检索结果-内蒙古大学图书馆

A Wormhole Attack detection Algorithm Integrated With the Node Trust Optimization Model in WSNs

IEEE SENSORS JOURNAL 2022年第7期22卷 7361-7370页

作者： Teng, Zhijun Du, Chunqiu Li, Meng Zhang, Hengjia Zhu, Weihua Northeast Elect Power Univ Minist Educ Key Lab Modern Power Syst Simulat & Control & Ren Jilin 132000 Jilin Peoples R China Northeast Elect Power Univ Sch Elect Engn Jilin 132000 Jilin Peoples R China Jilin Univ Sch Comp Sci & Technol Changchun 130012 Peoples R China Jilin Elect Informat Vocat & Tech Coll Sch Comp Sci Jilin 132000 Jilin Peoples R China

The openness of Wireless Sensor Networks (WSNs) layout makes them vulnerable to attacks. One of the most threatening attacks is the wormhole attack. The wormhole attack is difficult to be detected since it causes false routing by private tunnels and damages to WSNs in data transmission. Therefore, in order to resist wormhole attacks and improve network performance, this paper proposes a detection algorithm integrated with the node trust optimization model (NTOM-DA) against wormholes in WSNs. First, add the node whose number of neighbors exceeds the threshold to the list of suspicious nodes, and then the exclusive neighbors of suspicious nodes communicate with each other. Mark the path whose hops exceed the wormhole threshold as the path to be tested. Establish a trust model to calculate the node trust and evaluate the path trust. The simulation results show that NTOM-DA is superior in detecting wormhole attacks. Even in the face of a network with high node density and high attack degree, it still has a high detection rate and a low false-positive rate, which effectively guarantees the safe and reliable operation of WSNs.

关键词： Wireless sensor networks detection algorithms Sensors Routing Data communication Optimization Layout Wireless sensor networks wormhole attack wormhole threshold trust model path trust evaluation

来源：评论

学校读者我要写书评

暂无评论

Small Target detection From Infrared Remote Sensing Images Using Local Adaptive Thresholding

引用

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2022年 15卷 1941-1952页

作者： Liu, Chang Xie, Fengying Dong, Xiaomeng Gao, Hongxia Zhang, Haopeng Beihang Univ Sch Astronaut Image Proc Ctr Beijing 100191 Peoples R China China Acad Space Technol Beijing 100094 Peoples R China

Small target detection from the infrared remote sensing image is a challenge task. In this article, a novel local adaptive threshold algorithm combined with heterogeneity and compactness filters is proposed to detect the small target from the infrared remote sensing images. First, the infrared image is filtered by a heterogeneity filter to enhance the target saliency. Then, the enhanced image is filtered by a compactness filter to generate a target candidate region map. Finally, for each pixel in the target candidate region, a local adaptive threshold is calculated from the enhanced image to determine whether it is a target pixel or not, and thus, the targets are extracted out. The designed heterogeneity filter and compactness filter can effectively suppress the background clutter, enhance the target, and generate target candidate regions. The proposed adaptive thresholding is a local threshold method, which is calculated in a small local window and can effectively reduce the false alarm and missing alarm. Qualitative and quantitative experiments are conducted on synthetic images and real images. The experiment results show that, with good target enhancement and background suppression, and high detection accuracy, the proposed method outperforms other state-of-the-art methods.

关键词： Feature extraction detection algorithms Remote sensing Object detection Clutter Kernel Extraterrestrial measurements Adaptive threshold background suppression infrared dim small target (IDST) remote sensing image target enhancement

来源：评论

学校读者我要写书评

暂无评论

Urban Interior Boundaries Delimitation Respecting to Human Mobility

引用

IEEE ACCESS 2024年 12卷 159635-159647页

作者： Wei, Yu Zhao, Xi Taiyuan Univ Technol Coll Comp Sci & Technol Coll Data Sci Taiyuan 030024 Peoples R China Xi An Jiao Tong Univ Sch Management Key Lab Minist Educ Proc Control & Efficiency Engn Xian 710049 Peoples R China

