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Articles 1651 - 1680 of 5389

Full-Text Articles in Engineering

Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou Jul 2022

Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou

Journal of System Simulation

Abstract: Aiming at the shortcomings of high computational complexity and low simulation accuracy of traditional forest fire spread model, a forest fire spread simulation model based on swarm intelligence is proposed.By establishing fuel factor matrix and landform factor matrix, and combining with the real-time meteorological information, the computational complexity is reduced; the spread behavior of the forest fire is abstracted as the cluster behavior of each module fire point, and the correlation between modules is considered to improve the accuracy of forest fire spread simulation model.The model is compared with Wang Zhengfei model and two-dimensional cellular automata model. …

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Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu Jul 2022

Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu

Journal of System Simulation

Abstract: The green open vehicle routing problem with two-dimensional loading constraints (2L-GOVRP) is integration of the green open vehicle routing problem and two-dimensional bin packing problem. The model of 2L-GOVRP is established and a two-stage optimization algorithm (TSOA) is proposed to minimize fuel consumption. In the first stage of TSOA, adaptive whale optimization algorithm (AWOA) is designed to solve the vehicle routing problem, which determine the initial delivery route of the vehicle (the initial solution of 2L-GOVRP). The algorithm has four kinds of variable neighborhoods local operation to perform a local search. In the second stage of TSOA, the skyline …

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A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma Jul 2022

A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma

Journal of System Simulation

Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …

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Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng Jul 2022

Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng

Journal of System Simulation

Abstract: Aircraft engine remaining useful life (RUL) prediction is the core issue in equipmentfailure prognostics and health management (PHM). Aiming at the characteristics of high dimensionality, high lag and complexity of engine data, a multi-scale attention-based bidirectional long short-term memory neural network model based on self-training weights is proposed. Multi-scale features are extracted through bidirectional long short-term memory neural network (BiLSTM) of different scales. A fusion algorithm based on self-training weights is proposed, and an attention mechanism is introduced to screen features at different scales to improve prediction accuracy. Various models are compared on the NASA's C-MAPSS data set. The …

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Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li Jul 2022

Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li

Journal of System Simulation

Abstract: Based on the needs of China's space science strategy and series of on-orbit and forthcoming satellite missions in China's Strategic Priority Program on space science, data processing framework and key technologies of the satellite ground segment are studied. A general technical framework SDPF (space science satellite data processing framework) is proposed with two-layer scheduling engine, including mission-level and resource-level. The design and implementation of an automatic, efficient, real-time and standard space science satellite data processing system has been established. In this way, complicated processing procedures on large-scale data from multi-satellite missions and multi-payload can be completed quickly in parallel. …

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Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng Jul 2022

Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng

Journal of System Simulation

Abstract: For multi-view rendering tasks, a theoretical analysis of ultra-real-time visual simulation is given in terms of implementation principle and feasibility. Based on the theoretical results, an ultra-real-time visual simulation architecture is designed, which decouples the simulation and rendering computation. A parallel-rendering-based ultra-real-time visual simulation method is proposed to solve the problems of rendering task assignment, simulation world synchronization, and rendering-execution time selection. An ultra-real-time visual simulation system is implemented based on Unreal Engine 4 (UE4), the performance of which is demonstrated on a designated application case per rendering efficiency and ultra-real-time simulation.

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Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian Jul 2022

Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian

Journal of System Simulation

Abstract: The formal verification of smart contracts researches mainly focus on programming language-level vulnerabilities, and the transaction ordering dependence is more difficult to be detected as a blockchain-level vulnerability.The latent transaction ordering dependence vulnerability in smart contracts is formally verified based on colored Petri nets.The latent vulnerability in the Decode reward contractis analyzed, anda colored Petri net model of the contract itself and its execution environment is established from top to bottom.The attacker model is introduced to consider the situation that the contract is attacked. By running the model to verify the existence of transaction ordering dependence vulnerability in …

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Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components, Ling Hong, Rongmin Wu, Jianwu Zhou, Tian Xia, Xiaojie Li, Pengjie Tian, Hao Peng, Chunhui Shou Jul 2022

Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components, Ling Hong, Rongmin Wu, Jianwu Zhou, Tian Xia, Xiaojie Li, Pengjie Tian, Hao Peng, Chunhui Shou

