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Real-Time Heuristics And Metaheuristics For Static And Dynamic Weapon Target Assignments, Alexander G. Kline 2018 Air Force Institute of Technology

Real-Time Heuristics And Metaheuristics For Static And Dynamic Weapon Target Assignments, Alexander G. Kline

Theses and Dissertations

The problem of targeting and engaging individual missiles (targets) with an arsenal of interceptors (weapons) is known as the weapon target assignment problem. This problem has been well-researched since the seminal work in 1958. There are two distinct categories of the weapon target assignment problem: static and dynamic. The static weapon target assignment problem considers a single instance in which a known number of incoming missiles is to be engaged with a finite number of interceptors. By contrast, the dynamic weapon target assignment problem considers either follow on engagement(s) should the first engagement(s) fail, a subsequent salvo of incoming missiles, …


Thermal Comfort In Heated-And-Ventilated-Only Warehouses, Christian Taber, Donald G. Colliver 2018 Big Ass Fans

Thermal Comfort In Heated-And-Ventilated-Only Warehouses, Christian Taber, Donald G. Colliver

Biosystems and Agricultural Engineering Faculty Publications

Building energy codes and standards contain minimum requirements that provide a path to energy efficient buildings and building systems. ASHRAE/IES Standard 90.1 and the International Energy Conservation Code (IECC) are the main national building code models in the United States. Both Standard 90.1 and the IECC are updated on three-year cycles with the goal of reducing building energy consumption.


Classifying Interdependencies In The Food And Agriculture Critical Infrastructure Sector, John Doerpinghaus 2018 University of Arkansas, Fayetteville

Classifying Interdependencies In The Food And Agriculture Critical Infrastructure Sector, John Doerpinghaus

Graduate Theses and Dissertations

This work classifies examples of infrastructure interdependencies found in the food and agriculture critical infrastructure sector. Interdependencies are identified through an examination of rice and poultry agriculture throughout the state of Arkansas. The subtleties of interdependence examples in the food and agriculture sector are inadequately captured by the well-studied interdependence classification taxonomies. Through 39 interviews, we develop an understanding of the subtle temporal, geographic, and productivity scales of interdependence in over 100 examples and present five new, distinct classifications of interdependence: (1) dynamic physical, (2) dynamic geographic, (3) deadline, (4) delay, and (5) human, economic, and natural resource interdependencies. An …


Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown 2018 University of Arkansas, Fayetteville

Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown

Graduate Theses and Dissertations

Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists …


Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He 2018 Fairfield University

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in …


Table Of Contents Jitim Vol 27 Issue 3, 2018, 2018 California State University, San Bernardino

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents


System Engineering Analysis Of Terraforming Mars With An Emphasis On Resource Importation Technology, Brandon Wong 2018 Loyola Marymount University

System Engineering Analysis Of Terraforming Mars With An Emphasis On Resource Importation Technology, Brandon Wong

LMU Theses and Dissertations

This project uses System Engineering principles to delve into the viability of different methods for Terraforming Mars, with a comparison between Paraterraforming, Terraforming and Bioforming. It will then examine one subsystem that will be integral to the terraforming process, which is the space infrastructure necessary to import enough gases to recreate Earth’s atmosphere on Mars. It will analyze the viability of Chemical Rockets, Nuclear Rockets, Space Elevators, Skyhooks, Rotovators, Mass Drivers, Launch Loops and Orbital Rings for this subsystem and provide recommendations for an implementation plan.


Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang 2018 University of Arkansas, Fayetteville

Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang

Graduate Theses and Dissertations

Regression analysis fits predictive models to data on a response variable and corresponding values for a set of explanatory variables. Often data on the explanatory variables come at a cost from commercial databases, so the available budget may limit which ones are used in the final model.