Administrative divisions are regional divisions of the state for the purpose of hierarchical administration. With the development of urbanization process, a concern arising from the changing urban dynamics is that whether current administrative division accords with urban development? Following the concept of urban space formed by human activities, existing studies have sought proxies for human activities and then delineated urban boundaries formed by human activities from a data-driven perspective. However, their lack of exploration into the implicit human activity patterns behind the proxies results in weak interpretability and rationality of methods and results. This paper studies the delineation of urban interior boundaries respecting to human mobility patterns. Specifically, this paper first uses human mobility as a proxy to construct a network that represents spatial interaction in urban regions. Then we explore the region-based human crowd mobility patterns to reveal the mechanisms behind the formation of urban space through human activities. Finally, we employ the community detection technology to naturally delimit the urban interior boundaries formed by human mobility, and make a comparison with the official urban boundaries. Taking Xi'an in Shaanxi Province of China as an example, we conduct the delineation on the spatial interaction network based on the real mobility information of 24,770,715 mobile phone users in the whole city. We find that human mobility can establish a stable correlation between regions (or capture the objective correlations between regions), and the human crowd patterns are applicable for mining unusual urban regions from the perspective of anomaly detection, which are of great significance for understanding the urban spatial structure based on empirical evidence. In addition, in the final delineation result, some unexpected communities that are closely linked due to human activities appear from the results, and these findings help t

关键词： Urban areas Entropy Correlation Trajectory Cognition Reliability detection algorithms Uncertainty Spatial databases Space exploration Administrative divisions a data-driven perspective urban interior boundaries human mobility patterns community detection

来源：评论

学校读者我要写书评

暂无评论

Observer-Based Attack and Disturbance Mitigation for Heavy-Duty Vehicles in an Autonomous Docking Application

引用

IEEE ACCESS 2024年 12卷 142488-142504页

作者： Bin Bashar, Labid Nazaruddin, Yul Yunazwin Raja, Andi Cakravastia Arisaputra Wardana, Ananta Adhi Bahiuddin, Irfan Rijanto, Estiko Hasan, Agus Widyotriatmo, Augie Inst Teknol Bandung Instrumentat & Control Program Bandung 40132 Indonesia Inst Teknol Bandung Instrumentat & Control Res Grp Bandung 40132 Indonesia Inst Teknol Bandung Ind & Technoecon Syst Res Grp Bandung 40132 Indonesia Univ Airlangga Fac Adv Technol & Multidiscipline Robot & Artificial Intelligence Surabaya 60115 Indonesia Univ Gadjah Mada Vocat Coll Mech Engn Dept Yogyakarta 55281 Indonesia Natl Res & Innovat Agcy BRIN Res Ctr Smart Mechatron Bandung 40135 Indonesia Norwegian Univ Sci & Technol Dept ICT & Nat Sci N-6025 Alesund Norway

A heavy-duty vehicle (HDV) finds applications in various fields, particularly logistics and freight transportation, involving the movement of containers from ports to local warehouses and eventual delivery destinations. In smart ports, the process has been automated, necessitating the vehicle's autonomous docking and undocking. Such a cyber-physical system faces the risk of cyberattacks and internal disturbances posing hazardous situations within the terminal. Therefore, it becomes crucial to identify and mitigate any cyberattacks as well as disturbances during the docking and undocking procedures. This research aims to develop an observer-based detection and mitigation system for actuator attacks and disturbances for autonomous docking of HDVs, employing a point stabilization-based control strategy. The methodology outlined in this study involves analytical proof of the asymptotic stability of the detection and mitigation system, complemented by numerical simulations and experiments to provide a quantitative evaluation. The proposed system design utilizes the Lyapunov direct method to establish the asymptotic stability of the detection system and subsequently integrates it with the point stabilization controller to design the mitigation system, ultimately contributing to the asymptotic stability of the desired configuration for docking the vehicles. The simulation of autonomous docking is performed, demonstrating the ability of the detection and mitigation system, in conjunction with the point stabilization controller, to detect simulated actuator attacks and mitigate their effects, resulting in a smooth docking process at the desired configuration. Experimental results validate the effectiveness of the controller, as the vehicle consistently achieves the desired configuration. Although this work primarily focuses on cyberattacks, it is worth noting that, for safety reasons within container ports, the experimental investigation tackles actuator disturbances instead

