Operations Research, Systems Engineering and Industrial Engineering Commons^™

Analysis Of Autonomous Unmanned Aerial Systems Based On Operational Scenarios Using Value Modelling, Akash Vidyadharan, Robert Philpott Iii, Benjamin J. Kwasa, Christina L. Bloebaum

Engineering Management and Systems Engineering Faculty Research & Creative Works

In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, …

Underwater Object Tracking Strategy Via Multi-Scale Retinex And Partial Least Squares Analysis, Baochen Hao, Yue Zhu, Ruijie Chang, Rui Nian, Bo He, Lujie Cao, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Object Tracking is One of the Most Essential and Fundamental Tasks in Ocean Investigations Recent Years. in This Paper, We Try to Capture Multi-Scale Retinex (MSR) Model as Well as the Partial Least Square (Pls) Analysis for Underwater Object Tracking. We First Make Use of Multi-Scale Retinex Model to Evolve and Enhance the Partial Color Constancy from the Underwater Video Sequences, Which Could Provide a Versatile Automatic Strategy to Simultaneous Sharpening, Dynamic Range Compression and Color Rendition. the Partial Least Square Analysis is Further Taken to Capture the Trajectories of Underwater Objects by Learning a Set of Underwater Appearance …

Underwater Image Super-Resolution Reconstruction With Local Self-Similarity Analysis And Wavelet Decomposition, Xiaorun Wang, Rui Nian, Bo He, Bing Zheng, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Target Detecting is an Important Technique for the Development of the Ocean Engineering and Exploration Also a Significant Task of the Ocean Detecting. It Plays a Substantial Role Not Only for the Civil Economy but Also for the National Security. the Formation of the Super-Resolution Underwater Image is Significant Topic in Ocean Detecting Field. in Order to Enhance the Visual Quality of Images Obtained by Underwater Imaging Systems, Super Resolution (Sr) Reconstruction is Introduced, Including Single-Frame and Multi-Frame Sr Algorithms. Real-World Images Often Contain Singularities Such as Edges and High-Frequency Textured Regions. as a Result, These Methods Suffer from …

Underwater Image Segmentation With Co-Saliency Detection And Local Statistical Active Contour Model, Yue Zhu, Baochen Hao, Baohua Jiang, Rui Nian, Bo He, Xinmin Ren, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Image Segmentation of Underwater Environment with Inhomogeneous Intensity Turns Out to Be One of the Most Challenging Topics These Years. in This Paper, We Try to Combine Co-Saliency Detection with Local Statistical Active Contour Model Together for Underwater Image Segmentation. the Cluster-Based Algorithm is First Taken for Co-Saliency Detection, Which Makes Salient Region in the Underwater Images Be Highlighted. the Local Statistical Active Contour Model, a Novel Region-Based Level Set Method, is Then Made Full Use of two Segment Underwater Images. It is Shown in Our Simulation Experiment that Our Proposed Scheme Could Achieve Great Segmentation Performance in Both Efficiency …

A Depth Estimation Model From A Single Underwater Image With Non-Uniform Illumination Correction, Shichang Zhang, Xiaofei Gong, Rui Nian, Bo He, Yaomin Wang, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Visual Understanding Tends to Be One of the Most Important Challenges in Ocean Investigations Recent Years. in This Paper, We Make an Attempt to Develop a Depth Estimation Approach from One Single Underwater Image with Non-Uniform Illumination Correction. First, We Try to Remove the Relatively Strong Reflection Layer from the Scene Layer in Those Underwater Images with Non-Uniform Illumination and Rely on the Saturation Detection to Characterize the Local Regions of the Artificial Illumination in Underwater Images for Compensation in Depth Estimation. Then We Try to Implement Underwater Dark Channel Prior and Basically Consider the Blue and Green Color …

Rethinking The Design Of Low-Cost Point-Of-Care Diagnostic Devices, Faith W. Kimani, Samuel M. Mwangi, Benjamin J. Kwasa, Abdi M. Kusow, Benjamin K. Ngugi, Jiahao Chen, Xinyu Liu, Rebecca Cademartiri, Martin M. Thuo

