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

Engineering Commons™

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

Artificial Intelligence and Robotics

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1831 - 1860 of 5391

Full-Text Articles in Engineering

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

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

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

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

Monocular Semantic Slam Method Based On Object Relation Description, Shiqi Lin, Jikai Wang, Haoyuan Pei, Hao Zhao, Zonghai Chen Feb 2022

Monocular Semantic Slam Method Based On Object Relation Description, Shiqi Lin, Jikai Wang, Haoyuan Pei, Hao Zhao, Zonghai Chen

Journal of System Simulation

Abstract: Semantic information perception of the external environment and accurate positioning are the keys to autonomous navigation and operation of mobile robots. This paper proposes a method of semantic simultaneous localization and mapping (SLAM) based on a monocular camera. The system completes three-dimensional (3D) object detection while estimating the trajectory. We model the 3D objects with cuboids. Then, the semantic meanings, color distribution, size and neighborhood topology of the objects are extracted as descriptors for the accurate matching of objects between different frames. The camera pose, map points and object landmarks are optimized jointly in the backend of the system. …

Go to article

Research On Nonlinear Evaluation Method Of Situational Hot Spots, Tengjiao Mao, Dongge Zhang, Xuefeng Liang, Yanjie Niu, Minggang Yu, Ming He Feb 2022

Research On Nonlinear Evaluation Method Of Situational Hot Spots, Tengjiao Mao, Dongge Zhang, Xuefeng Liang, Yanjie Niu, Minggang Yu, Ming He

Journal of System Simulation

Abstract: The excessive amount of data and information in the situation map is likely to produce a huge cognitive load that exceeds the physiological limit. This can lead to delays in the perception, judgment, and decision-making of the commander, or even failure of decision-making activities in severe cases. For this reason, situation information needs to be processed to assess and highlight situational hotspots so that cognitive overload can be tackled. Based on the aggregation factors of collaborative targets, this paper takes the effective impact possibility of situational targets and the collaboration as the indicators, derives the attention function, and designs …

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

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

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

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

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

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

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub Feb 2022

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub

Computer Vision Faculty Publications

For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features and small number of available samples. Different types of omics data show various aspects of samples. Integration and analysis of multi-omics data give us a broad view of tumours, which can improve clinical decision making. Omics data, mainly DNA methylation and gene expression profiles are usually high dimensional data with a lot of molecular features. In recent years, variational autoencoders (VAE) [13] have been extensively used in embedding image and text data into …

Go to article

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu Feb 2022

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Currently, renewable energy generation has received more and more attention. This article focuses on wind energy generation, one of the renewable energy sources. Aiming at the intermittent and unpredictable wind power problems, according to the day ahead bidding mechanism in the power market, this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model. First, this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount. Then, we analyze …

Go to article

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed Feb 2022

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Go to article

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub Jan 2022

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub

Computer Vision Faculty Publications

Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class …

Go to article

Transformers In Medical Imaging: A Survey, Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, Huazhu Fu Jan 2022

Transformers In Medical Imaging: A Survey, Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, Huazhu Fu

Computer Vision Faculty Publications

Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of convolutional neural networks (CNNs) as de facto operators. Capitalizing on these advances in computer vision, the medical imaging field has also witnessed growing interest for Transformers that can capture global context compared to CNNs with local receptive fields. Inspired from this transition, in this survey, we attempt to provide a comprehensive review of the applications of Transformers in medical imaging covering various aspects, ranging from recently proposed architectural designs to unsolved …

Go to article

Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin Jan 2022

Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin

LSU Master's Theses

Gravity survey has played an essential role in many geoscience fields ever since it was conducted, especially as an early screening tool for subsurface hydrocarbon exploration. With continued improvement in data processing techniques and gravity survey accuracy, in-depth gravity anomaly studies, such as characterization of Bouguer and isostatic residual anomalies, have the potential to delineate prolific regional structures and hydrocarbon basins. In this study, we focus on developing a cost-effective, quick, and computationally efficient screening tool for hydrocarbon exploration using gravity data employing machine learning techniques. Since land-based gravity surveys are often expensive and difficult to obtain in remote places, …

Go to article

Deep Learning-Based Quality Assessment Of Clinical Protocol Adherence In Fetal Ultrasound Dating Scans, Sevim Cengiz, Mohammad Yaqub Jan 2022

Deep Learning-Based Quality Assessment Of Clinical Protocol Adherence In Fetal Ultrasound Dating Scans, Sevim Cengiz, Mohammad Yaqub

Computer Vision Faculty Publications

To assess fetal health during pregnancy, doctors use the gestational age (GA) calculation based on the Crown Rump Length (CRL) measurement in order to check for fetal size and growth trajectory. However, GA estimation based on CRL, requires proper positioning of calipers on the fetal crown and rump view, which is not always an easy plane to find, especially for an inexperienced sonographer. Finding a slightly oblique view from the true CRL view could lead to a different CRL value and therefore incorrect estimation of GA. This study presents an AI-based method for a quality assessment of the CRL view …

Go to article

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub Jan 2022

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …

Go to article

Is Contrastive Learning Suitable For Left Ventricular Segmentation In Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub Jan 2022

Is Contrastive Learning Suitable For Left Ventricular Segmentation In Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub

Computer Vision Faculty Publications

Contrastive learning has proven useful in many applications where access to labelled data is limited. The lack of annotated data is particularly problematic in medical image segmenta-tion as it is difficult to have clinical experts manually annotate large volumes of data. One such task is the segmentation of cardiac structures in ultrasound images of the heart. In this paper, we argue whether or not contrastive pretraining is helpful for the segmentation of the left ventricle in echocardiography images. Furthermore, we study the effect of this on two segmentation networks, DeepLabV3, as well as the commonly used segmentation net-work, UNet. Our …

