Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 39301 - 39330 of 196021

Full-Text Articles in Engineering

Research On Decision-Making Of Closed-Loop Supply Chain For Dual-Channel Recovery Based On Game Theory, Ying Xu, Qinming Liu, Linsen Zhou Feb 2022

Research On Decision-Making Of Closed-Loop Supply Chain For Dual-Channel Recovery Based On Game Theory, Ying Xu, Qinming Liu, Linsen Zhou

Journal of System Simulation

Abstract: To tackle the difficulties and resource depletion in current packaging recycling, this paper constructs a centralized decision-making game model and three Stackelberg game models. Specifically, these Stackelberg game models are developed depending on the differences in the game power of participants in the closed-loop supply chain for dual-channel recovery, respectively corresponding to the cases where the manufacturer, the distributor or the third-party recycler is dominant. The optimal solutions of the four models are compared and analyzed. The benefits of decentralized decision-making do not reach the Pareto optimality as compared with centralized decision-making. An improved revenue sharing contract is …

Go to article

Modeling And Optimization For Manufacturing Cell Scheduling Based On Improved Wolf Pack Algorithm And Simulation, Zi'an Zhao, Hong Zhou, Yingjian Lei Feb 2022

Modeling And Optimization For Manufacturing Cell Scheduling Based On Improved Wolf Pack Algorithm And Simulation, Zi'an Zhao, Hong Zhou, Yingjian Lei

Journal of System Simulation

Abstract: Aiming at the domestic aircraft stall spin simulation training need, a stall spin simulation training system is developed. The training system consists of the multi-channel dome visual system, the semi-physical simulation cockpit and the maneuvering force control loading system, etc. Distributed simulation technology is used to develop a realistic man-in-the-loop simulation training environment. For the stall spin simulation, the multi-source aerodynamic data is processed comprehensively, and an unsteady aerodynamic model at high angle of attack (AOA) is constructed, and the heavy-load digital electric control loading technology is used to realize the simulation of stall spin alternating force and jitter …

Go to article

Optimal Path Planning For Multi-Stage Automatic Parking And Simulation Analysis, Qiming Wang, Gaoqiang Zong, Jinming Xu Feb 2022

Optimal Path Planning For Multi-Stage Automatic Parking And Simulation Analysis, Qiming Wang, Gaoqiang Zong, Jinming Xu

Journal of System Simulation

Abstract: To resolve the path planning for narrow parallel parking spaces and the discontinuous curvature of the parking trajectory, this paper proposes a method of optimal multi-stage parking path planning considering collision avoidance constraints. A trajectory equation for the center of the vehicle rear axle is derived for the case when the steering wheel speed is constant. A function of collision avoidance constraints is developed to ensure the safe parking of the vehicle. With the center of the rear axle of the parking path as the control point, the optimal path is solved according to parking indicators such as the …

Go to article

Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (4th-Casam-N): I. Mathematical Framework, Dan Gabriel Cacuci Feb 2022

Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (4th-Casam-N): I. Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the fourth-order comprehensive sensitivity analysis methodology for nonlinear systems (abbreviated as “4th-CASAM-N”) for exactly and efficiently computing the first-, second-, third-, and fourth-order functional derivatives (customarily called “sensitivities”) of physical system responses (i.e., “system performance parameters”) to the system’s (or model) parameters. The qualifier “comprehensive” indicates that the 4th-CASAM-N methodology enables the exact and efficient computation not only of response sensitivities with respect to the customary model parameters (including computational input data, correlations, initial and/or boundary conditions) but also with respect to imprecisely known material boundaries, caused by manufacturing tolerances, of the system under consideration. The 4th-CASAM-N …

Go to article

Vehicle Routing Problem With Refined Oil Secondary Distribution Considering Workload Balance, Zhenping Li, Guang Yang, Qianqian Han Feb 2022

Vehicle Routing Problem With Refined Oil Secondary Distribution Considering Workload Balance, Zhenping Li, Guang Yang, Qianqian Han