In this dissertation, two budget-constrained regression models are proposed for continuous and categorical variables respectively using Mixed Integer Nonlinear Programming (MINLP) to choose the explanatory variables to be included in solutions. First, we propose a budget-constrained linear regression model for continuous response variables. Properties such as solvability and global optimality of the proposed …


Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. McGehee, James Torner, Wayne Wakeland, Robert Wallace 2018 Department of Epidemiology, College of Public Health University of Iowa

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Complex Systems Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health …


Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai YANG, Chaoyi SHAO, Hai WANG, Jieping YE 2018 Singapore Management University

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …


Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien NGUYEN, Akshat KUMAR, Hoong Chuin LAU 2018 Singapore Management University

Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Scaling decision theoretic planning to large multiagent systems is challenging due to uncertainty and partial observability in the environment. We focus on a multiagent planning model subclass, relevant to urban settings, where agent interactions are dependent on their collective influence'' on each other, rather than their identities. Unlike previous work, we address a general setting where system reward is not decomposable among agents. We develop collective actor-critic RL approaches for this setting, and address the problem of multiagent credit assignment, and computing low variance policy gradient estimates that result in faster convergence to high quality solutions. We also develop difference …


Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki KULKARNI, Hoong Chuin LAU, Hai WANG, Sathyavarathan SIVABALASINGAM, Trong Khiem TRAN 2018 Singapore Management University

Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran

Research Collection School Of Computing and Information Systems

Effective traffic management can help port operators gain a competitive edge in service level and efficient use of limited resources. One critical aspect of traffic management is gate operations management, ensuring a good customer experience to logistic carriers and considering the impact of congestion in and around the port. In this paper, we describe the design and implementation of a decision support tool to help gate operators plan for future scenarios with fluctuating demand and limited resources. We propose a simulation optimization framework which incorporates theoretical results from queuing theory to approximate complex multi-lane multi-server systems. Our major contribution in …


Discrete Event Simulation And Cost Model For Optimization Of Manufacturing Resource Usages Associated With Implementation Of A Redesigned Product, Alexander Eierle 2018 Florida Institute of Technology

Discrete Event Simulation And Cost Model For Optimization Of Manufacturing Resource Usages Associated With Implementation Of A Redesigned Product, Alexander Eierle

Theses and Dissertations

This paper demonstrates an approach to evaluating production factors related to schedule and resources based on changes to the production process. A discrete event simulation model was developed to evaluate different production factors, such as arrival times, number of entities, resource availabilities, and work in process (WIP) times, compared to the total yield at a production facility. This model helped to develop relationships between the required asset resource usages and the overall production resource allocation with the related effects to process wait times and production outputs. A comparative analysis with cost was performed to determine the effect that varied resources …


Data-Enabled Computational Multiscale Method In Materials Science And Engineering, Shaoping Xiao, Amaury Lendasse, Renjie Hu 2018 Missouri University of Science and Technology

Data-Enabled Computational Multiscale Method In Materials Science And Engineering, Shaoping Xiao, Amaury Lendasse, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the Community of Computational Materials Science, One of the Challenges in Hierarchical Multiscale Modeling is Information-Passing from One Scale to Another, especially from the Molecular Model to the Continuum Model. a Machine-Learning-Enhanced Approach, Proposed in This Paper, Provides an Alternative Solution. in the Developed Hierarchical Multiscale Method, Molecular Dynamics Simulations in the Molecular Model Are Conducted First to Generate Datasets, Which Represents Physical Phenomena at the Nanoscale. the Datasets Are Then Used to Train Neural Networks for Failure Classification and Stress Regressions. Finally, the Well-Trained Learning Machines Are Implemented in the Continuum Model to Study the Mechanical Behaviors of …


Blood-Based Biomarkers For Predicting The Risk For Five-Year Incident Coronary Heart Disease In The Framingham Heart Study Via Machine Learning, Meeshanthini V. Dogan, Steven R.H. Beach, Ronald L. Simons, Amaury Lendasse, Brandan Penaluna, Robert A. Philibert 2018 Missouri University of Science and Technology

