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Articles 4141 - 4170 of 25595
Full-Text Articles in Computer Engineering
Development Of Two Stage Optimization-Based Demand Response Technique For Smart Homes Under Real Time Pricing, Govind Rai Goyal, Shelly Vadhera
Development Of Two Stage Optimization-Based Demand Response Technique For Smart Homes Under Real Time Pricing, Govind Rai Goyal, Shelly Vadhera
Turkish Journal of Electrical Engineering and Computer Sciences
Residential load management deals with two major objectives viz. minimizing the cost of monthly electricity bill and peak demand of power consumption. Both objectives can be achieved by effective operational scheduling of smart home appliances. These two objectives are conflicting in nature because rescheduling of appliances in order to minimize one objective may result in the rise of another. To achieve both objectives concurrently, an algorithm is suggested in this paper based on artificial intelligent techniques like cuckoo search, hybrid GA-PSO, and adaptive cuckoo search. The proposed algorithm is tested successfully on seven households of different monthly power consumption and …
Improved Object Re-Identification Via More Efficient Embeddings, Ertugrul Bayraktar
Improved Object Re-Identification Via More Efficient Embeddings, Ertugrul Bayraktar
Turkish Journal of Electrical Engineering and Computer Sciences
Object reidentification (ReID) in cluttered rigid scenes is a challenging problem especially when same-looking objects coexist in the scene. ReID is accepted to be one of the most powerful tools for matching the correct identities to each individual object when issues such as occlusion, missed detections, multiple same-looking objects coexisting in the same scene, and disappearance of objects from the view and/or revisiting the same region arise. We propose a novel framework towards more efficient object ReID, improved object reidentification (IO-ReID), to perform object ReID in challenging scenes with real-time processing in mind. The proposed approach achieves distinctive and efficient …
A Novel Covid-19 Herd Immunity-Based Optimizer For Optimal Accommodation Of Solar Pv With Battery Energy Storage Systems Including Variation In Load And Generation, Sumanth Pemmada, Nita Patne, Divyesh Kumar, Ashwini Manchalwar
A Novel Covid-19 Herd Immunity-Based Optimizer For Optimal Accommodation Of Solar Pv With Battery Energy Storage Systems Including Variation In Load And Generation, Sumanth Pemmada, Nita Patne, Divyesh Kumar, Ashwini Manchalwar
Turkish Journal of Electrical Engineering and Computer Sciences
The world has now looked towards installing more renewable energy sources type distributed generation (DG), such as solar photovoltaic DG (SPVDG), because of its advantages to the environment and the quality of power supply it produces. However, these sources' optimal placement and size are determined before their accommodation in the power distribution system (PDS). This is to avoid an increase in power loss and deviations in the voltage profile. Furthermore, in this article, solar PV is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG as well as the reduction in peak demand. This paper …
3d Point Cloud Classification With Acgan-3d And Vacwgan-Gp, Onur Ergün, Yusuf Sahi̇lli̇oğlu
3d Point Cloud Classification With Acgan-3d And Vacwgan-Gp, Onur Ergün, Yusuf Sahi̇lli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Machine learning and deep learning techniques are widely used to make sense of 3D point cloud data which became ubiquitous and important due to the recent advances in 3D scanning technologies and other sensors. In this work, we propose two networks to predict the class of the input 3D point cloud: 3D Auxiliary Classifier Generative Adversarial Network (ACGAN-3D) and Versatile Auxiliary Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (VACWGAN-GP). Unlike other classifiers, we are able to enlarge the limited data set with the data produced by generative models. We consequently aim to increase the success of the model by …
Teamwork Optimization Based Dtc For Enhanced Performance Of Im Based Electric Vehicle, Anjan Kumar Sahoo, Ranjan Kumar Jena
Teamwork Optimization Based Dtc For Enhanced Performance Of Im Based Electric Vehicle, Anjan Kumar Sahoo, Ranjan Kumar Jena
Turkish Journal of Electrical Engineering and Computer Sciences
The tailpipe emissions caused by vehicles using internal combustion engines are a significant source of air pollution. To reduce the health hazards caused by air pollution, advanced countries are now adopting the use of electric vehicles (EVs). Due to the advancement of electric vehicles, research and development efforts are being made to improve the performance of EV motors. With a nominal reference stator flux, the classical induction motor drive generates significant flux, torque ripple, and current harmonics. In this work, a teamwork optimization algorithm (TOA)-based optimal stator flux strategy is suggested for torque ripple reduction applied in a classical direct …
