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Missouri University of Science and Technology

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Articles 571 - 600 of 839

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

Trenchless Water Pipe Condition Assessment Using Artificial Neural Network, Zong Woo Geem, Chung-Li Tseng, Juhwan Kim, Cheolho Bae Nov 2007

Trenchless Water Pipe Condition Assessment Using Artificial Neural Network, Zong Woo Geem, Chung-Li Tseng, Juhwan Kim, Cheolho Bae

Engineering Management and Systems Engineering Faculty Research & Creative Works

In order to assess the water pipe condition without excavating, artificial neural network (ANN) model was developed and applied to real-world case in South Korea. for the input in this ANN model, 11 factors such as (1) pipe material, (2) diameter, (3) pressure head, (4) inner coating, (5) outer coating, (6) electric recharge, (7) bedding condition, (8) age, (9) trench depth, (10) soil condition, and (11) number of road lanes were used; and, for the output, overall pipe condition index was derived based on 5 factors such as (1) outer corrosion, (2) crack, (3) pin hole, (4) inner corrosion, and …

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Predictive Congestion Control Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani Nov 2007

Predictive Congestion Control Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel …

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Effects Of Electromagnetic Interference On Control Area Network Performance, Fei Ren, Y. Rosa Zheng, Maciej Jan Zawodniok, Jagannathan Sarangapani Nov 2007

Effects Of Electromagnetic Interference On Control Area Network Performance, Fei Ren, Y. Rosa Zheng, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effects of electromagnetic interference (EMI) on control area network (CAN) communications are investigated by hardware experiments. Distinct CAN bit rates, communication cables, and networks are used to test effects of EMI on CAN bus. Waveforms of CAN data frames in EMI environment are observed and analyzed for figuring out details of effects. Experiments show that the EMI pulses frequently encountered in automobile and off-road machinery can cause the reduction of bit rates and errors in high-speed CAN communications. Replacing traditional unshielded parallel communication cables with shielded communication cables is proved to be an effective method of …

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Workshop - Building Reflective Team Skills With A T-Group, Ray Luechtefeld, Steve Eugene Watkins Oct 2007

Workshop - Building Reflective Team Skills With A T-Group, Ray Luechtefeld, Steve Eugene Watkins

Engineering Management and Systems Engineering Faculty Research & Creative Works

ABET criteria require that engineering graduates have the ability to "function on multidisciplinary teams" and "communicate effectively". An important component of these skills is the ability to reflect on one's personal actions and the dynamics occurring within the group. This workshop is intended to provide participants with a practical exercise that can help students become more self-reflective and aware of group dynamics, while demonstrating the use of the "virtual facilitator" system to improve group dialogue. The workshop will engage the participants in a self- directed learning exercise modeled after T-Groups. This exercise will help participants: 1) Become aware of their …

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Expert System For Team Facilitation Using Observational Learning, Ray Luechtefeld, R. K. Singh, Steve Eugene Watkins Oct 2007

Expert System For Team Facilitation Using Observational Learning, Ray Luechtefeld, R. K. Singh, Steve Eugene Watkins

Engineering Management and Systems Engineering Faculty Research & Creative Works

While ABET criteria require that engineering graduates be able to "function on multidisciplinary teams" and "communicate effectively", the need for effective team skills goes far deeper. One solution is the use of a computationally intelligent "virtual facilitator" that contains a subset of the expert knowledge of a skilled facilitator. The "virtual facilitator" models behaviors of an expert facilitator to engineering student teams as they are working together. Albert Bandura's theory of observational learning suggests that skills can be developed through observation of expert "others" engaged in practice. Preliminary research indicates that students can increase beneficial team behaviors (such as inquiry) …

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Energy-Efficient Hybrid Key Management Protocol For Wireless Sensor Networks, Timothy J. Landstra, Maciej Jan Zawodniok, Jagannathan Sarangapani Oct 2007

