Hardware-In-The-Loop Simulation Platform Of Loop Control For Municipal Solid Waste Incineration Process,
2023
1.Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China;2.Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China;3.Beijing Institute of Artificial Intelligence, Beijing 100124, China;
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,
2023
War Research Institute, Academy of Military Science, Beijing 100091, China;
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 …
Design And Implementation Of Industrial Robot Remote Monitoring System In Cloud Manufacturing,
2023
1.School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China;
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,
2023
1.PLA 96901 Troops, Beijing 100094, China;
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 …
Machine Learning-Based Simulation Research Of On-Line Subway Pedestrian Flow Control,
2023
1.Tianjin University of Technology, Tianjin 300000, China;
Machine Learning-Based Simulation Research Of On-Line Subway Pedestrian Flow Control, Jiajie Shi, Peng Yang, Yannan Pi
Journal of System Simulation
Abstract: In recent years, a large number of digital experiments have been carried out in the field of space launch, such as digital design verification, digital joint training and simulation training, and rocket-ground joint simulation evaluation, all of which involve the space launch information visualization. Through virtual reality technology, system simulation technology, data visualization technology, etc., on the basis of multi-thread, multi-module architecture design idea, and message queue system interaction mode, the space launch visual simulation analysis technology platform with functions of data management, scenario management, calculation management, and script management is constructed. The application cases of visual simulation analysis …
Takeout Distribution Routes Optimization Considering Order Clustering Under Dynamic Demand,
2023
Transportation Engineering College, Dalian Maritime University, Dalian 116026, China;
Takeout Distribution Routes Optimization Considering Order Clustering Under Dynamic Demand, Houming Fan, Fushan Xian, Huaiqi Wang
Journal of System Simulation
Abstract: Takeout distribution optimization includes order allocation and route planning. Aiming at dynamic order and rider position change, with the goal of minimizing the overtime order proportion, average delivery time and average travel distance,a two-stage mathematical model is established based on the idea of pre-optimization and dynamic adjustment. In the pre-optimization stage, an improved variable neighborhood search algorithm is designed to obtain the initial distribution scheme. In the dynamic adjustment stage, a periodic optimization strategy is adopted to transform the problem into a virtual distribution center vehicle problem for solution. In each stage,different clustering methods are used to optimize the …
Online Classification Method For Motor Imagery Eeg With Spatial Information,
2023
1.School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China;
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 …
Simulation Of Occluded Pedestrian Detection Based On Improved Yolo,
2023
Liangjiang International College, Chongqing University of Technology, Chongqing 401135, China;
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 …
Evacuation Dynamics Research Based On Evolutionary Game Theory,
2023
School of Civil Engineering and Transportation, Hebei University of Technology, Tianjin 300401, China;
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 …
Efficient Hmm Map Matching Method Using R-Tree And Trajectory Segmentation,
2023
1.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China;
Efficient Hmm Map Matching Method Using R-Tree And Trajectory Segmentation, Yanjiao Song, Jiayue Zhou, Longhao Wang, Jing Wu, Rui Li, Xiaoping Rui
Journal of System Simulation
Abstract: In view of the incapability of traditional methods to efficiently process massive trajectory data, an improved HMM (hidden-Markov model) map matching algorithm is proposed. Spatial index for road networks is established through R-tree spatial index. GPS trajectory data are segmented based on the position change rates of trajectory points. R-tree index is used to quickly determine the candidate road section that sub-trajectories belong to, and the key points of the sub-trajectories instead of the entire sub-trajectories are selected to judge which road the sub-trajectories should be matched with. The map matching of each sub-trajectory is carried out on …
Research On Digital Twin Credibility Assessment Process And Index,
2023
Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China;
Research On Digital Twin Credibility Assessment Process And Index, Fan Yang, Ping Ma, Wei Li, Ming Yang
Journal of System Simulation
Abstract: With the application field expansion of digital twin technology, in order to meet the requirement of digital twin credibility and promote the digital twin credibility assessment, the credibility assessment process and indicators of digital twin are researched. The development process of digital twin is analyzed and the construction method of flexible multi-layer digital twin credibility assessment process model based on IDEF0 is proposed. Two index systems, process-stage-activity layers(P-S-A) and activity-element-feature layers(A-E-F),are proposed to solve the problems of defect backtracking and evaluation of complex objects. Several examples of index system are given.
