Digital Commons Network^™

Ambulatory Biopotential Measurement, Lakshmi Chitra Penugonda

Theses

Biopotential signals measure the electrical activity of different parts of the body. Conventional bedside monitors only provide information about the body under restricted conditions. Observation and documentation of biopotential signal during daily activities and the relation to patient symptoms may be important factors for clinical decision-making. Ambulatory monitoring helps to monitor the biopotential signal of a patient in the natural environment. The effective ambulatory system can help a physician to diagnose the patient's abnormality.

In this project, a low cost and flexible ambulatory biopotential system, compared to the commercially available systems, was designed and tested. Concurrently a software program was …

Pnl Applied To Economics, Barbara Diaz, Tomohiro Takagi, Sema E. Alptekin

Industrial and Manufacturing Engineering

This work is a continuation of Zadeh’s research on Precisiated Natural language. Precisiated Natural Language (PNL) provides a system for computation and deduction of propositions expressed in a natural language. The importance of PNL for economics is discussed. The improved process of PNL is presented using a real world example from economics.

2005 - The Tenth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Tenth Annual Symposium of Student Scholars, held on April 8, 2005. Includes abstracts from the presentations and posters.

Nsf Advance: Institutional Transformation For Faculty Diversity - Faculty Worklife Survey Results, Manuela Romero, Ann Q. Gates

Departmental Technical Reports (CS)

The The University of Texas at El Paso (UTEP) received an NSF ADVANCE grant in October 2003 to create an initiative for institutional change with the goal of serving as a model for other institutions that desire to increase the representation and advancement of women, including underrepresented minorities, in academic science and engineering careers. In the first year of the grant, co-PI's Ann Gates and Patricia Witherspoon worked with the ADVANCE Program Evaluator, Manuela Romero, to create an instrument to survey faculty work life at UTEP. The instrument is based on the "Study of Faculty Work Life" survey instrument that …

Generalized Phase Space Projection For Nonlinear Noise Reduction, Michael T. Johnson, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Improved phase space projection methods, adapted from related work in the linear signal processing field based on subspace decomposition, are presented for application to the problem of additive noise reduction in the context of phase space analysis. These methods improve upon existing methods such as Broomhead–King singular spectrum analysis projection by minimizing overall signal distortion subject to constraints on the residual error, rather than using a direct least-squares fit. This results in a range of weighted projections which estimate and compensate for the portion of the principal component's singular values corresponding to noise rather than signal energy, and which include …

Specification Of A Common Framework For Characterizing Alignment, Paolo Bouquet, Marc Ehrig, Jerome Euzenat, Enrico Franconi, Pascal Hitzler, Markus Krotzsch, Luciano Serafini, Giorgos Stamu, York Sure, Sergio Tessaris

Computer Science and Engineering Faculty Publications

Definition of a common framework for characterizing alignment of heterogeneous information. This report describes various approaches towards this goal and shows the relations between them. It also provides a description of the alignment sructure and process.

Parameter Based Synthesis Of Sign Language, Amanda Irving

Theses

The primary objective of this project is to demonstrate synthesis of signs in American Sign Language with a finite number of parameters. The parameters in this method include 22 key locations, six location modifiers, six orientation indicators, 46 hand shapes, six predefined movements and seven possible end effectors. These parameters can be used in conjunction with a computer script and they maximize precision and versatility while minimizing development time and resources. The parameters for each sign are stored in an individual text file averaging approximately half a kilobyte.

The success of this project is demonstrated using UGS's Jack Software, Version …

Analyst-Focused Arabic Information Retrieval, Robert N. Oddy, Ann R. Diekema, Jean Hannouche, Elizabeth Liddy, Grant Ingersoll

School of Information Studies - Faculty Scholarship

An English-Arabic Cross-Language Information Retrieval Environment was created in which the analyst can query an Arabic database in English and retrieve a set of relevant Arabic documents. The retrieved Arabic documents are automatically translated into English to facilitate readability by the English-only analyst. Proper names of people, places, and organizations are extracted from the retrieved documents and transliterated from Arabic into English. They are presented to the analyst and serve to provide a brief summarization of the retrieved document search query in English. Cross-Language Information Retrieval (CLIR), itself a desideratum in the ARDA workshop, is a special case of Information …

Methods For Approximate Reasoning, Perry Groot, Pascal Hitzler, Ian Horrocks, Boris Motik, Jeff Z. Pan, Heiner Stuckenschmidt, Daniele Turi, Holger Wache

Computer Science and Engineering Faculty Publications

This deliverable shows examples about approximating symbolic inference engines in a Semantic Web environment. Approaches of language weakening, knowledge compilation, and approximated deduction are presented. The last one is evaluated in practical applications with mixed results.