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reducing the global diseases burden requires effective diagnosis and treatment. In the developing world, accurate diagnosis can be the most expensive and time-consuming aspect of health care. Healthcare cost can, however, be reduced by use of affordable rapid diagnostic tests (RDTs). In the developed world, low-cost RDTs are being developed in many research laboratories; however, they are not being equally adopted in the developing countries. This disconnect points to a gap in the design philosophy, where parameterization of design variables ignores the most critical component of the system, the point-of-use stakeholders (e.g., doctors, nurses and patients). Herein, we demonstrated that …

Engineering Cyber Physical Systems: Preface, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Multi-faceted systems of the future will entail complex logic with many levels of reasoning in intricate arrangement. The organization of these systems involves a web of connections and demonstrates self-driven adaptability. They are designed for autonomy and may exhibit emergent behavior that can be visualized.

Complex Adaptive Systems have dynamically changing meta-architectures. Finding an optimal architecture for these systems is a multi-criteria decision making problem often involving many objectives in the order of 20 or more. This creates "Pareto Breakdown" which prevents ordinary multi-objective optimization approaches from effectively searching for an optimal solution; saturating the decision maker with large sets …

Establishing Rules For Self-Organizing Systems-Of-Systems, David M. Curry, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Self-organizing systems-of-systems offer the possibility of autonomously adapting to new circumstances and tasking. This could significantly benefit large endeavors such as smart cities and national defense by increasing the probability that new situations are expediently handled. Complex self-organizing behaviors can be produced by a large set of individual agents all following the same simple set of rules. While biological rule sets have application in achieving human goals, other rules sets may be necessary as these goals are not necessarily mirrored in nature. To this end, a set of system, rather than biologically, inspired rules is introduced and an agent-based model …

Instance Selection Using Genetic Algorithms For An Intelligent Ensemble Trading System, Youngmin Kim, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Instance selection is a way to remove unnecessary data that can adversely affect the prediction model, thereby selecting representative and relevant data from the original data set that is expected to improve predictive performance. Instance selection plays an important role in improving the scalability of data mining algorithms and has also proven to be successful over a wide range of classification problems. However, instance selection using an evolutionary approach, as proposed in this study, is different from previous methods that have focused on improving accuracy performance in the stock market (i.e., Up or Down forecast). In fact, we propose a …

Time Series Classification Using Deep Learning For Process Planning: A Case From The Process Industry, Nijat Mehdiyev, Johannes Lahann, Andreas Emrich, David Lee Enke, Peter Fettke, Peter Loos

Engineering Management and Systems Engineering Faculty Research & Creative Works

Multivariate time series classification has been broadly applied in diverse domains over the past few decades. However, before applying the classification algorithms, the vast majority of current studies extract hand-engineered features that are assumed to detect local patterns in the time series. Therefore, the efficiency and precision of these classification approaches are heavily dependent on the quality of variables defined by domain experts. Recent improvements in the deep learning domain offer opportunities to avoid such an intensive hand-crafted feature engineering which is particularly important for managing the processes based on time-series data obtained from various sensor networks. In our paper, …

Loading Time Flexibility In Cross-Docking Systems, Dincer Konur, Mihalis M. Golias

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this study, we investigate truck-to-door assignment problem for loading outgoing trucks in a cross-docking system with flexible handling times. Specifically, a truck's loading time depends on the number of workers assigned to the outbound door, where the truck is being loaded. An optimization problem is formulated to jointly determine the number of workers and the trucks to be loaded at each door. The resulting problem is a nonlinear integer programming model. Due to the complexity of this model, two evolutionary heuristic methods are proposed for solution. First heuristic method is based on truck assignments while the second heuristic is …

A Low-Dimensional Vector Representation For Words Using An Extreme Learning Machine, Paula Lauren, Guangzhi Qu, Guang Bin Huang, Paul Watta, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Word Embeddings Are a Low-Dimensional Vector Representation of Words that Incorporates Context. Two Popular Methods Are Word2vec and Global Vectors (Glove). Word2vec is a Single-Hidden Layer Feedforward Neural Network (Slfn) that Has an Auto-Encoder Influence for Computing a Word Context Matrix using Backpropagation for Training. Glove Computes the Word Context Matrix First Then Performs Matrix Factorization on the Matrix to Arrive at Word Embeddings. Backpropagation is a Typical Training Method for SLFN's, which is Time Consuming and Requires Iterative Tuning. Extreme Learning Machines (Elm) Have the Universal Approximation Capability of SLFN's, based on a Randomly Generated Hidden Layer Weight Matrix …