Energy-Efficient Hybrid Key Management Protocol For Wireless Sensor Networks, Timothy J. Landstra, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we propose a subnetwork key management strategy in which the heterogeneous security requirements of a wireless sensor network are considered to provide differing levels of security with minimum communication overhead. Additionally, it allows the dynamic creation of high security subnetworks within the wireless sensor network and provides subnetworks with a mechanism for dynamically creating a secure key using a novel and dynamic group key management protocol. The proposed energy-efficient protocol utilizes a combination of pre-deployed group keys and initial trustworthiness of nodes to create a level of trust between neighbors in the network. This trust is later …

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Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes Oct 2007

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the …

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Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes Oct 2007

Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.

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Case Study: Applying A Regional Cge Model For Estimation Of Indirect Economic Losses Due To Damaged Highway Bridges, Chakkaphan Tirasirichai, David Lee Enke Oct 2007

Case Study: Applying A Regional Cge Model For Estimation Of Indirect Economic Losses Due To Damaged Highway Bridges, Chakkaphan Tirasirichai, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Destruction from natural and man-made disasters can result in extensive damage to the affected area's infrastructure. While the destruction results in costs that are necessary to restore the physical destruction and repair of existing infrastructure, a wider economic impact is often indirectly measured and felt. Policymakers generally focus only on losses that are directly caused by the destruction, such as the replacement of roads and bridges, yet tend to overlook the consequences from indirect economic losses. This study proposes a framework to estimate the indirect economic loss due to damaged bridges within the highway system of a major metropolitan area. …

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Distributed Energy Resources: Issues And Challenges, Badrul H. Chowdhury, Chung-Li Tseng Aug 2007

Distributed Energy Resources: Issues And Challenges, Badrul H. Chowdhury, Chung-Li Tseng

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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State-Of-The-Art And Evolution In Public Data Sets And Competitions For System Identification, Time Series Prediction And Pattern Recognition, Joos Vandewalle, Johan Suykens, Bart De Moor, Amaury Lendasse Aug 2007

State-Of-The-Art And Evolution In Public Data Sets And Competitions For System Identification, Time Series Prediction And Pattern Recognition, Joos Vandewalle, Johan Suykens, Bart De Moor, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

It is the Aim of Reproducible Research to Provide Mechanisms for Objective Comparison of Methods, Algorithms, Software and Procedures in Various Research Topics. in This Paper, We Discuss the Role of Data Sets, Benchmarks and Competitions in the Fields of System Identification, Time Series Prediction, Classification, and Pattern Recognition in View of Creating an Environment of Reproducible Research. Important Elements Are the Data Sets, their Origin, and the Comparison Measures that Will Be Used to Rank the Performance of the Methods. the Issues Are Discussed, a Comparison is Made and Recommendations Are Given. © 2007 IEEE.

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Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Jul 2007

Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …

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Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani Jul 2007

Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for general multi-input and multi- output affine unknown nonlinear discrete-time systems in the presence of bounded disturbances. Adaptive critic designs consist of two entities, an action network that produces optimal solution and a critic that evaluates the performance of the action network. The critic is termed adaptive as it adapts itself to output the optimal cost-to-go function and the action network is adapted simultaneously based on the information from the critic. In our online learning method, one NN is designated as the …

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Encouraging Lifelong Learning For Engineering Management Undergraduates, Susan L. Murray, Stephen A. Raper Jun 2007

Encouraging Lifelong Learning For Engineering Management Undergraduates, Susan L. Murray, Stephen A. Raper

Engineering Management and Systems Engineering Faculty Research & Creative Works

The current ABET guidelines place an emphasis on life-long learning for our undergraduate students. What is life-long learning? How can we encourage students to consider global issues, current events, or even anything "that isn't going to be on the next test"? In this paper we present survey results evaluating habits of undergraduate students entering an engineering management program and seniors related to life-long learning including attending professional society meetings, reading trade publications, reading business related books, and other learning outside of the classroom activities. This paper also presents a two semester effort to increase life-long learning activities among undergraduate engineering …

