Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Electrical and Computer Engineering (96)
- Civil and Environmental Engineering (70)
- Physical Sciences and Mathematics (49)
- Mechanical Engineering (48)
- Social and Behavioral Sciences (45)
-
- Operations Research, Systems Engineering and Industrial Engineering (36)
- Computer Sciences (35)
- Science and Technology Studies (34)
- Computer Engineering (30)
- Power and Energy (23)
- Civil Engineering (20)
- Chemical Engineering (15)
- Biomedical Engineering and Bioengineering (14)
- Aerospace Engineering (13)
- Artificial Intelligence and Robotics (13)
- Environmental Engineering (10)
- Public Affairs, Public Policy and Public Administration (10)
- Transportation (9)
- Transportation Engineering (8)
- Environmental Sciences (7)
- Business (6)
- Electrical and Electronics (6)
- Medicine and Health Sciences (6)
- Operational Research (6)
- Other Civil and Environmental Engineering (6)
- Energy Systems (5)
- Systems Engineering and Multidisciplinary Design Optimization (5)
- Systems and Communications (5)
- Theory and Algorithms (5)
- Institution
-
- University of Wollongong (41)
- Missouri University of Science and Technology (32)
- Utah State University (31)
- University of Kentucky (23)
- Brigham Young University (22)
-
- Singapore Management University (21)
- University of Nebraska - Lincoln (18)
- Florida International University (13)
- Old Dominion University (13)
- Cleveland State University (11)
- Edith Cowan University (11)
- Technological University Dublin (7)
- Air Force Institute of Technology (6)
- Marquette University (6)
- University of Texas Rio Grande Valley (6)
- Engineering Conferences International (5)
- Wayne State University (5)
- Michigan Technological University (4)
- University of Texas at El Paso (4)
- Boise State University (3)
- California Polytechnic State University, San Luis Obispo (3)
- Purdue University (3)
- The British University in Egypt (3)
- University of Massachusetts Amherst (3)
- University of Nevada, Las Vegas (3)
- City University of New York (CUNY) (2)
- Florida Institute of Technology (2)
- Rowan University (2)
- San Jose State University (2)
- Santa Clara University (2)
- Publication Year
- Publication
-
- Faculty Publications (30)
- Faculty of Engineering and Information Sciences - Papers: Part A (28)
- Electrical and Computer Engineering Faculty Research & Creative Works (27)
- Research Collection School Of Computing and Information Systems (21)
- Civil and Environmental Engineering Faculty Publications (18)
-
- Electrical and Computer Engineering Faculty Publications (14)
- FIU Electronic Theses and Dissertations (13)
- Power and Energy Institute of Kentucky Faculty Publications (10)
- All ECSTATIC Materials (8)
- Research outputs 2014 to 2021 (7)
- Faculty of Engineering and Information Sciences - Papers: Part B (6)
- Civil and Environmental Engineering Faculty Research Publications (5)
- Articles (4)
- Biological Systems Engineering: Papers and Publications (4)
- Departmental Technical Reports (CS) (4)
- Electrical and Computer Engineering Faculty Publications and Presentations (4)
- Faculty of Engineering - Papers (Archive) (4)
- Mechanical Engineering Faculty Publications and Presentations (4)
- Publications (4)
- Chemical Engineering (3)
- Department of Civil and Environmental Engineering: Faculty Publications (3)
- Department of Computer Science and Engineering: Dissertations, Theses, and Student Research (3)
- Electrical and Computer Engineering Faculty Research and Publications (3)
- Engineering Management and Systems Engineering Faculty Research & Creative Works (3)
- Integrated Continuous Biomanufacturing II (3)
- JTRP Technical Reports (3)
- KWRRI Research Reports (3)
- Mechanical & Aerospace Engineering Faculty Publications (3)
- Mechanical Engineering Graduate Research (3)
- Michigan Tech Publications (3)
Articles 1 - 30 of 337
Full-Text Articles in Engineering
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …
Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang
Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang
Faculty Publications
The advent of Urban Air Mobility (UAM) has necessitated a paradigm shift in aircraft design from traditional regression methods to physics-based analysis and the use of modern computational methods. This paper explores the intricacies of UAM aircraft design, acknowledging the limitations of historical empirical equations and advocating for the use of physics-based tools in the early stages of the design process. It underscores the importance of Multidisciplinary Design, Analysis, and Optimization (MDAO) as a means to integrate physics-based tools for conceptual design, facilitating decisions on configuration and sizing. The paper presents a comprehensive survey and review of computational models across …
Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao
Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao
Research Collection School Of Computing and Information Systems
This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …
Optimal Algorithm For Managing On-Campus Student Transportation, Youssef Harrath Dr.
