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Articles 691 - 720 of 846

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

An Enhanced Least-Squares Approach For Reinforcement Learning, Hailin Li, Cihan H. Dagli Jan 2003

An Enhanced Least-Squares Approach For Reinforcement Learning, Hailin Li, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents an enhanced least-squares approach for solving reinforcement learning control problems. Model-free least-squares policy iteration (LSPI) method has been successfully used for this learning domain. Although LSPI is a promising algorithm that uses linear approximator architecture to achieve policy optimization in the spirit of Q-learning, it faces challenging issues in terms of the selection of basis functions and training samples. Inspired by orthogonal least-squares regression (OLSR) method for selecting the centers of RBF neural network, we propose a new hybrid learning method. The suggested approach combines LSPI algorithm with OLSR strategy and uses simulation as a tool to …

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Combining Evolving Neural Network Classifiers Using Bagging, Sunghwan Sohn, Cihan H. Dagli Jan 2003

Combining Evolving Neural Network Classifiers Using Bagging, Sunghwan Sohn, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The performance of the neural network classifier significantly depends on its architecture and generalization. It is usual to find the proper architecture by trial and error. This is time consuming and may not always find the optimal network. For this reason, we apply genetic algorithms to the automatic generation of neural networks. Many researchers have provided that combining multiple classifiers improves generalization. One of the most effective combining methods is bagging. In bagging, training sets are selected by resampling from the original training set and classifiers trained with these sets are combined by voting. We implement the bagging technique into …

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Cooperative Cleaning For Distributed Autonomous Robot Systems Using Fuzzy Cognitive Maps, H. Subramanian, Cihan H. Dagli Jan 2003

Cooperative Cleaning For Distributed Autonomous Robot Systems Using Fuzzy Cognitive Maps, H. Subramanian, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cooperative Autonomous Cleaning is a simple challenge that can be implemented with the help of Fuzzy Cognitive Maps (FCM) by simulating the actual thinking process of the human. The human mind organizes its thoughts in priorities and this feature could be exploited well if a priori knowledge of the system exists. This technique has been attempted here for a DARS.

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Emergence And Artificial Life, Nil H. Kilicay, Cihan H. Dagli Jan 2003

Emergence And Artificial Life, Nil H. Kilicay, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper focuses on emergent phenomena and the utilization of computer simulations, basically agent-based modeling to understand emergent phenomena. Agent-based simulation models have a promising future in the social sciences, from management to economies, political science, sociology and anthropology. This paper attempts to realize their full scientific potential by reviewing recent applications in engineering management and addresses the set of challenges confronted by this method. Common methodology for constructing an agent-based model is also discussed with the aim of highlighting how artificial life and management can be brought together to develop decision making aid tools.

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Web Personalization Using Neuro-Fuzzy Clustering Algorithms, Kartik Menon, Cihan H. Dagli Jan 2003

Web Personalization Using Neuro-Fuzzy Clustering Algorithms, Kartik Menon, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Different users have different needs from the same web page and hence it is necessary to develop a system which understands the needs and demands of the users. Web server logs have abundant information about the nature of users accessing it. In this paper we discussed how to mine these web server logs for a given period of time using unsupervised and competitive learning algorithm like Kohonen''s self organizing maps (SOM) and interpreting those results using Unified distance Matrix (U-matrix). These algorithms help us in efficiently clustering users based on similar web access patterns and each cluster having users with …

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Performance & Project Spirit Of Student Design Competition Teams, Bradley Marcus Davis Jan 2003

Performance & Project Spirit Of Student Design Competition Teams, Bradley Marcus Davis

Masters Theses

"Student design competition teams present a valuable research possibility in the field of work group research. They are widely available and present greater learning opportunities than do class project groups. This study intended to create an instrument to measure the level of project spirit and team performance in order to establish a link between these two concepts. In the present study, nine student design competition teams from the University of Missouri - Rolla (UMR) campus (n = 186) were surveyed. The results indicate a strong correlation of the project spirit variables (project culture, project commitment, project citizenship, and project satisfaction) …

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Composite Structures Using Asphalt Based Roofing Scrap Materials: Eiera -- Final Report, V. J. Flanigan, K. Chandrashekhara, Susan L. Murray Sep 2002

Composite Structures Using Asphalt Based Roofing Scrap Materials: Eiera -- Final Report, V. J. Flanigan, K. Chandrashekhara, Susan L. Murray