Journal of System Simulation

Abstract: The small-signal model of a DC/DC converter is usually built by the analytic method, and its accuracy is verified by the frequency domain method. A new idea is developed to model the small signal of the converter, i.e., directly using the frequency domain method.The design process is as follows: The principle and modeling mechanism of the frequency domain method are analyzed, and the realization flow of Matlab modeling is introduced. A typical phase-shifted full-bridge converter is taken as the design object, and a simulation model is built by Simulink. The transfer function is obtained on the basis of …

Go to article

Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng Feb 2022

Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng

Journal of System Simulation

Abstract: To solve the difficulty in job scheduling in the complex and transient multi-user, multi-queue, and multi-data-center cloud computing environment, this paper proposed a job scheduling method based on deep reinforcement learning. A system model of cloud job scheduling and its mathematical model were built, and an optimization goal consisting of transmission time, waiting time, and execution time was obtained. A job scheduling algorithm based on deep reinforcement learning was designed, and its state space, action space, and reward function were given. A simulated cloud job scheduler was designed and developed, and simulated scheduling experiments were conducted on it. The …

Go to article

Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang Feb 2022

Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang

Journal of System Simulation

Abstract: Crowd evacuation in a multi-floor environment is a popular social concern, while the stagnation phenomenon easily occurs when simulating a multi-floor complex environment with the traditional social force model. Therefore, An improved social force model is proposed by a wavelet neural network, and a new multi-floor evacuation model is built. In the model, a pedestrian's direction of movement is obtained by the field model, which is used as the self-driving direction of the social force model. Meanwhile, the evaluation indexes of the exit congestion degree, path congestion degree, and average velocity in a multi-floor environment are given, and a …

Go to article

Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao Feb 2022

Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao

Journal of System Simulation

Abstract: To classify pixels of natural landform edges in remote sensing images, this paper proposes a multi-channel fusion model and a decoder-side module model both integrating an edge detection module. The edge detection module takes the Canny operator as the base to perform closed operations and mean filtering, as a result of which accurate image edges can be achieved. Based on DeepLabV3+, the semantic segmentation network is connected with an edge planning module in parallel at encoder and decoder sides respectively. The experimental results show that the two improved networks can achieve a better segmentation effect on a high-resolution natural …

Go to article

Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su Feb 2022

Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su

Journal of System Simulation

Abstract: The picket fence effect of fast Fourier transform (FFT) restricts the demodulation performance of the underwater acoustic(UWA) communication systemusing orthogonal frequency division multiplexing (OFDM). To solve this problem, we propose a demodulation algorithm based on ZoomFFT. Specifically, the received signal is processed by frequency shifting and downsampling forarefined spectrum, which improves the spectralresolution and weakens the picketfence effect.Meanwhile, the channel response is refined, and the channel equalization algorithm is constructed on the basis of the minimum mean square error (MMSE) principle to eliminate the channel influence. Simulations show that the performance of underwater acoustic OFDM demodulation algorithm based on …

Go to article

Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye Feb 2022

Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye

Journal of System Simulation

Abstract: An algorithm is proposed to greatly improves the face detection rate and ensures the accuracy by adjusting the size of input images, expanding the minimum face size, and reducing the scaling ratio between layers of the detection window. The detection efficiency of this algorithm is 18 times higher than that of the original MTCNN. By building a new CNN structure model for the detection of eyes and mouths, we can achieve network detection accuracy of 95.6%. The proposed network is cascaded with the original MTCNN to continue classifying and locating the eyes and mouth in the formerly …

Go to article

Research On Design Method For Transfer Function Of Dc/Dc Converter System Based On Frequency Domain Method, Song Gao, Xue Yin, Jiantao Xu, Yuhao Miao Feb 2022

Research On Design Method For Transfer Function Of Dc/Dc Converter System Based On Frequency Domain Method, Song Gao, Xue Yin, Jiantao Xu, Yuhao Miao

