Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- University of Nebraska - Lincoln (4192)
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Chinese Chemical Society | Xiamen University (2029)
- Wright State University (2027)
-
- Old Dominion University (1921)
- China Coal Technology and Engineering Group (CCTEG) (1799)
- University of Kentucky (1290)
- Air Force Institute of Technology (1166)
- Missouri University of Science and Technology (1102)
- Utah State University (903)
- Singapore Management University (888)
- Embry-Riddle Aeronautical University (866)
- University of Nevada, Las Vegas (866)
- Washington University in St. Louis (825)
- University of Arkansas, Fayetteville (620)
- University of Central Florida (583)
- Changsha University of Science and Technology (570)
- Chulalongkorn University (462)
- Montana Tech Library (447)
- Purdue University (406)
- Portland State University (395)
- University of Colorado Law School (384)
- University of South Florida (380)
- Neutrosophic Systems with Applications (375)
- National Taiwan Ocean University (328)
- University of Texas at El Paso (320)
- University of Dayton (288)
- Technological University Dublin (257)
- Santa Clara University (255)
- Keyword
-
- Machine learning (477)
- Engineering (407)
- Computer Science (370)
- Deep learning (357)
- Montana (299)
-
- Department of Computer Science and Engineering (285)
- Simulation (262)
- Gas (260)
- And Energy; Structural Materials; Sustainability (248)
- Energy Systems; Environmental Indicators and Impact Assessment; Environmental Monitoring; Mining Engineering; Oil (248)
- Machine Learning (228)
- Optimization (227)
- Applied sciences (223)
- Sustainability (199)
- Numerical simulation (182)
- Artificial intelligence (181)
- Technical writing (159)
- College of Engineering and Computer Science (157)
- Newsletters (157)
- Science news (157)
- Classification (144)
- Genetic algorithm (133)
- Climate change (131)
- Modeling (126)
- Cybersecurity (120)
- Deep Learning (120)
- Butte (118)
- Water quality (118)
- Colorado (117)
- Security (117)
- Publication Year
- Publication
-
- Journal of System Simulation (3880)
- Nebraska Tractor Tests (3402)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Journal of Electrochemistry (2029)
- Coal Geology & Exploration (1799)
-
- Computer Science & Engineering Syllabi (1312)
- Theses and Dissertations (1119)
- Research Collection School Of Computing and Information Systems (858)
- All Computer Science and Engineering Research (683)
- Electronic Theses and Dissertations (636)
- World of Coal Ash Proceedings (580)
- Journal of China & Foreign Highway (570)
- Reports (548)
- Faculty Publications (424)
- Bachelors Theses and Reports, 1928 - 1970 (419)
- Neutrosophic Systems with Applications (375)
- Browse all Theses and Dissertations (342)
- USF Tampa Graduate Theses and Dissertations (340)
- Electrical & Computer Engineering Faculty Publications (331)
- Journal of Marine Science and Technology–Taiwan (328)
- Electrical & Computer Engineering Theses & Dissertations (320)
- Electrical and Computer Engineering Faculty Research & Creative Works (303)
- Journal of Digital Forensics, Security and Law (300)
- Open Access Theses & Dissertations (299)
- Graduate Theses and Dissertations (295)
- Dissertations (249)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (246)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (240)
- Applied Environmental Research (216)
- Journal of Sustainable Mining (213)
- Publication Type
Articles 5161 - 5190 of 40933
Full-Text Articles in Engineering
Electric Vehicles Contribute To China's Energy Security And Carbon Peaking And Carbon Neutrality, Jianfeng Guo, Xuemei Zhang, Qi Cao, Fu Gu
Electric Vehicles Contribute To China's Energy Security And Carbon Peaking And Carbon Neutrality, Jianfeng Guo, Xuemei Zhang, Qi Cao, Fu Gu
Bulletin of Chinese Academy of Sciences (Chinese Version)
The current international situation is complicated and unstable, and China is in the midst of an important economic transition as it deals with the twin concerns of energy security and carbon peaking and carbon neutrality (referred to as dual carbon goals). Although the dual carbon goals aim a strong emphasis on energy security, certain emission reduction strategies will place restrictions on energy security that is directly connected, such as energy supply and grid load, making it challenging to simultaneously fulfill the optimization goal. China now has the task of figuring out how to rationalize and optimize the coordinated promotion of …
