At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper propo...At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper proposes a localization algorithm assisted by mobile anchor node and based on region determination(LMRD), which not only improves the positioning accuracy of nodes positioning but also reduces the energy consumption. This algorithm is divided into two stages: region determination stage and location positioning stage. In the region determination stage, the target region is divided into several sub-regions by the region division strategy with the smallest overlap rate which can reduce the number of virtual anchor nodes and lock the target node to a sub-region, and then through the planning of mobile nodes to optimize the travel path, reduce the moving distance, and reduce system energy consumption. In the location positioning stage, the target node location can be calculated using the HILBERT path planning and trilateration. The simulation results show that the proposed algorithm can improve the positioning accuracy when the energy consumption is reduced.展开更多
Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location i...Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.展开更多
In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioni...In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.展开更多
For mobile anchor node static path planning cannot accord the actual distribution of node for dynamic adjustment. We take advantage of the high localization accuracy and low computational complexity of ad-hoc localiza...For mobile anchor node static path planning cannot accord the actual distribution of node for dynamic adjustment. We take advantage of the high localization accuracy and low computational complexity of ad-hoc localization system( AHLos)algorithm. This article introduces mobile anchor nodes instead of the traditional fixed anchor nodes to improve the algorithm. The result shows that, through introduce the mobile anchor node, the information of initial anchor nodes can be configured more flexible.Meanwhile,with the use of the approximate location and the transition path,the distance and energy consumption of the mobile anchor node is greatly reduced.展开更多
Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN...Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so on.In spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of anchors.The efficiency of the WSN can be considerably influenced by the node localization accuracy.Therefore,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)forWSN.The major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in theWSN.Since the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the technique.The application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO algorithm.In order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.展开更多
For the application of wireless sensor networks in the military field, one of the main challenges is security. To solve the problem of verifying the location claim for a node, a new location verifica- tion algorithm c...For the application of wireless sensor networks in the military field, one of the main challenges is security. To solve the problem of verifying the location claim for a node, a new location verifica- tion algorithm called node cooperation based location secure verification （NCBLSV） algorithm is proposed. NCBLSV could verify malicious nodes by contrasting neighbor nodes and nodes under beam width angle using an adaptive array antenna at a base point. Simulation experiments are con- ducted to evaluate the performance of this algorithm by varying the communication range and the an- tenna beam width angle. Results show that NCBLSV algorithm has high probability of successful ma- licious nodes detection and low probability of false nodes detection. Thus, it is proved that the NCBLSV algorithm is useful and necessary in the wireless sensor networks security.展开更多
The localization of ion channels on myelinated axon is closely related with the saltatory conduction of action potential (AP). Abnormal changes in these channels contribute to multiple mental diseases. The development...The localization of ion channels on myelinated axon is closely related with the saltatory conduction of action potential (AP). Abnormal changes in these channels contribute to multiple mental diseases. The development of cryo-Electron Tomography (cryo-ET) has provided a promising prospect for peering into ion channels in their native environment at high resolution. Previous achievements are reviewed here on cryo-ET. Accordingly, a cryo-ET workflow is designed for understanding ion channels localization in myelinated axon, especially nodes of Ranvier, which are significant for the saltatory conduction involved in the propagation of high-speed AP. The workflow is divided into six parts: the preparation of neural cultures with myelin, antibodies and immunofluorescence staining, frozen-hydrated sample preparation, cryo-ET imaging, cryo-correlative light and electron microscopy (cryo-CLEM) imaging, three-dimensional (3D) reconstruction and refinement. The purpose is to conceive a possible solution for the problems related to ion channel compounds including localization, conformation dynamics, accessory structures of ion channel and transient regulatory factors, and thus provide insights into treating neurological diseases caused by abnormal ion channels activity.展开更多
Localization of the sensor nodes is a key supporting technology in wireless sensor networks （WSNs）. In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter （KF） is ...Localization of the sensor nodes is a key supporting technology in wireless sensor networks （WSNs）. In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter （KF） is proposed. Mobile node movement model is analyzed and online sequential iterative method is used to compute location result. The detailed steps of mobile sensor node self-localization adopting extended Kalman filter （EKF） is designed. The simulation results show that the accuracy of the localization estimator scheme designed is better than those of maximum likelihood estimation （MLE） and traditional KF algorithm.展开更多
In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization...In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.展开更多