Blood-Based Biomarkers For Predicting The Risk For Five-Year Incident Coronary Heart Disease In The Framingham Heart Study Via Machine Learning, Meeshanthini V. Dogan, Steven R.H. Beach, Ronald L. Simons, Amaury Lendasse, Brandan Penaluna, Robert A. Philibert

Engineering Management and Systems Engineering Faculty Research & Creative Works

An Improved Approach for Predicting the Risk for Incident Coronary Heart Disease (CHD) Could Lead to Substantial Improvements in Cardiovascular Health. Previously, We Have Shown that Genetic and Epigenetic Loci Could Predict CHD Status More Sensitively Than Conventional Risk Factors. Herein, We Examine Whether Similar Machine Learning Approaches Could Be Used to Develop a Similar Panel for Predicting Incident CHD. Training and Test Sets Consisted of 1180 and 524 Individuals, respectively. Data Mining Techniques Were Employed to Mine for Predictive Biosignatures in the Training Set. an Ensemble of Random Forest Models Consisting of Four Genetic and Four Epigenetic Loci Was …


Introduction To Data Analytics And Emerging Real-World Use Cases, Art Chaovalitwongse 2018 University of Arkansas, Fayetteville

Introduction To Data Analytics And Emerging Real-World Use Cases, Art Chaovalitwongse

Operations Management Presentations

Data analytics is a rapidly emerging interdisciplinary research area that involves advances in engineering, computer science, statistics and operations research. This webinar is focused on introducing the foundation of data analytics and emerging real-world use cases of data analytics. This presentation will begin with a discussion of the mathematical and statistical modeling aspects of various levels of data analytics (i.e., descriptive, predictive and prescriptive). In this webinar, you will hear an overview of data analytics in real world problems ranging from healthcare analytics, retail analytics and financial analytics.


Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy 2018 Purdue University

Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy

Purdue Journal of Service-Learning and International Engagement

Apoorva Sulakhe and Shefali Rana are graduate students in the School of Industrial Engineering at Purdue. They have both been teaching assistants under their coauthor, Dr. Vincent Duffy, while supervising multiple projects. Coauthors Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, and Alyssa Zielinski are listed in alphabetical order. They were all seniors in School of Industrial Engineering at the time of this project in 2017. The purpose of their study, described in this article, was to develop an application to provide users with accurate information about diseases spreading in their geographic locations.


Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey 2018 Southwestern Oklahoma State University

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching …


Characterizing Interfacial Bonds In Hybrid Metal Am Structures, John Ross Linn 2018 Brigham Young University

Characterizing Interfacial Bonds In Hybrid Metal Am Structures, John Ross Linn

Theses and Dissertations

The capabilities of various metal Additive Manufacturing (AM) processes, such as Powder Bed Fusion – Laser (PBF-L) and Direct Energy Deposition (DED) are increasing such that it is becoming ever more common to use them in industrial applications. The ability to print atop a substrate broadens that scope of applications. There is ongoing research regarding the mechanical properties of additively processed materials, but little regarding the interaction between additive material and its substrate. An understanding of the mechanical and performance properties of the AM/substrate interface is imperative. This paper describes a study of the strength properties of AM/substrate interfaces, with …


Logistics Best Practices For Regional Food Systems: A Review, Anuj Mittal, Caroline C. Krejci, Teri J. Craven 2018 University of Texas at Arlington

Logistics Best Practices For Regional Food Systems: A Review, Anuj Mittal, Caroline C. Krejci, Teri J. Craven

Industrial, Manufacturing, and Systems Engineering Faculty Publications - Archive

The modern industrial food supply system faces many major environmental and social sustainability challenges. Regional food systems, in which consumers prefer geographically proximate food producers, offer a response to these challenges. However, the costs associated with distributing food from many small-scale producers to consumers have been a major barrier to long-term regional food system success. Logistics best practices from conventional supply chains have the potential to improve the efficiency and effectiveness of regional food supply chains (RFSCs). This paper provides a structured and in-depth review of the existing literature on RFSC logistics, including recommended and implemented best practices. The purpose …


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