Study Of Helical Antenna Endowing Short Wire Length And Compact Structure For High-Frequency Operations And Its Exclusive Manufacturing Process, Meli̇h Aslan, Kaan Şik, İzzet Güzelkara, İbrahi̇m Tuna Özdür, Veli̇ Tayfun Kiliç
Study Of Helical Antenna Endowing Short Wire Length And Compact Structure For High-Frequency Operations And Its Exclusive Manufacturing Process, Meli̇h Aslan, Kaan Şik, İzzet Güzelkara, İbrahi̇m Tuna Özdür, Veli̇ Tayfun Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a study of a helical antenna resonating at high-frequency (HF) band with a very compact structure is reported. The designed antenna's S11 parameter magnitude change with frequency was calculated for different geometrical parameters. For each case, first, only a single parameter was changed. Then for a fair comparison, multiple parameters were changed simultaneously while the total wire length was set to be constant. Also, shifts in resonance frequencies and variations in -10 dB bandwidths were investigated. Our results show that resonance behaviour changes distinctively with the geometrical parameters and it allows shortening of the antenna wire length. …
A Multistep Fusion Matcher Approach For Large Scale Latent Fingerprint/Palmprint Recognition, İsmai̇l Kilinç, Yusuf Oğuzhan Artan, Emre Başeski̇
A Multistep Fusion Matcher Approach For Large Scale Latent Fingerprint/Palmprint Recognition, İsmai̇l Kilinç, Yusuf Oğuzhan Artan, Emre Başeski̇
Turkish Journal of Electrical Engineering and Computer Sciences
Latent fingerprints are ubiquitously used as forensic evidence by law enforcement agencies in solving crimes. However, due to deformations and artifacts within latent fingerprint images, performance of the automated latent recognition systems are far from desired levels. A basic matcher specifically designed for clean fingerprints using a minutiae-based matching algorithm can have high speed and accuracy in a sensor-to-sensor matching task, but low accuracy in matching latent prints, due to scale, rotation and quality differences between latent and sensor images. In this study, we propose a unique multistep fusion matcher (FM) on top of a base matcher that would utilize …
Reconstructing Dynamic Human Shapes From Sparse Silhouettes Via Latent Space Optimization Of Parametric Shape Models, Kanika Singla, Parma Nand
Reconstructing Dynamic Human Shapes From Sparse Silhouettes Via Latent Space Optimization Of Parametric Shape Models, Kanika Singla, Parma Nand
Turkish Journal of Electrical Engineering and Computer Sciences
The problem of dynamic 3D reconstruction has gained popularity over the last few years with most approaches relying on data driven learning and optimization methods. However this is quite a challenging task because of the need for tracking different features in both space and time?that too of deformable objects-where such robust tracking may not always be possible. A common way to better ground the problem is by using some forms of regularizations primarily on the shape representations. Over the years, mesh-based linear blend skinning models have been the standard for fitting templates of humans to the observed time series data …
Analysis And Usage Of Natural Language Features In Success Prediction Of Legislative Testimonies, Marine Cossoul
Analysis And Usage Of Natural Language Features In Success Prediction Of Legislative Testimonies, Marine Cossoul
Master's Theses
Committee meetings are a fundamental part of the legislative process in which
constituents, lobbyists, and legislators alike can speak on proposed bills at the
local and state level. Oftentimes, unspoken “rules” or standards are at play in
political processes that can influence the trajectory of a bill, leaving constituents
without a political background at an inherent disadvantage when engaging with
the legislative process. The work done in this thesis aims to explore the extent to
which the language and phraseology of a general public testimony can influence a
vote, and examine how this information can be used to promote civic …
A Modified Space Vector Modulation Based Rotor Flux Oriented Control Of Six-Phase Asymmetrical Induction Motor Drive, Krunal Shah, Rakesh Maurya
A Modified Space Vector Modulation Based Rotor Flux Oriented Control Of Six-Phase Asymmetrical Induction Motor Drive, Krunal Shah, Rakesh Maurya
Turkish Journal of Electrical Engineering and Computer Sciences