To alleviate the localization error introduced by irregular sensor network deployment, a new mo bile path localization based on key nodes （MPLPK） protocol is proposed. It can recognize all con cave/convex nodes in t...To alleviate the localization error introduced by irregular sensor network deployment, a new mo bile path localization based on key nodes （MPLPK） protocol is proposed. It can recognize all con cave/convex nodes in the network as fixed anchor nodes, and simplify the following localization process based on these key nodes. The MPLPK protocol is composed of three steps. After all key nodes are found in the network, a mobile node applying improved minimum spanning tree （MST） algorithm is introduced to traverse and locate them. By taking the concave/convex nodes as anchors, the complexity of the irregular network can be degraded. And the simulation results demonstrate that MPEPK has 20% to 40% accuracy improvements than connectivity-based and anchor-free three-di- mensional localization （CATL） and approximate convex decomposition based localization （ACDL）.展开更多
Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major proble...Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor nodes.WSN comprises a massive number of SNs and records the position of the nodes,which becomes a tedious process.Besides,the SNs might be subjected to node mobility and the position alters with time.So,a precise node localization(NL)manner is required for determining the location of the SNs.In this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for WSN.The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes.The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season.In addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown SNs.For demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.展开更多
Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand...Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.展开更多
In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization...In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.展开更多
Major fields such as military applications,medical fields,weather forecasting,and environmental applications use wireless sensor networks for major computing processes.Sensors play a vital role in emerging technologie...Major fields such as military applications,medical fields,weather forecasting,and environmental applications use wireless sensor networks for major computing processes.Sensors play a vital role in emerging technologies of the 20th century.Localization of sensors in needed locations is a very serious problem.The environment is home to every living being in the world.The growth of industries after the industrial revolution increased pollution across the environment.Owing to recent uncontrolled growth and development,sensors to measure pollution levels across industries and surroundings are needed.An interesting and challenging task is choosing the place to fit the sensors.Many meta-heuristic techniques have been introduced in node localization.Swarm intelligent algorithms have proven their efficiency in many studies on localization problems.In this article,we introduce an industrial-centric approach to solve the problem of node localization in the sensor network.First,our work aims at selecting industrial areas in the sensed location.We use random forest regression methodology to select the polluted area.Then,the elephant herding algorithm is used in sensor node localization.These two algorithms are combined to produce the best standard result in localizing the sensor nodes.To check the proposed performance,experiments are conducted with data from the KDD Cup 2018,which contain the name of 35 stations with concentrations of air pollutants such as PM,SO_(2),CO,NO_(2),and O_(3).These data are normalized and tested with algorithms.The results are comparatively analyzed with other swarm intelligence algorithms such as the elephant herding algorithm,particle swarm optimization,and machine learning algorithms such as decision tree regression and multi-layer perceptron.Results can indicate our proposed algorithm can suggest more meaningful locations for localizing the sensors in the topology.Our proposed method achieves a lower root mean square value with 0.06 to 0.08 for localizing with Stations 1 to 5.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
Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area ...Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area and they can easily track the information. It will help them to block the signal transmission and reception. Now, the intention is to track the position of the jammer where it is fixed. The existing methods rely on the indirect measurements and the boundary node to find the jammer’s position which degrades the accuracy of the localization. To improve the efficiency, this paper proposed an efficient method namely Coincered Node Based Localization of jammers to find the position of the jammer with high level of accuracy. The proposed system uses the direct measurements, which is the jammer signal strength. The effectiveness can also be increased by using the coincered node that will stumble across the true position of the jammer. The proposed work is compared with existing methods. Then the proposed mechanism proves better to find the jammer location. The simulation results estimate that the accuracy of the localization achieves better performance than the existing schemes.展开更多
This article analyzes the shift factors of the descending node local time for sun-synchronous satellites and proposes a shift control method to keep the local time shift within an allowance range. It is found that the...This article analyzes the shift factors of the descending node local time for sun-synchronous satellites and proposes a shift control method to keep the local time shift within an allowance range. It is found that the satellite orbit design and the orbit injection deviation are the causes for the initial shift velocity, whereas the atmospheric drag and the sun gravitational perturbation produce the shift acceleration. To deal with these shift factors, a shift control method is put forward, through such methods as orbit variation design, orbit altitude, and inclination keeping control. The simulation experiment and practical application have proved the effectiveness of this control method.展开更多
BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.A...BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.AIM To clarify the anatomical basis of laparoscopic LLND in two fascial spaces and to evaluate its efficacy and safety in treating locally advanced low rectal cancer(LALRC).METHODS Cadaveric dissection was performed on 24 pelvises,and the fascial composition related to LLND was observed and described.Three dimensional-laparoscopic total mesorectal excision with LLND was performed in 20 patients with LALRC,and their clinical data were analyzed.RESULTS The cadaver study showed that the fascia propria of the rectum,urogenital fascia,vesicohypogastric fascia and parietal fascia lie side by side in a medial-lateral direction constituting the dissection plane for curative rectal cancer surgery,and the last three fasciae formed two spaces(Latzko's pararectal space and paravesical space)which were the surgical area for LLND.Laparoscopic LLND in two fascial spaces was performed successfully in all 20 patients.The median operating time,blood loss and postoperative hospitalization were 178(152-243)min,55(25-150)mL and 10(7-20)d,respectively.The median number of harvested LLNs was 8.6(6-12),and pathologically positive LLN metastasis was confirmed in 7(35.0%)cases.Postoperative complications included lower limb pain in 1 case and lymph leakage in 1 case.CONCLUSION Our preliminary surgical experience suggests that laparoscopic LLND based on fascial spaces is a feasible,effective and safe procedure for treating LALRC.展开更多
Identifying influential nodes in complex networks is one of the most significant and challenging issues,which may contribute to optimizing the network structure,controlling the process of epidemic spreading and accele...Identifying influential nodes in complex networks is one of the most significant and challenging issues,which may contribute to optimizing the network structure,controlling the process of epidemic spreading and accelerating information diffusion.The node importance ranking measures based on global information are not suitable for large-scale networks due to their high computational complexity.Moreover,they do not take into account the impact of network topology evolution over time,resulting in limitations in some applications.Based on local information of networks,a local clustering H-index(LCH)centrality measure is proposed,which considers neighborhood topology,the quantity and quality of neighbor nodes simultaneously.The proposed measure only needs the information of first-order and second-order neighbor nodes of networks,thus it has nearly linear time complexity and can be applicable to large-scale networks.In order to test the proposed measure,we adopt the susceptible-infected-recovered(SIR)and susceptible-infected(SI)models to simulate the spreading process.A series of experimental results on eight real-world networks illustrate that the proposed LCH can identify and rank influential nodes more accurately than several classical and state-of-the-art measures.展开更多
基金supported by National Natural Science Foundation of China (Nos. U1806201, 61671261)Key Research and Development Program of Shandong Province (No. 2016GGX101007)+1 种基金China Postdoctoral Science Foundation (No. 2017T100490)University Science and Technology Planning Project of Shandong Province (Nos. J17KA058, J17KB154)
文摘At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper proposes a localization algorithm assisted by mobile anchor node and based on region determination(LMRD), which not only improves the positioning accuracy of nodes positioning but also reduces the energy consumption. This algorithm is divided into two stages: region determination stage and location positioning stage. In the region determination stage, the target region is divided into several sub-regions by the region division strategy with the smallest overlap rate which can reduce the number of virtual anchor nodes and lock the target node to a sub-region, and then through the planning of mobile nodes to optimize the travel path, reduce the moving distance, and reduce system energy consumption. In the location positioning stage, the target node location can be calculated using the HILBERT path planning and trilateration. The simulation results show that the proposed algorithm can improve the positioning accuracy when the energy consumption is reduced.
文摘Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.
基金the Nation-alKey Research&Development Program of China un-der Grant No.2020YFC1511702 and Open Fund of IPOC(BUPT)No.IPOC2021ZT20.
文摘In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.
基金National Natural Science Foundations of China(Nos.U1162202,61203157)the Fundamental Research Funds for the Central Universities and Shanghai Leading Academic Discipline Project,China(No.B504)
文摘For mobile anchor node static path planning cannot accord the actual distribution of node for dynamic adjustment. We take advantage of the high localization accuracy and low computational complexity of ad-hoc localization system( AHLos)algorithm. This article introduces mobile anchor nodes instead of the traditional fixed anchor nodes to improve the algorithm. The result shows that, through introduce the mobile anchor node, the information of initial anchor nodes can be configured more flexible.Meanwhile,with the use of the approximate location and the transition path,the distance and energy consumption of the mobile anchor node is greatly reduced.
文摘Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so on.In spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of anchors.The efficiency of the WSN can be considerably influenced by the node localization accuracy.Therefore,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)forWSN.The major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in theWSN.Since the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the technique.The application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO algorithm.In order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.
基金Supported by the National High Technology Research and Development Programme of China （ No. 2004AA001210） and the National Natural Science Foundation of China （No. 60532030）.
文摘For the application of wireless sensor networks in the military field, one of the main challenges is security. To solve the problem of verifying the location claim for a node, a new location verifica- tion algorithm called node cooperation based location secure verification （NCBLSV） algorithm is proposed. NCBLSV could verify malicious nodes by contrasting neighbor nodes and nodes under beam width angle using an adaptive array antenna at a base point. Simulation experiments are con- ducted to evaluate the performance of this algorithm by varying the communication range and the an- tenna beam width angle. Results show that NCBLSV algorithm has high probability of successful ma- licious nodes detection and low probability of false nodes detection. Thus, it is proved that the NCBLSV algorithm is useful and necessary in the wireless sensor networks security.