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Engineering Management And Industrial Engineering: Similarities And Differences, Cassandra C. Elrod, Ashley Rasnic, William Daughton Jun 2007

Engineering Management And Industrial Engineering: Similarities And Differences, Cassandra C. Elrod, Ashley Rasnic, William Daughton

Business and Information Technology Faculty Research & Creative Works

Engineering Management is a broad and diverse field of engineering, thereby making it difficult to define exactly what the degree encompasses. At the same time, the somewhat related degree of Industrial Engineering is better understood. Some universities offer a Bachelor of Science degree in Engineering Management with an emphasis in Industrial Engineering, while others offer a Bachelor of Science degree in Industrial Engineering with an emphasis in Engineering Management. In today's world of competitive academia, many wonder if these degree fields are similar enough to be used interchangeably or if there is a distinct difference separating the two degrees, making …

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Short-Term Stock Market Timing Prediction Under Reinforcement Learning Schemes, Hailin Li, Cihan H. Dagli, David Lee Enke Apr 2007

Short-Term Stock Market Timing Prediction Under Reinforcement Learning Schemes, Hailin Li, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

There are fundamental difficulties when only using a supervised learning philosophy to predict financial stock short-term movements. We present a reinforcement-oriented forecasting framework in which the solution is converted from a typical error-based learning approach to a goal-directed match-based learning method. The real market timing ability in forecasting is addressed as well as traditional goodness-of-fit-based criteria. We develop two applicable hybrid prediction systems by adopting actor-only and actor-critic reinforcement learning, respectively, and compare them to both a supervised-only model and a classical random walk benchmark in forecasting three daily-based stock indices series within a 21-year learning and testing period. The …

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Systems Architecting Heuristics For Systems Engineering Management And Embedded Systems Engineering, Mark S. Anderson, Cihan H. Dagli Apr 2007

Systems Architecting Heuristics For Systems Engineering Management And Embedded Systems Engineering, Mark S. Anderson, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Software development for United States Air Force (USAF) weapon systems is a "right here, right now" prize captured by those who can rapidly develop requirements and deliver a quality product. The Air Logistics Centers (ALCs) located at Tinker Air Force Base (AFB), Oklahoma, Warner-Robins AFB, Georgia, and Hill AFB, Utah develop requirements utilizing 3400 funding to capture this prize. The ALCs identify these requirements as corrective maintenance or perfective and adaptive maintenance. Colleen A. Calimer and John L. BeVier introduce the concept of the "Embedded Systems Engineer" in their 2004 INCOSE paper "Embedded Systems Engineering: Managing Systems Complexity, Change, and …

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System Evaluation And Description Using Abstract Relation Types (Art), Joseph J. Simpson, Ann K. Miller, Cihan H. Dagli Apr 2007

System Evaluation And Description Using Abstract Relation Types (Art), Joseph J. Simpson, Ann K. Miller, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Two abstract relation types (ART) are developed to represent, describe and establish a computational framework for a system. An abstract relation type is closely related to and builds upon two fundamental ideas. The first idea is the binary relation and structural modeling techniques developed by John N. Warfield. The second idea is the concept of abstract data types. These two ideas are combined to create an abstract relation type that provides a structured representation and computational method for systems and system components. The complete system description approach is based on six abstract relation types: context, concept, functions, requirements, architecture, and …

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An Evaluation Of Mahalanobis-Taguchi System And Neural Network For Multivariate Pattern Recognition, Jungeui Hong, Rajesh Jugulum, Kioumars Paryani, K. M. Ragsdell, Genichi Taguchi, Elizabeth A. Cudney Jan 2007

An Evaluation Of Mahalanobis-Taguchi System And Neural Network For Multivariate Pattern Recognition, Jungeui Hong, Rajesh Jugulum, Kioumars Paryani, K. M. Ragsdell, Genichi Taguchi, Elizabeth A. Cudney

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.