Journal of System Simulation

Abstract: A robust optimal synchronization control method based on coupling dynamics model of the H-type motion platform is proposed for the problem that the H-type motion platform driven directly by permanent magnet linear synchronous motor has uncertainties such as biaxial coupling, parameter perturbation and external disturbances, which affect the synchronization control accuracy and robustness of the system. A biaxial coupling dynamics model is established based on Euler-Lagrange equation. The cross coupling synchronization controller is designed to effectively combine the single-axis tracking error with the biaxial synchronization error and its rate of change. TheH∞robust optimal synchronous controller …

Go to article

Research On Collaborative Computing Offloading Model For Base Station Groups Based On Fireworks Algorithm, Bin Xu, Wenqing Yan, Zhuofan Han, Guangshen He, Tao Deng, Yunkai Zhao, Jin Qi Feb 2022

Research On Collaborative Computing Offloading Model For Base Station Groups Based On Fireworks Algorithm, Bin Xu, Wenqing Yan, Zhuofan Han, Guangshen He, Tao Deng, Yunkai Zhao, Jin Qi

Journal of System Simulation

Abstract: Internet of Vehicles (IoV), AR, AI, and other computing-intensive, time-delay-sensitive applications are developing rapidly. However, due to the relatively insufficient computing capacity of mobile devices, such application tasks face serious latency, which seriously affects user experience and even fails to meet the needs of users. To solve this problem, by comprehensively considering delays and costs, we propose a cooperative computing offloading model based on a multi-user and multi-mobile edge computing (multi-MEC) server for base station groups. In addition, an improved fireworks algorithm based on convex optimization (CVX-FWA) is presented to solve the model and perform reasonable offloading and resource …

Go to article

Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li Feb 2022

Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li

Journal of System Simulation

Abstract: It is an important pretreatment of a virtual orthodontic system to accurately segment teeth from a dental model. In the present methods, all patches are computed directly. To solve this problem, this paper proposes a segmentation line detection method based on target region constraint, which narrows down the detection range to the area around the actual segmentation line. In this method, the cutting plane and the cutting line are automatically formed according to the positions of seed points. The detection range is determined by the search for the position with the greatest negative curvature on the cutting line. The …

Go to article

Component Design And Simulation Of Netted Radar Fusion Processing, Jing Wu, Zhiming Xu, Xiaofeng Ai, Feng Zhao, Shunping Xiao Feb 2022

Component Design And Simulation Of Netted Radar Fusion Processing, Jing Wu, Zhiming Xu, Xiaofeng Ai, Feng Zhao, Shunping Xiao

Journal of System Simulation

Abstract: Data fusion processing technology is the core of netted radars. Taking the air-defense radar network as the reference, this paper builds a component-based and reconfigurable data fusion algorithm library. With the component design method, the process of data fusion is divided into different components, such as data validity check, error match, time-space match, plot association, plot fusion, track initiation, track filtering, track association, track fusion, and track management. Each component involves different algorithms with a unified external interface, and algorithms can be chosen by parameter setting to meet different fusion requirements. Then, the complete processing template forplot fusion and …

Go to article

Efficient Capture Of Co2 And Its Selective Reduction To Formic Acid Using Tin-Based Nanomaterials, Emmanuel Oluwaseun Abdul Feb 2022

Efficient Capture Of Co2 And Its Selective Reduction To Formic Acid Using Tin-Based Nanomaterials, Emmanuel Oluwaseun Abdul

Dissertations and Theses

CO2 emissions from the combustion of fossil fuels and other anthropogenic sources have become the main contributing factors to global warming. Chemical methods of absorbing/capturing CO2 from combustion flue gases have made it a sought-after approach in engineering emission solutions because of its simplistic and convenient operation and high absorption efficiency. The conversion of CO2 into renewable fuels and high energy density chemicals by clean and economic processes has drawn scientists' attention over the decades. The electrocatalytic conversion of CO2 using Sn-based materials has been demonstrated to be a promising method for producing formate, an important …

Go to article

Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren Feb 2022

Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren

Journal of System Simulation

Abstract: To accommodate the dark and unstructured underwater working environment, the near-body pressure distribution characteristics of a bionic robot fish undulating in near wall region is studied. The feasibility of using artificial lateral line(ALL) to estimate the wall effect and flow field parameters is analyzed theoretically. A CFD(computational fluid dynamics) coupled solution model for near-body pressure simulation of a bionic robotic fish swimming near the wall is established and a near-body pressure data extraction and processing method is proposed. The effect of the wall clearance, inlet flow velocity and strouhal number (St) on the fish near-body pressure distribution …