文摘The localization of ion channels on myelinated axon is closely related with the saltatory conduction of action potential (AP). Abnormal changes in these channels contribute to multiple mental diseases. The development of cryo-Electron Tomography (cryo-ET) has provided a promising prospect for peering into ion channels in their native environment at high resolution. Previous achievements are reviewed here on cryo-ET. Accordingly, a cryo-ET workflow is designed for understanding ion channels localization in myelinated axon, especially nodes of Ranvier, which are significant for the saltatory conduction involved in the propagation of high-speed AP. The workflow is divided into six parts: the preparation of neural cultures with myelin, antibodies and immunofluorescence staining, frozen-hydrated sample preparation, cryo-ET imaging, cryo-correlative light and electron microscopy (cryo-CLEM) imaging, three-dimensional (3D) reconstruction and refinement. The purpose is to conceive a possible solution for the problems related to ion channel compounds including localization, conformation dynamics, accessory structures of ion channel and transient regulatory factors, and thus provide insights into treating neurological diseases caused by abnormal ion channels activity.
基金Project supported by the Shanghai Leading Academic Discipcine Project (Grant No.S30108)the National Natural Science Foundation of China (Grant No.60872021)the Science and Technology Commission of Shanghai Municipality (Grant No.08DZ2231100)
文摘Localization of the sensor nodes is a key supporting technology in wireless sensor networks （WSNs）. In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter （KF） is proposed. Mobile node movement model is analyzed and online sequential iterative method is used to compute location result. The detailed steps of mobile sensor node self-localization adopting extended Kalman filter （EKF） is designed. The simulation results show that the accuracy of the localization estimator scheme designed is better than those of maximum likelihood estimation （MLE） and traditional KF algorithm.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work underGrant Number(RGP 1/322/42)PrincessNourah bint Abdulrahman UniversityResearchers Supporting Project number(PNURSP2022R303)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.
基金Supported by the National Natural Science Foundation of China(No.61133016)the Sichuan Science and Technology Support Project(No.2013GZ0022)+1 种基金the Scientific Research Fund of Xinjiang Provincial Education Department(No.XJEDU2013128)the Technology Supporting Xinjiang Project(No.201491121)
文摘To alleviate the localization error introduced by irregular sensor network deployment, a new mo bile path localization based on key nodes （MPLPK） protocol is proposed. It can recognize all con cave/convex nodes in the network as fixed anchor nodes, and simplify the following localization process based on these key nodes. The MPLPK protocol is composed of three steps. After all key nodes are found in the network, a mobile node applying improved minimum spanning tree （MST） algorithm is introduced to traverse and locate them. By taking the concave/convex nodes as anchors, the complexity of the irregular network can be degraded. And the simulation results demonstrate that MPEPK has 20% to 40% accuracy improvements than connectivity-based and anchor-free three-di- mensional localization （CATL） and approximate convex decomposition based localization （ACDL）.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP 1/279/42)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R114)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor nodes.WSN comprises a massive number of SNs and records the position of the nodes,which becomes a tedious process.Besides,the SNs might be subjected to node mobility and the position alters with time.So,a precise node localization(NL)manner is required for determining the location of the SNs.In this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for WSN.The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes.The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season.In addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown SNs.For demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.
基金the VNUHCM-University of Information Technology’s Scientific Research Support Fund.
文摘Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.
基金supported by Ulsan Metropolitan City-ETRI joint cooperation project[21AS1600,Development of intelligent technology for key industriesautonomous human-mobile-space autonomous collaboration intelligence technology].
文摘In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.
