Operations Research, Systems Engineering and Industrial Engineering Commons^™

Beyond Passswords: Usage And Policy Transformation, Alan S. Alsop

Theses and Dissertations

The purpose of this research is to determine whether the transition to a two-factor authentication system is more secure than a system that relied only on what users “know” for authentication. While we found that factors that made passwords inherently vulnerable did not transfer to the PIN portion of a two-factor authentication system, we did find significant problems relating to usability, worker productivity, and the loss and theft of smart cards. The new authentication method has disrupted our ability to stay connected to ongoing mission issues, forced some installations to cut off remote access for their users and in one …

Improved Hyperspectral Image Testing Using Synthetic Imagery And Factorial Designed Experiments, Joseph P. Bellucci

Theses and Dissertations

The goal of any remote sensing system is to gather data about the geography it is imaging. In order to gain knowledge of the earth's landscape, post-processing algorithms are developed to extract information from the collected data. The algorithms can be intended to classify the various ground covers in a scene, identify specific targets of interest, or detect anomalies in an image. After the design of an algorithm comes the difficult task of testing and evaluating its performance. Traditionally, algorithms are tested using sets of extensively ground truthed test images. However, the lack of well characterized test data sets and …

Towards The Development Of A Defensive Cyber Damage And Mission Impact Methodology, Larry W. Fortson Jr.

Theses and Dissertations

The purpose of this research is to establish a conceptual methodological framework that will facilitate effective cyber damage and mission impact assessment and reporting following a cyber-based information incidents. Joint and service guidance requires mission impact reporting, but current efforts to implement such reporting have proven ineffective. This research seeks to understand the impediments existing in the current implementation and to propose an improved methodology. The research employed a hybrid historical analysis and case study methodology for data collection through extensive literature review, examination of existing case study research and interviews with Air Force members and civilian personnel employed as …

Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …

Recommendations For A Standardized Program Management Office (Pmo) Time Compliance Network Order (Tcno) Patching Process, Michael Czumak Iii

Theses and Dissertations

Network security is a paramount concern for organizations utilizing computer technology, and the Air Force is no exception. Network software vulnerability patching is a critical determinant of network security. The Air Force deploys these patches as Time Compliance Network Orders (TCNOs), which together with associated processes and enforced timelines ensure network compliance. While the majority of the network assets affected by this process are Air Force owned and operated, a large number are maintained by external entities known as Program Management Offices (PMOs). Although these externally controlled systems provide a service to the Air Force and reside on its network, …

Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham

Research Collection School Of Computing and Information Systems

My research goal is to build large-scale intelligent systems (both single- and multi-agent) that reason with uncertainty in complex, real-world environments. I foresee an integration of such systems in many critical facets of human life ranging from intelligent assistants in hospitals to offices, from rescue agents in large scale disaster response to sensor agents tracking weather phenomena in earth observing sensor webs, and others. In my thesis, I have taken steps towards achieving this goal in the context of systems that operate in partially observable domains that also have transitional (non-deterministic outcomes to actions) uncertainty. Given this uncertainty, Partially Observable …

Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen

Research Collection School Of Computing and Information Systems

A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates …

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 …

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, …

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.

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 …

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.

Route Aware Predictive Congestion Control Protocol For Wireless Sensor Networks, Carl Larsen, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Congestion in wireless sensor networks (WSN) may lead to packet losses or delayed delivery of important information rendering the WSN-based monitoring or control system useless. In this paper a routing-aware predictive congestion control (RPCC) yet decentralized scheme for WSN is presented that uses a combination of a hop by hop congestion control mechanism to maintain desired level of buffer occupancy, and a dynamic routing scheme that works in concert with the congestion control mechanism to forward the packets through less congested nodes. The proposed adaptive approach restricts the incoming traffic thus preventing buffer overflow while maintaining the rate through an …

Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents two 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 signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.

Adaptive Power Control Protocol With Hardware Implementation For Wireless Sensor And Rfid Reader Networks, Kainan Cha, Jagannathan Sarangapani, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

The development and deployment of radio frequency identification (RFID) systems render a novel distributed sensor network which enhances visibility into manufacturing processes. In RFID systems, the detection range and read rates will suffer from interference among high-power reading devices. This problem grows severely and degrades system performance in dense RFID networks. Consequently, medium access protocols (MAC) protocols are needed for such networks to assess and provide access to the channel so that tags can be read accurately. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a …

Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, 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. …

Neural Network Control Of Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as opposed …

Online Reinforcement Learning Control Of Unknown Nonaffine Nonlinear Discrete Time Systems, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel neural network (NN) based online reinforcement learning controller is designed for nonaffine nonlinear discrete-time systems with bounded disturbances. The nonaffine systems are represented by nonlinear auto regressive moving average with exogenous input (NARMAX) model with unknown nonlinear functions. An equivalent affine-like representation for the tracking error dynamics is developed first from the original nonaffine system. Subsequently, a reinforcement learning-based neural network (NN) controller is proposed for the affine-like nonlinear error dynamic system. The control scheme consists of two NNs. One NN is designated as the critic, which approximates a predefined long-term cost function, whereas an …

Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate …

Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, 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 affine nonlinear discrete-time systems with applications to nanomanipulation. In the online NN reinforcement learning method, one NN is designated as the critic NN, which approximates the long-term cost function by assuming that the states of the nonlinear systems is available for measurement. An action NN is employed to derive an optimal control signal to track a desired system trajectory while minimizing the cost function. Online updating weight tuning schemes for these two NNs are also derived. By using the Lyapunov approach, …

Multi-Phase Flow Analysis In Oil And Gas Engineering Systems And Its Modelling, Orlando F. Ayala, Luis F. Ayala, Orlando M. Ayala

Engineering Technology Faculty Publications

[Introduction] Two-phase flow is very common in industrial processes and its applications were already in use in ages as remote as the era of Archimedes. At the present time, many industrial processes rely on multi-phase phenomena for the transport of energy and mass or for material processing. During the last century, the nuclear, chemical and petroleum industries propelled intense research activity in the area. Their efforts have been aimed at the demystification of the mechanisms taking place during this complex flow situation.