Journal of System Simulation

Abstract: High temperature solid oxide fuel cell (SOFC) is a high temperature and efficient hydrogen-electric conversion device. Its high temperature operating environment puts forward higher requirements for thermal insulation of stack and balance of plants(BoP) in the system. In this paper, a lumped SOFC system model is established based on the thermal efficiency-heat transfer unit number method (ε-NTU method), in combination with limited measurable parameters for high-temperature system.Quantitative analysis of components temperature and heat transfer among components can be achieved by heat exchange simulation between components and BoP hot-box environment. A simple feedback controlleris designed for system self-starting and operation. …

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Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics, Tong Wang, Guangtao Shang, Shan Gao Jul 2022

Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics, Tong Wang, Guangtao Shang, Shan Gao

Journal of System Simulation

Abstract: Simultaneous Localization and Mapping (SLAM) is a key technology for mobile robots to complete map construction and positioning tasks in an unknown environment. Aiming at the map fusion problem in multi-robot SLAM, a heuristic search method is proposed to guide the repeated regions of the local map for map fusion. Each robot can build a local map without knowing its relative position, and send the local map information to the same workstation, and use the similarity of the local map as the judgment index to fuse to obtain the optimal global map.Verified on the robot physical platform, the …

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Aerial Target Threat Assessment Method Based On Deep Learning, Huimin Chai, Yong Zhang, Xinyue Li, Yanan Song Jul 2022

Aerial Target Threat Assessment Method Based On Deep Learning, Huimin Chai, Yong Zhang, Xinyue Li, Yanan Song

Journal of System Simulation

Abstract: Due to many factors of aerial target threat assessment and the lack of self-learning ability of current assessment methods, a deep neural network model for aerial target threat assessment is established using deep learning theory. In order to improve the fitting effect of the model training, a symmetric pre-training method is given. The hidden layers of the model are pre-trained layer by layer, and finally the whole model is trained. Sample data and air to air simulation scene experiments are carried out respectively. The experiments results show that the accuracy of the model using the symmetric pre-training method is …

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Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System, Xuewen Wu, Jingxian Liao Jul 2022

Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System, Xuewen Wu, Jingxian Liao

Journal of System Simulation

Abstract: Considering the delay, energy consumption and computing resource cost, the utility maximization problem in collaborative cloud-edge system is constructed, and divided into three subproblems: computing resource allocation, uplink power allocation and task offloading strategy. A game-based resource allocation and task offloading(GRATO) scheme is proposed to solve those subproblems. The optimal solution of computing resource allocation is obtained by using convex optimization conditions; a low complexity uplink power allocation method is designed to reduce wireless interfere; a game-based distributed task offloading algorithm (GDTOA) is proposed to optimize the task offloading strategy. Simulation results show that the performance of GRATO is …

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Research On Inpainting Algorithm Of Digital Murals Based On Enhanced Structural Information, Ziying Zhang, Hua Zhou Jul 2022

Research On Inpainting Algorithm Of Digital Murals Based On Enhanced Structural Information, Ziying Zhang, Hua Zhou

Journal of System Simulation

Abstract: According to the fact that the murals of Fahai Temple in Beijing are missing in blocks and the missing area is structure information, a structure-enhancing digital image restoration algorithm is proposed to solve the problem of insufficient consideration of image structure information in Criminisi algorithm. When calculating the priority function of the filling block, the curvature calculation of the linear convolution is integrated into the data item, and the weight of the structure information is increased to achieve the goal of repairing the structure information-rich region in priority; the regional covariance method is introduced in the similarity calculation of …

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Simulation Research On Covid-19 Transmission And Control Measures Based On SeiIRd Model, Jing Wang, Ying Dong Jul 2022

Simulation Research On Covid-19 Transmission And Control Measures Based On SeiIRd Model, Jing Wang, Ying Dong

Journal of System Simulation

Abstract: With the spread of the novel coronavirus pneumonia around the world, the data and transmission mechanism are analyzed. The SEIiRD model is constructed based on the existing SEIRD model, and the infected population is divided into asymptomatic infections, mild infections, severe infections and critical infections. The impact of the transmission rate of different infected people on the development of the epidemic was analyzed. Simulation experiments were carried out on the basis of fitting real data, and it was found that the main infected populations that affected the discovery of the epidemic were asymptomatic and mildly infected. On …