关键词： Seaports Prevention and mitigation Containers Computer crime Actuators Docking stations Resilience Cyberattack detection algorithms Autonomous systems Observers Heavy-duty vehicle cyberattack disturbance detection autonomous docking control observer

来源：评论

学校读者我要写书评

暂无评论

Design of Human-Computer Interaction Gesture Tracking Model Based on Improved PSO and KCF algorithms

引用

IEEE ACCESS 2024年 12卷 39913-39925页

作者： He, Dinghua Yang, Yan Wu, Rangzhong Wuhan Polytech Sch Informat Technol Applicat & Innovat Wuhan 430074 Peoples R China China Univ Geosci Sch Mech Engn & Elect Informat Wuhan 430074 Peoples R China

The detection and tracking of gesture targets is an important aspect in the dynamic gesture recognition. To meet the accuracy and speed requirements of human-computer interaction for dynamic gesture recognition, this study explores long-term gesture recognition under monocular RGB cameras. This study uses an improved particle swarm optimization algorithm as the feature extraction method, and introduces a mixed Gaussian model and kernel correlation filtering to complete gesture detection and tracking. And it has constructed a dynamic gesture tracking model on the ground of kernel correlation filtering. The experimental results show that the skin color based gesture detection algorithm has the minimum average relative error value of 0.321 on different datasets, with accuracy and recall rates higher than 0.8. The maximum correlation coefficient R-squared value is 0.823, and the detection speed reaches 36.32 frames per second. And this detection method has high repeatability on different datasets, with better detection accuracy for different gesture targets. The F1 value of the gesture tracking model has the largest area of the receiver operation characteristic curve, and the two error values of the model are small, resulting in better gesture tracking performance. In human-computer interaction systems, the detection accuracy and target rejection rate of this method have been significantly improved, and the subjective evaluation of the interaction system by the subjects is relatively high, resulting in good application effects. This study enriches the theoretical foundation of dynamic gesture detection and tracking technology, and improves the quality level of gesture tracking in the field of human-computer interaction. This helps to expand the application scope of human-computer interaction.

关键词： Human computer interaction Particle swarm optimization Skin Image color analysis Gesture recognition Tracking detection algorithms Feature extraction Filtering Target tracking Heuristic algorithms Gaussian processes Human-computer interaction particle swarm optimization skin tone model kernel correlation filtering dynamic gesture detection hand tracking

来源：评论

学校读者我要写书评

暂无评论

Evaluation of the Interference Performance of FMCW Radar Sensors in Dense Indoor Environments

引用

IEEE ACCESS 2024年 12卷 46834-46850页

作者： Reitz, Philipp Kuenzle, Christian Franchi, Norman Luebke, Maximilian Friedrich Alexander Univ Erlangen Nurnberg Chair Elect Smart City Syst D-91058 Erlangen Germany

