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Articles 1591 - 1620 of 5401
Full-Text Articles in Artificial Intelligence and Robotics
Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth
Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth
Publications
Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Doctoral Dissertations and Master's Theses
Accurate characterization of fragment fly-out properties from high-speed warhead detonations is essential for estimation of collateral damage and lethality for a given weapon. Real warhead dynamic detonation tests are rare, costly, and often unrealizable with current technology, leaving fragmentation experiments limited to static arena tests and numerical simulations. Stereoscopic imaging techniques can now provide static arena tests with time-dependent tracks of individual fragments, each with characteristics such as fragment IDs and their respective position vector. Simulation methods can account for the dynamic case but can exclude relevant dynamics experienced in real-life warhead detonations. This research leverages machine learning methodologies to …
Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong
Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong
Research Collection School Of Computing and Information Systems
Electricity demands are increasing significantly and the traditional power grid system is facing huge challenges. As the desired next-generation power grid system, smart grid can provide secure and reliable power generation, and consumption, and can also realize the system’s coordinated and intelligent power distribution. Coordinating grid power distribution usually requires mutual communication between power distributors to accomplish coordination. However, the power network is complex, the network nodes are far apart, and the communication bandwidth is often expensive. Therefore, how to reduce the communication bandwidth in the cooperative power distribution process task is crucially important. One way to tackle this problem …
Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong
Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong
Research Collection School Of Computing and Information Systems
Electricity demands are increasing significantly and the traditional power grid system isfacing huge challenges. As the desired next-generation power grid system, smart grid can providesecure and reliable power generation, and consumption, and can also realize the system’s coordinatedand intelligent power distribution. Coordinating grid power distribution usually requiresmutual communication between power distributors to accomplish coordination. However, the powernetwork is complex, the network nodes are far apart, and the communication bandwidth is oftenexpensive. Therefore, how to reduce the communication bandwidth in the cooperative power distributionprocess task is crucially important. One way to tackle this problem is to build mechanismsto selectively send out …
Supporting The Discovery, Reuse, And Validation Of Cybersecurity Requirements At The Early Stages Of The Software Development Lifecycle, Jessica Antonia Steinmann
Supporting The Discovery, Reuse, And Validation Of Cybersecurity Requirements At The Early Stages Of The Software Development Lifecycle, Jessica Antonia Steinmann
Doctoral Dissertations and Master's Theses
The focus of this research is to develop an approach that enhances the elicitation and specification of reusable cybersecurity requirements. Cybersecurity has become a global concern as cyber-attacks are projected to cost damages totaling more than $10.5 trillion dollars by 2025. Cybersecurity requirements are more challenging to elicit than other requirements because they are nonfunctional requirements that requires cybersecurity expertise and knowledge of the proposed system. The goal of this research is to generate cybersecurity requirements based on knowledge acquired from requirements elicitation and analysis activities, to provide cybersecurity specifications without requiring the specialized knowledge of a cybersecurity expert, and …
Parallel Simulation System Of Equipment Precision Maintenance Based On Cloud-Edge-End Architecture, Yanqiang Di, Ting Li, Shaochong Feng, Qiongyao Liu, Jianhong Lü, Zhijia Chen, Yang Zhang, Pengfei Cao
Parallel Simulation System Of Equipment Precision Maintenance Based On Cloud-Edge-End Architecture, Yanqiang Di, Ting Li, Shaochong Feng, Qiongyao Liu, Jianhong Lü, Zhijia Chen, Yang Zhang, Pengfei Cao
Journal of System Simulation
Abstract: Aiming at the demands of equipment precision maintenance, based on the previous research results of equipment parallel simulation, the algorithm of equipment remaining useful life (RUL)prediction is optimized and a parallel simulation system for equipment precision maintenance with cloud-edge-end architecture is designed. At the equipment end, the system collects equipment status data and preprocesses it with edge devices. At the cloud end, based on simulation model, in parallel with the equipment entity, the system dynamically predicts the RUL of equipment. The prediction results are applied to the formulation and deduction of equipment maintenance plans to support the equipment …
Unmanned Air Vehicles Launching Aircraft Combat System And Key Technologies For Penetrating Counterair, Minghao Li, Wenhao Bi, An Zhang, Wenxuan Sun