A Content-Based Fuzzy Image Database Based On The Fuzzy Artmap Architecture, M. Uysal, Fatoş Tünay Yarman Vural

Turkish Journal of Electrical Engineering and Computer Sciences

A major design issue in content-based image retrieval system is the selection of the feature set. This study attacks the problem of finding a discriminative feature for each class, which is optimal in some sense. Fuzzy ARTMAP architecture is used to find this discriminative feature set. For this purpose, initially, a large variety of features are extracted from the regions of the pre-segmented images. Then, the feature set of each object class is learned using the Fuzzy Art Map Architecture, by identifying the weights of each feature for each object class. In the querying phase, trained set of feature weights …

Color Image Profiling Using Fuzzy Sets, Amine Ait Younes, Isis Truck, Herman Akdag

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, a software for image indexing and retrieval is presented. The classification proposed here is based on the dominant color(s) of the images. The process consists in assigning a colorimetric profile to the image in HLS space (Hue, Lightness, Saturation). First, the definition of hue is done thanks to a fuzzy representation to take into account the non-uniformity of colors distribution. And then, lightness and saturation are represented through linguistic qualifiers also defined in a fuzzy way. Finally, the profile is built through fuzzy functions representing the membership degree of the image to different classes. In order to …

Negative Reinforcement And Backtrack-Points For Recurrent Neural Networks For Cost-Based Abduction, Donald C. Wunsch, Ashraf M. Abdelbar, M. A. El-Hemaly, Emad A. M. Andrews

Electrical and Computer Engineering Faculty Research & Creative Works

Abduction is the process of proceeding from data describing a set of observations or events, to a set of hypotheses which best explains or accounts for the data. Cost-based abduction (CKA) is an AI formalism in which evidence to be explained is treated as a goal to be proven, proofs have costs based on how much needs to be assumed to complete the proof, and the set of assumptions needed to complete the least-cost proof are taken as the best explanation for the given evidence. In this paper, we introduce two techniques for improving the performance of high order recurrent …

An Embedded Real-Time Neuro-Fuzzy Controller For Mobile Robot Navigation, Nian Zhang, Daryl G. Beetner, Donald C. Wunsch, B. Hemmelman, Ahmad Hasan

Electrical and Computer Engineering Faculty Research & Creative Works

A reactive fuzzy logic based control strategy was developed for mobile robot navigation. To decrease the number of fuzzy rules and related processing, a RAM-based neural network was combined with the fuzzy logic strategy. The fuzzy rules are used to interpret sensor information. The neural network uses results from the fuzzy logic as well as environmental information to make navigation decisions. The feasibility of this neuro-fuzzy approach was demonstrated on a mobile robot using a simple, 8-bit microcontroller. Experiments show the approach works well, as the robot was able to successfully avoid objects while seeking a goal in real-time. The …

Compressed Pattern Matching For Text And Images, Tao Tao

Electronic Theses and Dissertations

The amount of information that we are dealing with today is being generated at an ever-increasing rate. On one hand, data compression is needed to efficiently store, organize the data and transport the data over the limited-bandwidth network. On the other hand, efficient information retrieval is needed to speedily find the relevant information from this huge mass of data using available resources. The compressed pattern matching problem can be stated as: given the compressed format of a text or an image and a pattern string or a pattern image, report the occurrence(s) of the pattern in the text or image …

The Development Of A Fuzzy Model To Quantify Training Andeducational Factors And The Resulting Impact On Student Successand Lear, Chandre Butler

Electronic Theses and Dissertations

The utilization of fuzzy mathematical modeling for quantification of the quality of training and educational delivery is an innovative application that can result in measurable and repeatable results. This research was designed to apply proven quantification techniques and Industrial Engineering methodologies to a nontraditional environment. The outcomes of this research provide the foundation, initial steps and preliminary validation for the development of a systematic fuzzy theoretical model to be applied for the quantification of various areas within training and education delivery. The test bed for this methodology is Orange County Public School system, the twelfth largest school district in the …

Speaker Identification Based On Discriminative Vector Quantization And Data Fusion, Guangyu Zhou

Electronic Theses and Dissertations

Speaker Identification (SI) approaches based on discriminative Vector Quantization (VQ) and data fusion techniques are presented in this dissertation. The SI approaches based on Discriminative VQ (DVQ) proposed in this dissertation are the DVQ for SI (DVQSI), the DVQSI with Unique speech feature vector space segmentation for each speaker pair (DVQSI-U), and the Adaptive DVQSI (ADVQSI) methods. The difference of the probability distributions of the speech feature vector sets from various speakers (or speaker groups) is called the interspeaker variation between speakers (or speaker groups). The interspeaker variation is the measure of template differences between speakers (or speaker groups). All …