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Interactive Construction Of Scientific Workflow Based On Process Mining, Jun Liu, Yang Gao, Tao Xu, Qing Zhao, Guihua Shan, Xuebin Chi Jul 2022

Interactive Construction Of Scientific Workflow Based On Process Mining, Jun Liu, Yang Gao, Tao Xu, Qing Zhao, Guihua Shan, Xuebin Chi

Journal of System Simulation

Abstract: When dealing with large-scale or complex workflows, the construction efficiency of traditional interactive workflow construction methods is very low. To solve this problem, a workflow construction method based on process mining is proposed. Heuristic methods are used to collect process fragments. The specially designed relation description language is used to record the process description of different levels and aspects in the workflow as text. The text is translated to generate process relational data, which will be output to the process discovery algorithm to generate a sound workflow network. An interactive workflow construction software has been developed and tested in …

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A Quantization Training Algorithm Of Adaptive Learning Quantization Scale Fators, Hui Nie, Kangshun Li, Yang Su Jul 2022

A Quantization Training Algorithm Of Adaptive Learning Quantization Scale Fators, Hui Nie, Kangshun Li, Yang Su

Journal of System Simulation

Abstract: Deep neural network model is difficult to effectively deploy in embedded terminals due to its excessive number of components, andone of the solutions is model miniaturization (such as model quantization, knowledge distillation, etc.). To address this problem, a quantization training algorithm (referred to as LSQ-BN algorithm) based on adaptive learning of quantizationscale factors with BN folding is proposed.A single CNN (convolutional neural) is usedtoconstruct BN folding and achieve BN and CNN fusion. During the process of quantitative training,the quantization scale factors are set as model parameters. An adaptive quantizationscale factor initialization scheme is proposed to solve the problem …

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Joint Shift Scheduling Method For Call Center With Mechanism Of Delay Information, Miao Yu, Manru Li, Yu Zhao Jul 2022

Joint Shift Scheduling Method For Call Center With Mechanism Of Delay Information, Miao Yu, Manru Li, Yu Zhao

Journal of System Simulation

Abstract: A joint shift scheduling method is studied for call center with delay information. According to the queue model of call center with delay information, the influence rule of the customer's patience and abandonment behavior is addressed, and a mechanism of delay information is proposed to estimate the waiting time of customers. Considering the influence of non-stationary arrival and other factors, the scheduling model of the call centers is established by the discrete Event-Scheduling approach. Based on the proposed evaluation method of delay information, the joint shift scheduling method by simulation optimization is designed to solve the scheduling problem …

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Modeling And Simulation Of Ultra Supercritical Unit Using A Composite Weighted Human Learning Network, Chuanliang Cheng, Chen Peng, Deliang Zeng, Tengfei Zhang Jul 2022

Modeling And Simulation Of Ultra Supercritical Unit Using A Composite Weighted Human Learning Network, Chuanliang Cheng, Chen Peng, Deliang Zeng, Tengfei Zhang

Journal of System Simulation

Abstract: Intermediate point temperature is an important parameter in ultra supercritical (USC) unit. However, due to strong nonlinearity, it is difficult to determine the form and coefficients of the corresponding model by using traditional methods. In order to get a better control effect, a novel composite weighted human learning optimization network (CWHLON) is proposed to tackle the above-mentioned problems. Though the real-time dynamic linear model, the characteristics of the object are accurately simulated. In the simulation experiment, CWHLON is compared with the traditional recursive least squares and other three meta heuristic methods. The data show that the proposed method improves …

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Research On The Number Of Passengers On The Platform Of Rail Transit Station Considering Congestion Propagation, Wei Chen, Zongping Li, Can Liu, Yanni Ju Jul 2022

Research On The Number Of Passengers On The Platform Of Rail Transit Station Considering Congestion Propagation, Wei Chen, Zongping Li, Can Liu, Yanni Ju

Journal of System Simulation

Abstract: It is the basis of improving the safety guarantee ability of urban rail transit system to study and master the change law of the number of passengers in the urban rail transit station under the condition of Congestion Propagation. From the point of view of multi subsystem of passenger, station and train, combined with the multi-attribute characteristics of passenger flow, platform and train, the calculation model of the number of passengers in urban rail transit station is established based on system dynamics. A multi group sensitivity simulation experiment is designed to analyze the influence factors of the number of …