Brute-Force Missing Data Extreme Learning Machine For Predicting Huntington's Disease, Anton Akusok, Emil Eirola, Kaj Mikael Björk, Yoan Miche, Hans Johnson, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Paper Presents a Novel Procedure to Train Extreme Learning Machine Models on Datasets with Missing Values. in Effect, a Separate Model is Learned to Classify Every Sample in the Test Set, However, this is Accomplished in an Efficient Manner Which Does Not Require Accessing the Training Data Repeatedly. Instead, a Sparse Structure is Imposed on the Input Layer Weights, Which Enables Calculating the Necessary Statistics in the Training Phase. an application to Predicting the Progression of Huntington's Disease from Brain Scans is Presented. Experimental Comparisons Show Promising Results Equivalent to the State of the Art in Machine Learning with …

Using The Voice Of The Student To Evaluate Learning Management Systems, Elizabeth A. Cudney, Susan L. Murray, Brittany Groner, Katie M. Kaczmarek, Bonnie Wilt, Kamaria Blaney, Julie Phelps

Engineering Management and Systems Engineering Faculty Research & Creative Works

A learning management system is an educational tool employed in higher education to organize, document, track, report, and deliver courses. Selecting the appropriate learning management system is a critical decision for a university. This study explores the usability of two leading systems, Blackboard and Canvas, from the students’ perspective. The goal is to gather and analyze user preferences in order to select an appropriate learning management system. Data was collected through surveys of student’s experience with the two learning management systems. The survey evaluated the ease of the following tasks: finding course documents, viewing grades, ease of navigation, intuitiveness, and …

Work Zone Simulator Analysis: Driver Performance And Acceptance Of Missouri Alternate Lane Shift Configurations, Suzanna Long, Ruwen Qin, Dincer Konur, Ming-Chuan Leu, S. Moradpour, S. Thind, H. Nadathur

Engineering Management and Systems Engineering Faculty Research & Creative Works

The objective of this project is to evaluate MoDOT’s alternate lane shift sign configuration for work zones. The single signproposed by MoDOT provides the traveler with enough information to let them know that all lanes are available to shift around thework zone, whereas the MUTCD signs require drivers to see two signs. This research simulation project evaluates the drivers’ laneshifting performance and acceptance of the alternate lane shift sign proposed by MoDOT to be used on work zones as compared tothe MUTCD lane shift signs. Based on the study results, no difference was observed between MUTCD lane shift sign andMoDOT …

Trends In Engineering Management Education From 2011–2015, William Daughton

Engineering Management and Systems Engineering Faculty Research & Creative Works

The American Society for Engineering Education provides comprehensive data on enrollment and graduation rates for all engineering fields at the Bachelor's, Master's, and PhD levels. In addition, data are provided on the demographics of the various fields. This information, coupled with Accreditation Board for Engineering and Technology data, presents an opportunity to explore the trends in higher education in Engineering Management in the last five years. Contrasts to earlier times and implications for the future are presented as a result of the analysis of these trends.

A New Reinforcement Learning Algorithm With Fixed Exploration For Semi-Markov Decision Processes, Angelo Michael Encapera

Masters Theses

"Artificial intelligence or machine learning techniques are currently being widely applied for solving problems within the field of data analytics. This work presents and demonstrates the use of a new machine learning algorithm for solving semi-Markov decision processes (SMDPs). SMDPs are encountered in the domain of Reinforcement Learning to solve control problems in discrete-event systems. The new algorithm developed here is called iSMART, an acronym for imaging Semi-Markov Average Reward Technique. The algorithm uses a constant exploration rate, unlike its precursor R-SMART, which required exploration decay. The major difference between R-SMART and iSMART is that the latter uses, in addition …

Micro-Grid Implementation Of A Rooftop Photovoltaic System, Pranav Nitin Godse

Masters Theses

"In recent years, solar power has been a popular form of renewable energy. This research conducts a cost analysis in implementing a rooftop photovoltaic system as part of an energy management schema for a university campus. The proposed system would be installed on the roof of one of the largest buildings on campus at Missouri University of Science and Technology, Toomey Hall; the objective function of the research involves reducing dependence on conventional energy sources on campus. Toomey Hall houses the Department of Mechanical and Aerospace Engineering (MAE) and is the largest academic unit on campus. Considering the vast expanse …