Go to article

Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu Feb 2022

Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu

Journal of System Simulation

Abstract: In order to resolve the nonlinear and ill-posed inverse problem of the image reconstruction of electrical capacitance tomography (ECT), an image reconstruction algorithm based on one-dimensional convolutional neural network (1D CNN) is presented. The nonlinear mapping relationship between the independent measurement value of ECT system and the gray value of reconstructed image is established by 1D CNN. Six typical flow regimes with random distribution are obtained by the finite element simulation software and a 1D CNN is successfully trained. Simulation and static experiments are carried out and the reconstructed images using linear back projection, Landweber iterative algorithm and 1D …

Go to article

Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao Feb 2022

Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao

Journal of System Simulation

Abstract: Social learning is defined as the process that consumers use online reviews to fetch more precise information about product quality.Consequently, consumers would be more likely to purchase the product if the product quality learned was higher than their expectation, reference point effect named.To understand the impact of this effect in social learning on a firm's product decisions, we built a multi-agent model to solve the problem through simulation. According to the results, the reference point effect has a negative influence on the firm. The firm has to higher the product quality and price and therefore loses some profits. …

Go to article

Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei Feb 2022

Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei

Journal of System Simulation

Abstract: In order to find out the source of VOCs(volatile organic compounds) emission and diffusion to the target area, and prevent the target area from further pollution, this paper propose an analytical method of VOCs hazard causes in related areas based on object function Petri net. The net structure describes the relationship between the potential pollution sources and the target area, and the operation of the net system reflects the change of VOCs hazard degree in the target area, and the calculation of hazard degree is integrated into the operation of the Petri net system. Through the actual case study, …

Go to article

Lod Modeling Method For Three-Dimensional Objects With Energy Operator, Yongzhi Wang, Zhenchao Li, Pengyu Liu, Hui Wang Feb 2022

Lod Modeling Method For Three-Dimensional Objects With Energy Operator, Yongzhi Wang, Zhenchao Li, Pengyu Liu, Hui Wang

Journal of System Simulation

Abstract: Current level of detail (LOD) modeling methods do not combine simplification and subdivision, which results in models not being rich in detail level. Therefore, the energy operator was used to combine the simplification algorithm of a three-dimensional (3D) object model with the subdivision algorithm, and a LOD modeling method based on an energy operator was proposed for 3D objects. The method involves three major steps: calculation of energy operators for 3D models, model simplification and model subdivision based on an energy operator. Experiments show that this method can generate models with rich levels of detail and has good visualization …

Go to article

Review Of System Of Systems Combat Effectiveness Evaluation And Optimization Methods, Ziwei Zhang, Qisheng Guo, Zhiming Dong, Ang Gao, Yifei Wang Feb 2022

Review Of System Of Systems Combat Effectiveness Evaluation And Optimization Methods, Ziwei Zhang, Qisheng Guo, Zhiming Dong, Ang Gao, Yifei Wang

Journal of System Simulation

Abstract: The characteristics of system-of-systems combat effectiveness evaluation and optimization are analyzed. In light of the "holism", this paper proposes an idea of dividing system of systems combat effectiveness evaluation and optimization into three stages of comprehensive evaluation, analysis, and optimization. As for the practical problems that need to be solved in the three stages, typical methods suitable for each stage are summarized.The advantages and disadvantages of different methods are then compared. In view of the practical difficulties in implementing system of systems combat effectiveness evaluation and optimization guided by the "holism", this paper puts forward the next research directions …

Go to article

Simulation And Optimization Of A New Multi-Channel Contact Center System, Junxiang Li, Lichao Li, Kun Ma Feb 2022

Simulation And Optimization Of A New Multi-Channel Contact Center System, Junxiang Li, Lichao Li, Kun Ma