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Multi-Stage Multi-Agv Path Planning With Walk Under Shelves For Robotic Mobile Fulfillment Systems, Teng Li, Peipei Ding, Jinfang Liu Jul 2022

Multi-Stage Multi-Agv Path Planning With Walk Under Shelves For Robotic Mobile Fulfillment Systems, Teng Li, Peipei Ding, Jinfang Liu

Journal of System Simulation

Abstract: Aiming at the problem of increasing travel time due to turning and obstacle avoidance in robotic mobile fulfillment systems(RMFS) with large-scale multi-AGV path planning, a path planning model with the shortest task completion time is established. A path planning model considering no-load AGV that can pass through the shelf is proposed, and the model is solved by an improving A* algorithm. The AGV operation stage is divided, an turning penalty value is introduced into the A* algorithm to reduce the turning times, and the obstacle avoidance priority with the obstacle avoidance waiting time is set. The simulation results show …

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Design And Simulation Of Ts Fuzzy Based Cooperative Control Of Missile Formation, Yexin Zhang, Yu Cheng, Hongyan Yan, Xuwei Fan, Xu Zhang, Yi Tian Jul 2022

Design And Simulation Of Ts Fuzzy Based Cooperative Control Of Missile Formation, Yexin Zhang, Yu Cheng, Hongyan Yan, Xuwei Fan, Xu Zhang, Yi Tian

Journal of System Simulation

Abstract: Aiming at the requirement of cooperative operation of multi-missile formation, a cooperative control algorithm of multi-missile formation based on Takagi-Sugeno(TS) fuzzy control theory is proposed.The flight speed, trajectory angle and trajectory deflection angle of the missile are taken as parameters in the leader-follower mode missile formation flying system.The local asymptotically stable controller is designed by using the systemlocal linearization of multiple groups of equilibrium pointsduring the whole flight process.Through the expert experience method,the membership function and fuzzy rules for the system are designedwith TS fuzzy theory, and the whole multi-missile cooperative control system is completed and the stability …

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Machine Learning Approach For Classifying Power Outage In Secondary Electric Distribution Network, Stephan Mgaya, Hellen Maziku Jul 2022

Machine Learning Approach For Classifying Power Outage In Secondary Electric Distribution Network, Stephan Mgaya, Hellen Maziku

Tanzania Journal of Engineering and Technology (TJET)

Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still faces a challenge in effectively classifying power line outage due to the nature of imbalanced datasets. …

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Big Data Analytics Framework For Effective Higher Education Institutions, George Matto Jul 2022

Big Data Analytics Framework For Effective Higher Education Institutions, George Matto

Tanzania Journal of Engineering and Technology (TJET)

There has been an increased dependency on Information and Communication Technologies (ICTs) in undertaking various activities in Higher Education Institutions (HEIs) ecosystems. Because of that, huge volumes of data have increasingly been generated. There have been, for instance, considerable amounts of data generated through electronic platforms involved in students’ admission and registration process, students’ academic records management, teaching and learning data, curriculum related data, and several other administrative data. Analysis of data generated from these platforms stands to give students, lecturers, HEIs Management, policy makers and implementers, and other stakeholders useful insights that would help in improving HEIs’ effectiveness. Unfortunately, …

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Control And Planning For Mobile Manipulators Used In Large Scale Manufacturing Processes, Joshua T. Nguyen Jul 2022

Control And Planning For Mobile Manipulators Used In Large Scale Manufacturing Processes, Joshua T. Nguyen

LSU Master's Theses

Sanding operations in industry is one of the few manufacturing tasks that has yet to achieve automation. Sanding tasks require skilled operators that have developed a sense of when a work piece is sufficiently sanded. In order to achieve automation in sanding with robotic systems, this developed sense, or intelligence, that human operators have needs to be understood and implemented in order to achieve, at the minimum, the same quality of work. The system will also need to have the equivalent reach of a human operator and not be constrained to a single, small workspace. This thesis developed solutions for …

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A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela Jul 2022