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The uses of recycled materials in composites provide the potential for large cost savings and a solution to the ever-growing disposal problem. Shingles contain petroleum based binders and fillers, which used as a valuable resource in composite production. Composites offer inherent advantages over traditional materials in regard to corrosion resistance, design flexibility and extended service life. Use of scrap-roofing shingles as a core material in glass fiber reinforced composite materials offer potential low cost composite products such as sound barrier system, railroad ties and other building materials including blocks. In the present work, processes have been developed for shredding scrap …

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Engineering Management At Umr -- Alumni Voices, Stephen A. Raper Jun 2002

Engineering Management At Umr -- Alumni Voices, Stephen A. Raper

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Department of Engineering Management at the University of Missouri-Rolla is among the oldest of its kind in the United States, and has over 2000 Bachelors level alumni graduates. The Department will undergo ABET accreditation under the new assessment based criteria in the fall of 2002. The new criteria specify that engineering programs should seek to continuously improve their degree offerings through an ongoing assessment process that includes constituent input. Our own department has specified undergraduate alumni as one of the prime or key constituents that will be queried for input into our own processes. For the first time in …

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A Comparative Study Of Just-In-Time (Jit) And Theory Of Constraints (Toc) Systems With Varying Constraint Locations And Operational Characteristics, Pirun Hemmondharop Jan 2002

A Comparative Study Of Just-In-Time (Jit) And Theory Of Constraints (Toc) Systems With Varying Constraint Locations And Operational Characteristics, Pirun Hemmondharop

Doctoral Dissertations

"Various researchers have extolled the benefits of Theory of Constraints (TOC), Just-in-Time (JIT), and other manufacturing strategies. Some supporters of JIT argue it is the least costly, while others point to the overall benefits of TOC. There are conflicting claims as to the best manufacturing philosophies which is compounded by the fact that no one system is best in every situation. The success of a production system truly depends on the manufacturing environment rather than the philosophy being used. This study uses computer simulations of differing manufacturing environments to compare Just-in-Time (JIT) and Theory of Constraints (TOC) philosophies over two …

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Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan Jan 2002

Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan

Electrical and Computer Engineering Faculty Research & Creative Works

A multilayer neural network (NN) controller in discrete-time is designed to deliver a desired tracking performance for a class of nonlinear systems with input deadzones. This multilayer NN controller has an adaptive critic NN architecture with two NNs for compensating the deadzone nonlinearity and a third NN for approximating the dynamics of the nonlinear system. A reinforcement learning scheme in discrete-time is proposed for the adaptive critic NN deadzone compensator, where the learning is performed based on a certain performance measure, which is supplied from a critic. The adaptive generating NN rejects the errors induced by the deadzone whereas a …

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Prediction Of Electric Load Using Kohonen Maps - Application To The Polish Electricity Consumption, Amaury Lendasse, M. Cottrell, V. Wertz, M. Verleysen Jan 2002

Prediction Of Electric Load Using Kohonen Maps - Application To The Polish Electricity Consumption, Amaury Lendasse, M. Cottrell, V. Wertz, M. Verleysen

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Problem of Electrical Load Forecasting Presents Some Particularities, Compared to the Generic Problem of Time-Series Prediction. One of These Particularities is that Several Values (Corresponding to One Day of Consumption) Are Usually Expected as the Result of the Prediction. in This Paper, We Propose an Original Method Dividing the Problem into Three Parts: Prediction of the Daily Mean, of the Daily Standard Deviation and of the Normalized Daily Profile. for the Mean and the Standard Deviation, Radial Function Networks Are Used as Nonlinear Approximations. for the Normalized Profile, a Method based on Kohonen Maps is Proposed. This Method is …

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A Distributed Discrete-Time Neural Network Architecture For Pattern Allocation And Control, A.T. Chronopoulos, Jagannathan Sarangapani Jan 2002

A Distributed Discrete-Time Neural Network Architecture For Pattern Allocation And Control, A.T. Chronopoulos, Jagannathan Sarangapani

Computer Science Faculty Research & Creative Works

No abstract provided.

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Retention Of Female Faculty Members, Susan L. Murray, Mariesa Crow, Suzanna M. Rose Jun 2001

Retention Of Female Faculty Members, Susan L. Murray, Mariesa Crow, Suzanna M. Rose

Engineering Management and Systems Engineering Faculty Research & Creative Works

The recruitment and the retention of female undergraduate and graduate students into engineering courses is discussed. A similar challenge lies in recruiting female faculty member from the limited pool of candidates in several fields at most universities. It is found that about half the females who were hired did not stay at the university. It is suggested that programs should be introduced to encourage mentoring and career development as such improvements would benefit all faculty members both female and male.