Journal of System Simulation

Abstract: In the actual operation of a contact center, it often encounters a large number of calls caused by an emergency. A traditional call center with a simple first-come-first-served queuing rule can hardly handle the rapid increase of calls properly. In this regard, without changing the number of seats, the call-back service channel for evacuating tasks and the special service channel for ensuring the service level are added. Considering customer abandonment, a new multi-channel queuing model for a contact center is built. This model is simulated by FlexSim software, and the results are comparatively analyzed. It is found that …

Go to article

Energy Consumption Prediction For Air-Conditioning System Based On Dynamic Temperature Control, Yan Bai, Lulu Wu, Yin'e He, Yuying Wang Feb 2022

Energy Consumption Prediction For Air-Conditioning System Based On Dynamic Temperature Control, Yan Bai, Lulu Wu, Yin'e He, Yuying Wang

Journal of System Simulation

Abstract: To solve the problem of energy consumption prediction for air-conditioning systems implementing dynamic temperature control, we designed a dynamic temperature control strategy and obtained a dataset on the hourly energy consumption of the air-conditioning system through EnergyPlus simulation. An improved particle swarm optimization-back propagation neural network (IPSO-BPNN) prediction model was built on the basis of energy consumption analysis by an integrated method. Clustering, classification, and correlation analysis methods were integrated to mine the energy consumption pattern of the air-conditioning system and determine the input variables for the prediction model. A nonlinear change strategy was designed to adjust the inertia …

Go to article

Torrefaction Of Oil Palm Empty Fruit Bunch Biomass, Mohamad Azri Sukiran Feb 2022

Torrefaction Of Oil Palm Empty Fruit Bunch Biomass, Mohamad Azri Sukiran

Student Works (2020-2029)

Empty fruit bunches (EFB) have great potential to be used as a renewable fuel. Its current low rate of utilization due largely to high moisture content and low calorific value (CV) can be overcome via a thermal pretreatment namely torrefaction. This study investigated the effects of torrefaction temperature, residence time, particle size and moisture content on EFB’s final products distribution and their characteristics in a fixed bed reactor. The solid products (torrefied EFB) obtained were analyzed by various methods such as proximate and ultimate analyses, CV, scanning electron microscopy (SEM), Fourier transform infrared (FTIR), x-ray diffraction (XRD) and thermogravimetric analysis …

Go to article

Computational Study On The Microscopic Adsorption Characteristics Of Linear Alkylbenzene Sulfonates With Different Chain Lengths On Anthracite Surface, Xuanlai Chen, Guochao Yan, Guang Xu, Xianglin Yang, Jinfa Dong, Zidong Liang, Shuai Wei Feb 2022

Computational Study On The Microscopic Adsorption Characteristics Of Linear Alkylbenzene Sulfonates With Different Chain Lengths On Anthracite Surface, Xuanlai Chen, Guochao Yan, Guang Xu, Xianglin Yang, Jinfa Dong, Zidong Liang, Shuai Wei

Mining Engineering Faculty Research & Creative Works

In order to explore the influence of different lengths of hydrophobic carbon chains on the diffusion characteristics of surfactants on the surface of anthracite, six linear alkyl benzene sulfonates with different hydrophobic carbon chain lengths were selected (mC, m = 8, 10, 12, 14, 16, 18; m represents the numbers of carbon atoms in the hydrophobic carbon chain), and molecular dynamics (MD) simulations were adopted. Models of surfactant-anthracite, surfactant-graphite layer, and water-surfactant-anthracite were constructed. After analyzing a series of properties such as adsorption energy, diffusion coefficient, radial distribution function (RDF), and hydrophobic tail order parameters, it was found that 12C …

Go to article

Comparative Study Of Decision Tree Models For Bearing Fault Detection And Classification, Armin Moghadam, Fatemeh Davoudi Kakhki Feb 2022

Comparative Study Of Decision Tree Models For Bearing Fault Detection And Classification, Armin Moghadam, Fatemeh Davoudi Kakhki