In view of the attractive features like improved torque density, reduction torque pulsation, superior fault tolerance, reduced power rating of voltage source converter, and sterling noise characteristics of six-phase asymmetrical induction motor (SPAIM) as compared to its three-phase counterpart, the SPAIM is considered for the study. In this paper, mathematical modelling of SPAIM is carried out in the synchronous reference frame and then indirect rotor field-oriented control (IRFOC) of SPAIM using a modified carrier wave-based space vector modulation (SVM) scheme is developed. A Simulink model of the proposed system configuration is developed and a simulation study is carried out. In …
Spayk: An Environment For Spiking Neural Network Simulation, Aykut Görkem Gelen, Ayten Atasoy
Spayk: An Environment For Spiking Neural Network Simulation, Aykut Görkem Gelen, Ayten Atasoy
Turkish Journal of Electrical Engineering and Computer Sciences
In research areas such as mobile robotics and computer vision, energy and computational efficiency have become critical. This has greatly increased interest in high-efficiency neuromorphic hardware and spiking neural networks. Because neuromorphic hardware is not yet widely available, spiking neural network studies are conducted by simulations. There are numerous simulators available today, each designed for a specific purpose. In this paper, a novel and open source package (SPAYK) for simulating spiking neural networks is presented. SPAYK has been proposed to speed up spiking neural network research. In the majority of simulators, networks are expressed with differential equations and require advanced …
Procedural Model Of The Monitoring System, Fayzullajon Botirov
Procedural Model Of The Monitoring System, Fayzullajon Botirov
Chemical Technology, Control and Management
This article discusses the process of monitoring information security incidents and factors affecting the effectiveness of monitoring. A procedural model of the functioning of the information security incident monitoring system is constructed, based on the study of its structure, the principles of operation of individual components and literature data, the analysis of individual stages.
Knowledge Graph Empowered Machine Learning Pipelines For Improved Efficiency, Reusability, And Explainability, Revathy Venkataramanan, Aalap Tripathy, Martin Foltin, Hong Yung Yip, Annmary Justine, Amit Sheth
Knowledge Graph Empowered Machine Learning Pipelines For Improved Efficiency, Reusability, And Explainability, Revathy Venkataramanan, Aalap Tripathy, Martin Foltin, Hong Yung Yip, Annmary Justine, Amit Sheth
Publications
Artificial intelligence (AI) pipelines are complex, heavily parameterized, and expensive to execute in terms of time and computational resources. Consequently, it is onerous to run experiments with all possible parameter combinations to achieve an optimal solution. However, these AI experiments can be optimized by recommending relevant parameters to commence the experiments, reducing search space significantly, which can be fine tuned further. The relevant parameters can be identified by observing the metadata of pipelines executed in the past, and the relevant pipeline with relevant parameters can be recommended to the user. Currently, there are various metadata frameworks that automatically record the …
Comprehensive Wind Speed Forecasting-Based Analysis Of Stacked Stateful & Stateless Models, Swayamjit Saha, Amogu Uduka, Hunter Walt, James Lucore
Comprehensive Wind Speed Forecasting-Based Analysis Of Stacked Stateful & Stateless Models, Swayamjit Saha, Amogu Uduka, Hunter Walt, James Lucore
Graduate Student Research Symposium
Wind speed is a powerful source of renewable energy, which can be used as an alternative to the non-renewable resources for production of electricity. Renewable sources are clean, infinite and do not impact the environment negatively during production of electrical energy. However, while eliciting electrical energy from renewable resources viz. solar irradiance, wind speed, hydro should require special planning failing which may result in huge loss of labour and money for setting up the system. In this poster, we discuss four deep recurrent neural networks viz. Stacked Stateless LSTM, Stacked Stateless GRU, Stacked Stateful LSTM and Statcked Stateful GRU which …
Author Gender Identification Considering Gender Bias, Manuela N. Jeyaraj, Sarah Jane Delany
Author Gender Identification Considering Gender Bias, Manuela N. Jeyaraj, Sarah Jane Delany
Conference papers
