M. Bodruzzaman

Adams, Robin S.(Scssion I In6)

doi.ieeecomputersociety.org

Meeting The Abet Computer Competency Requirement In The Department Of Electrical And Computer Engineering At Tennessee State University

1998 Annual Conference Proceedings

Recent ABET visit and our desire to review, evaluate and plan for development of computer facilit... more Recent ABET visit and our desire to review, evaluate and plan for development of computer facilities within the College of Engineering and Technology and the Department of Electrical and Computer Engineering in specific, provided us an opportunity to access our current level of computer use and computer facilities. This evaluation is listed in tabular form. This also provided us an opportunity to develop guidelines for meeting ABET computer use and facilities requirements and plan for future developments in our program to meet Engineering Criteria 2000 requirements. The Electrical Engineering curriculum, and its concentration in Computers, requires at least two student written computer projects for all o its major courses. Wordprocessed technical reports and oral presentation have now became a norm in our program. At least two laboratories are equipped with latest model computers with major higher level programming language compilers, and application software such as Matlab, LabVIEW, LabWindow and other simulation and modeling software. Students have access to Internet via Netscape browser for information retrieval and use of resources that are available elsewhere. Computer-based data acquisition experience is acquired in the Control Systems, Circuits, and Electrical Systems Design Laboratories. Additionally many students work with faculty on various federal and industry funded research projects and use computers for real-time data acquisition, signal/image processing, energy related research, predictive maintenance, intelligent controls and robotics areas. This paper examines the computer competency skills acquired by our students towards meeting ABET criteria and presents a model plan for evaluating such competencies. The Required Level of Competency After reviewing the ABET Criteria for accrediting programs in Engineering in general and Electrical, Electronic(s), Computer and similarly named engineering programs in specific, we identified that the following topics be considered in evaluating the desired competencies that an electrical and/or computer engineering graduate should have acquired as part of the undergraduate curriculum requirements. These are listed under ABET criteria IV.C.3.g and IV.C.6.c. x Experience with advanced features of at least one major operating system: This requirement could be satisfied if the student had experience with Windows 95, Windows NT

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Reconfigurable Distributed Control Systems for Turbine Engine Operation Uncertainties

52nd AIAA/SAE/ASEE Joint Propulsion Conference, 2016

An efficient two dimensional moving average model for texture analysis and synthesis

Proceedings IEEE Southeastcon '92

A linear 2D moving average model which serves a dual purpose in the analysis and synthesis of sto... more A linear 2D moving average model which serves a dual purpose in the analysis and synthesis of stochastic texture is presented. This model is based on the assumption that a stochastic texture is produced by convolving an uncorrelated random field with a 2D filter which completely characterizes the texture. A simple and effective algorithm, involving the computation of arithmetic average,

Neural Network Based Montioring and Control of Fluidized Bed

In this report, a summary on the work done on the chaotic behavior control in FBC systems project... more In this report, a summary on the work done on the chaotic behavior control in FBC systems project will be given. And an update to the chaos control method we design to control the chaotic behavior in an FBC system will be discussed. This method includes a fully recurrent neural network called the Dynamic System Imitator @SI). The DSI was specially designed to mimic the behavior of a wide variety of dynamic systems in the real world. It is found to be capable of learning both the transient and steady state behavior of a dynamic system. The DSI was applied for modeling of linear, non-linear and chaotic systems. It is also successfully used for iterative prediction of chaotic system behavior. A general methodology for using the DSI to control a non-linear system is studied. This methodology is applied to control the chaotic behavior of the Lorenz System as a typical chaotic system. A plan is also outlined for this method to be applied to the Fluidized Bed Combustion (FBC) system for the prediction and control of its chaotic behavior. The chaotic pressure data, from an experimental fluidized bed combustion system, was obtained from the Morgan town Energy Technology Center (METC). These data represent some normal and abnormal mixing process in an FBC system. The results of chaos analysis, applied to these data, will be presented. These techniques are used to identify the system behavior at different conditions, to estimate the system order, to construct the system attractor, and to locate the chaotic behavior in the pressure-drop time series data. Preliminary analysis show that both the normal and abnormal conditions of the FBC have chaotic characteristics. The overall objective is to know more about the characteristics of the time series at different conditions, to find an appropriate model for the system, and to apply a neuro-chaos controller to preserve the normal operational performance of the system.