Faculty Research, Scholarly, and Creative Activity

Fault diagnosis of bearings is essential in reducing failures and improving functionality and reliability of rotating machines. As vibration signals are non-linear and non-stationary, extracting features for dimension reduction and efficient fault detection is challenging. This study aims at evaluating performance of decision tree-based machine learning models in detection and classification of bearing fault data. A machine learning approach combining the tree-based classifiers with de-rived statistical features is proposed for localized fault classification. Statistical features are extracted from normal and faulty vibration signals though time do-main analysis to develop tree-based models of AdaBoost (AD), classification and regression trees (CART), LogitBoost …

Go to article

Unsupervised Machine Learning For Pattern Identification In Occupational Accidents, Fatemeh Davoudi Kakhki, Steven Freeman, Gretchen Mosher Feb 2022

Unsupervised Machine Learning For Pattern Identification In Occupational Accidents, Fatemeh Davoudi Kakhki, Steven Freeman, Gretchen Mosher

Faculty Research, Scholarly, and Creative Activity

Creating safe work environment is significant in saving workers’ lives, improving corporates’ social responsibility and sustainable development. Pattern identification in occupational accidents is vital in elaborating efficient safety counter-measures aiming at improving prevention and mitigating outcomes of future incidents. The objective of this study is to identify patterns related to the occurrence of occupational accidents in non-farm agricultural work environments based on workers’ compensation claims data, using latent class clustering method as an un-supervised machine learning modeling approach. The result showed injury profiles and incident dynamics have low, average, and high levels of risks based on the main causes and …

Go to article

Cobalt Ferrite Nano-Composites For The Oxidation Of Phenols In Oil Refinery Wastewater, Amira Mohamed Feb 2022

Cobalt Ferrite Nano-Composites For The Oxidation Of Phenols In Oil Refinery Wastewater, Amira Mohamed

Theses and Dissertations

Phenolic compounds have the tendency to persist in the environment over a long period making them a main source of concern because of their toxic characteristics towards humans and animals (Bruce et al., 1987). Therefore, existence of phenolic compounds in aquatic environment is unfavourable and as a result, many treatment techniques have been implemented to treat the wastewater produced from petroleum refineries. Petroleum refineries are among the top industries that produces significant quantities of high phenol concentration wastewater. Photo-catalysis is a promising and effective method to treat phenol present in oil refineries effluent. In this study, the photo-catalyst used is …

Go to article

Analysis And Simulation Of Energy Performances Of Additive Manufacturing Systems, Mohammad Hassan Feb 2022

Analysis And Simulation Of Energy Performances Of Additive Manufacturing Systems, Mohammad Hassan

LSU Doctoral Dissertations

Additive manufacturing (AM) is an evolving technology that offers distinct advantages over conventional subtractive manufacturing by fabricating a variety of complex-shaped parts with mass customization. Selective laser melting (SLM), electron beam melting (EBM), and fused filament fabrication (FFF) are popular AM processes. A recent growing trend in AM suggests the necessity of an energy study to explore energy performance measures. In this research, a comprehensive energy study is performed for various AM processes with three objectives. The first objective of this study is to assess relationships between energy performance measures and two key process parameters (infill patterns and infill percentages) …

Go to article

Deep-Precognitive Diagnosis: Preventing Future Pandemics By Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Chao Cheng, Jing Zhang, Tianyang Wang, Min Xu Feb 2022

Deep-Precognitive Diagnosis: Preventing Future Pandemics By Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Chao Cheng, Jing Zhang, Tianyang Wang, Min Xu

Computer Vision Faculty Publications

Deep learning-based Computer-Aided Diagnosis has gained immense attention in recent years due to its capability to enhance diagnostic performance and elucidate complex clinical tasks. However, conventional supervised deep learning models are incapable of recognizing novel diseases that do not exist in the training dataset. Automated early-stage detection of novel infectious diseases can be vital in controlling their rapid spread. Moreover, the development of a conventional CAD model is only possible after disease outbreaks and datasets become available for training (viz. COVID-19 outbreak). Since novel diseases are unknown and cannot be included in training data, it is challenging to recognize them …

Go to article

First Prev Next Last