Writing style and choice of words used in textual content can vary between men and women both in terms of who the text is talking about and who is writing the text. The focus of this paper is on author gender prediction, identifying the gender of who is writing the text. We compare closed and open vocabulary approaches on different types of textual content including more traditional writing styles such as in books, and more recent writing styles used in user generated content on digital platforms such as blogs and social media messaging. As supervised machine learning approaches can reflect …
Comparing Boys’ And Girls’ Attitudes Toward Computer Science, Danielle Scott, Amiee Zou, Sharin Rawhiya Jacob, Debra Richardson, Mark Warschauer
Comparing Boys’ And Girls’ Attitudes Toward Computer Science, Danielle Scott, Amiee Zou, Sharin Rawhiya Jacob, Debra Richardson, Mark Warschauer
Journal of Computer Science Integration
Women are severely underrepresented in computer science (CS) degrees and careers. While student interest is a key predictor of success, little is known about how elementary students from underserved groups, such as girls, develop their interest in CS. To address this issue, we examined the differences in attitudes between upper elementary girls and boys towards CS after participating in a yearlong, inquiry-based CS curriculum designed for diverse learners. Pre-and-post surveys on students’ attitudes towards CS (n = 108) were delivered before and after student participation in the curriculum. Results from the survey showed only two demonstrated significant differences between boys …
Cognitive Software Defined Networking And Network Function Virtualization And Applications, Sachin Sharma, Avishek Nag
Cognitive Software Defined Networking And Network Function Virtualization And Applications, Sachin Sharma, Avishek Nag
Articles
The emergence of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has revolutionized the Internet. Using SDN, network devices can be controlled from a centralized, programmable control plane that is decoupled from their data plane, whereas with NFV, network functions (such as network address translation, firewall, and intrusion detection) can be virtualized instead of being implemented on proprietary hardware. In addition, Artificial Intelligence (AI) and Machine Learning (ML) techniques will be key to automating network operations and enhancing customer service. Many of the challenges behind SDN and NFV are currently being investigated in several projects all over the world using …
Demand Forecasting Method Of Emergency Materials Based On Metabolic Gray Markov, Long Ma, Baodong Qin, Na Lu, Meng Kou
Demand Forecasting Method Of Emergency Materials Based On Metabolic Gray Markov, Long Ma, Baodong Qin, Na Lu, Meng Kou
Journal of System Simulation
Abstract: In order to improve the prediction accuracy of the demand for emergency materials of people affected by the disaster, a forecasting method based on metabolism-gray Markov's is proposed. To realize the dynamic prediction of the number of people affected by the disaster, according to demand forecast ideas, the prediction model of metabolism-gray Markov fused is constructed progressively through gray, Markov and metabolism theories. A flexible demand forecasting model for emergency supplies is built through safety stock theory to complete the balance of supply and demand between people number and the materials demand. The prediction results of different …
Online Classification Method For Motor Imagery Eeg With Spatial Information, Fengwei Yang, Peng Chen, Kai Xi, Hualin Pu, Xueyin Liu
Online Classification Method For Motor Imagery Eeg With Spatial Information, Fengwei Yang, Peng Chen, Kai Xi, Hualin Pu, Xueyin Liu
Journal of System Simulation
Abstract: EEG-based BCI system can help the daily life and rehabilitation training of limb movement disorders patients. Due to the low signal-to-noise ratio and large individual differences of EEG signals, the accuracy and efficiency of EEG feature extraction and classification are not high, which affects the wide application of online BCI system. A CNN with spatial information is proposed for the online classification of MI-EEG signals. The reordered MI-EEG is convolved horizontally and vertically respectively. With the contralateral effect of motor imagery ERD/ERS phenomenon, the spatial information in MI-EEG is fully utilized to achieve the real-time acquisition and classification of …
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit, Yafei Mei, Ying Liao, Kejie Gong, Xingyu Zheng
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit, Yafei Mei, Ying Liao, Kejie Gong, Xingyu Zheng
Journal of System Simulation