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Neural network-based monitoring and control of fluidized bed. Quarterly progress report, October 1, 1995--December 31, 1995

In this report, a summary on the work done on the chaotic behavior control in FBC systems project... more In this report, a summary on the work done on the chaotic behavior control in FBC systems project will be given. And an update to the chaos control method we design to control the chaotic behavior in an FBC system will be discussed. This method includes a fully recurrent neural network called the Dynamic System Imitator @SI). The DSI was specially designed to mimic the behavior of a wide variety of dynamic systems in the real world. It is found to be capable of learning both the transient and steady state behavior of a dynamic system. The DSI was applied for modeling of linear, non-linear and chaotic systems. It is also successfully used for iterative prediction of chaotic system behavior. A general methodology for using the DSI to control a non-linear system is studied. This methodology is applied to control the chaotic behavior of the Lorenz System as a typical chaotic system. A plan is also outlined for this method to be applied to the Fluidized Bed Combustion (FBC) system for the prediction and control of its chaotic behavior. The chaotic pressure data, from an experimental fluidized bed combustion system, was obtained from the Morgan town Energy Technology Center (METC). These data represent some normal and abnormal mixing process in an FBC system. The results of chaos analysis, applied to these data, will be presented. These techniques are used to identify the system behavior at different conditions, to estimate the system order, to construct the system attractor, and to locate the chaotic behavior in the pressure-drop time series data. Preliminary analysis show that both the normal and abnormal conditions of the FBC have chaotic characteristics. The overall objective is to know more about the characteristics of the time series at different conditions, to find an appropriate model for the system, and to apply a neuro-chaos controller to preserve the normal operational performance of the system.

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Modernization of Engineering Research Institute at Tennessee State University

Funding from 1997 DoD HBCU/MI infrastructure support for educational instrumentation provided sup... more Funding from 1997 DoD HBCU/MI infrastructure support for educational instrumentation provided support for Tennessee State University to modernize its Engineering Research Institute (ERI). State of the art equipment with associated software was purchased to enhance the research capabilities of image processing, concurrent manufacturing, networking and communication and robotics and machine vision laboratories. The impact of this equipment led to completion of 13 undergraduate senior capstone design projects and 14 masters' theses during 1999-2000 In addition 7 new graduate level courses were established to enrich the electrical and mechanical engineering curriculum and enhance the career opportunities of our students. The equipment funds were leveraged to obtain two new grants in robotics from NASA Ames and JPL totaling $631,000, and a contract from BWXT-Yl2 security complex for $198,000 Based on enhanced research capabilities Tennessee Board of Regents approved Ph.D degree progr...

LabVIEW program design for on-line data acquisition and predictive maintenance

Proceedings of Thirtieth Southeastern Symposium on System Theory

... Sujatha Srinivasan, LabVIEW Program Design for Data Acquisition and Prediction of a Fan-Moto... more

Chaotic behavior control in fluidized bed systems using artificial neural network. Quarterly progress report, April 1, 1996--June 30, 1996

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Chaotic classification of electromyographic (EMG) signals via correlation dimension measurement

Proceedings IEEE Southeastcon '92

A set of intramuscular electromyographic signals were collected from various patient groups durin... more A set of intramuscular electromyographic signals were collected from various patient groups during ramp muscle contraction. The signals were collected using a real-time data acquisition system. The signals were tested for their chaotic behavior using spectral analysis and Poincare map techniques. MATLAB based software tools were developed to compute and plot the correlation function for each data set to determine the time lag for the first zero crossing. This time lag was used to create the signals state-space model. A two-dimensional state-space was created and plotted one state versus the other to observe the Poincare map. A correlation integral was computed for each state-space data set, and the correlation dimension values were then calculated by differentiating these correlation integral signals for each data set. The correlation dimension values were found to be different for different patient groups. The results show promise for online classification of neuromuscular patient groups

<title>Speaker recognition using neural network and adaptive wavelet transform</title>