Fuzzifying [Sic] Markov Decision Process, Ahmed Syed Irshad

LSU Master's Theses

Markov decision processes have become an indispensable tool in applications as diverse as equipment maintenance, manufacturing systems, inventory control, queuing networks and investment analysis. Typically we have a controlled Markov chain on a suitable state space in which transitional probabilities depend on the policy (or decision maker) which comes from a set of possible actions. The main problem of interest would be to find an optimal policy that minimizes the associated cost. Linear Programming has been widely used to find the optimal Markov decision policy. It requires solutions of large systems of simultaneous linear equations. By the fact that the …

Interval Neutrosophic Sets And Logic; Theory And Applications In Computing, Haibin Wang, Florentin Smarandache, Yan-Qing Zhang, Rajshekhar Sunderraman

Branch Mathematics and Statistics Faculty and Staff Publications

This book presents the advancements and applications of neutrosophics. Chapter 1 first introduces the interval neutrosophic sets which is an instance of neutrosophic sets. In this chapter, the definition of interval neutrosophic sets and set-theoretic operators are given and various properties of interval neutrosophic set are proved. Chapter 2 defines the interval neutrosophic logic based on interval neutrosophic sets including the syntax and semantics of first order interval neutrosophic propositional logic and first order interval neutrosophic predicate logic. The interval neutrosophic logic can reason and model fuzzy, incomplete and inconsistent information. In this chapter, we also design an interval neutrosophic …

Implementation Of A New Self-Tuning Fuzzy Pid Controller On Plc, Onur Karasakal, Engi̇n Yeşi̇l, Müjde Güzelkaya, İbrahi̇m Eksi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the self-tuning method for fuzzy PID controllers that has been developed in a previous study of the authors is implemented on PLC in order to control some standard processes formed on FEEDBACK PCS 327 Process Control Simulator. In this tuning method, the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral coefficient of the fuzzy PID controller are adjusted using a fuzzy inference mechanism with a new input called ``normalized acceleration''. The results of the implementation have been compared with those of the classical fuzzy PID controller without a …

A Dynamic Neuro-Fuzzy Model Providing Bio-State Estimation And Prognosis Prediction For Wearable Intelligent Assistants, Yu Wang, Jack M. Winters

Biomedical Engineering Faculty Research and Publications

Background

Intelligent management of wearable applications in rehabilitation requires an understanding of the current context, which is constantly changing over the rehabilitation process because of changes in the person's status and environment. This paper presents a dynamic recurrent neuro-fuzzy system that implements expert-and evidence-based reasoning. It is intended to provide context-awareness for wearable intelligent agents/assistants (WIAs).

Methods

The model structure includes the following types of signals: inputs, states, outputs and outcomes. Inputs are facts or events which have effects on patients' physiological and rehabilitative states; different classes of inputs (e.g., facts, context, medication, therapy) have different nonlinear mappings to a …

An Adaptive Mamdani Fuzzy Logic Based Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

An adaptive Mamdani based fuzzy logic controller has been designed for controlling a static compensator (STATCOM) in a multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently control a STATCOM during different disturbances in the network. A model free approach using the controller output error is applied for training purposes that adaptively changes the controller output parameters based on a gradient descent method. Moreover, shrinking span membership functions are used for a more stable and accurate control performance. Simulation results show that the proposed controller outperforms the conventional …

Hardware Implementation Of A Mamdani Fuzzy Logic Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Satish Rajagopalan, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

A Mamdani based fuzzy logic controller is designed and implemented for controlling a STATCOM, which is connected to a 10 bus multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently provide control signals for the STATCOM during different disturbances in the network The proposed controller is implemented using the M67 DSP board and is interfaced to the multimachine power system simulated on a real-time digital simulator (RTDS). Experimental results are provided, showing that the proposed controller provides more effective damping than the conventional PI controller in a typical …

Cognitive Memory Effects On Non-Linear Video-Based Learning, Katherine Renee Comeaux

LSU Master's Theses

During an informative learning process, information, material, facts and ideas are typically conveyed in a linear arrangement. Individuals are frequently distracted during this process with their attention being diverted to an interruption (Internet, phone call, etc). When presented with any new information, the mind evolves through problem solving and evaluation procedures. The way in which that information is processed and perceived depends on: (a) original presentation (b) examination of material and (c) an individualistic measurement of success. However, when faced with an interruption, the person is forced to deal with non-linear arrangement of information. This research investigates nonlinear presentation or …