Key Elements, Mechanism Analysis And Evaluation Indicators Of Digital And Intelligent Integration Transformation And Development Of Manufacturing Industry, Xiaoqiang Sun, Xiuyun Gao, Yumei Wang
Key Elements, Mechanism Analysis And Evaluation Indicators Of Digital And Intelligent Integration Transformation And Development Of Manufacturing Industry, Xiaoqiang Sun, Xiuyun Gao, Yumei Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
The digital and intelligent integration transformation of manufacturing industry has become an important driving force for the high-quality development of traditional manufacturing enterprises. This study clarifies the main research context and key issues of scholars on the digital and intelligent integration transformation of manufacturing industry, refines the goals, main elements, and influencing factors of digital and intelligent integration transformation of manufacturing industry, builds a power network model for the transformation and development of digital and intelligent integration of manufacturing industry according to the system feedback principle of system dynamics, analyzes the mechanism of action between various elements of the system, …
Development Of An Empirical Ground-Motion Model For Post-Mining Induced Seismicity Near Gardanne, France, Pierre Gehl, Pascal Dominique, Hideo Aochi, Mickael Delatre, Jannes Kinscher, Isabelle Contrucci
Development Of An Empirical Ground-Motion Model For Post-Mining Induced Seismicity Near Gardanne, France, Pierre Gehl, Pascal Dominique, Hideo Aochi, Mickael Delatre, Jannes Kinscher, Isabelle Contrucci
Journal of Sustainable Mining
Since the closure of mining activities in 2003, the coal basin of Gardanne in South-East France has experienced thousands of small-magnitude earthquake events, mostly triggered by the flooding of mine workings. Some of these events have been powerful enough to be strongly felt by the population, generating nuisance and concern about potential damage to buildings. The aim of this study is to improve the characterisation of the level of ground motion at the surface, by developing a ground-motion model for post-mining induced seismicity, based on several years of recorded data. A Bayesian-based method is applied to the data in order …
Hydraulic Borehole Mining (Hbm) Technology Employed In Lignite Mining – Technical, Economic And Market Aspects, Bartłomiej Jura, Piotr Krawczyk, Jacek Skiba, Natalia Howaniec
Hydraulic Borehole Mining (Hbm) Technology Employed In Lignite Mining – Technical, Economic And Market Aspects, Bartłomiej Jura, Piotr Krawczyk, Jacek Skiba, Natalia Howaniec
Journal of Sustainable Mining
The results of a cost-effectiveness and economic efficiency assessment of the Hydraulic Borehole Mining (HBM) technology applied to lignite mining are presented. The Dynamic Generation Cost, the Net Present Value, and the Internal Rate of Return were calculated for the extraction of lignite at a rate of about 3.44 million Mg/year from a mining parcel of 1 2.5 km, taking into account CAPEX and OPEX. The cost of mining 1 Mg of lignite using the HBM technology was reported to be lower than its market prices before the energy crisis in Europe caused by the war in Ukraine. The values …
Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur
Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur
Journal of Sustainable Mining
In mining, where production is affected by several factors, including equipment availability, it is necessary to develop reliable models to accurately predict mine production to improve operational efficiency. Hence, in this study, four (4) machine learning algorithms – namely: artificial neural network (ANN), random forest (RF), gradient boosting regression (GBR) and decision tree (DT)) – were implemented to predict mine production. Multiple Linear Regression (MLR) analysis was used as a baseline study for comparison purposes. In that regard, one hundred and twenty-six (126) datasets from an open-pit gold mine were used. The developed models were evaluated and compared using the …
The Santa Clara, 2024-02-16, Santa Clara University
The Santa Clara, 2024-02-16, Santa Clara University
The Santa Clara
No abstract provided.