Visual Information Processing II, 1993

ABSTRACT

Development of a neural network predictor for wind power

Increasing public concern about environmental impact of emissions from fossil fuel generating sta... more Increasing public concern about environmental impact of emissions from fossil fuel generating stations, disposal of hazardous materials and threat of nuclear mishap is causing great uncertainty in approval and installation of traditional large generating stations to meet future energy needs. Additionally federal regulation regarding the level of CO{sub 2} and SO{sub 2} emission is urging utilities to consider non-polluting sources of power in their overall generation mix to meet continued increasing demand for electric power also as they retire old generation stations. PURPA is requiring utilities to provide access to their transmission and distribution systems for independent power producers. All of this is forcing the utility industry to consider alternate sources of power especially renewable and non-polluting sources such as wind power. Because of its very nature wind is very unpredictable and thus the power from wind electric power systems. As the wind power sources gain more r...

Identifying the modes of a vibratory system excited by narrow band random excitations

Proceedings of Southeastcon '93, 1993

The random decrement technique is investigated in connection with the analysis of the modes of a ... more The random decrement technique is investigated in connection with the analysis of the modes of a vibratory system excited by a narrow-band random oscillation. A discrete version of the random decrement technique is applied in which the excitation has a bandlimited spectrum. The results obtained with this method are compared with the results obtained using the linear prediction method. The passband is within the bandlimited spectrum of the random excitation and includes the complete frequency response of one or more modes of the free vibration of the structure. Since these modes are excited by natural forces, they reflect the main characteristics of the structure. The signature obtained by the random decrement method is superior to that obtained by the linear prediction method. The resulting signature has been used to monitor the structural health of vibratory systems under test.<<ETX>>

Chaotic behavior monitoring & control in fluidized bed systems using artificial neural network. Quarterly progress report, July 1, 1996September 30, 1996

We have developed techniques to control the chaotic behavior in Fluidized Bed Systems (FBC) syste... more We have developed techniques to control the chaotic behavior in Fluidized Bed Systems (FBC) systems using recurrent neural networks. For the sake of comparison of the techniques we have developed with the traditional chaotic system control methods, in the past three months we have been investigating the most popular and first known chaotic system control technique known as the OGY method. This method was developed by Edward Ott, Celso Grebogi and James York in 1990. In the past few years this method was further developed and applied by many researchers in the field. It was shown that this method has potential applications to a large cross section of problems in many fields. The only remaining question is whether it will prove possible to move from laboratory demonstrations on model systems to real world situations of engineering importance. We have developed computer programs to compute the OGY parameters from a chaotic time series, to control a chaotic system to a desired periodic ...

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Online prognostics of aircraft turbine engine component's remaining useful life (RUL)

IEEE SOUTHEASTCON 2014, 2014

Prognostics refers to the estimation of remaining useful life (RUL) of components of a system aft... more Prognostics refers to the estimation of remaining useful life (RUL) of components of a system after a fault has been identified. Online prognostics indicates the estimation of RUL every time a new health data is provided to the user. In this paper, an artificial neural network (ANN) based approach is proposed for designing a prognostic system for aircraft turbine engine. A trained ANN is developed to estimate the health parameters such as component efficiency (η) and flow capacity (γ). The ANN was trained for a very small value of mean squared error (MSE). Then a forecasting (prediction) method is used to model the trend of estimated health parameters. The model is developed by autoregressive technique (AR) and all the data processing is done online. The proposed prognostic system also compute the distribution of the end of life (EoL) estimation of the failed component. The EoL and RUL estimation are implemented by modeling the health data using moving window and progressive window. The standard deviation (σ) of the distribution of estimated EoL indicates that progressive window performs better than the moving window with a σ reduction factor of 0.6 and 0.5 for η and γ respectively.

Stability Prediction of Nonlinear System Using Multilayer Feed-forward Artificial Neural Network

The 24th Southeastern Symposium on and The 3rd Annual Symposium on Communications, Signal Processing Expert Systems, and ASIC VLSI Design System Theory, 1992

ABSTRACT

High-resolution estimation and on-line monitoring of natural frequency of aircraft structure specimen under random vibration