Do Maps Guide The Way To Npd Success? Theoretical And Practical Aspects Of Knowledge Mapping In Product Development, Antonie J, Jetter

Engineering and Technology Management Faculty Publications and Presentations

New product development success largely depends on the ability to combine newly acquired information on customer demands and technological options with knowledge that exists within the company. Project organization and high employee turnover, however, make it difficult to be informed about what knowledge is available within the company and to access it successfully. Knowledge maps, a popular concept in present knowledge management, offer a possible solution by ?guiding the way to knowledge?. Their purpose, structure and content varies greatly, as does their ability to capture different aspects of knowledge. This paper investigates the theoretical basis of different types of knowledge …

The Effects Of Gender And Regional Dialect On Performance In Aviation Communication, Erin E. Mccollum

Master's Theses - Daytona Beach

The purpose of this study was to analyze the performance effects of gender and regional dialect on air traffic control statement recall. Sixty-one student volunteers participated in the experiment. Thirty-one participants held a pilot’s license and 30 participants had no flight experience. Each participant listened to one CD with 60 ATC statements each representing a male and female voice and New England, Southern, and General American dialect. Participants were asked to recall exactly what they heard. If the participant could not understand what they heard, they requested a repeat. The participant’s performance was recorded to CD and analyzed. Demographic questionnaires …

Default Reasoning Over Domains And Concept Hierarchies, Pascal Hitzler

Computer Science and Engineering Faculty Publications

W.C. Rounds and G.-Q. Zhang have proposed to study a form of disjunctive logic programming generalized to algebraic domains [1]. This system allows reasoning with information which is hierarchically structured and forms a (suitable) domain. We extend this framework to include reasoning with default negation, giving rise to a new nonmonotonic reasoning framework on hierarchical knowledge which encompasses answer set programming with extended disjunctive logic programs. We also show that the hierarchically structured knowledge on which programming in this paradigm can be done, arises very naturally from formal concept analysis. Together, we obtain a default reasoning paradigm for conceptual …

Non-Lexical Conversational Sounds In American English, Nigel Ward

Departmental Technical Reports (CS)

This article analyzes the non-lexical conversational sounds (conversational grunts) of English, including such items as uh-huh, un-hn, um, mm, and oh, based primarily on examination of a few hundred occurrences in a corpus of conversations. The data includes extensive phonetic variation, suggesting that these items are best explained, not as fixed words, but as dynamic creations. In particular, the vast majority of these items can be generated by a simple model consisting of 10 component sounds and 2 combining rules. Moreover, each of these component sounds seems to bear some meaning or function which is fairly constant across grunts and …

Ascertaining The Importance Of Neurons To Develop Better Brain-Machine Interfaces, Justin C. Sanchez, Jose M. Carmena, Mikhail A. Lebedev, Miguel A.L. Nicolelis, John G. Harris, Jose C. Principe

Electrical and Computer Engineering Faculty Research & Creative Works

In the design of brain-machine interface (BMI) algorithms, the activity of hundreds of chronically recorded neurons is used to reconstruct a variety of kinematic variables. A significant problem introduced with the use of neural ensemble inputs for model building is the explosion in the number of free parameters. Large models not only affect model generalization but also put a computational burden on computing an optimal solution especially when the goal is to implement the BMI in low-power, portable hardware. In this paper, three methods are presented to quantitatively rate the importance of neurons in neural to motor mapping, using single …

Time Series Classification Using Gaussian Mixture Models Of Reconstructed Phase Spaces, Richard J. Povinelli, Michael T. Johnson, Andrew C. Lindgren, Jinjin Ye

Electrical and Computer Engineering Faculty Research and Publications

A new signal classification approach is presented that is based upon modeling the dynamics of a system as they are captured in a reconstructed phase space. The modeling is done using full covariance Gaussian mixture models of time domain signatures, in contrast with current and previous work in signal classification that is typically focused on either linear systems analysis using frequency content or simple nonlinear machine learning models such as artificial neural networks. The proposed approach has strong theoretical foundations based on dynamical systems and topological theorems, resulting in a signal reconstruction, which is asymptotically guaranteed to be a complete …

Parametric Synthesis Of Sign Language, Jerome Allen

Theses

The isolation of the deaf community from mainstream society is in part due to the lack of knowledge most hearing people have of sign language. To most, there seems to be little need to learn a language that is spoken by such a small minority unless perhaps a relative is unable to hear. Even with a desire to learn, the task may seem insurmountable due to the unique formational and grammatical rules of the language.

This linguistic rift has led to the call for an automatic translation system with the ability to take voice or written text as input and …