Optimal Algorithm For Managing On-Campus Student Transportation, Youssef Harrath Dr.
Faculty Research & Publications
This study analyzed the transportation issues at the University of Bahrain Sakhir campus, where a bus system with an unorganized and fixed number of buses allocated each semester was in place. Data was collected through a survey, on-site observations, and student schedules to estimate the number of buses needed. The study was limited to students who require to move between buildings for academic purposes and not those who choose to ride buses for other reasons. An algorithm was designed to calculate the optimal number of buses for each time slot, and for each day. This solution could improve transportation efficiency, …
Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter
Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter
Faculty Publications
In the Lady in the Lake scenario, a mobile agent, L, is pitted against an agent, M, who is constrained to move along the perimeter of a circle. L is assumed to begin inside the circle and wishes to escape to the perimeter with some finite angular separation from M at the perimeter. This scenario has, in the past, been formulated as a zero-sum differential game wherein L seeks to maximize terminal separation and M seeks to minimize it. Its solution is well-known. However, there is a large portion of the state space for which the canonical solution does not …
Optimization Of Removal Of Toluene From Industrial Wastewater Using Rsm Box– Behnken Experimental Design, Dariush Jafari, Morteza Esfandyari, Mehdi Mojahed
Optimization Of Removal Of Toluene From Industrial Wastewater Using Rsm Box– Behnken Experimental Design, Dariush Jafari, Morteza Esfandyari, Mehdi Mojahed
Department of Civil and Environmental Engineering: Faculty Publications
The study is concerned with the adsorption of toluene from real wastewater using granular beads of activated carbon. The adsorbent was analyzed before and after the process using Scanning Electron Microscope analysis to characterize its surface characteristics. The adsorption parameters including solution pH, contact time, dosage of adsorbent, temperature and toluene initial concentration were optimized using response surface methodology (RSM) Box-Behnken experimental design to maximize the toluene adsorption. The adsorption capacity of the adsorbent was 298 mg g−1 and the maximum toluene removal was 99.5% which was achieved in the following optimal conditions: pH: 2, 100 min, adsorbent dosage: …
Optimization Of Removal Of Toluene From Industrial Wastewater Using Rsm Box– Behnken Experimental Design, Dariush Jafari, Morteza Esfandyari, Mehdi Mojahed
Optimization Of Removal Of Toluene From Industrial Wastewater Using Rsm Box– Behnken Experimental Design, Dariush Jafari, Morteza Esfandyari, Mehdi Mojahed
Department of Civil and Environmental Engineering: Faculty Publications
The study is concerned with the adsorption of toluene from real wastewater using granular beads of activated carbon. The adsorbent was analyzed before and after the process using Scanning Electron Microscope analysis to characterize its surface characteristics. The adsorption parameters including solution pH, contact time, dosage of adsorbent, temperature and toluene initial concentration were optimized using response surface methodology (RSM) Box-Behnken experimental design to maximize the toluene adsorption. The adsorption capacity of the adsorbent was 298 mg g− 1 and the maximum toluene removal was 99.5% which was achieved in the following optimal conditions: pH: 2, 100 min, adsorbent …
Optimization Of A Bioreactor, Ali Alshami
Optimization Of A Bioreactor, Ali Alshami
AI Assignment Library
The primary objective of this assignimentis to learn to work effectively as a team, and to design an experiment where optimization is essential.