Efficiency Optimization Method For Data Sampling In Power Grid Topology Scheduling Simulation, Yingying Zhao, Pusen Dong, Tianchen Zhu, Fan Li, Yun Su, Zhenying Tai, Qingyun Sun, Hang Fan
Efficiency Optimization Method For Data Sampling In Power Grid Topology Scheduling Simulation, Yingying Zhao, Pusen Dong, Tianchen Zhu, Fan Li, Yun Su, Zhenying Tai, Qingyun Sun, Hang Fan
Journal of System Simulation
Abstract: To address the large simulation computational workload and low simulation speed caused by the scale and complexity of the new power system, a simulation acceleration method for topology scheduling based on the distributed and quantization mechanisms is proposed. The parallelization of topology scheduling models is used to increase the scale of data simulation sampling in unit time. The introduced quantization operators accelerate the computation speed of the topology scheduling model operators, reduces the time cost of the every single simulation. Case studies confirm the effectiveness of the topology simulation acceleration, in which the available transfer capacity of the simulated …
Runoff Intelligent Prediction Method Based On Broad-Deep Fusion Time-Frequency Analysis, Ying Han, Lehao Wang, Shumei Wang, Xiang Zhang, Xingxing Luo
Runoff Intelligent Prediction Method Based On Broad-Deep Fusion Time-Frequency Analysis, Ying Han, Lehao Wang, Shumei Wang, Xiang Zhang, Xingxing Luo
Journal of System Simulation
Abstract: Broad learning system(BLS) is introduced to tackle the existed disadvantage that LSTM-based runoff prediction model is easy to fall into local optimization. To reduce the influence of noise on the prediction results, the variational mode decomposition (VMD) is adopted to transform the onedimensional time-domain runoff signal to the two-dimensional time-frequency plane. The runoff prediction model based on VMD-LSTM-BLS is proposed. The simulation results demonstrate that the prediction accuracy of the new model is more significantly improved compared with the baseline model and the existing LSTM-based runoff prediction model.
Simulation Platform Of Agv System Scheduling Algorithms In Uncertain Environment, Zhihao Shi, Haihui Shen
Simulation Platform Of Agv System Scheduling Algorithms In Uncertain Environment, Zhihao Shi, Haihui Shen
Journal of System Simulation
Abstract: As a complete automated guided vehicle(AGV) system scheduling algorithm, it must include conflict-handling strategy, together with common dispatching strategy and routing algorithm. However, due to the uncertainty, characteristics of such scheduling algorithm are difficult to be analyzed theoretically, and the relevant study is lacking. An AGV system simulation platform based on the discreteevent simulation technique is designed and developed, which can flexibly set the scheduling problem, choose the dispatching strategy, routing algorithm, and conflict-handling strategy for the scheduling algorithm, to run the simulation. The platform has a visual interface, from which the running status of AGVs and the performance …
Research On Motion Planning Of Hexapod Robot Based On Drl And Free Gait, Xinpeng Wang, Huiqiao Fu, Guizhou Deng, Kaiqiang Tang, Chunlin Chen, Canghao Liu
Research On Motion Planning Of Hexapod Robot Based On Drl And Free Gait, Xinpeng Wang, Huiqiao Fu, Guizhou Deng, Kaiqiang Tang, Chunlin Chen, Canghao Liu
Journal of System Simulation
Abstract: To improve the passability and the motion performance of the hexapod robot in the unstructured environment, a multi-contact motion planning algorithm based on DRL and free gait planner is proposed. Firstly, the free gait planner obtains the reachable footholds under the target state and outputs the optimal gait sequence. The center of mass motion policy of the hexapod robot in the randomly generated plum blossom pile environment is obtained by using deep reinforcement learning training. To ensure the reachability between adjacent states of the robot in motion, the state transition feasibility model is used to judge the state transition …
Robust Predictive Control Of Nonplanar Fully-Actuated Uavs, Yun Ma, Yuan Wang, Meng Li, Peng Wang, Yanling Tang
Robust Predictive Control Of Nonplanar Fully-Actuated Uavs, Yun Ma, Yuan Wang, Meng Li, Peng Wang, Yanling Tang
Journal of System Simulation