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Understanding Behavior Of System Of Systems Through Computational Intelligence Techniques, Nil H. Kilicay, Cihan H. Dagli Jan 2007

Understanding Behavior Of System Of Systems Through Computational Intelligence Techniques, Nil H. Kilicay, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The world is facing an increasing level of systems integration leading towards systems of systems (SoS) that adapt to changing environmental conditions. The number of connections between components, the diversity of the components and the way the components are organized can lead to different emergent system behavior. Therefore, the need to focus on overall system behavior is becoming an unavoidable issue. The problem is to develop methodologies appropriate for better understanding behavior of system of systems before the design and implementation phase. This paper focuses on computational intelligence techniques used for analysis of complex adaptive systems with the aim of …

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Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow Jan 2007

Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow

Engineering Management and Systems Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly …

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Identifying Useful Variables For Vehicle Braking Using The Adjoint Matrix Approach To The Mahalanobis-Taguchi System, Elizabeth A. Cudney, Kenneth M. Ragsdell, Kioumars Paryani Jan 2007

Identifying Useful Variables For Vehicle Braking Using The Adjoint Matrix Approach To The Mahalanobis-Taguchi System, Elizabeth A. Cudney, Kenneth M. Ragsdell, Kioumars Paryani

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Mahalanobis Taguchi System (MTS) is a diagnosis and forecasting method for multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. MTS is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set …

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Effective Use Of Process Capability Indices For Supplier Management, Elizabeth A. Cudney, David Drain Jan 2007

Effective Use Of Process Capability Indices For Supplier Management, Elizabeth A. Cudney, David Drain

Engineering Management and Systems Engineering Faculty Research & Creative Works

Process capability indices were originally invented to enable an organization to make economically sound decisions for process management. Process capability is a comparison of the voice of the process with the voice of the customer. Current practice is to use Cp and Cpk regardless of the validity of the underlying assumptions necessary for their use. Even if all necessary assumptions are satisfied, important problems can be missed if these indices are the sole process evaluation examined. Customer-supplier axioms are introduced to motivate more useful process evaluations and foster long-term harmonious relationships. This paper explores the alternative capability indices Cpm, Cpmk, …

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Technology And Competence Alignment To The Roadmap, Mihir M. Gokhale, Donald D. Myers Jan 2007

Technology And Competence Alignment To The Roadmap, Mihir M. Gokhale, Donald D. Myers

Engineering Management and Systems Engineering Faculty Research & Creative Works

Roadmaps serve as a useful graphical tool to integrate strategic objectives, technology-assessment, technology-road mapping and product road mapping against an axis of time. Much research has been done related to linking specific technologies with the product roadmap. It is equally important to understand how the sourcing of this technology can be done. This leads to the discussion of competence development to meet the technology gap. the paper describes the alignment of this technology and competence with the overall roadmap. © 2008 IEEE.

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A Comparison Of Techniques To Forecast Consumer Satisfaction For Vehicle Ride, Elizabeth A. Cudney, David Drain, Kenneth M. Ragsdell, Kioumars Paryani Jan 2007

A Comparison Of Techniques To Forecast Consumer Satisfaction For Vehicle Ride, Elizabeth A. Cudney, David Drain, Kenneth M. Ragsdell, Kioumars Paryani

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a comparison of methods for the identification of a reduced set of useful variables using a multidimensional system. the Mahalanobis-Taguchi System and a standard statistical technique are used reduce the dimensionality of vehicle ride based on consumer satisfaction ratings. the Mahalanobis-Taguchi System and cluster analysis are applied to vehicle ride. the research considers 67 vehicle data sets for the 6 vehicle ride parameters. This paper applies the Mahalanobis-Taguchi System to forecast consumer satisfaction and provides a comparison of results with those obtained from a standard statistical approach to the problem. Copyright © 2007 SAE International.

