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Articles 91 - 120 of 12600
Full-Text Articles in Physical Sciences and Mathematics
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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. …
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 …
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Turkish Journal of Electrical Engineering and Computer Sciences
It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Turkish Journal of Electrical Engineering and Computer Sciences
In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Turkish Journal of Electrical Engineering and Computer Sciences
Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Turkish Journal of Electrical Engineering and Computer Sciences
Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …
Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu
Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …
Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin
Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin
Computer Science: Faculty Publications and Other Works
Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 and n = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use …
The Aim To Decentralize Economic Systems With Blockchains And Crypto, Mary Lacity
The Aim To Decentralize Economic Systems With Blockchains And Crypto, Mary Lacity
Arkansas Law Review
As an information systems (“IS”) professor, I wrote this Article for legal professionals new to blockchains and crypto. This target audience likely is most interested in crypto for its legal implications—depending on whether it functions as currencies, securities, commodities, or properties; however, legal professionals also need to understand crypto’s origin, how transactions work, and how they are governed.
Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng
Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng
Journal of System Simulation
Abstract: The advancement of artificial intelligence technology has significantly enhanced the utilization of mobile robots in various fields such as industry, aerospace, and agriculture. The autonomous obstacle avoidance capability of these robots is crucial to the safety and efficiency of their operations in diverse settings. Path planning, a key technology in obstacle avoidance, plays an essential role in the overall performance of these systems. This paper presents a comprehensive review of path planning technology for mobile robots, categorizing the algorithms into global planning and local obstacle avoidance according to their operational requirements. Specific focus is given to the global planning …
Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang
Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang
Journal of System Simulation
Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …
Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang
Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang
Journal of System Simulation
Abstract: The rapid development of the drone industry has promoted the opening of low-altitude, forming a wave of ultra-low-altitude air transportation in cities sweeping over the world. However, the existing trajectory planning algorithms do not consider the division method and operating rules of the ultra-low-altitude airspace. They are not suitable for the collaborative trajectory planning of multiple UAVs in the urban ultra-low-altitude air transportation scenario, which may restrict the development of the ultra-low-altitude air transportation industry. This paper explores a multi-UAV collaborative trajectory planning method for urban ultra-low-altitude air transportation scenario based on the airspace flight altitude layer architecture. Specifically, …
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Journal of System Simulation
Abstract: Aiming at the lack of directionality of traditional dot product attention, this paper proposes a directed attention model (DAM) based on cosine similarity. To effectively represent the direction relationship between the spatial and temporal features of video frames, the paper defines the relationship function in the attention mechanism using the cosine similarity theory, which can remove the absolute value of the relationship between features. To reduce the computational burden of the attention mechanism, the operation is decomposed from two dimensions of time and space. The computational complexity is further optimized by combining linear attention operation. The experiment is divided …
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Journal of System Simulation
Abstract: Hardware-in-the-loop simulation system is a complex distributed simulation system, and its design and integration directly affect the system performance and construction goals. Based on years of experience, this paper first summarizes the design of the overall scheme and analyzes the performance requirements of real-time, compatibility, scalability, and security. Then, the paper describes the overall scheme of a typical hardware-in-the-loop simulation system, including the functional hierarchy, operation mechanism, and structural composition. Finally, it summarizes the contents and steps of the system integration testing, acceptance testing, and credibility evaluation method.