Abstract: Targeting the problem that nonplanar fully-actuated unmanned aerial vehicles (UAVs) are susceptible to external winds and unmodeled dynamics, the predictive control system with good robustness is designed. A nonlinear motion model with six degrees of freedom is established through the Newton-Euler approach. A linear extended state observer is designed to estimate the state variables by transforming the system affected by matched and unmatched disturbances into an equivalent system only affected by the matched disturbances. A predictive controller is designed for the equivalent system to reduce the output oscillation and input surging and a disturbance compensator is also designed to …
Reconnaissance Mission Planning Method For Air-Ground Heterogeneous Unmanned Systems, Guohui Zhang, Ya'nan Zhang, Ang Gao, Aoyu Xu
Reconnaissance Mission Planning Method For Air-Ground Heterogeneous Unmanned Systems, Guohui Zhang, Ya'nan Zhang, Ang Gao, Aoyu Xu
Journal of System Simulation
Abstract: Compared with the air-based homogeneous unmanned system, the motion capabilities, resource payloads, and combat scenes in the air-ground heterogeneous unmanned system increase the number of constraint conditions and significantly increase the computational complexity of the solution model. The modeling of collaborative combat missions and the efficient solution of large-scale problems are the key issues. With the time, path cost, and reconnaissance benefit as the objective functions, considering the constraints such as the endurance of unmanned platforms, a multi-objective programming model for the reconnaissance missions of an air-ground heterogeneous unmanned system is constructed. Aiming at the urban combat environments with …
A Simplification Method Of Large-Scale Unit Commitment Model Based On Boundary Method, Yanping Xu, Mingxin Zhao, Xiaohui Qin, Keyou He, Xiaohan Wu, Pei Zhang
A Simplification Method Of Large-Scale Unit Commitment Model Based On Boundary Method, Yanping Xu, Mingxin Zhao, Xiaohui Qin, Keyou He, Xiaohan Wu, Pei Zhang
Journal of System Simulation
Abstract: As the scale of power grid expands, in the market environment, the variables and constraints in the security-constrained unit commitment (SCUC) model considering power grid security constraints increase significantly and the solvability of the model reduces. When the model scale is too large, even the existing commercial solvers cannot solve it. Aiming at the model rapid solving, from the perspective of reducing the number of model constraints, a linear constraint simplification method based on the boundary method is proposed. The proposed method can effectively reduce the model's size by eliminating the redundant linear constraints. The IEEE-39, WECC 179 and …
Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power, Jijun Shui, Daogang Peng, Yankan Song, Qiang Zhou
Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power, Jijun Shui, Daogang Peng, Yankan Song, Qiang Zhou
Journal of System Simulation
Abstract: To better meet the development needs of China's new power system, an optimal scheduling strategy of virtual power plant(VPP) with carbon emission and carbon penalty considering the uncertainty of wind power and photovoltaic power is proposed. The mathematical description of photovoltaic(PV), wind turbine(WT), combined heat and power(CHP) unit and energy storage system (ESS) is carried out, and a wind-solar output model considering the uncertainty is established. The scenario generation and reduction method is used to generate the typical scenario. To maximize the overall operation benefit of VPP, considering carbon emission cost and carbon penalty, an optimal scheduling model of …
Flipper Control Method For Tracked Robot Based On Deep Reinforcement Learning, Hainan Pan, Bailiang Chen, Kaihong Huang, Junkai Ren, Chuang Cheng, Huimin Lu, Hui Zhang
Flipper Control Method For Tracked Robot Based On Deep Reinforcement Learning, Hainan Pan, Bailiang Chen, Kaihong Huang, Junkai Ren, Chuang Cheng, Huimin Lu, Hui Zhang
Journal of System Simulation
Abstract: Tracked robots with flippers have certain terrain adaptation capabilities. To improve the intelligent operation level of robots in complex environments, it is significant to realize the flipper autonomously control. Combining the expert experience in obstacle crossing and optimization indicators, Markov decision process(MDP) modeling of the robot's flipper control problem is carried out and a simulation training environment based on physics simulation engine Pymunk is built. A deep reinforcement learning control algorithm based on dueling double DQN(D3QN) network is proposed for controlling the flippers. With terrain information and robot state as the input and the four flippers' angle as the …
Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network, Jing Chen, Zhaochong Zhang, Linkai Wang, Mai An, Wei Wang
Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network, Jing Chen, Zhaochong Zhang, Linkai Wang, Mai An, Wei Wang
Journal of System Simulation
Abstract: To address the problem that the traditional short-time passenger flow prediction method does not consider the temporal characteristics similarity between the inter-temporal passenger flows, a shorttime passenger flow prediction model k-CNN-LSTM is proposed by combining the improved k-means clustering algorithm with the CNN and the LSTM. The k-means is used to cluster the intertemporal timeseries data, the k-value is determined by using the gap-statistic, and a traffic flow matrix model is constructed. A CNN-LSTM network is used to process the short-time passenger flows with spatial and temporal characteristics. The model is tested and parameter tuned by the real dataset. …
Ground Target Recognition And Damage Assessment Of Patrol Missiles Based On Multi-Source Information Fusion, Yibo Xu, Qinghua Yu, Yanjuan Wang, Ce Guo, Shiru Feng, Huimin Lu
Ground Target Recognition And Damage Assessment Of Patrol Missiles Based On Multi-Source Information Fusion, Yibo Xu, Qinghua Yu, Yanjuan Wang, Ce Guo, Shiru Feng, Huimin Lu
Journal of System Simulation
Abstract: For the multiple patrol missiles to attack the high defense capacity targets, a mobile ground target detection and damage assessment method based on multi-source information fusion is proposed. The multi-source information fusion of infrared images and RGB images is carried out by using IoU determination. A novel two-stage tightly coupled damage assessment method based on YOLO-VGGNet of patrol missiles to mobile ground targets is proposed. This method can fully use the advantage of deep semantic information extraction of CNNs and introduce the infrared damaging information simultaneously to achieve the online and real-time damage assessment of mobile ground targets. The …
Research Advances On Electric Vehicle Routing Problem Models And Algorithms, Helin Zhuang, Xiaoyun Xia, Kangshun Li, Zefeng Chen, Xianchao Zhang
Research Advances On Electric Vehicle Routing Problem Models And Algorithms, Helin Zhuang, Xiaoyun Xia, Kangshun Li, Zefeng Chen, Xianchao Zhang
Journal of System Simulation
Abstract: The development of electric vehicle provides an alternative to conventional fuel vehicles for logistics companies. Using electric vehicles has the merits of less pollution and low noise, but the characteristics of limited cruising range and limited number of charging stations are new challenges. Electric vehicle routing problems(EVRPs) have been widely used in transportation, logistics and other fields, and have received much attention. A comprehensive survey of EVRP and its many variants are presented and the respective backgrounds and applicable conditions are analyzed. The solving approaches of EVRPs are categorized, the strengths and weaknesses of each algorithm are analyzed, and …
Optimal Dispatch Of Microgrid Clusters Considering Energy Storage Life And Communication Failures, Jianfang Jiao, Anjie Wang, Guang Wang, Jiale Xie
Optimal Dispatch Of Microgrid Clusters Considering Energy Storage Life And Communication Failures, Jianfang Jiao, Anjie Wang, Guang Wang, Jiale Xie
Journal of System Simulation
Abstract: To ensure the economy and stability of microgrid operation, the power fluctuations of renewable energy source (RES) and the lifetime characteristics of battery energy storage system (BESS) should be considered. The influence of charging and discharging depth and rate on the lifetime of BESS is researched, a model of battery energy storage system for real-time optimal scheduling is established, and the alternating direction method of multipliers is adopted for the distributed optimal scheduling of microgrid clusters. The distributed optimization method does not require any global information and can protect the privacy of microgrid in the maximum extent. Simulation results …
Dynamic Spatio-Temporal Anomaly-Aware Correlation Filtering Object Tracking Algorithm, Yunfei Qiu, Xiangrui Bu, Boqiang Zhang