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Performance Prediction Based Resource Selection In Grid Environments, Peggy Lindner, Edgar Gabriel, Michael M. Resch Jan 2007

Performance Prediction Based Resource Selection In Grid Environments, Peggy Lindner, Edgar Gabriel, Michael M. Resch

Engineering Management and Systems Engineering Faculty Research & Creative Works

Deploying Grid technologies by distributing an application over several machines has been widely used for scientific simulations, which have large requirements for computational resources. The Grid Configuration Manager (GCM) is a tool developed to ease the management of scientific applications in distributed environments and to hide some of the complexities of Grids from the end-user. In this paper we present an extension to the Grid Configuration Manager in order to incorporate a performance-based resource brokering mechanism. Given a pool of machines and a trace file containing information about the runtime characteristics of the according application, GCM is able to select …

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The Development Of Hybrid Intelligent Systems For Technical Analysis Based Equivolume Charting, Thira Chavarnakul Jan 2007

The Development Of Hybrid Intelligent Systems For Technical Analysis Based Equivolume Charting, Thira Chavarnakul

Doctoral Dissertations

"This dissertation proposes the development of a hybrid intelligent system applied to technical analysis based equivolume charting for stock trading. A Neuro-Fuzzy based Genetic Algorithms (NF-GA) system of the Volume Adjusted Moving Average (VAMA) membership functions is introduced to evaluate the effectiveness of using a hybrid intelligent system that integrates neural networks, fuzzy logic, and genetic algorithms techniques for increasing the efficiency of technical analysis based equivolume charting for trading stocks"--Introduction, page 1.

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Quality Loss Function - Common Methodology For Nominal-The-Best, Smaller-The-Better, And Larger-The-Better Cases, Naresh Kumar Sharma, Kenneth M. Ragsdell Jan 2007

Quality Loss Function - Common Methodology For Nominal-The-Best, Smaller-The-Better, And Larger-The-Better Cases, Naresh Kumar Sharma, Kenneth M. Ragsdell

Engineering Management and Systems Engineering Faculty Research & Creative Works

The quality loss function developed by Dr. Genichi Taguchi considers three cases including nominal-the-best, smaller-the-better, and larger-the-better. the methodology used to deal with the larger-the-better case is slightly different from that for the smaller-the-better and nominal-the-better cases. This paper attempts to bring about similarity among the three cases by introducing a term called the "target-mean ratio" and proposing a common formula for all three cases. the "target-mean ratio" can take different values to represent all three cases to bring about consistency and simplify the model. Also, it eliminates the assumption of target performance at infinite level and brings the model …

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Spatial Diversity In Signal Strength Based Wlan Location Determination Systems, Anil Ramachandran, Jagannathan Sarangapani Jan 2007

Spatial Diversity In Signal Strength Based Wlan Location Determination Systems, Anil Ramachandran, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Literature indicates that spatial diversity can be utilized to compensate channel uncertainties such as multipath fading. Therefore, in this paper, spatial diversity is exploited for locating stationary and mobile objects in the indoor environment. First, space diversity technique is introduced for small scale motion and temporal variation compensation of received signal strength and it is demonstrated analytically that it enhances location accuracy. Small scale motion refers to movements of the transmitter and/or the receiver of the order of sub-wavelengths while temporal effects refer to environmental variations with time. A novel metric is introduced for selection combining in order to improve …

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An Online Approximator-Based Fault Detection Framework For Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani Jan 2007

An Online Approximator-Based Fault Detection Framework For Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a fault detection scheme is developed for nonlinear discrete time systems. The changes in the system dynamics due to incipient failures are modeled as a nonlinear function of state and input variables while the time profile of the failures is assumed to be exponentially developing. The fault is detected by monitoring the system and is approximated by using online approximators. A stable adaptation law in discrete-time is developed in order to characterize the faults. The robustness of the diagnosis scheme is shown by extensive mathematical analysis and simulation results.

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