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Advantages Of Using Fuzzy Class Memberships In Self-Organizing Map And Support Vector Machines, Sunghwan Sohn, Cihan H. Dagli Jan 2001

Advantages Of Using Fuzzy Class Memberships In Self-Organizing Map And Support Vector Machines, Sunghwan Sohn, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The self-organizing map (SOM) is naturally unsupervised learning, but if a class label is known, it can be used as the classifier. In a SOM classifier, each neuron is assigned a class label based on the maximum class frequency and classified by a nearest neighbor strategy. The drawback when using this strategy is that each pattern is treated by equal importance in counting class frequency regardless of its typicalness. For this reason, the fuzzy class membership can be used instead of crisp class frequency and this fuzzy membership-label neuron provides another perspective of a feature map. This fuzzy class membership …

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Decreasing Returns To Shareholders From Randd Spending In The Computer Industry, Del A. Mank, Halvard Nystrom Jan 2001

Decreasing Returns To Shareholders From Randd Spending In The Computer Industry, Del A. Mank, Halvard Nystrom

Engineering Management and Systems Engineering Faculty Research & Creative Works

This article explores the relationship between stockholder value changes and corporate research and development (RandD) spending in the computer industry. Researchers attempted to tie RandD expenditures and its various measurable effects to future results of the firms within an industry, with mixed results. They identify a positive, short-term relationship between stockholder share price movements and firm announcements of plans to increase RandD expenditures. They also show that industries with higher RandD intensities grow faster than those with low RandD intensities. However, little research is available that effectively relates RandD expenditures to future share price performance of the firms within an …

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Using A Neuro-Fuzzy-Genetic Data Mining Architecture To Determine A Marketing Strategy In A Charitable Organization's Donor Database, Korakot Hemsathapat, Cihan H. Dagli, David Lee Enke Jan 2001

Using A Neuro-Fuzzy-Genetic Data Mining Architecture To Determine A Marketing Strategy In A Charitable Organization's Donor Database, Korakot Hemsathapat, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper describes the use of a neuro-fuzzy-genetic data mining architecture for finding hidden knowledge and modeling the data of the 1997 donation campaign of an American charitable organization. This data was used during the 1998 KDD Cup competition. In the architecture, all input variables are first preprocessed and all continuous variables are fuzzified. Principal component analysis (PCA) is then applied to reduce the dimensions of the input variables in finding combinations of variables, or factors, that describe major trends in the data. The reduced dimensions of the input variables are then used to train probabilistic neural networks (PNN) to …

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The Relationship Between R&D Spending And Shareholder Returns In The Computer Industry, Del A. Mank, Halvard Nystrom Jan 2000

The Relationship Between R&D Spending And Shareholder Returns In The Computer Industry, Del A. Mank, Halvard Nystrom

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper explores the relationship between corporate R&D spending and growth in stockholder value. corporate R&D, at the macroeconomic level, mounts to controllable, discriminate, elective spending with the management intent of creating future revenue and profit opportunities for the firm. It is firmly established that different industries tend to have different levels of R&D investments as a percentage of revenue. Researchers have used R&D expenditures and their various measurable effects as proxies for inventive output in attempts to correlate current R&D &om to future results of the firms within an industry. Other studies have significantly related announced increases in firm …

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Plastic Manufacturing Process Selection Methodology Using Self-Organizing Map (Som)/Fuzzy Analysis, R. Raviwongse, Venkat Allada, T. Sandidge Jan 2000

Plastic Manufacturing Process Selection Methodology Using Self-Organizing Map (Som)/Fuzzy Analysis, R. Raviwongse, Venkat Allada, T. Sandidge

Engineering Management and Systems Engineering Faculty Research & Creative Works

For plastic products, one of the crucial decisions made during the preliminary design stage is the selection of an appropriate manufacturing process. In many industries, the selection of the manufacturing process is primarily based on the empirical knowledge and past experience of the manufacturing personnel. This selection procedure may result in inconsistent or poor choices if the manufacturing personnel fail to map correctly the product characteristics with the manufacturing efficacy of various manufacturing processes. This paper presents an intelligent self-organizing map (SOM)/fuzzy-based model to aid designers in the selection of an appropriate plastic manufacturing process. The plastic part attributes are …

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Large Machine-Part Family Formation Utilizing A Parallel Art1 Neural Network, David Lee Enke, Kanchitpol Ratanapan, Cihan H. Dagli Jan 2000