Proceedings of National Aerospace and Electronics Conference (NAECON'94), 1994

ABSTRACT The growth of structural damage reduces the stiffness which results in decrease in the n... more ABSTRACT The growth of structural damage reduces the stiffness which results in decrease in the natural frequency of a specimen (coupon) under random vibration. However, the identification of the natural frequency is not a trivial problem because the coupons are shaken in a random fashion in which many closely-spaced frequencies are involved. The signal may have other redundant frequencies involved which are close to the natural frequency The simplest way to identify the frequencies of multiple sinusoids is the Fourier transform spectral analysis. However, when the frequencies of interest are closely spaced, the Fourier transform spectrum analysis fails to resolve these frequencies. In this paper these facts are shown for a real vibration signal. High resolution frequency estimation approach, such as the forward-backward linear prediction (FBLP) method, is adopted here to identify all the prominent frequencies in a certain bandwidth. From the pth order FBLP model, we estimate p positive frequencies. Among these p frequencies, the one that will decrease as the structure degenerates, is the natural frequency and is monitored in an on-line mode. An estimation of natural frequency and its prediction is made regularly (every one second) based on all available estimated natural frequencies once the structure enters the fatigue zone. The system is useful for on-line health monitoring of any structure under random vibration. We have applied this system to monitor several aluminum coupons of aircraft structure. The tests were performed at the Wright Research Lab and the software monitoring system was developed at Tennessee State University

Neural network-based codebook search for image compression

Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105), 2000

ABSTRACT This paper presents an efficient and fast encoding of still images using the feedforward... more ABSTRACT This paper presents an efficient and fast encoding of still images using the feedforward neural network technique for codebook search. The image to be coded is first clustered into a small subset of neighboring images and then the neural network-based encoder is used to find the best matching code sequences in the codebook. This subset is then used as a candidate set and an exhaustive search is then performed within this subset to find an optimal code sequence which minimizes the perceptual error between coded and decoded images. In this work, a generic codebook is developed using non-causal differential pulse coded modulation (DPCM) with residual mean removal and vector quantization using Linde, Buzo and Gray (1980) method. The codebook is analyzed to identify a pattern in the codebook. This pattern is used to train a neural network to obtain the approximate index of the pattern in the codebook. Then, an extensive search is done around this approximate position identified by the neural network to obtain the nearest neighbor of the pattern. Since the candidate set is usually much smaller that the whole code book, there is a substantial saving in codebook search time for coding an image as compared to the traditional method using full codebook search by the LBG algorithm

Meeting ABET EC 2000 through student research participation

FIE'99 Frontiers in Education. 29th Annual Frontiers in Education Conference. Designing the Future of Science and Engineering Education. Conference Proceedings (IEEE Cat. No.99CH37011, 1999

Ever since the announcement of ABET Engineering Criteria 2000, there has been increased emphasis ... more Ever since the announcement of ABET Engineering Criteria 2000, there has been increased emphasis to identify tools and methods, and to develop programs and mechanisms that can be easily implemented and evaluated to satisfy various EC 2000 criteria. Each program will develop methods that are consistent with that program's objectives and also satisfy ABET criteria. ABET Criteria II.3 Program Outcomes and Assessment requires engineering programs to document, through an assessment process, that their graduates meet the criteria 3 items (a) through (k) requirements. This paper discusses the undergraduate student participation in faculty funded research in its College of Engineering and Technology. It also shows how most of the Criteria 3 requirements can be met by just undergraduate student participation in faculty research. This is especially helpful in meeting some of the difficult criteria such as the ability to function on multidisciplinary teams, ability to identify, formulate and solve engineering problems, ability to communicate effectively, and a recognition of the need for, and an ability to engage in lifelong learning. This paper discusses the student participation in various research programs and how this research participation has contributed to their abilities in the areas discussed. It also lists some of the faculty publications that have contributed to the course development, design enhancement and program development.

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Biologically motivated servomechanism kinematic models

Proceedings IEEE Southeastcon '95. Visualize the Future, 1995

ABSTRACT Forward and inverse kinematic models for a human like (HL) robot joint are developed and... more ABSTRACT Forward and inverse kinematic models for a human like (HL) robot joint are developed and used to simulate the behavior of the joint. The forward kinematic model of the HL joint is found simply to consist of two rotational motions about fixed coordinate frames. The inverse tangent (atan2) function technique is used to develop an inverse kinematic model of the HL joint. This technique also prevents singular values from occurring in the calculations. Simulation results of the forward kinematic model are presented

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