Design And Development Of Ultrabroadband, High-Gain, And High-Isolation Thz Mimo Antenna With A Complementary Split-Ring Resonator Metamaterial, Ammar Armghan, Khaled Aliqab, Meshari Alsharari, Osamah Alsalman, Juveriya Parmar, Shobhit K. Patel
Design And Development Of Ultrabroadband, High-Gain, And High-Isolation Thz Mimo Antenna With A Complementary Split-Ring Resonator Metamaterial, Ammar Armghan, Khaled Aliqab, Meshari Alsharari, Osamah Alsalman, Juveriya Parmar, Shobhit K. Patel
Department of Mechanical and Materials Engineering: Faculty Publications
The need for high-speed communication has created a way to design THz antennas that operate at high frequencies, speeds, and data rates. In this manuscript, a THz MIMO antenna is designed using a metamaterial. The two-port antenna design proposed uses a complementary splitring resonator patch. The design results are also compared with a simple patch antenna to show the improvement. The design shows a better isolation of 50 dB. A broadband width of 8.3 THz is achieved using this complementary split-ring resonator design. The percentage bandwidth is 90%, showing an ultrabroadband response. The highest gain of 10.34 dB is achieved …
Performance Modeling And Optimization For A Fog-Based Iot Platform, Shensheng Tang
Performance Modeling And Optimization For A Fog-Based Iot Platform, Shensheng Tang
Electrical and Computer Engineering Faculty Publications
A fog-based IoT platform model involving three layers, i.e., IoT devices, fog nodes, and the cloud, was proposed using an open Jackson network with feedback. The system performance was analyzed for individual subsystems, and the overall system was based on different input parameters. Interesting performance metrics were derived from analytical results. A resource optimization problem was developed and solved to determine the optimal service rates at individual fog nodes under some constraint conditions. Numerical evaluations for the performance and the optimization problem are provided for further understanding of the analysis. The modeling and analysis, as well as the optimization design …
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Research Collection School Of Computing and Information Systems
Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.
Unmanned-Aircraft-System-Assisted Early Wildfire Detection With Air Quality Sensors †, Doaa Rjoub, Ahmad Alsharoa, Ala'eddin Masadeh
Unmanned-Aircraft-System-Assisted Early Wildfire Detection With Air Quality Sensors †, Doaa Rjoub, Ahmad Alsharoa, Ala'eddin Masadeh
Electrical and Computer Engineering Faculty Research & Creative Works
Numerous Hectares of Land Are Destroyed by Wildfires Every Year, Causing Harm to the Environment, the Economy, and the Ecology. More Than Fifty Million Acres Have Burned in Several States as a Result of Recent Forest Fires in the Western United States and Australia. According to Scientific Predictions, as the Climate Warms and Dries, Wildfires Will Become More Intense and Frequent, as Well as More Dangerous. These Unavoidable Catastrophes Emphasize How Important Early Wildfire Detection and Prevention Are. the Energy Management System Described in This Paper Uses an Unmanned Aircraft System (UAS) with Air Quality Sensors (AQSs) to Monitor Spot …
Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir
Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir
Electrical and Computer Engineering Publications
In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …
Environmental Efficiency Assessment Of Dublin Port Using Two-Stage Non-Radial Dea Model, Boban Djordjević, Raja Maitra, Bidisha Ghosh
Environmental Efficiency Assessment Of Dublin Port Using Two-Stage Non-Radial Dea Model, Boban Djordjević, Raja Maitra, Bidisha Ghosh
Articles
Global maritime trade has reached 11 billion tons and accounts for more than 80% of global merchandise trade (United Nations Conference on Trade & Development (UNCTAD), 2019). As a result, there is a wide range of vessels, from very large bulk carriers (coal, ores, grains, etc., and crude oil/refinery carriers) to container ships to various cruise ships and naval vessels. To efficiently accommodate these various vessels, ports have had to evolve from wharves to efficient logistical hubs within the larger supply chain that move vessels deeper into the hinterland. Port development is critical to managing the growing volume of cargo …
Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang
Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.
Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy
Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy
Publications
Neural networks have emerged as a powerful and versatile class of machine learning models, revolutionizing various fields with their ability to learn complex patterns and make accurate predictions. The performance of neural networks depends significantly on the appropriate choice of hyperparameters, which are critical factors governing their architecture, regularization, and optimization techniques. As the demand for high-performance neural networks grows across diverse applications, the need for efficient optimization and hyperparameter tuning methods becomes paramount. This paper presents a comprehensive exploration of optimization strategies and hyperparameter tuning techniques for neural networks. Neural networks have emerged as a powerful and versatile class …
Improving Safety Service Patrol Performance, Mecit Cetin, Hong Yang, Kun Xie, Sherif Ishak, Guocong Zhai, Junqing Wang, Giridhar Kattepogu
Improving Safety Service Patrol Performance, Mecit Cetin, Hong Yang, Kun Xie, Sherif Ishak, Guocong Zhai, Junqing Wang, Giridhar Kattepogu
Civil & Environmental Engineering Faculty Publications
Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: …
Low-Fidelity Design Optimization And Parameter Sensitivity Analysis Of Tilt-Rotor Evtol Electric Propulsion Systems, Tyler Critchfield, Andrew Ning
Low-Fidelity Design Optimization And Parameter Sensitivity Analysis Of Tilt-Rotor Evtol Electric Propulsion Systems, Tyler Critchfield, Andrew Ning
Faculty Publications
Urban air mobility requires a multidisciplinary approach to tackle the important chal- lenges facing the design of these aircraft. This work uses low-to-mid fidelity tools to model rotor aerodynamics, blade structures, vehicle aerodynamics, and electric propulsion for a tilt-rotor electric vertical takeoff and landing (eVTOL) aircraft. We use gradient-based design optimization and extensive parameter sensitivity analysis to explore the design space and complex tradeoffs of tilt-rotor distributed electric propulsion systems.
Multiple Uav-Lidar Placement Optimization Under Road Priority And Resolution Requirements, Zachary Osterwisch, Omar Rinchi, Ahmad Alsharoa, Hakim Ghazzai, Yehia Massoud
Multiple Uav-Lidar Placement Optimization Under Road Priority And Resolution Requirements, Zachary Osterwisch, Omar Rinchi, Ahmad Alsharoa, Hakim Ghazzai, Yehia Massoud
Electrical and Computer Engineering Faculty Research & Creative Works
An unmanned aerial vehicle (UAV) integrated with the remote sensing technology of light detection and ranging (LiDAR) can provide accurate and real-time road traffic information. In this paper, we propose to equip UAVs with LiDAR sensors for Intelligent Transportation Systems (ITS) applications. The goal is to find the optimal 3D placement of multiple UAV-LiDAR (ULiDs) for a given road segmentation. We formulate an optimization problem to find the optimal placement such that the road coverage efficiency is maximized. The optimization problem is constrained by notable ULiD specifications such as field-of-view (FoV), point-cloud density, geographic information system (GIS) location, and road …
Optimizing Technical And Economic Aspects Of Off-Grid Hybrid Renewable Systems: A Case Study Of Manoka Island, Cameroon, Reagan J. J. Molu, Serge R. D. Naoussi, Patrice Wira, Wulfran F. Mbasso, Saatong T. Kenfack, Barun K. Das, Enas Ali, Muhannad J. Alshareef, Sherif S. M. Ghoneim
Optimizing Technical And Economic Aspects Of Off-Grid Hybrid Renewable Systems: A Case Study Of Manoka Island, Cameroon, Reagan J. J. Molu, Serge R. D. Naoussi, Patrice Wira, Wulfran F. Mbasso, Saatong T. Kenfack, Barun K. Das, Enas Ali, Muhannad J. Alshareef, Sherif S. M. Ghoneim
Research outputs 2022 to 2026
The lack of accessible and reliable electrical energy in Cameroon has become a pervasive obstacle to the nation's progress, with energy availability, quality, and cost identified as key hindrances to development over the past 15 years. Conventional solutions that rely on combustion engines and electrochemical storage systems have proven to be cost-prohibitive, limited in power output, and constrained in capacity. The dependence on traditional diesel generators has perpetuated maintenance challenges and a continuous demand for fuel supply, while the accompanying noise and pollution have restricted their use in residential areas. Recognizing the imperative of reducing dependence on fossil fuels and …
Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning
Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning
Faculty Publications
Optimizing wind farm layouts is an important step in designing an efficient wind farm. Optimizing wind farm layouts is also a difficult task due to computation times increasing with the number of turbines present in the farm. The most computationally expensive part of gradient- based optimization is calculating the gradient. In order to reduce the expense of gradient calculation, we performed a study on the use of sparsity in wind farm layout optimization. This paper presents the findings of the sparsity study and provides a method to use sparsity in wind farm layout optimization. We tested this sparsity method by …
Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu
Research Collection School Of Computing and Information Systems
Recommender systems learn from historical user-item interactions to identify preferred items for target users. These observed interactions are usually unbalanced following a long-tailed distribution. Such long-tailed data lead to popularity bias to recommend popular but not personalized items to users. We present a gradient perspective to understand two negative impacts of popularity bias in recommendation model optimization: (i) the gradient direction of popular item embeddings is closer to that of positive interactions, and (ii) the magnitude of positive gradient for popular items are much greater than that of unpopular items. To address these issues, we propose a simple yet efficient …
Optimal Synthesis Of Crank-Rocker Mechanisms With Optimum Transmission Angle For Desired Stroke And Time-Ratio Using Genetic Programming, Bahman Ahmadi, Behnam Ahmadi
Optimal Synthesis Of Crank-Rocker Mechanisms With Optimum Transmission Angle For Desired Stroke And Time-Ratio Using Genetic Programming, Bahman Ahmadi, Behnam Ahmadi
Michigan Tech Publications
Dimensional synthesis of crank-rocker mechanisms applied to provide some desired values of stroke and time ratio, is of utmost importance for designing an efficient mechanism. In the synthesis and manufacturing of crank-rocker mechanisms, the designers are further challenged by other design criteria, such as quality of motion. In this study, a novel approach based on genetic programming (GP) is proposed for dimensional synthesis of planar crank-rocker mechanisms with optimum transmission angle over the desired stroke and time-ratio. An analytical approach is elaborated which leads to an interesting relationship of length of the coupler and rocker links. It is, therefore, advised …
A Comparative Performance Analysis Of The Novel Turboaux Engine With A Turbojet Engine, And A Low-Bypass Ratio Turbofan Engine With An Afterburner, Kaleab Fetahi, Sharanabasaweshwara A. Asundi, Arthur C. Taylor
A Comparative Performance Analysis Of The Novel Turboaux Engine With A Turbojet Engine, And A Low-Bypass Ratio Turbofan Engine With An Afterburner, Kaleab Fetahi, Sharanabasaweshwara A. Asundi, Arthur C. Taylor
Mechanical & Aerospace Engineering Faculty Publications
Presented herein is a comparative performance analysis of a novel turbofan engine with an auxiliary combustion chamber, nicknamed the TurboAux engine, against a turbojet engine, and a low bypass ratio turbofan engine with an afterburner is presented. The TurboAux engine is an adaption of the low-bypass ratio turbofan engine, but with secondary combustion in an auxiliary bypass annular combustion chamber for thrust augmentation. The TurboAux engine is envisioned with the desire to facilitate clean secondary burning of fuel at temperatures higher than in the main combustion chamber with air exiting the low-pressure compressor. The comparative study starts by analyzing the …
Design Of Solvent-Assisted Plastics Recycling: Integrated Economics And Environmental Impacts Analysis, Austin L. Lehr, Kayla L. Heider, Emmanuel A. Aboagye, John D. Chea, Jake P. Stengel, Pahola Thathiana Benavides, Kirti M. Yenkie
Design Of Solvent-Assisted Plastics Recycling: Integrated Economics And Environmental Impacts Analysis, Austin L. Lehr, Kayla L. Heider, Emmanuel A. Aboagye, John D. Chea, Jake P. Stengel, Pahola Thathiana Benavides, Kirti M. Yenkie