文摘Major fields such as military applications,medical fields,weather forecasting,and environmental applications use wireless sensor networks for major computing processes.Sensors play a vital role in emerging technologies of the 20th century.Localization of sensors in needed locations is a very serious problem.The environment is home to every living being in the world.The growth of industries after the industrial revolution increased pollution across the environment.Owing to recent uncontrolled growth and development,sensors to measure pollution levels across industries and surroundings are needed.An interesting and challenging task is choosing the place to fit the sensors.Many meta-heuristic techniques have been introduced in node localization.Swarm intelligent algorithms have proven their efficiency in many studies on localization problems.In this article,we introduce an industrial-centric approach to solve the problem of node localization in the sensor network.First,our work aims at selecting industrial areas in the sensed location.We use random forest regression methodology to select the polluted area.Then,the elephant herding algorithm is used in sensor node localization.These two algorithms are combined to produce the best standard result in localizing the sensor nodes.To check the proposed performance,experiments are conducted with data from the KDD Cup 2018,which contain the name of 35 stations with concentrations of air pollutants such as PM,SO_(2),CO,NO_(2),and O_(3).These data are normalized and tested with algorithms.The results are comparatively analyzed with other swarm intelligence algorithms such as the elephant herding algorithm,particle swarm optimization,and machine learning algorithms such as decision tree regression and multi-layer perceptron.Results can indicate our proposed algorithm can suggest more meaningful locations for localizing the sensors in the topology.Our proposed method achieves a lower root mean square value with 0.06 to 0.08 for localizing with Stations 1 to 5.
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%.
文摘Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area and they can easily track the information. It will help them to block the signal transmission and reception. Now, the intention is to track the position of the jammer where it is fixed. The existing methods rely on the indirect measurements and the boundary node to find the jammer’s position which degrades the accuracy of the localization. To improve the efficiency, this paper proposed an efficient method namely Coincered Node Based Localization of jammers to find the position of the jammer with high level of accuracy. The proposed system uses the direct measurements, which is the jammer signal strength. The effectiveness can also be increased by using the coincered node that will stumble across the true position of the jammer. The proposed work is compared with existing methods. Then the proposed mechanism proves better to find the jammer location. The simulation results estimate that the accuracy of the localization achieves better performance than the existing schemes.
基金supported by the China Postdotoral Science Foundation(20060401004)
文摘This article analyzes the shift factors of the descending node local time for sun-synchronous satellites and proposes a shift control method to keep the local time shift within an allowance range. It is found that the satellite orbit design and the orbit injection deviation are the causes for the initial shift velocity, whereas the atmospheric drag and the sun gravitational perturbation produce the shift acceleration. To deal with these shift factors, a shift control method is put forward, through such methods as orbit variation design, orbit altitude, and inclination keeping control. The simulation experiment and practical application have proved the effectiveness of this control method.
基金Supported by The National Natural Science Foundation of China,No.81874201.
文摘BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.AIM To clarify the anatomical basis of laparoscopic LLND in two fascial spaces and to evaluate its efficacy and safety in treating locally advanced low rectal cancer(LALRC).METHODS Cadaveric dissection was performed on 24 pelvises,and the fascial composition related to LLND was observed and described.Three dimensional-laparoscopic total mesorectal excision with LLND was performed in 20 patients with LALRC,and their clinical data were analyzed.RESULTS The cadaver study showed that the fascia propria of the rectum,urogenital fascia,vesicohypogastric fascia and parietal fascia lie side by side in a medial-lateral direction constituting the dissection plane for curative rectal cancer surgery,and the last three fasciae formed two spaces(Latzko's pararectal space and paravesical space)which were the surgical area for LLND.Laparoscopic LLND in two fascial spaces was performed successfully in all 20 patients.The median operating time,blood loss and postoperative hospitalization were 178(152-243)min,55(25-150)mL and 10(7-20)d,respectively.The median number of harvested LLNs was 8.6(6-12),and pathologically positive LLN metastasis was confirmed in 7(35.0%)cases.Postoperative complications included lower limb pain in 1 case and lymph leakage in 1 case.CONCLUSION Our preliminary surgical experience suggests that laparoscopic LLND based on fascial spaces is a feasible,effective and safe procedure for treating LALRC.
基金Project supported by the National Natural Foundation of China(Grant No.11871328)the Shanghai Science and Technology Development Funds Soft Science Research Project(Grant No.21692109800).
文摘Identifying influential nodes in complex networks is one of the most significant and challenging issues,which may contribute to optimizing the network structure,controlling the process of epidemic spreading and accelerating information diffusion.The node importance ranking measures based on global information are not suitable for large-scale networks due to their high computational complexity.Moreover,they do not take into account the impact of network topology evolution over time,resulting in limitations in some applications.Based on local information of networks,a local clustering H-index(LCH)centrality measure is proposed,which considers neighborhood topology,the quantity and quality of neighbor nodes simultaneously.The proposed measure only needs the information of first-order and second-order neighbor nodes of networks,thus it has nearly linear time complexity and can be applicable to large-scale networks.In order to test the proposed measure,we adopt the susceptible-infected-recovered(SIR)and susceptible-infected(SI)models to simulate the spreading process.A series of experimental results on eight real-world networks illustrate that the proposed LCH can identify and rank influential nodes more accurately than several classical and state-of-the-art measures.