Abstract: For relative motion spacecraft, when the actuator fails and the external disturbance and system uncertainty occur simultaneously, a finite-time fault-tolerant control method is proposed on the basis of the robustness of sliding mode control. A single-rigid spacecraft integrated attitude-orbit model is established based on Lie Group SE(3), and the relative motion spacecraft error dynamic equation is derived in exponential coordinates. A class of non-singular fast terminal sliding surface is designed, and the equivalent adaptive method is adopted to design the controller to estimate and compensate the total disturbance. The proposed fault-tolerant control algorithm can be independent from fault diagnosis …
Evacuation Dynamics Research Based On Evolutionary Game Theory, Qiaoru Li, Jinxiu Yan, Xiaoyong Tian, Kun Li, Xia Li
Evacuation Dynamics Research Based On Evolutionary Game Theory, Qiaoru Li, Jinxiu Yan, Xiaoyong Tian, Kun Li, Xia Li
Journal of System Simulation
Abstract: In order to study the impact of individual cooperative behavior on the overall pedestrian evacuation efficiency, combined with cellular automata and social force model, the co-evolution of evacuation system dynamics and "cooperative behavior" is studied, and an evacuation dynamics research method based on evolutionary game theory is proposed. The cellular automata model is used as the basic simulation framework, and the social force model is used to represent the psychological repulsion among the practitioners. The evacuation individual strategy is updated through evolutionary game. The simulation results show that when the game gain coefficient exceeds a certain threshold, the …
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network, Hong Sun, Yuxiang Zhang, Yuelan Ling
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network, Hong Sun, Yuxiang Zhang, Yuelan Ling
Journal of System Simulation
Abstract: Since the first application of convolutional neural network to the field of super-resolution image reconstruction (super-resolution convolutional neural network, SRCNN), a large number of studies have proved that deep learning can improve the effect of image reconstruction. Aiming at the too many parameters in the image super-resolution network and the insufficient utilization of image features resulting in less available high-frequency information, a loss extraction feedback attention network (LEFAN) is proposed to reuse parameters in a circular way and increase the reuse of low-resolution image features to capture more high-frequency information. The loss caused in the reconstruction process is extracted …
Computation Offloading Strategy Based On Stackelberg Game And Drl, Xianwei Zhou, Qixu Gong, Songsen Yu
Computation Offloading Strategy Based On Stackelberg Game And Drl, Xianwei Zhou, Qixu Gong, Songsen Yu
Journal of System Simulation
Abstract: To achieve the optimal computation offloading strategy for two kinds of MEC users in 5G hybrid private network, Stackelberg game is used to build the model of the competition for MEC server resources of two kinds of users, andthe strategies of complete information game and partially incomplete information game are researched respectively. It is proved that there is only one Nash equilibrium solution in the complete information scenario. In the incomplete information scenario, the environment is modeled as POMDP, and a two-stage deep reinforcement learning(TSDRL) is proposed to obtain the optimal computation offloading strategy. Simulation results show the proposed …
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Journal of System Simulation
Abstract: The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation …
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources, Naiyang Xue, Dan Ding, Yutong Jia, Zhiqiang Wang, Yuan Liu
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources, Naiyang Xue, Dan Ding, Yutong Jia, Zhiqiang Wang, Yuan Liu
Journal of System Simulation
Abstract: Joint scheduling of heterogeneous TT&C resources as research object, a deep Q network (DQN) algorithm based on reinforcement learning is proposed. The characteristics of the joint scheduling problem of heterogeneous TT&C resources being fully analyzied and mathematical language being used to describe the constraints affecting the solution, a resource joint scheduling model is established. From the perspective of applying reinforcement learning, two neural networks with the same structure and the action selection strategies based onεgreedy algorithm are respectively designed after Markov decision process description, and DQN solution framework is established. The simulation results show that DQN-based heterogeneous …
Hardware-In-The-Loop Simulation Platform Of Loop Control For Municipal Solid Waste Incineration Process, Tianzheng Wang, Jian Tang, Heng Xia, Junfei Qiao
Hardware-In-The-Loop Simulation Platform Of Loop Control For Municipal Solid Waste Incineration Process, Tianzheng Wang, Jian Tang, Heng Xia, Junfei Qiao
Journal of System Simulation