Go to article

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub Jan 2022

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub

Computer Vision Faculty Publications

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep …

Go to article

Challenges In Covid-19 Chest X-Ray Classification: Problematic Data Or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, Mohammad Yaqub Jan 2022

Challenges In Covid-19 Chest X-Ray Classification: Problematic Data Or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, Mohammad Yaqub

Computer Vision Faculty Publications

The value of quick, accurate, and confident diagnoses cannot be undermined to mitigate the effects of COVID-19 infection, particularly for severe cases. Enormous effort has been put towards developing deep learning methods to classify and detect COVID-19 infections from chest radiography images. However, recently some questions have been raised surrounding the clinical viability and effectiveness of such methods. In this work, we carry out extensive experiments on a large COVID-19 chest X-ray dataset to investigate the challenges faced with creating reliable solutions from both the data and machine learning perspectives. Accordingly, we offer an in-depth discussion into the challenges faced …

Go to article

Modeling And Simulation Of Emergency Medical Resources Allocation In Shanghai During Covid-19, Changjia Fan, Yanqiu Du, Liang Di, Hu Kai, Jiayan Huang Jan 2022

Modeling And Simulation Of Emergency Medical Resources Allocation In Shanghai During Covid-19, Changjia Fan, Yanqiu Du, Liang Di, Hu Kai, Jiayan Huang

Journal of System Simulation

Abstract: Modeling and simulating on the allocation of emergency medical resources in Shanghai with COVID-19 is carried out. Based on the SEIR model of infectious diseases, combined with the process of outpatients visiting and inpatients treatment, a SEIOWHR(susceptible-exposed-infected-outpatients- waiting to hospitalized-hospitalized-removed) system dynamics model is established. If the Wuhan epidemic occurred in Shanghai, based on the model, the amount of emergency medical resources needed, the gap time of medical resources and the disease progression of patients who are waiting to hospitalized under the different supply of medical resources is simulated, and the key factors in the allocation of medical …

Go to article

A Fast Simulation Method For Ship Target Sar Signal Echo, Yuan Fei, Jianhong Li, Yin Hao, Yuhao Wang, Hong Sheng Jan 2022

A Fast Simulation Method For Ship Target Sar Signal Echo, Yuan Fei, Jianhong Li, Yin Hao, Yuhao Wang, Hong Sheng

Journal of System Simulation

Abstract: In order to meet the application requirements of synthetic aperture radar (SAR) in ocean remote sensing, a fast simulation method for the ship target SAR echo generation is presented, which carries out the accurate electromagnetic modeling to the important ship targets. “Four paths" model is used to calculate the complex echo between the ship target and sea surface, and the facet model is used to model the sea surface backscattering. After the two parts of echoes being synthesized, the SAR echo of whole scene is gotten, and the echo is processed by spot SAR imaging processing algorithm to verify …

Go to article

Study On Bidirectional Coupling Of Human Thermal Comfort Parameters And Cabin Thermal Environment, Jue Qu, Dayan Wang, Wang Wei, Sina Dang Jan 2022

Study On Bidirectional Coupling Of Human Thermal Comfort Parameters And Cabin Thermal Environment, Jue Qu, Dayan Wang, Wang Wei, Sina Dang

Journal of System Simulation

Abstract: At present, for the existing cockpit heat system, are studied more the airflow tissue parameters of the thermal environment and the human heat regulation is taken into account less, which leads to the low accuracy of simulation result evaluating the human thermal comfort. Through CFD (computational fluid dynamics) method, energy equation, RANS (reynolds-average navier-stokes) equation, and N-S(navier-stokes) equation, by combining the human temperature distribution with the cabin thermal environment parameters, the cabin heat system model based on the human heat regulation is established. The model considers the interacting influence of the human thermal regulation and the thermal environmental airflow …

Go to article

Time-Varying Output Formation Tracking Control Of Discrete-Time Heterogeneous Multi-Agent Systems, Xiaolong Qi, Xuguang Yang Jan 2022

Time-Varying Output Formation Tracking Control Of Discrete-Time Heterogeneous Multi-Agent Systems, Xiaolong Qi, Xuguang Yang

Journal of System Simulation

Abstract: Aiming at the discrete-time heterogeneous multi-agent systems with different dimensions and parameters, the time-varying output formation tracking control is studied by using the output regulation method. Assuming that the multi-agents system is consisted of multiple followers and multiple leaders, and the followers can't obtain the leaders' states, the distributed observers are designed by using the neighboring relative information. Based on the states of the distributed observers, the time-varying output formation tracking protocols and algorithm are presented by using the states feedback, and the sufficient conditions that guarantee the protocols' effectiveness are also given. The simulation results show that, …

Go to article

Wsn Clustering Routing Protocol For Bridge Structure Health Monitoring, Li Gang, Caixia Zhang, Shaolin Hu, Xiangdong Wang, Guo Jing Jan 2022

Wsn Clustering Routing Protocol For Bridge Structure Health Monitoring, Li Gang, Caixia Zhang, Shaolin Hu, Xiangdong Wang, Guo Jing

Journal of System Simulation

Abstract: In the specific application of bridge structure health monitoring (BSHM), clustering based only on the geographic location of nodes or using a single-hop strategy to complete inter-cluster routing may cause the unstability of the entire wireless sensor networks(WSN). For WSN in BSHM scenario, the concept of "energy distribution" is proposed, and an energy balance clustering routing protocol energy balance protocol(EBP) is designed. The second clustering, the high-energy areas in WSN bear more energy consumption, and a multi hop strategy based on region division is designed to control the number of forwarding hops. The simulation results show that, compared with …

Go to article

First Prev Next Last