Unmanned Air Vehicles Launching Aircraft Combat System And Key Technologies For Penetrating Counterair, Minghao Li, Wenhao Bi, An Zhang, Wenxuan Sun
Journal of System Simulation
Abstract: Penetrating counterair is an important countermeasure to the anti-access/area denial environment. Under this operational requirement, the unmanned air vehicles launching aircraft (UAVLA)has received much attention due to the advantages of load quantity and variety, operational range and duration, and development time and cost. Based on the review of the concept development and supporting research related to the UAVLA, the top-level concepts of operations such as the component systems,operational process, operational events tracking, and information interaction of the UAVLA combat system (UAVLACS) are designed. The key technologies of the system are prospected from four aspects:intelligent cognition of battlefield situation under …
Opnet Based Simulation Of Hybrid Tdma Protocol For Helicopters Datalink, Yanfang Fu, Nan Zhang, Jianing Wei, Shaochun Qu, Ying Lu, Chang Liu
Opnet Based Simulation Of Hybrid Tdma Protocol For Helicopters Datalink, Yanfang Fu, Nan Zhang, Jianing Wei, Shaochun Qu, Ying Lu, Chang Liu
Journal of System Simulation
Abstract: For the current time slot allocation problem of the data link, an improved hybrid time slot allocation protocol based on grey relational analysis is proposed and implemented. Through the aggregation of throughput, delay and load of current message buffer by grey relational analysis, the comprehensive evaluation index is obtained, and the time slot is allocated dynamically. The fixed time slot allocation is also adopted to ensure that at least one time slot is available for nodes in the network.Simulation results show that compared with the fixed TDMA(time division multiple access) protocol and the P-TDMA(priority-TDMA) protocol, the proposed protocol …
Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen
Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen
Journal of System Simulation
Abstract: As the key technology of multi-agent game confrontation, opponent modeling is a typical cognitive modeling method of agent's behavior. Several typical models of multi-agent game confrontation,non-stationary problems, and meta-game theory are introduced; opponent modeling methods that concludes the frontier theory of opponent modeling are summarized, and the applications and challenges are analyzed. Based on the theory of meta-game, a general opponent modeling framework is constructed with three modules: opponent policy recognition and generation, opponent policy space reconstruction,and opponent exploitation. It is expected to provide theoretical and methodological reference for opponent modeling in multi-agent game confrontation.
Siamese Object Tracking Algorithm Combined With The Intersection Over Union Loss, Wei Zhou, Yuxiang Liu, Guangping Liao, Xin Ma
Siamese Object Tracking Algorithm Combined With The Intersection Over Union Loss, Wei Zhou, Yuxiang Liu, Guangping Liao, Xin Ma
Journal of System Simulation
Abstract: To improve the accuracy of the object bounding box regression prediction of the SiamRPN,solve the problem of low discrimination of positive samples in classification prediction and the lack of correlation between regression prediction and classification prediction, an improved object tracking algorithm of SiamRPN which combined with IoU(intersection over union) loss is proposed. A joint optimization module of IoU-smooth L1 is designed to optimize the IoU loss of the best positive sample and the smooth L1 loss of other positive samples jointly. According to the regression prediction results, the weighted classification prediction is performed on the positive samples with the …
Relative-Residual-Based Dynamic Schedule For Decoding Of Ldpc Codes, Fatang Chen, Hebin Li, Zhihao Zhang, Zhiqiang Mei
Relative-Residual-Based Dynamic Schedule For Decoding Of Ldpc Codes, Fatang Chen, Hebin Li, Zhihao Zhang, Zhiqiang Mei
Journal of System Simulation
Abstract: In order to solve the problems of the oscillation phenomenon and greedy characteristics in the dynamic scheduling decoding algorithm for low-density parity-check (LDPC) codes, the relative-residual-based dynamic schedule (RRB-BP) algorithm is proposed based on variable-to-check residual belief propagation (VC-RBP) algorithm. The variable nodes are grouped, then the relative residual value of the message passed by the variable nodes to the check node is taken as a reference, and the node with the largest relative residual value is updated in priority to accelerate the decoding convergence speed. For variable nodes oscillating in the decoding process, the posterior LLR (log likelihood …
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Journal of System Simulation
Abstract: Based on the comprehensive consideration of economic indicators and environmental factors, the energy-efficient scheduling problem of multi-objective flexible job shop with uncertain processing time is studied. The interval number is used to describe uncertain processing time of the workpiece, and the optimization model for energy-efficient problem of interval flexible job shop scheduling is established to minimize the maximum interval completion time and total energy consumption. According to the domination relation of interval possibility degree, an effective interval multi-objective evolutionary algorithm is designed. The simulation experiments of the interval multi-objective evolutionary algorithm, SPEA-II and NSGA-II are carried out through 15 …
Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu
Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu
Journal of System Simulation
Abstract: In the early stage of major public health events, medical supplies are rapidly consumed and severely insufficient. In order to distribute medical supplies in a reasonable and efficient manner, research on the distribution of emergency medical materials is carried out. The entropy method is introduced to determine the urgency of demand points, thus could give priority to the demand points with high urgency and make the distribution routing as short as possible on that basis to realize the construction of a split delivery and multi-objective emergency medical materials scheduling model based on different urgency of demand points. Meanwhile the …
Design Of Optical Compound Eye Simulation Software For Small Aircraft Applications, Qiming Qi, Ruigang Fu, Ping Wang, Min Wang, Hongqi Fan
Design Of Optical Compound Eye Simulation Software For Small Aircraft Applications, Qiming Qi, Ruigang Fu, Ping Wang, Min Wang, Hongqi Fan
Journal of System Simulation
Abstract: Optical compound eye has the advantages of large field of view, multiple viewing angles and high resolution. With another advantage that it can conformal combine with small aircraft, optical compound eye has application value in reconnaissance and surveillance, target detection, image navigation and other aspects. An optical compound eye simulation software for small aircraft is designed for the current situation of long development period of optical compound eye design and high cost of flight test in practical applications. The software integrates compound eye imaging, aircraft simulation and data management, and each functional module is extensible. The simulation results show …
Mesoscopic Modeling And Simulation Of Mixed Traffic Flow Of Buses And Vehicles, Yiting Zhu, Yun Yan, Zhaocheng He
Mesoscopic Modeling And Simulation Of Mixed Traffic Flow Of Buses And Vehicles, Yiting Zhu, Yun Yan, Zhaocheng He
Journal of System Simulation
Abstract: Aiming at the problem that the existing mesoscopic simulation models only convert buses into several standard vehicles and ignore the movement difference between buses and vehicles, a mesoscopic simulation model of mixed traffic flow is proposed. In the process of road driving, on the one aspect, we consider the feature that bus speed is usually lower than vehicle speed, and correspondingly establish the reduction function of bus speed; on the other aspect, we consider the influences of bus-station queue overflow on the adjacent lanes, and correspondingly construct the lane-based speed model of mixed flow.Moreover, we use the …
Electrical Resistance Tomography And Flow Pattern Identification Method Based On Deep Residual Neural Network, Weiguo Tong, Shichao Zeng, Lifeng Zhang, Zhe Hou, Jiayue Guo
Electrical Resistance Tomography And Flow Pattern Identification Method Based On Deep Residual Neural Network, Weiguo Tong, Shichao Zeng, Lifeng Zhang, Zhe Hou, Jiayue Guo
Journal of System Simulation
Abstract: Aiming at the low accuracy of inverse problem imaging and flow pattern recognition in electrical resistance tomography (ERT), a two-phase flow electrical resistance tomography and flow pattern recognition method based on the deep residual neural network is proposed. The finite element method is used to model the ERT forward problem to construct the "boundary voltage-conductivity distribution-flow pattern category" dataset of various gas-liquid two-phase flow distributions. The residual neural network for ERT image reconstruction and flow pattern identification of gas-liquid two-phase flow is built and trained. The two outputs of the residual neural network are processed respectively to obtain …
Study On Invulnerability Of Urban Agglomeration Passenger Traffic Network Considering Time Characteristics, Chengbing Li, Yunfei Li, Peng Wu
Study On Invulnerability Of Urban Agglomeration Passenger Traffic Network Considering Time Characteristics, Chengbing Li, Yunfei Li, Peng Wu
Journal of System Simulation
Abstract: The cascading failure invulnerability study of comprehensive passenger transport network in urban agglomeration is helpful to improve the safety and transportation efficiency of intercity travel. In order to be consistent with the actual situation, a comprehensive passenger transport network model for urban agglomerations is constructed based on multi-layer complex network theory and actual passenger flow. The passenger transport network cascading failure invulnerability model considering time characteristics is established with unit time step. The spatial and temporal evaluation indexes are put forward to analyze the network situation in each period. Taking Hu-Bao-E-Yu urban agglomeration as an example, the results show …
Research On Ofdm Signal Detection Method Based On Intrawell Stochastic Resonance Of Bistable System, Gaohui Liu, Ying Liang
Research On Ofdm Signal Detection Method Based On Intrawell Stochastic Resonance Of Bistable System, Gaohui Liu, Ying Liang
Journal of System Simulation