Large Machine-Part Family Formation Utilizing A Parallel Art1 Neural Network, David Lee Enke, Kanchitpol Ratanapan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The binary adaptive resonance (ART1) neural network algorithm has been successfully implemented in the past for the classifying and grouping of similar vectors from a machine-part matrix. A modified ART1 paradigm which reorders the input vectors, along with a modified procedure for storing a group's representation vectors, has proven successful in both speed and functionality in comparison to former technique. This paradigm has been adapted and implemented on a neurocomputer utilizing 256 processors which allows the computer to take advantage of the inherent parallelism of the ART1 algorithm. The parallel implementation results in tremendous improvements in the speed of the …

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Simple Ensemble-Averaging Model Based On Generalized Regression Neural Network In Financial Forecasting Problems, Cihan H. Dagli, Parinya Disorntetiwat Jan 2000

Simple Ensemble-Averaging Model Based On Generalized Regression Neural Network In Financial Forecasting Problems, Cihan H. Dagli, Parinya Disorntetiwat

Engineering Management and Systems Engineering Faculty Research & Creative Works

Introduces an ensemble-averaging model based on a GRNN (generalized regression neural network) for financial forecasting. The model trains all input individually using GRNNs and uses a simple ensemble-averaging committee machine to improve the accuracy performance. In a financial problem, there are many different factors that can effect the asset price movement at different times. An experiment is implemented in two different data sets, S&P 500 index and currency exchange rate. The predictive abilities of the model are evaluated on the basis of root mean squared error, standard deviation and percent direction correctness. The study shows a promising result of the …

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Analysis Of Intangible Factors In Waste Minimization Projects, Halvard E. Nystrom, William Ralph Kehr Jan 2000

Analysis Of Intangible Factors In Waste Minimization Projects, Halvard E. Nystrom, William Ralph Kehr

Engineering Management and Systems Engineering Faculty Research & Creative Works

Continual population growth and rising standards of living that accelerate the consumption of limited resources, are forcing society to encourage conservation of these resources. These resources not only include raw material, but also the areas to dispose of the wastes. As a result, communities are driving industries towards waste minimization by limiting waste generation and landfill availability. Firms'' environmentally friendly strategies can gain competitive advantage by leading in environmental practices. This advantage emanates from the reduction of risk of environmental regulatory overreaction, as well as improved asset utilization and landfill utilization. However, these intangible benefits are difficult to identify and …

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Exercising Real Unit Operational Options Under Price Uncertainty, Chung-Li Tseng Jan 2000

Exercising Real Unit Operational Options Under Price Uncertainty, Chung-Li Tseng

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we use the real options framework to value the operation flexibility of a power plant. The power plant operation is formulated as a multi-stage stochastic problem. We assume that there are hourly spot markets for both electricity and the fuel used by the generator, and that their prices follow some Ito processes. At each hour, the power plant operator must decide whether or not to run the unit so as to maximize expected profit. However, the unit operation is subject to decision lead times and minimum uptime and downtime constraints, so the commitment decision must take into …

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Strategy Planning For Technological Discontinuities In A Changing Regulatory Environment, William Ralph Kehr, Halvard E. Nystrom Jan 2000

Strategy Planning For Technological Discontinuities In A Changing Regulatory Environment, William Ralph Kehr, Halvard E. Nystrom

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper describes an approach to the analysis of publicly available financial data for individual industries. These methods enable the analyst to assess past practices and the historical rate of technological diffusion during the transition period of discontinuous technological change. This assessment can provide a basis of comparison for current changes in their industry. These methods are applied to small rural telephone companies during the period of 1960 to 1996. Annual data is presented detailing the change from aerial distribution cable to buried cable by the roughly 600 rural telephone companies financed through loans from the Rural Utilities Services, a …

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Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli Jul 1999

Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli

Computer Science Faculty Research & Creative Works

The creation of strategies to meet abstract goals is an important behavior exhibited by natural organisms. A situation requiring the development of such strategies is the predator-evader problem. To study this problem, Khepera robots are chosen as the competing agents. Using computer simulations the evolution of the adaptive behavior is studied in a predator-evader interaction. A bilaterally symmetrical multilayer perceptron neural network architecture with evolvable weights is used to model the “brains” of the agents. Evolutionary programming is employed to evolve the predator for developing adaptive strategies to meet its goals. To study the effect of learning on evolution a …

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The Effectiveness Of An On-Line Graduate Engineering Management Course, Rosemarie Maffei Evans, Madison Daily, Susan L. Murray Jun 1999

The Effectiveness Of An On-Line Graduate Engineering Management Course, Rosemarie Maffei Evans, Madison Daily, Susan L. Murray