Dynamic Spatio-Temporal Anomaly-Aware Correlation Filtering Object Tracking Algorithm, Yunfei Qiu, Xiangrui Bu, Boqiang Zhang
Journal of System Simulation
Abstract: In view of the fact that the background perception algorithm does not establish a relationship with the spatio-temporal domain characteristics of the target, and cannot accurately deal with the occlusion, deformation and other abnormal tracking, a object tracking algorithm which can adaptively perceive the spatio-temporal anomalies is proposed. In the training stage of correlation filter, the adaptive spatial regularization term is introduced to establish a relationship with the spatio-temporal characteristics of sample. The abnormal perception method is proposed according to the peak value of response map. Taking advantage of the different confidence of historical filter and the continuity of …
Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders, Jianpeng Mou, Weili Xiong
Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders, Jianpeng Mou, Weili Xiong
Journal of System Simulation
Abstract: In order to further improve the fault detection performance and fully mine the timing and hidden feature information, a fault detection method based on convolutional auto encoder is proposed. On the basis of modeling the original information set, the modeling of cumulative information and rate of change information is added to enhance the mining of implicit information; The three reconstructed information sets are sampled by sliding windows, and time series feature extraction and modeling are performed based on convolutional auto encoders. Bayesian fusion of the decision results of the convolutional auto encoder is performed to obtain the statistics, and …
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Journal of System Simulation
Abstract: Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by …
Bus Traffic Strategy Based On Immune Theory In Network Environment, Cao Li, Rui Zheng, Xiaolu Ma, Ziqiong Ding, Junyi Zhong, Sheng Zhang, Jingjing Qi
Bus Traffic Strategy Based On Immune Theory In Network Environment, Cao Li, Rui Zheng, Xiaolu Ma, Ziqiong Ding, Junyi Zhong, Sheng Zhang, Jingjing Qi
Journal of System Simulation
Abstract: In V2X network environment, the bus system can obtain dynamic global information and the bus traffic strategy is carried out based on the road scene between adjacent bus stops. The mathematical model of bus rapid traffic is constructed with the difference of green time ratio as the main parameter. A hybrid genetic operator is proposed on the basis of the combination of genetic algorithm and immune theory, the design of affinity, the selection of excellent antibodies. A bus traffic strategy based on immune theory is proposed on the basis of the improvement of adaptive crossover and mutation probability. The …
Research On Vehicle Detection Method Based On Improved Yolox-S, Xiliu Zhang, Xiaoling Zhang, Minjun He
Research On Vehicle Detection Method Based On Improved Yolox-S, Xiliu Zhang, Xiaoling Zhang, Minjun He
Journal of System Simulation
Abstract: A improved vehicle detection model based on multi-scale feature fusion of YOLOX network is proposed to solve the problem of missing and false detection of small vehicle targets. Ghost-cross stage partial(CSP) based on the depth separable convolution is designed to replace part of cross stage partial in network to speed up the speed of detection. The max pooling mode of model is improved to Softpool mode, and coordinate attention mechanism is introduced to enhance the feature expression of target to be detected and to optimize the problem of target missing detection. Focal Loss is selected as the confidence loss …
Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation, Jianbin Dou, Xiaobing Wang, Hongjian Yang, Yulong Gao
Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation, Jianbin Dou, Xiaobing Wang, Hongjian Yang, Yulong Gao
Journal of System Simulation
Abstract: The characteristics of the army's conventional infrared imaging guide missile hardware-in-theloop simulation system used for test and evaluation is analyzed, and a system that can meet the test and evaluation requirement of infrared imaging guide missile is designed. The key technologies such as universal system design, rapid iterative development design of heterogeneous communication data, high radiation infrared interference dual channel coupling simulation, high-precision timing and synchronization, generation of complex battlefield environment are solved. The application of the system is verified on the typical anti-tank missile and helicopter borne missile tests. The system can be used for infrared imaging guide …