Data Analysis Of Lane Merge And Lane Shift Sign Configurations In A Freeway Workzone, Satwinder Singh Thind

Masters Theses

"In this study, driver responses to alternative lane shift and lane merge signs are analyzed and compared using a driving simulation system. In particular, driver responses to the lane merge signs proposed by the Missouri Department of Transportation (MoDOT) are compared to the current lane merge signs recommended by the Manual on Uniform Traffic Control Devices (MUTCD) and driver responses to the lane shift signs proposed by MoDOT are compared to current lane shift signs recommended by MUTCD. The driving simulation system is composed of a driving simulator and a PC with data recording program such that the position coordinates, …

Shortest-Distance And Minimum-Cost Self-Charging Path Problems: Formulations And Application, Marc Monroe Teeter

Masters Theses

"In this study, self-charging paths for an electric bus are analyzed. Wireless-power-transfer technologies, when integrated on a road network, enable dynamic charging of electric vehicles. Roads implemented with a wireless-power-transfer technology are referred to as electric-roads in this study. Electric vehicles traversing on electric-roads, therefore, can be dynamically charged. This can further eliminate the need for static charging, i.e., the electric vehicle will not need to stop for charging.

This thesis analyzes the design of transit routes for an electric-bus so that the electric-bus is charged by only electric-roads. Specifically, the focus is on designing a path, which passes through …

Multi-Objective Combinatorial Optimization Problems In Transportation And Defense Systems, Hadi Farhangi

Doctoral Dissertations

"Multi-objective Optimization problems arise in many applications; hence, solving them efficiently is important for decision makers. A common procedure to solve such problems is to generate the exact set of Pareto efficient solutions. However, if the problem is combinatorial, generating the exact set of Pareto efficient solutions can be challenging. This dissertation is dedicated to Multi-objective Combinatorial Optimization problems and their applications in system of systems architecting and railroad track inspection scheduling. In particular, multi-objective system of systems architecting problems with system flexibility and performance improvement funds have been investigated. Efficient solution methods are proposed and evaluated for not only …

A Bounded Actor-Critic Algorithm For Reinforcement Learning, Ryan Jacob Lawhead

Masters Theses

"This thesis presents a new actor-critic algorithm from the domain of reinforcement learning to solve Markov and semi-Markov decision processes (or problems) in the field of airline revenue management (ARM). The ARM problem is one of control optimization in which a decision-maker must accept or reject a customer based on a requested fare. This thesis focuses on the so-called single-leg version of the ARM problem, which can be cast as a semi-Markov decision process (SMDP). Large-scale Markov decision processes (MDPs) and SMDPs suffer from the curses of dimensionality and modeling, making it difficult to create the transition probability matrices (TPMs) …

Programming Problems On Time Scales: Theory And Computation, Rasheed Basheer Al-Salih

Doctoral Dissertations

"In this dissertation, novel formulations for several classes of programming problems are derived and proved using the time scales technique. The new formulations unify the discrete and continuous programming models and extend them to other cases "in between." Moreover, the new formulations yield the exact optimal solution for the programming problems on arbitrary isolated time scales, which solve an important open problem. Throughout this dissertation, six distinct classes of programming problems are presented as follows. First, the primal as well as the dual time scales linear programming models on arbitrary time scales are formulated. Second, separated linear programming primal and …

Attitudes Towards Face-To-Face Meetings In Virtual Engineering Teams: Perceptions From A Survey Of Defense Projects, Lawrence R. Blenke, Abhijit Gosavi, William Daughton

Engineering Management and Systems Engineering Faculty Research & Creative Works

Modes of communication used in virtual defense projects have changed dramatically over the years with tools such as email and video-conferencing dominating face-to-face (FTF) meetings. We conducted a survey at a defense firm with an aim to test current attitudes towards FTF meetings – with respect to significant problems faced, project success, transfer of technical requirements, preference for FTF vis-à-vis virtual meetings, differences between virtual and co-located environments, criticality of various forms of communication, and whether FTF meetings were scheduled as often as desired. Our survey participants, about one hundred in number, were experienced engineers, technicians, and program managers – …