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the summer of 1997, the Engineering Management Department of the University of Missouri-Rolla's (UMR) began offering its first Internet-based graduate level course. This course, Advanced Production Management, was designed to utilize a combination of Internet-based tools, such as EMail and Chat rooms to create a alternative means for the delivery of course material. This paper will draw these following conclusions from more than a year of research, which included over 100 students in six different course offerings. First, the Internet-based students performed equally as well as the control group students. Second, students tend to have exaggerated time requirement expectations …

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Moving Transportation Toward Sustainable Development: The Need For A Paradigm Shift, Bahador Ghahramani, Stephen A. Raper Jun 1999

Moving Transportation Toward Sustainable Development: The Need For A Paradigm Shift, Bahador Ghahramani, Stephen A. Raper

Engineering Management and Systems Engineering Faculty Research & Creative Works

Despite progress in controlling exhaust emissions, the increase of cars on the road will surpass progress in emission control technology. The automobile is currently responsible for 50% of world fossil fuel consumption, 15-20% of CO2 emissions worldwide and overwhelming particulate air pollution in many urban centers. Current efforts in emissions control have been focused on improving the efficiency of fuels and automobiles and their emissions. However, as a mode of transportation, the automobile is one of the most inefficient, both in environmental and economic costs. Even the most efficient cars developed today will still significantly contribute to the amount …

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Use Of Feedforward Neural Networks For Machine Vision Calibration, Mark B. Lynch, Cihan H. Dagli, Mahesh Vallenki Apr 1999

Use Of Feedforward Neural Networks For Machine Vision Calibration, Mark B. Lynch, Cihan H. Dagli, Mahesh Vallenki

Engineering Management and Systems Engineering Faculty Research & Creative Works

Machine vision calibration is an important step to obtaining usable measurements in inspection and automation operations. Conventional calibration techniques require the development of elaborate mathematical models and have prior knowledge of many parameters. Creating a suitable model and obtaining reasonable values for some calibration parameters is often difficult and error prone. In this article, a neural network approach is presented as an indirect non-linear optimization method to machine vision calibration. This approach does not require a mathematical model be developed nor any prior knowledge about the setup or calibration parameters. A universal calibration approach is developed and utilized in various …

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Integrated Manufacturing System For Precision Press Tooling, S. Chaturvedi, Venkat Allada Jan 1999

Integrated Manufacturing System For Precision Press Tooling, S. Chaturvedi, Venkat Allada

Engineering Management and Systems Engineering Faculty Research & Creative Works

The press tooling industry, characterized by many small-scale job-shops, is facing an increasingly competitive global market. This comes at a time when there is a shortage of experienced process planners and unavailability of affordable CAD/CAM systems that could provide an integrated solution for manufacturing sheet metal tooling. Many commercially available CAD/CAM systems are either too expensive or too narrow in scope, in the sense that they provide only point solutions. The design of press tools and its manufacturing functions are highly specialized and knowledge-intensive in nature. This paper presents a framework and the implementation details of an integrated system that …

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A Biologically Inspired Connectionist Model For Image Feature Extraction In 2d Pattern Recognition, Cihan H. Dagli, Raymond K. Chafin Jan 1999

A Biologically Inspired Connectionist Model For Image Feature Extraction In 2d Pattern Recognition, Cihan H. Dagli, Raymond K. Chafin

Engineering Management and Systems Engineering Faculty Research & Creative Works

A new edge detection method is presented which borrows from recent research into primate vision biology, and offers improved noise performance over classical methods. Beginning with spatio-temporal shunting models for retinal cones, horizontal cells, bipolar cells, and retinal ganglions, a set of simplified steady-state solutions are developed which lend themselves to efficient computation on standard computer equipment. The retinal model output is found to be nominally equivalent to the classical edge detector, but is produced differently. A simplified model of the lateral geniculate nucleus (LGN) has been produced. Taking the output of the retinal model, the LGN simple cell and …

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Short-Term Generation Asset Valuation, Chung-Li Tseng, G. Barz Jan 1999

Short-Term Generation Asset Valuation, Chung-Li Tseng, G. Barz

Engineering Management and Systems Engineering Faculty Research & Creative Works

We present a method for valuing a power plant over a short term period using Monte Carlo simulation. The power plant valuation problem is formulated as a multi stage stochastic problem. We assume there are hourly markets for both electricity and the fuel used by the generator, and their prices follow some Ito processes. At each hour, the power plant operator must decide to run or not to run the unit so as to maximize expected profit. A certain lead time for commitment decision is necessary to start up a unit. The commitment decision, once made, is subject to physical …

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