Design Of 3d Visualization Monitoring System For Oil Field Pumping Unit Based On Unity3d, Liqiang Liu, Wenlei Sun, Yi Wang, Bingkai Wang
Design Of 3d Visualization Monitoring System For Oil Field Pumping Unit Based On Unity3d, Liqiang Liu, Wenlei Sun, Yi Wang, Bingkai Wang
Journal of System Simulation
Abstract: Aiming at the defects of single monitoring form, low degree of 3D visualization and poor linkage of pumping unit, the information-physical real-time mapping is introduced to develop the 3D visualization monitoring system for oil field pumping unit. The digital space of pumping unit are designed and the design architecture of virtual-real interaction layer is built. The composition and relation framework of 3D visualization system are built. Combined with the inverse kinematics, the mathematical model is built, and the overall architecture of the pumping unit 3D visualization system is designed based on the five-dimensional model and Unity3D platform. The beam …
Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska
Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska
Journal of Sustainable Mining
The exploitation carried out in the Bielszowice part of the Ruda Hard Coal Mine is mainly accompanied by seismic and rock burst hazards. The occurrence of high-energy tremors may be associated with many factors, e.g., fracturing of thick layers of high-strength rocks or destruction processes of a stressed and/or thick coal seam. These factors are often combined when excavating a single longwall panel. Determining the causes of strong tremors is of fundamental importance for mining and rock burst prevention. The extraction of the 004z longwall panel in the top layer of coal seam No. 504 was designed in complex geological …
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum
National Training Aircraft Symposium (NTAS)
Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce. While VSRPs primarily focus on operational safety, report narratives often describe factors such as fatigue, workload, culture, staffing, and health, directly or indirectly impacting mental health. These reports can provide individual and organizational insights into aviation personnel's physical and psychological well-being. This poster introduces the AVIation Analytic Neural network for Safety events (AVIAN-S) model as a potential tool to extract and monitor these insights. AVIAN-S is a novel machine-learning model that leverages natural language processing (NLP) to analyze …
Mmwave Rat Optimization: Mac Layer Initial Access Design And Transport Layer Integration, Suresh Srinivasan
Mmwave Rat Optimization: Mac Layer Initial Access Design And Transport Layer Integration, Suresh Srinivasan
Dissertations and Theses
MmWave Radio Access Technology (RAT) is a promising technology for wireless communication due its large bandwidth and is already being deployed in 5G cellular and emerging WiFi technologies. MmWave systems use highly directional beams with narrow beamwidths to overcome the high path loss associated with their frequency bands. A mmWave radio can be used either in a standalone mode (where all radios use the same technology) or simultaneously with other technologies such as LTE and low frequency WiFi in a communication mode commonly referred to as integrated mode. This thesis proposes two methods to optimize mmWave RAT performance in both …
Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa
Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa
Theses and Dissertations
Bone marrow lesions (BMLs), occurs from fluid build up in the soft tissues inside your bone. This can be seen on magnetic resonance imaging (MRI) scans and is characterized by excess water signals in the bone marrow space. This disease is commonly caused by osteoarthritis (OA), a degenerative join disease where tissues within the joint breakdown over time [1]. These BMLs are an emerging target for OA, as they are commonly related to pain and worsening of the diseased area until surgical intervention is required [2]–[4]. In order to assess the BMLs, MRIs were utilized as input into a regression …