Frequency-modulated continuous-wave (FMCW) radars are becoming increasingly important in industrial applications due to their low cost, simple signal processing, and high resolution. The research is driven by the growing trend of radar applications in industrial settings, including tasks like autonomous robot navigation, radar-based monitoring of humans, and enhancing safety across various scenarios, such as smart factories, traffic control, or environmental monitoring. The network of distributed sensor nodes is a feature to be implemented by the sixth generation of wireless mobile networks. As a result, 6G will become an enabler technology that will develop even further use cases and advance the expansion of these technologies. Therefore, the mutual interference of these sensor systems is becoming highly relevant since they can be avoided by scheduling the individual resources of the sensor nodes by a network structure. This paper investigates the interference behavior of FMCW radar sensors in a dense indoor scenario. In these environments, in particular, the reliability of the sensor system plays an important role, and disruption can have critical consequences like not recognizing a target, triggering a false alarm, or the complete failure of the sensing. To correctly classify the expected interference in the overall context, the paper investigates the physical layer effects on the performance, such as multipath propagation, channel spread, delay, Doppler shift, and attenuation. By evaluating these effects using state-of-the-art signal processing, it was revealed that a high channel spread in particular and the dynamics of the radar channel can significantly reduce the detection quality, as the interference power can exceed the received power by up to 20 dB, depending on the scenario. The simulation results given in this paper show that a potential communication between the radars and compliance with a synchronization delay, the interference problems can be reliab

关键词： Interference Chirp Radar Sensors Delays Radar signal processing Time-frequency analysis Frequency modulation Continuous wavelet transforms Channel estimation Robot sensing systems Sensor systems Physical layer Wireless sensor networks Wireless communication Environmental monitoring Telecommunication traffic detection algorithms Performance evaluation Channel simulation CIR FMCW radar industrial radar interference interference mitigation mmWave multipath

来源：评论

学校读者我要写书评

暂无评论

Yolov5s-PSG: Improved Yolov5s-Based Helmet Recognition in Complex Scenes

引用

IEEE ACCESS 2025年 13卷 34915-34924页

作者： Li, Yi Shi, Xiaolin Xu, Xiaolong Zhang, Han Yang, Fan Liaoning Univ Technol Coll Mech Engn & Automat Jinzhou 121001 Peoples R China Northwestern Polytech Univ Sch Mech Engn Inst Intelligent Mfg Xian 710072 Peoples R China

In the field of industrial safety, due to the existence of color, distance and other reasons in complex industrial environments caused by the helmet small target detection methods have the problem of misdetection and omission, and the Yolov5s model for real-time detection of helmets is not ideal. for the purpose of Improvement of extraction capabilities multi-scale features, improve the network's focus on key features, and achieve an excellent balanced effect for accuracy and speed, the model Yolov5s-PSG based on Yolov5s improvement is proposed. First, the C3_PPA module improves the detection accuracy through a multi-branch feature extraction strategy and an attention mechanism. Second, the SimAM attention mechanism enhances the inspection accuracy by adaptively weighting the feature maps and thus improving the detection efficiency. Finally, the GSconv convolutional layer combines the SC module and the DSC module in a channel shuffling manner to infiltrate the information of the SC module within some of the information of the DSC module, which improves the detection speed without changing the ***5s-PSG model outperforms the conventional target inspection in terms of accuracy, recall, map value, and loss function, where the accuracy is improved to 93.1%, recall to 91.2%, and map value to 94.6%. These findings are important for helmet inspection to find the optimal solution in terms of accuracy and speed for better helmet inspection in shop-floor factory environments.

关键词： Safety Head Accuracy Feature extraction YOLO Inspection Production facilities Attention mechanisms Computational modeling detection algorithms Helmet Yolov5s target detection attention mechanism

来源：评论

学校读者我要写书评

暂无评论

detection by Block- and Band-Permuted Data

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2022年 70卷 5778-5790页

作者： Li, Dan Aubry, Augusto De Maio, Antonio Fu, Yaowen Marano, Stefano Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China Univ Naples Federico II DIETI I-80125 Naples Italy Univ Salerno DIEM I-84084 Fisciano Italy

Unlabeled detection is an important problem in large sensor networks faced with big-data applications. The focus of this paper is on decision problems in which the data vector received at the fusion center (FC), tasked to perform the final inference, undergoes an unknown permutation. Two representative permutation models are considered, whose structure is imposed by practical considerations. The first is the arc-block permutation model, where the observations are split into different blocks of size arc, and independent data permutations affect each block. The second is the r-banded permutation model, in which each sample of the vector received by the FC lies at most r positions ahead or behind its original location. To solve these challenging detection tasks, three detectors for both permutation models are proposed. The first is inspired by the uniformly most powerful invariant principle;the second relies on a distribution-averaged strategy;and the third is designed according the generalized likelihood ratio approach. The performance of these detectors is investigated by computer experiments and their relative merits are discussed.