A Practical Approach To Evaluating The Economic And Technical Feasibility Of Led Luminaires, Sean M. Schmidt, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

LED roadway luminaires are currently under consideration for widespread implementation with departments of transportation, facilities managers, and city planners. This research focuses on a case study in Missouri and presents relevant research findings calculated by the authors as part of a project funded by the Missouri Department of Transportation. Although high-pressure sodium (HPS) luminaires have been the standard product for roadway illumination, advances in LED technologies have led many departments of transportation to consider them as viable options along state routes. For this case study, pilot sites were developed across the state of Missouri in sites assessed as moderately busy, …

Cognition-Based Approaches For High-Precision Text Mining, George John Shannon

Doctoral Dissertations

"This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both the breadth and depth of knowledge extracted from text. This research has made contributions in the areas of a cognitive approach to automated concept recognition in.

Cognitive approaches to search, also called concept-based search, have been shown to improve search precision. Given the tremendous amount of electronic text generated in our digital …

Developing Restoration Schemes For A Road Transportation Network In The Event Of A Disaster, Ebin Antony

Masters Theses

"Transportation systems such as rail, road, and waterways are key component of critical infrastructure systems, providing connectivity between other components to enable the production and distribution of goods and services. During large scale disasters such as earth quakes and floods, this connectivity is disrupted, restricting or completely halting the flow of goods and services. To ensure that the connectivity between the different modes of transportation are restored in an aftermath of these disruptions, the interdependence between them and the importance of individual elements to the overall connectivity have to be studied and formulated to develop a system-level restoration plan. This …

Underwater Image Enhancement Strategy With Virtual Retina Model And Image Quality Assessment, Yaomin Wang, Ruijie Chang, Ruinian, Bo He, Xunfei Liu, Jen Hwa Guo, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Image Enhancement is One of the Most Essential and Fundamental Tasks in Ocean Investigations Recent Years. in This Paper, We Made an Attempt to Develop One Adaptive Underwater Image Enhancement Approach with the Help of the Virtual Retina Model and the Image Quality Assessment (IQA). the Virtual Retina Model, Which Yields Comparatively High Correlation with the Human Vision System, is First Taken to Achieve Simultaneous Ambiguity Removing and Detail Enhancing of Single Image Due to the Specific Mechanisms of Different Retinal Sub-Layers. after This, an Adaptive Image Enhancement Strategy is Taken with One Kind of No-Reference Image Quality Assessment …

Underwater Non-Rigid 3d Shape Reconstruction Via Structure From Motion For Fish Ethology Research, Renzheng Che, Xiao Xu, Rui Nian, Bo He, Meimei Chen, Cheng Zhang, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Try to Develop a General Framework of 3d Shape Reconstruction Strategy with Extremely Rare Point Cloud Extracted for Fish Ethology Research. Particle Filter is First Taken to Focus on Fish Trajectory Tracking from Monocular Video Sequence. the Speeded Up Robust Features (Surf) Technique Will Be Adopted to Match the Same Tracking Fish Across the overlapping View Fields with More Stable and Accurate Features. Non-Rigid 3d Shape Reconstruction Will Be Finally Developed with the Help of Expectation Maximization (Em) Model and Linear Dynamical System (LDS). It is Shown from Our Simulation Experiment that the Developed Scheme of …

Underwater Scene Search Scheme Via Similarity Measure And Sparse Representation For Autonomous Underwater Vehicle, Zhiyuan Wang, Yue Geng, Congcong Shi, Rui Nian, Bo He, Tianhong Yan, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Scene Search Turns Out to Be One of the Most Challenging Topics in the Underwater Image Analysis. in This Paper, We Present One Underwater Scene Search Scheme Combined with Similarity Measure and Sparse Representation. the Color Histogram is First Adopted to Classify the Candidate Image Patches for Each Kind of the Underwater Scene. at the Same Time, the Feature Similarity (FSIM) Considers a Full Reference of the Complementary Terms, I.e., the Phase Congruency (Pc) and the Image Gradient Magnitude (Gm), to Reflect and Generate the Similarity Map between the Query Image Patch and the Reference One. Sparse Representation is …