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

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Multi-Objective Evolutionary Algorithm Based On Rbf Network For Solving The Stochastic Vehicle Routing Problem, Yunyun Niu, Jie Shao, Jianhua Xiao, Wen Song, Zhiguang Cao Jul 2022

Multi-Objective Evolutionary Algorithm Based On Rbf Network For Solving The Stochastic Vehicle Routing Problem, Yunyun Niu, Jie Shao, Jianhua Xiao, Wen Song, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Solving the multi-objective vehicle routing problem with stochastic demand (MO-VRPSD) is challenging due to its non-deterministic property and conflicting objectives. Most multi -objective evolutionary algorithm dealing with this problem update current population without any guidance from previous searching experience. In this paper, a multi -objective evolutionary algorithm based on artificial neural networks is proposed to tackle the MO-VRPSD. Particularly, during the evolutionary process, a radial basis function net-work (RBFN) is exploited to learn the potential knowledge of individuals, generate hypoth-esis and instantiate hypothesis. The RBFN evaluates individuals with different scores and generates new individuals with higher quality while taking into …

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Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin Jun 2022

Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin

Karakalpak Scientific Journal

Ushbu maqolada zamonaviy axborot-kommunikatsiya texnologiyalaridan foydalanishni kengaytirish maqsadida raqamli tasvirni qayta ishlash usullari va algoritmlari tahlil qilinadi. Maqolada, shuningdek, raqamli tasvirni qayta ishlash, tasvirni segmentatsiyalash usullari, WaterShed, MeanShift, FloodFill, GrabCut algoritmlarining afzalliklari va kamchiliklari o'rganiladi.

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Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen Jun 2022

Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen

USF Tampa Graduate Theses and Dissertations

Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …

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An Unsupervised Deep Neural Network For Image Fusion, Peipei Zhou, Xinglin Hou Jun 2022

An Unsupervised Deep Neural Network For Image Fusion, Peipei Zhou, Xinglin Hou

Journal of System Simulation

Abstract: Due to the low dynamic range of camera, can not be expressed in the different region of the high dynamic scene a single-exposure image. An unsupervised depth neural network is constructed to fuse the multi-exposure images into a high dynamic image. Based on the VGG-Net, encoding and decoding sub-networks are designed. Guided by the structural similarity of the images before and after fusion, a loss function suitable for image fusion is designed by introducing the weight factors based on the local image information, and the valid information of the different input images is given consideration. Compared with the …

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Research And Simulation Of Internet Of Vehicles Task Offloading Based On Mobile Edge Computing, Peng Cheng, Wenzhu Zhang, Shuhan Xie, Zixuan Yang Jun 2022

Research And Simulation Of Internet Of Vehicles Task Offloading Based On Mobile Edge Computing, Peng Cheng, Wenzhu Zhang, Shuhan Xie, Zixuan Yang

Journal of System Simulation

Abstract: In order to use the computing resources of edge devices to provide high-quality services, a joint resource allocation and task offloading mechanism is designed for the Internet of Vehicles architecture based on mobile edge computing. In the mechanism, the original problem is decomposed into two sub-problems of resource allocation and offloading decision. The original problem is simplified into the resource allocation of maximizing system capacity, and the initial offloading set is obtained through the proportional resource allocation algorithm; the above problem is solved by the joint offloading decision-making and resource allocation mechanism. The stable experimental results are obtained …

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Design And Realization Of 6-Dof Parachuting Simulation Training System, Xiaoguang Zhou, Peng Zhu, Yuanyuan Zhang, Huan Lu, Yuan Zhou Jun 2022

Design And Realization Of 6-Dof Parachuting Simulation Training System, Xiaoguang Zhou, Peng Zhu, Yuanyuan Zhang, Huan Lu, Yuan Zhou

Journal of System Simulation

Abstract: Aiming at restoring the 6-DOF motion process of each stage during parachuting, a 6-DOF parachuting simulation training system is designed and implemented. The architecture of the simulator is designed, and the realization of the sub-systems such as the motion calculation, 6-DOF motion platform, control loading system, virtual reality scene, somatosensory system and management console is explained. Compared with the same type of parachute simulator, this system has introduced a 6-DOF motion platform which can drive the trainees to simulate the various postures of parachuting. It can also help the trainees master the control methods of parachute and enhance the …

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