Abstract: In order to solve the problem of weak OFDM (orthogonal frequency division multiplexing)signal detection at the receiver in OFDM transmission system, the intrawell stochastic resonance of bistable system is combined with the OFDM signal enhancement and demodulation process. Analytical expression is derived for the time required to change from zero state to potential well state for the intrawell stochastic resonance system under the excitation of multicarrier signals, and the energy loss of multicarrier signals in one symbol caused by the transient response is analyzed. The steady-state output equation of system is derived, and the problem of superimposing the …
Architecture Design And Prototype Verification Of Railway Vehicle Dynamics Cloud Platform, Junjie Sheng, Zhao Tang, Shaodi Dong, Shuyang Wu, Hao Liang
Architecture Design And Prototype Verification Of Railway Vehicle Dynamics Cloud Platform, Junjie Sheng, Zhao Tang, Shaodi Dong, Shuyang Wu, Hao Liang
Journal of System Simulation
Abstract: Since almost all the software in the railway vehicle field is controlled by foreign capital, it is difficult to catch up with the development of independent vehicle system software based on single machine deployment mode in a short time. In view of this, a set of autonomous and controllable vehicle system dynamics software architecture based on cloud platform is proposed. Based on the railway vehicle system dynamics and cloud services, a cloud platform with automatic process modeling, cloud computing,post-processing analysis is built. A simulation model of a trailer caris applied in the platform, and compared with the SIMPACK …
A High Resolution Reconstruction Method Of Temperature Distribution In Acoustic Tomography, Lifeng Zhang, Yu Miao
A High Resolution Reconstruction Method Of Temperature Distribution In Acoustic Tomography, Lifeng Zhang, Yu Miao
Journal of System Simulation
Abstract: Accurate measurement temperature distribution is important for industrial production. In order to solve the number of mesh divisions will impact reconstruction accuracy in acoustic tomography, the TR-RBF (Tikhonov regularization-radial basis function) reconstruction algorithm is rebuilt to reconstruct the temperature field with high resolution. The Tikhonov regularization is used to reconstruct the ultrasound time of flight (TOF) to obtain a temperature distribution on coarse grids, and use local weighted regression method to smooth processing; use RBF neural networks to predict the temperature distribution on fine grids. Through numerical simulation with and without noise, compared with ART,SVD and Tikhonov, the proposed …
Research On Cooperative Adaptive Cruise Control Strategy Based On Improved Mpc, Qiming Wang, Jiangyue Jiang, Zhichao Lü, Hanzu Zhang
Research On Cooperative Adaptive Cruise Control Strategy Based On Improved Mpc, Qiming Wang, Jiangyue Jiang, Zhichao Lü, Hanzu Zhang
Journal of System Simulation
Abstract: To solve the problems of environmental interference, sensor noise and poor tracking stability of time-varying speed, an improved MPC (model predictive control) algorithm based on KF (kalman filtering) is proposed. The longitudinal kinematics model of CACC(cooperative adaptive cruise control)between vehicles is established and the discrete state space equation is created. KF is used to reduce the noise of state variables, and at the same time, the prediction model is designed for robustness. The CACC control objectives are analyzed under different working conditions and the objective optimization functions are created. Verify by building Simulink and CarSim co-simulation model, the simulation …
Simulation Of The Market Exclusive Competition Between Platforms, Wen Zheng, Zhe Zhang, Jingyi Zhu
Simulation Of The Market Exclusive Competition Between Platforms, Wen Zheng, Zhe Zhang, Jingyi Zhu
Journal of System Simulation
Abstract: As for the problem of an exclusive competition between the platforms, 2 competing PlatformsAgent, 100 ConsumersAgent and 300 SellersAgent are introduced and encapsulated into a closed market environment in BarriersModelSwarm. A two-sided market system is constructed with the cross-network externality. Through BarriersObserverSwarm, the Agents attribute information and behavior strategy are cross-called, and the virtual connection class Orderand ArrayList class in the Virtual Connection Classes are generated to run cyclically. The unilateral dependence degree of Consumers/SellersAgent is triggered, which restores the exclusive of the two-sided market competition in comparison with the platform transaction scale, market concentration, and platform cumulative capital. …
Turbofan Engine Fault Prediction Based On Evidential Reasoning And Belief Rule Base, Hailong Zhu, Ruxia Jia, Liang Zhang, Wei He
Turbofan Engine Fault Prediction Based On Evidential Reasoning And Belief Rule Base, Hailong Zhu, Ruxia Jia, Liang Zhang, Wei He
Journal of System Simulation
Abstract: Aiming at the fault prediction problem of a turbofan engine, a fault prediction model based on evidential reasoning (ER) and belief rule base (BRB) is proposed. In order to describe the health state of turbofan engine, ER algorithm is adopted to fuse the state information. Combined with prior knowledge, a hybrid driven simulation prediction of BRB model is established. Projection covariance matrix adaptive evolution strategy (P-CMA-ES) is used to optimize the model parameters. The validity of the model is verified by experiments. Experimental results show that the proposed method not only accurately predicts the probability of failure …
Modulation Recognition Algorithm Based On Truncated Migration And Parallel Resnet, Yecai Guo, Qingwei Wang
