The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater...The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.展开更多
The Internet of Things(IoT)is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems.These networks of wireless sensors monitor...The Internet of Things(IoT)is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems.These networks of wireless sensors monitor the physical environment and report the collected data to the base station,allowing for smarter decisions.Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane.However,in some application areas,such as various surveillances,underwater monitoring systems,and various environmental monitoring applications,wireless sensors are deployed in a three-dimensional plane.Recently,localization-based applications have emerged as one of the most promising services related to IoT.In this paper,we propose a novel distributed range-free algorithm for node localization in wireless sensor networks.The proposed three-dimensional hop localization algorithm is based on the distance error correction factor.In this algorithm,the error decreases with the localization process.The distance correction factor is used at various stages of the localization process,which ultimately mitigates the error.We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm.The simulation results are compared with some of the well-known existing algorithms in the literature.The results show that the proposed three-dimensional error-correctionbased algorithm performs better than existing algorithms.展开更多
Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization...Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization is the process of identifying the target node’s location.In this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models.Initially,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D WSN.The position of the anchor nodes is fixed for detecting the location of the target.Further,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node localization.In the regular and irregular surfaces,this hybrid algorithm effectively performs the localization process.The suggested hybrid algorithm converges very fast in the three-dimensional(3D)environment.The accuracy of the proposed node localization process is 94.25%.展开更多
To improve the sense of reality on perception, an improved algorithm of 3D shape haptic rendering is put forward based on a finger mounted vibrotactile device. The principle is that the interactive information and the...To improve the sense of reality on perception, an improved algorithm of 3D shape haptic rendering is put forward based on a finger mounted vibrotactile device. The principle is that the interactive information and the shape information are conveyed to users when they touch virtual objects at mobile terminals by attaching the vibrotactile feedback on a fingertip. The extraction of shape characteristics, the interactive information and the mapping of shape in formation of vibration stimulation are key parts of the proposed algorithm to realize the real tactile rendering. The contact status of the interaction process, the height information and local gradient of the touch point are regarded as shape information and used to control the vibration intension, rhythm and distribution of the vibrators. With different contact status and shape information, the vibration pattern can be adjusted in time to imitate the outlines of virtual objects. Finally, the effectiveness of the algorithm is verified by shape perception experiments. The results show that the improved algorithm is effective for 3D shape haptic rendering.展开更多
Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of iden...Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of identifying puncture points,a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction.According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal,the proposed algorithm can provide an optimal route for a drainage tube for the hematoma,the precise position of the puncture point,and preoperative planning information,which have considerable instructional significance for clinicians.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42172312 and 52211540395)support from the Institut Universitaire de France(IUF).
文摘The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.
基金the Research Grant of Kwangwoon University in 2020.
文摘The Internet of Things(IoT)is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems.These networks of wireless sensors monitor the physical environment and report the collected data to the base station,allowing for smarter decisions.Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane.However,in some application areas,such as various surveillances,underwater monitoring systems,and various environmental monitoring applications,wireless sensors are deployed in a three-dimensional plane.Recently,localization-based applications have emerged as one of the most promising services related to IoT.In this paper,we propose a novel distributed range-free algorithm for node localization in wireless sensor networks.The proposed three-dimensional hop localization algorithm is based on the distance error correction factor.In this algorithm,the error decreases with the localization process.The distance correction factor is used at various stages of the localization process,which ultimately mitigates the error.We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm.The simulation results are compared with some of the well-known existing algorithms in the literature.The results show that the proposed three-dimensional error-correctionbased algorithm performs better than existing algorithms.
基金appreciation to King Saud University for funding this research through the Researchers Supporting Program number(RSPD2024R918),King Saud University,Riyadh,Saudi Arabia.
文摘Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization is the process of identifying the target node’s location.In this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models.Initially,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D WSN.The position of the anchor nodes is fixed for detecting the location of the target.Further,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node localization.In the regular and irregular surfaces,this hybrid algorithm effectively performs the localization process.The suggested hybrid algorithm converges very fast in the three-dimensional(3D)environment.The accuracy of the proposed node localization process is 94.25%.
基金The National Natural Science Foundation of China(No.61473088)Six Talent Peaks Projects in Jiangsu Province
文摘To improve the sense of reality on perception, an improved algorithm of 3D shape haptic rendering is put forward based on a finger mounted vibrotactile device. The principle is that the interactive information and the shape information are conveyed to users when they touch virtual objects at mobile terminals by attaching the vibrotactile feedback on a fingertip. The extraction of shape characteristics, the interactive information and the mapping of shape in formation of vibration stimulation are key parts of the proposed algorithm to realize the real tactile rendering. The contact status of the interaction process, the height information and local gradient of the touch point are regarded as shape information and used to control the vibration intension, rhythm and distribution of the vibrators. With different contact status and shape information, the vibration pattern can be adjusted in time to imitate the outlines of virtual objects. Finally, the effectiveness of the algorithm is verified by shape perception experiments. The results show that the improved algorithm is effective for 3D shape haptic rendering.
基金funded by the National Science Foundation of China,Nos.51674121 and 61702184the Returned Overseas Scholar Funding of Hebei Province,No.C2015005014the Hebei Key Laboratory of Science and Application,and Tangshan Innovation Team Project,No.18130209B.
文摘Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of identifying puncture points,a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction.According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal,the proposed algorithm can provide an optimal route for a drainage tube for the hematoma,the precise position of the puncture point,and preoperative planning information,which have considerable instructional significance for clinicians.