Research On Real-Time Gesture Classification Algorithm Based On Imu And Semg Mixed Signals,
2023
1.School of Automation, Beijing Information Science and Technology University, Beijing 100192, China;
Research On Real-Time Gesture Classification Algorithm Based On Imu And Semg Mixed Signals, Tao Wang, Yingnian Wu, Rui Yang, Yueying Sun
Journal of System Simulation
Abstract: In order to improve the gesture classification accuracy of surface electromyography (sEMG), the mixed signal of attitude and sEMG is collected by inertial measurement unit (IMU) and EMG sensor, and a GRU-BiLSTM double-layer network real-time gesture classification algorithm is proposed. The first layer of gated recurrent unit (GRU) detects the mutation point of the initial mixed signal though energy combination operator feature and locates the starting point of the dynamic data. The second layer Bi-directional long short term memory (BiLSTM) classifies the motion state mixed signal into 10 gestures in two directions though energy kernel phase map feature. …
Computation Offloading Strategy Based On Stackelberg Game And Drl,
2023
School of Software, South China Normal University, Foshan 528225, China;
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 …
Machine Learning Methods For Computational Phenotyping Using Patient Healthcare Data With Noisy Labels,
2023
Center for Global Health, Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, BRF #323A, MSC10-5550915 Camino de Salud NE, Albuquerque, US, Department of Computer Science, University of New Mexico, Albuquerque, US
Machine Learning Methods For Computational Phenotyping Using Patient Healthcare Data With Noisy Labels, Praveen Kumar
Computer Science ETDs
Positive and Unlabeled (PU) learning problems abound in many real-world applications. In healthcare informatics, diagnosed patients are considered labeled positive for a specific disease, but being undiagnosed does not mean they can be labeled negative. PU learning can improve classification performance, and estimate the positive fraction, α, among unlabeled samples. However, algorithms based on the Selected Completely At Random (SCAR) assumption are inadequate when the SCAR assumption fails (e.g., severe cases overrepresented), and when class imbalance is substantial. This dissertation presents and evaluates new algorithms to overcome these limitations. The proposed methods outperform the state-of-art for α-estimation, enhance classification performance, …
Session11: Skip-Gcn : A Framework For Hierarchical Graph Representation Learning,
2023
SDSMT
Session11: Skip-Gcn : A Framework For Hierarchical Graph Representation Learning, Jackson Cates, Justin Lewis, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
Recently there has been high demand for the representation learning of graphs. Graphs are a complex data structure that contains both topology and features. There are first several domains for graphs, such as infectious disease contact tracing and social media network communications interactions. The literature describes several methods developed that work to represent nodes in an embedding space, allowing for classical techniques to perform node classification and prediction. One such method is the graph convolutional neural network that aggregates the node neighbor’s features to create the embedding. Another method, Walklets, takes advantage of the topological information stored in a graph …
Temporal Tensor Factorization For Multidimensional Forecasting,
2023
SDSMT
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …
Deep Learning Architectures For Visual Question Answering On Medical Images,
2023
University of Arkansas Little Rock
Deep Learning Architectures For Visual Question Answering On Medical Images, Venkat Ramana Kodali Kodali
Theses and Dissertations
The purpose of this research is to apply both computer vision and natural language processing techniques for visual question answering (VQA) on a medical image dataset. Deep learning and machine learning libraries were used in the research. The research includes understanding key achievements in the field of visual question answering, identifying techniques applied in general images and applying them along with new techniques to medical images. There are many more articles explaining the application of visual question answering to general images than on applying VQA specifically to medical images. In this research, I initially developed a model of VQA that …
A Proposed Meta-Reality Immersive Development Pipeline: Generative Ai Models And Extended Reality (Xr) Content For The Metaverse,
2023
Lindenwood University
A Proposed Meta-Reality Immersive Development Pipeline: Generative Ai Models And Extended Reality (Xr) Content For The Metaverse, Jay Ratican, James Hutson, Andrew Wright
Faculty Scholarship
The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the …
Emotion Classification Of Indonesian Tweets Using Bidirectional Lstm,
2023
Air Force Institute of Technology
Emotion Classification Of Indonesian Tweets Using Bidirectional Lstm, Aaron K. Glenn, Phillip M. Lacasse, Bruce A. Cox
Faculty Publications
Emotion classification can be a powerful tool to derive narratives from social media data. Traditional machine learning models that perform emotion classification on Indonesian Twitter data exist but rely on closed-source features. Recurrent neural networks can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that recurrent neural network variants can produce more than an 8% gain in accuracy in comparison with logistic regression and SVM techniques and a 15% gain over random forest when using FastText embeddings. This research found a statistical significance in the performance of …
Towards Carbon Neutrality: Prediction Of Wave Energy Based On Improved Gru In Maritime Transportation,
2023
Qingdao Institute of Bioenergy and Bioprocess Technology
Towards Carbon Neutrality: Prediction Of Wave Energy Based On Improved Gru In Maritime Transportation, Zhihan Lv, Nana Wang, Ranran Lou, Yajun Tian, Mohsen Guizani
Machine Learning Faculty Publications
Efficient use of renewable energy is one of the critical measures to achieve carbon neutrality. Countries have introduced policies to put carbon neutrality on the agenda to achieve relatively zero emissions of greenhouse gases and to cope with the crisis brought about by global warming. This work analyzes the wave energy with high energy density and wide distribution based on understanding of various renewable energy sources. This study provides a wave energy prediction model for energy harvesting. At the same time, the Gated Recurrent Unit network (GRU), Bayesian optimization algorithm, and attention mechanism are introduced to improve the model's performance. …