Modulation Recognition Algorithm Based On Truncated Migration And Parallel Resnet, Yecai Guo, Qingwei Wang
Journal of System Simulation
Abstract: A truncated migration data preprocessing algorithm is proposed for the problem of limited time series characteristics of the signal extracted by convolutional neural network. The distance unit at one end of the sampling matrix is truncated, migrated to the other end to form a new matrix, allowing the convolutional neural network to extract more sampling points and compare more symbolic information.An improved parallel ResNet is proposed, which focuses on features in both horizontal and vertical directions simultaneously by two parallel branches. The results show that the algorithm has an accuracy rate of about 10% higher than that of ordinary …
A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail
A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail
Theses and Dissertations
Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …
Products Pricing And Return Strategies For The Dual Channel Retailers, Jian Liu, Xinyue Sun, Yanyan Liu
Products Pricing And Return Strategies For The Dual Channel Retailers, Jian Liu, Xinyue Sun, Yanyan Liu
Electrical and Computer Engineering Faculty Research & Creative Works
This paper analyzed how different return strategies and return rates affect dual-channel retailers' profits and channel pricings. Return can stimulate sales; however, the return has presented significant challenges to retailers. The return has long been studied to maximize profit and pricing; however, the different return strategies for dual-channel retailers affect channel both. This paper aimed to study whether or not dual-channel retailers should allow customers to return items in two channels and whether or not the retailer should contract with the manufacturers and pay extra fees to return products. This study indicated when the retailer should allow customers' returns to …
Two-Phase Matheuristic For The Vehicle Routing Problem With Reverse Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Two-Phase Matheuristic For The Vehicle Routing Problem With Reverse Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Cross-dockingis a useful concept used by many companies to control the product flow. It enables the transshipment process of products from suppliers to customers. This research thus extends the benefit of cross-docking with reverse logistics, since return process management has become an important field in various businesses. The vehicle routing problem in a distribution network is considered to be an integrated model, namely the vehicle routing problem with reverse cross-docking (VRP-RCD). This study develops a mathematical model to minimize the costs of moving products in a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. A matheuristic based …
A Carbon-Aware Planning Framework For Production Scheduling In Mining, Nurual Asyikeen Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi
A Carbon-Aware Planning Framework For Production Scheduling In Mining, Nurual Asyikeen Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi
Research Collection School Of Computing and Information Systems
Managing the flow of excavated materials from a mine pit and the subsequent processing steps is the logistical challenge in mining. Mine planning needs to consider various geometric and resource constraints while maximizing the net present value (NPV) of profits over a long horizon. This mine planning problem has been modelled and solved as a precedence constrained production scheduling problem (PCPSP) using heuristics, due to its NP-hardness. However, the recent push for sustainable and carbon-aware mining practices calls for new planning approaches. In this paper, we propose an efficient temporally decomposed greedy Lagrangian relaxation (TDGLR) approach to maximize profits while …
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Journal of System Simulation
Abstract: Abstruct: A lot of research achievements have been made in image dehazing based on neural network,but there aiming at the fog residue, even the color distortion and texture loss, in complex outdoor image dehazing, an image dehazing network based on densely connected residual block and channel pixel attention is proposed. Densely connected residual blocks are used to extract and fuse the features of foggy images,and the repair module with channel pixel attention mechanism is used to repair the color and texture of the feature maps. The experimental results show that, compared with the existing methods, the proposed method and …
Research On Motion Recognition And Tracking For Space Survey And Launch Tasks, Bin Ren, Xiaoyu Wang
Research On Motion Recognition And Tracking For Space Survey And Launch Tasks, Bin Ren, Xiaoyu Wang
Journal of System Simulation
Abstract: Space survey and launch task has high precision and long cycle, and needs to be exposed to direct sunlight for a long time, so that the non-contact action calibration and comparison in a virtual working environment is an efficient way to improve the mission completion success rate. Aiming at the real-time motion tracking of aerospace personnel, a keyframe optimization algorithm for the action recognition is proposed. According to the bone data in the depth image, the bone features are extracted, and the keyframes are extracted by the feature threshold. The characteristic data of the keyframe is input into bi-directional …