, Committee Chair; Dr. Mark White, Committee Member
The research presented in this thesis describes the design and development of the EvBot II, a small, computationally powerful, and robust evolutionary robotics platform equipped with an acoustic array system. The EvBot II represents the next generation of autonomous robots for distributed robot-colony research, and its design has expanded the sensing capabilities and the overall performance of the EvBot robots by the incorporation of two microcontroller units, shaft encoders and a complete acoustic array system for tracking and navigation purposes. The design, development and test of this new robot is described in detail throughout this thesis, including the design of an USB data acquisition system capable of simultaneously sampling eight audio channels as required for the realization of the added acoustic array system. Experiments designed to evaluate the performance of this new robot and its components are also described in this thesis, as well as experimental results showing that it is a well-suited platform for the study of evolutionary robotics, distributed robot-colonies and sensors technologies.
Mathematical models for analysis of tissue regeneration in articular cartilage
(2008-09-04) Olson, Sarah Dianne; Dr. Alun Lloyd, Committee Member; Dr. Lori Setton, Committee Member; Dr. Mansoor Haider, Committee Chair; Dr. Mark White, Committee Member
A Pneumatically Actuated Brace Designed For Upper Extremity Stroke Rehabilitation
(2003-07-07) Merritt, Carey Reid; Dr. Mark White, Committee Member; Dr. Edward Grant, Committee Chair; Dr. Alexander Dean, Committee Member
Nearly 700,000 people suffered from stroke last year and those who survived were left with any number of disabilities. One of the most common disabilities in stroke is paralysis of the upper arm. Since therapy for this disability is expensive, patients are finding rehabilitation difficult to afford and manage. This thesis proposes an inexpensive pneumatic wearable garment for the patient to use for stroke rehabilitation. Unlike most rehabilitation robots, which are large, non-compliant, and expensive, this device will enable the patient to purchase the garment and move freely within their own home while rehabilitating their affected arm. In this thesis, a wearable elbow device similar to the proposed wearable garment was designed using an inexpensive elbow brace. The elbow brace used custom made artificial air muscles also known as McKibben Artificial Muscles to substitute for the biceps and triceps, which are responsible for flexion and extension of the human elbow. These artificial muscles were chosen for their low-cost, compliance, lightweight, and large force capabilities. The air muscles were designed and developed especially for this device and cost less than $3.00 to make and weigh approximately 11 g. This pneumatically actuated elbow brace was controlled using solenoid valves in conjunction with a Mitsubishi M32/83C 16-bit micro controller to achieve flexion and extension of the elbow. Experiments on the pneumatic elbow brace have shown that it is capable of moving a passive patient's arm within a 110° range, which is adequate for rehabilitation of the elbow.
Signal Processing using Wavelets for Enhancing Electronic Nose Performance
(2007-07-19) Phaisangittisagul, Ekachai; Dr. Edward Grant, Committee Member; Dr. H. Troy Nagle, Committee Chair; Dr. Charles Smith, Committee Member; Dr. Mark White, Committee Member
In recent years, many new technologies of electronic devices that mimic the mammalian olfactory system, electronic noses (e-noses), have been developed in many research institutions and commercial organizations around the world. These devices have been used in a wide range of applications such as food and beverage quality, environmental monitoring, medical diagnosis. Over the past decade, many researchers have spent a great deal of effort improving e-nose performance and also extended the use of the e-nose devices, not only for discriminating or classifying different odor samples, but also for quantifying an ingredient of a given odor sample. This dissertation focuses on two technical areas. First, an implementation of an e-nose signal processing system is developed to improve classification performance for small portable devices with fast response times and reduced cost. Second, the signal processing system is extended to odor mixture analysis. The advances made this research are based on a modern signal processing technique, specifically wavelet analysis. Ultimately, the performance of e-nose devices is highly dependent on the quality of features from the sensors' response. Therefore, a new transient feature extraction method using wavelet decomposition to capture the transient sensor's response has been developed. The evaluation of these transient features shows promising results in terms of classification performance, number of sensors employed in the e-nose device, and simplification of the classifier. For handling different types of odor samples, a simplified multiple classifier system is developed based on an "odor type signature." Analyzing mixtures of odors is a challenge for e-nose systems. Herein a new method is developed for predicting a sensor's response to mixtures of odors. The combination of wavelet decomposition and reconstruction is adopted to implement the mixed odor sensor-response predictor.