Abstract: To accurately simulate and realize the multiple input multiple output (MIMO) loop control of municipal solid waste incineration (MSWI) process, a distributed hardware-in-the-loop simulation platform consisting of a real device layer and a virtual object layer is developed based on the actual industrial process. The mechanism model is qualitatively described, and a data-driven virtual process object model in terms of loop control is established. The software subsystems of the platform and their cooperative operation mode are designed based on the control requirement. The hardware and software of the proposed platform are built and experimentally verified based on actual industrial …
A Simulation Method Of Airborne Radar Real-Time Detection Based On Three-Dimensional Subdivision, Ying Xu, Shuai Zhang, Zhige Xie, Xinhai Xu, Manhui Sun, Ning Guo
A Simulation Method Of Airborne Radar Real-Time Detection Based On Three-Dimensional Subdivision, Ying Xu, Shuai Zhang, Zhige Xie, Xinhai Xu, Manhui Sun, Ning Guo
Journal of System Simulation
Abstract: The emergence and rapid development of UAVs make the target detection of UAV airborne radar in combat simulation great research valuable. In the existing combat simulation platforms at home and abroad, the detection relationship between radar and target is pairwise interactive, and the calculation overhead increases linearly or ultra-linear following the increase of entity numbers, which is difficult to carry out the large-scale real-time combat simulation. Based on the concept of three-dimensional meshing, an airborne radar target detection simulation method is proposed, which can quickly judge the success or failure of detection by making a detection template before simulation …
Simulation Of Occluded Pedestrian Detection Based On Improved Yolo, Nan Xiang, Lu Wang, Chongliu Jia, Yuemou Jian, Xiaoxia Ma
Simulation Of Occluded Pedestrian Detection Based On Improved Yolo, Nan Xiang, Lu Wang, Chongliu Jia, Yuemou Jian, Xiaoxia Ma
Journal of System Simulation
Abstract: Aiming at the high missed detection rates and low accuracy of existing YOLO for occlusion and multi-scale pedestrian targets, an improved pedestrian detection algorithm is proposed. YOLO backbone is modified to enhance the capabilities of cross-scale feature extraction. To increase thepedestrian feature fusion capabilities of different scales, a spatial pyramid pooling module and two attention mechanisms are introduced at different positions in front of YOLO layers. Aiming at the detection performance degradation due to the extreme complexity of network module and to improve the model training efficiency, the network structure is pruned according to the actual …
Design And Implementation Of Industrial Robot Remote Monitoring System In Cloud Manufacturing, Yongkui Liu, Lin Zhang, Yingfu Liu, Jianyong Feng, Bo Yu, Wenbo Niu
Design And Implementation Of Industrial Robot Remote Monitoring System In Cloud Manufacturing, Yongkui Liu, Lin Zhang, Yingfu Liu, Jianyong Feng, Bo Yu, Wenbo Niu
Journal of System Simulation
Abstract: Considering the lack of the existing research on cloud manufacturing monitoring system and the lack of scalability and flexibility of existing remote monitoring system, and taking deep reinforcement learning-based industrial robot intelligent grasping as an application scenario, a micro-service architecture-based remote monitoring system for cloud manufacturing is developed, to carry out the requirement analysis and design of the monitoring system, and the remote monitoring of industrial robot intelligent grasping processes is realized. Test results show that the system can meet the monitoring requirements of resource providers, platform operator(s) and service consumers.
Design Of System Combat Simulation Platform For Complex Electromagnetic Environment, Baiyuan Ding, Fuling Mu, Yunpeng Li, Zhongkuan Chen, Chengyu Liu
Design Of System Combat Simulation Platform For Complex Electromagnetic Environment, Baiyuan Ding, Fuling Mu, Yunpeng Li, Zhongkuan Chen, Chengyu Liu
Journal of System Simulation
Abstract: War gaming and simulation can be divided into four levels of strategy、campaign、tactics and technique. Existing system combat simulation platforms of campaign and tactics at home and abroad cannot drive the special model of electromagnetic equipment in technique level, resulting in the low fidelity of battlefield complex electromagnetic environment simulation. To solve the problem, flexible analysis modeling and exercise system(FLAMES) model architecture as the reference, based on the simulation engine library of a discrete event system simulator(ADEVS), a flexible operation simulation platform(FOSim) is designed and developed, which integrates three levels of campaign, tactics and technology, supports three levels independence simulation …