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2022

Optimization

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Full-Text Articles in Engineering

Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu Dec 2022

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 Oct 2022

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 Oct 2022

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 Sep 2022

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 Aug 2022

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 Jul 2022

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 Jul 2022

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 Jun 2022

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 …


Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan Jun 2022

Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan

Graduate Student Scholarship

Fused Deposition Modeling (FDM) is a process that allows for the rapid production of functional parts through the deposition of fused material layers in a sequential manner. FDM has flexibility and the potential to create complicated parts. This study aims to optimize the FDM process parameters in terms of tensile strength, flexural strength, and longitudinal shrinkage using the Grey-Taguchi approach. The input parameters chosen to study the effects on dimension and mechanical properties are layer thickness, the raster angle, fill density, the number of contours, printing temperature, and printing speed. The Taguchi L27 orthogonal array is used as the statistical …


Optimal Kanban Number: An Integrated Lean And Simulation Modelling Approach, Angassu Girma Mullisa, Walid Abdul-Kader Mar 2022

Optimal Kanban Number: An Integrated Lean And Simulation Modelling Approach, Angassu Girma Mullisa, Walid Abdul-Kader

Mechanical, Automotive & Materials Engineering Publications

Kanban is credited as a major means to controlling the inventory within a manufacturing system. Determining the optimum number of Kanban is of great interest for manufacturing industries. To fulfill this aim, an integrated modelling approach using discrete-event simulation technique and Kanban Lean tool is developed for a pull system ensuring an optimum Kanban number. This research has developed a base-case simulation model which was statistically validated using ANOVA. Initial Kanban number obtained from the mathematical model of Toyota motor company is used to obtain initial results. A Kanban integrated simulation model is developed that employed the idea of pull …


Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh Jan 2022

Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh

Electrical and Computer Engineering Faculty Publications

A hybrid renewable energy source (HRES) consists of two or more renewable energy sources, such as wind turbines and photovoltaic systems, utilized together to provide increased system efficiency and improved stability in energy supply to a certain degree. The objective of this study is to present a comprehensive review of wind-solar HRES from the perspectives of power architectures, mathematical modeling, power electronic converter topologies, and design optimization algorithms. Since the uncertainty of HRES can be reduced further by including an energy storage system, this paper presents several hybrid energy storage system coupling technologies, highlighting their major advantages and disadvantages. Various …


A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad Jan 2022

A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad

All Works

The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate …


Data-Driven Decarbonization Of Residential Heating Systems: An Equity Perspective., John Wamburu, Emma Grazier, David Irwin, Christine Crago, Prashant Shenoy Jan 2022

Data-Driven Decarbonization Of Residential Heating Systems: An Equity Perspective., John Wamburu, Emma Grazier, David Irwin, Christine Crago, Prashant Shenoy

Publications

Since heating buildings using natural gas, propane and oil makes up a significant proportion of the aggregate carbon emissions every year, there is a strong interest in decarbonizing residential heating systems using new technologies such as electric heat pumps. In this poster, we conduct a data-driven optimization study to analyze the potential of replacing gas heating with electric heat pumps to reduce carbon emissions in a city-wide distribution grid. We seek to not only reduce the carbon footprint of residential heating, but also show how to do so equitably. Our results show that lower income homes have an energy usage …


Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Hoda Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado Jan 2022

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Hoda Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …


Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Abd El-Sattar Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado Jan 2022

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Abd El-Sattar Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …


Hamiltonian-Driven Adaptive Dynamic Programming With Efficient Experience Replay, Yongliang Yang, Yongping Pan, Cheng Zhong Xu, Donald C. Wunsch Jan 2022

Hamiltonian-Driven Adaptive Dynamic Programming With Efficient Experience Replay, Yongliang Yang, Yongping Pan, Cheng Zhong Xu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel efficient experience-replay-based adaptive dynamic programming (ADP) for the optimal control problem of a class of nonlinear dynamical systems within the Hamiltonian-driven framework. The quasi-Hamiltonian is presented for the policy evaluation problem with an admissible policy. With the quasi-Hamiltonian, a novel composite critic learning mechanism is developed to combine the instantaneous data with the historical data. In addition, the pseudo-Hamiltonian is defined to deal with the performance optimization problem. Based on the pseudo-Hamiltonian, the conventional Hamilton–Jacobi–Bellman (HJB) equation can be represented in a filtered form, which can be implemented online. Theoretical analysis is investigated in terms …


Thermoeconomic Analysis And Multi-Objective Optimization Of A Novel Trigeneration System Consisting Of Kalina And Humidificationdehumidification Desalination Cycles, Pooria Behnam, Meysam Faegh, Iman Fakhari, Pouria Ahmadi, Ehsan Faegh, Marc A. Rosen Jan 2022

Thermoeconomic Analysis And Multi-Objective Optimization Of A Novel Trigeneration System Consisting Of Kalina And Humidificationdehumidification Desalination Cycles, Pooria Behnam, Meysam Faegh, Iman Fakhari, Pouria Ahmadi, Ehsan Faegh, Marc A. Rosen

Research outputs 2022 to 2026

Low-temperature geothermal heat sources have the highest share of geothermal energy in the world. Utilization of these heat sources for energy and freshwater generation can play an important role in meeting energy and freshwater demands. To do so, this study aims to propose a novel trigeneration cycle powered by low-temperature geothermal sources. The proposed system, which is an integration of Kalina and humidification-dehumidification (HDH) cycles, is used for the generation of electricity, heating, and freshwater. For the Kalina cycle, an evaporative condenser is used. It also acts as a humidifier and heater of the humidification-dehumidification desalination cycle, resulting in a …


Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk Jan 2022

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …


Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern Jan 2022

Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern

Dissertations

Hate speech can be defined as forms of expression that incite hatred or encourage violence towards a person or group based on race, religion, gender, or sexual orientation. Hate speech has gravitated towards social media as its primary platform, and its propagation represents profound risks to both the mental well-being and physical safety of targeted groups. Countermeasures to moderate hate speech face challenges due to the volumes of data generated in social media, leading companies, and the research community to evaluate methods to automate its detection. The emergence of BERT and other pre-trained transformer-based models for transfer learning in the …


A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak Jan 2022

A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

An optimization routine is applied for the decoupling capacitor placement on Power Distribution Networks to identify the limit beyond which the placement of additional decaps is no longer effective, thus leading to wasting layout area and components, and to a cost increase. A specific test example from a real design is used together with the required target impedance and frequency band of interest for the PDN design. The effectiveness of the decap placement while selecting different layers of the stack-up, and while moving the upper limit of the PDN design band is analyzed. Such analysis leads to helpful insights based …


An Optimal Charging Solution For Commercial Electric Vehicles, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A.S. Masoum Jan 2022

An Optimal Charging Solution For Commercial Electric Vehicles, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A.S. Masoum

Research outputs 2022 to 2026

New government regulations and incentives promote the deployment of commercial electric vehicles to reduce carbon emissions from gasoline-fueled vehicles. For commercial electric vehicles (CEVs) operating in a fleet, charging processes are often performed at the depot where they begin and end their daily driving cycles, as well as at public stations on their routes. With the large penetration of CEVs in depots, simultaneous charging increases peak demand, which in turn impacts the electric network and increases the demand cost of a facility. These depot charging conditions influence the charging schedules of CEVs along their routes and the total service cost …