关键词： Unlabeled detection shuffled bits block permutation banded permutation detection algorithms

来源：评论

学校读者我要写书评

暂无评论

A Passive Islanding detection Method for Distribution Power Systems With Multiple Inverters

引用

IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS 2022年第5期10卷 5727-5737页

作者： Song, Guanhong Cao, Bo Chang, Liuchen Univ New Brunswick Emera & NB Power Res Ctr Smart Grid Technol Fredericton NB E3B 5A3 Canada

The high penetration of grid-connected distributed energy resources (DERs) leads to a need for smart inverters to enhance their performance and minimize the negative impacts of these resources on grid behavior. However, the interconnection of these smart inverters may interfere with their anti-islanding algorithms, which creates detection difficulties. Advanced islanding detection techniques are therefore required to detect and disrupt islanding operations under such an environment with system's disturbances and interferences. Even though various islanding detection methods have been developed in recent literature to identify islanding operations with high detection accuracy and minimized nondetection zone, these methods mainly focus on a single inverter system, which is incompatible in modern power system with high penetration of grid-connected inverters. In this article, an advanced passive islanding method is proposed for a single-phase distribution power system taking account of the interferences and disturbances brought by these grid-connected inverters. The effectiveness of the proposed passive islanding method is validated through experiments in a laboratory platform. Also, the experimental results have verified that the proposed methods can effectively terminate the islanding operation even with rich inverters' interferences.

关键词： Inverters Islanding Power systems Harmonic analysis Power system stability Resonant frequency Power system harmonics detection algorithms distributed power generation islanding

来源：评论

学校读者我要写书评

暂无评论

How to Protect Ourselves From Overlapping Community detection in Social Networks

引用

IEEE TRANSACTIONS ON BIG DATA 2022年第4期8卷 894-904页

作者： Liu, Dong Yang, Guoliang Wang, Yanwei Jin, Hu Chen, Enhong Henan Normal Univ Coll Comp & Informat Engn Key Lab Artificial Intelligence & Personalized Le Big Data Engn Lab Teaching Resources & Amp Assess Xinxiang 453007 Henan Peoples R China Henan Normal Univ Coll Comp & Informat Engn Xinxiang 453007 Henan Peoples R China Hanyang Univ Div Elect Engn Ansan 5588 South Korea Henan Normal Univ Xinxiang 453007 Henan Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Anhui Prov Key Lab Big Data Anal & Applicat Hefei 230000 Anhui Peoples R China

In recent years, overlapping community detection algorithms have been paid more and more attention, which not only reveal the real social relations, but also expose the possible communication channels between communities. Those individuals (or people) in the overlapping area are very important to the communities that can promote communication between two or more communities. On the other hand, from the privacy perspective, some people may not want to be found out in the overlapping areas. With this in mind, we raise a question "Can individuals modify their relationships to avoid the community discovery algorithms locating them into overlapping areas?" If this problem could be solved, these people may not need to worry about being disturbed. In particular, we first give three heuristic hiding strategies, i.e., Random Hiding(RH), Based Degree Hiding(DH) and Betweenness Hiding(BH), as comparison, utilizing the randomly the node, information of node degree and node betweenness centrality, respectively. And then, we propose a novel hiding algorithm by exploiting the importance degree of nodes in communities based on which the corresponding social connections are added or deleted called name BIH. Through extensive experiments, we show the effectiveness of the proposed algorithm in moving out a target node from overlapped areas.

关键词： detection algorithms Social networking (online) Privacy Image edge detection Complex networks Big Data Optimization Overlapping community detection community deception hiding privacy protection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：