Henry M. Rowan College of Engineering Faculty Scholarship
In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative …
Warp-Aware Adaptive Energy Efficiency Calibration For Multi-Gpu Systems, Zhuowei Wang, Xiaoyu Song, Lianglun Cheng, Hai Wan, Wuqing Zhao, Tao Wang
Warp-Aware Adaptive Energy Efficiency Calibration For Multi-Gpu Systems, Zhuowei Wang, Xiaoyu Song, Lianglun Cheng, Hai Wan, Wuqing Zhao, Tao Wang
Electrical and Computer Engineering Faculty Publications and Presentations
Massive GPU acceleration processors have been used in high-performance computing systems. The Dennard-scaling has led to power and thermal constraints limiting the performance of such systems. The demand for both increased performance and energy-efficiency is highly desired. This paper presents a multi-layer low-power optimisation method for warps and tasks parallelisms. We present a dynamic frequency regulation scheme for performance parameters in terms of load balance and load imbalance. The method monitors the energy parameters in runtime and adjusts adaptively the voltage level to ensure the performance efficiency with energy reduction. The experimental results show that the multi-layer low-power optimisation with …
Employing Boundary Element Approach With Genetic Algorithm To Increase Travel Range Of Repulsive Actuators, Yu Tian, Ronald N. Miles, Shahrzad Towfighian
Employing Boundary Element Approach With Genetic Algorithm To Increase Travel Range Of Repulsive Actuators, Yu Tian, Ronald N. Miles, Shahrzad Towfighian
Mechanical Engineering Faculty Scholarship
The design of repulsive electrostatic actuators having enlarged travel range is achieved by combining the boundary element approach and a genetic algorithm. The boundary element method enables calculating the electrostatic forces without time consuming finite element simulations. Once a static equation that uses a model of effective lumped mass solves the travel ranges, the GA maximizes travel ranges by optimizing the dimensional parameters. The effectiveness of the scheme is demonstrated with extensive experimental results showing the travel ranges of a micro out-of-plane actuator are increased by up to 190%. The developed platform can improve the signal-to-noise ratios and the performance …
Persistent Mapping Of Sensor Data For Medium-Term Autonomy, Kevin Nickels, Jason Gassaway, Matthew Bries, David Anthony, Graham W. Fiorani
Persistent Mapping Of Sensor Data For Medium-Term Autonomy, Kevin Nickels, Jason Gassaway, Matthew Bries, David Anthony, Graham W. Fiorani
Engineering Faculty Research
For vehicles to operate in unmapped areas with some degree of autonomy, it would be useful to aggregate and store processed sensor data so that it can be used later. In this paper, a tool that records and optimizes the placement of costmap data on a persistent map is presented. The optimization takes several factors into account, including local vehicle odometry, GPS signals when available, local map consistency, deformation of map regions, and proprioceptive GPS offset error. Results illustrating the creation of maps from previously unseen regions (a 100 m × 880 m test track and a 1.2 km dirt …
Training Set Optimization In An Artificial Neural Network Constructed For High Bandwidth Interconnects Design, Bo Pu, Heegon Kim, Xiao Ding Cai, Bidyut Sen, Chunchun Sui, Jun Fan
Training Set Optimization In An Artificial Neural Network Constructed For High Bandwidth Interconnects Design, Bo Pu, Heegon Kim, Xiao Ding Cai, Bidyut Sen, Chunchun Sui, Jun Fan
Electrical and Computer Engineering Faculty Research & Creative Works
In this article, a novel training set optimization method in an artificial neural network (ANN) constructed for high bandwidth interconnects design is proposed based on rigorous probability analysis. In general, the accuracy of an ANN is enhanced by increasing training set size. However, generating large training sets is inevitably time-consuming and resource-demanding, and sometimes even impossible due to limited prototypes or measurement scenarios. Especially, when the number of channels in required design are huge such as graphics double data rate (GDDR) memory and high bandwidth memory (HBM). Therefore, optimizing the training set selection process is crucial to minimizing the training …