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The major objectives will lead to a creation of framework that combines all the strengths of AMUSE’s complicated calculations, well-established commercial system process package and ISOPro’s flexible parameter optimization modules. Development of the process simulation code can be done using the solvent extraction process at Argonne National Laboratory in collaboration with the research team from Mechanical Engineering Department at UNLV.

Research accomplishments:

• Integrated the ASPEN-Plus process model with the ISOPro system engineering modeling package, developed by the UNLV team.
• Tested the simplified system process integration using the ISOPro package.
• Generated complete version of the ISOPro package user manual and tutorial. …

Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman

Research Collection School Of Computing and Information Systems

We introduce a weakening of standard gametheoretic δ-dominance conditions, called dominance, which enables more aggressive pruning of candidate strategies at the cost of solution accuracy. Equilibria of a game obtained by eliminating a δ-dominated strategy are guaranteed to be approximate equilibria of the original game, with degree of approximation bounded by the dominance parameter. We can apply elimination of δ-dominated strategies iteratively, but the for which a strategy may be eliminated depends on prior eliminations. We discuss implications of this order independence, and propose greedy heuristics for determining a sequence of eliminations to reduce the game as far as possible …

Towards Efficient Computation Of Quality Bounded Solutions In Pomdps: Expected Value Approximation And Dynamic Disjunctive Beliefs, Pradeep Reddy Varakantham, Rajiv Maheswaran, Tapana Gupta, Milind Tambe

Research Collection School Of Computing and Information Systems

While POMDPs (partially observable markov decision problems) are a popular computational model with wide-ranging applications, the computational cost for optimal policy generation is prohibitive. Researchers are investigating ever-more efficient algorithms, yet many applications demand such algorithms bound any loss in policy quality when chasing efficiency. To address this challenge, we present two new techniques. The first approximates in the value space to obtain solutions efficiently for a pre-specified error bound. Unlike existing techniques, our technique guarantees the resulting policy will meet this bound. Furthermore, it does not require costly computations to determine the quality loss of the policy. Our second …

Geometric Programming As A General Method For Phase And Reaction Equilibrium Calculations, Godwill Mrema

Tanzania Journal of Engineering and Technology (TJET)

Geometric programming has been used to calculate a large mtmber ofdifferent ideal and non-ideal equilibria, including, for reaction and For non-ideal Systems the primal program is solved a number Of times With the nan-ideal terms fixed each time. After each primal solution, the nan-ideal terms are "'hdated using the corresponding dun! solution. This iteration generally converges. We have included one counter-example, where the failure is caused by the equation Of state, which Cannot giu• correct roots.

Windmill Documentary, Timothy David Stoltenburg

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.

Correlation Of Numerical Ability And Quality Technician Best Performers In Manufacturing Quality Control Applications, Charles Wesley Shelton

All-Inclusive List of Electronic Theses and Dissertations

The occupation of Quality Technician has many duties requiring numerical operations. Business and industry place considerable emphasis on numerical ability when evaluating the performance of a Quality Technician. In this study, the numerical ability and performance classification of Quality Technicians were analyzed using a correlation analysis. lll A single case study was used to investigate this relationship. A modified Delphi Method was used to determine characteristics of a Quality Technician. Quality Technicians were evaluated by their direct supervisor and completed a standardized numerical ability test. The evaluations by the supervisor were used to classify each technician based on their performance. …

Finding A Length-Constrained Maximum-Sum Or Maximum-Density Subtree And Its Application To Logistics, Hoong Chuin Lau, Trung Hieu Ngo, Bao Nguyen Nguyen

Research Collection School Of Computing and Information Systems

We study the problem of finding a length-constrained maximum-density path in a tree with weight and length on each edge. This problem was proposed in [R.R. Lin, W.H. Kuo, K.M. Chao, Finding a length-constrained maximum-density path in a tree, Journal of Combinatorial Optimization 9 (2005) 147–156] and solved in O(nU) time when the edge lengths are positive integers, where n is the number of nodes in the tree and U is the length upper bound of the path. We present an algorithm that runs in O(nlog2n) time for the generalized case when the edge lengths are positive real numbers, which …

Supply Chain Information Sharing In A Macro Prediction Market, Zhiling Guo, Fang Fang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

This paper aims to address supply chain partners' incentives for information sharing from an information systems design perspective. Specifically, we consider a supply chain characterized by N geographically distributed retailers who order a homogeneous product from one manufacturer. Each retailer's demand risk consists of two parts: a systematic risk part that affects all retailers and an idiosyncratic risk part that only has a local effect. We propose a macro prediction market to effectively elicit and aggregate useful information about systematic demand risk. We show that such information can be used to achieve accurate demand forecast sharing and better channel coordination …

Cosign: A Parallel Algorithm For Coordinated Traffic Signal Control, Shih-Fen Cheng, Marina A. Epelman, Robert L. Smith

Research Collection School Of Computing and Information Systems

The problem of finding optimal coordinated signal timing plans for a large number of traffic signals is a challenging problem because of the exponential growth in the number of joint timing plans that need to be explored as the network size grows. In this paper, the game-theoretic paradigm of fictitious play to iteratively search for a coordinated signal timing plan is employed, which improves a system-wide performance criterion for a traffic network. The algorithm is robustly scalable to realistic-size networks modeled with high-fidelity simulations. Results of a case study for the city of Troy, MI, where there are 75 signalized …