WSN key recovery attack based on symmetric matrix decomposition by Xiangmin JI, Bo ZHAO, Jinhui LIU, Jianwei JIA, Huanguo ZHANG, Shuang XIANG

“…The key protocol is one of the crucial technologies to ensure the security for wireless sensor network（WSN）.Parakh,et al.proposed a key agreement for WSN based on matrix decomposition.However,the study revealed that the protocol had security risks.A key recovery attack scheme against this protocol was proposed by using the properties of symmetric matrix and permutation matrix.Based on intercepting the row and column vector of the node,elementary transformation was performed to construct a linear algebraic attack algorithm and the equivalent key was obtained.The computational complexity is O(N<sup>6</sup>).Experimental results show that the method can recover the equivalent key of the above protocol within the polynomial computational complexity and the memory consumption is within an acceptable range.In addition,an improved scheme for key agreement was proposed to resist the linear algebraic attack by using a random disturbance matrix,and the correctness and security analysis were also carried out.…”
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RESEARCH ON BEARING FAULT DIAGNOSIS BASED ON CEEMDAN FUZZY ENTROPY AND CONVOLUTIONAL NEURAL NETWORK (MT) by XIAO JunQing, JIN JiangTao, LI Chun, XU ZiFei, SUN Kang

“…Finally, the optimal component group was input to CNN for fault diagnosis, and the t-SNE popular learning algorithm was used for clustering visualization. The results show that compared with EMD-Fuzzy Entropy and EEMD-Fuzzy Entropy under different working conditions, the proposed method has stronger robustness and generalization, and t-SNE visualization makes the results more intuitive.…”
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Hydrological prediction in ungauged basins based on spatiotemporal characteristics. by Qun Zhao, Yuelong Zhu, Yanfeng Shi, Rui Li, Xiangtian Zheng, Xudong Zhou

“…Subsequently, we establish an initial regression model using the TrAdaBoost algorithm based on the hydrologic data from the selected watershed stations. …”
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A transmission technology of environmental monitoring for ocean based on over-the-horizon skywave by Guojun LI, Xiaofei XU, Changrong YE, Deping ZHANG, Lu TAN, Yakun XING

“…In view of the serious limitation of local resource supply for remote island and reef and the lack of low cost,high reliability long-distance transmission methods for environmental monitoring,relying on the mobile communication base stations widely distributed on the land,an over-the-horizon(OTH) skywave access network based on wide-area cooperative reception was proposed.The problems of channel fading,link asymmetry and spectrum congestion faced by remote island and reef environments monitoring for an OTH skywave transmission were solved from three aspects:physical layer,network layer and perceptive layer.The simulation results of the lower link transmission waveform and the multi-channel fusion algorithm in the typical skywave channel environment show that the reliable access of low-power transceiver in the remote island and reef within a range of 3 000 km could be guaranteed only through the cooperative reception of three access nodes.There was also some reference to monitoring of national ocean-going ships and border defence traffic pass monitoring.…”
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Research on optimal channel access method for distributed wireless network based on reliable multicast communication by Yizhu WANG, Zhou ZHANG, Piming MA, Baoquan REN

“…To address the low spectrum utilization issue of the distributed network due to multi-user collision and channel time-varying nature, the distributed channel access problem for multicast communication was investigated.Based on the optimal stopping theory, a statistical model of distributed channel access under wireless multicasts was established, and an optimal distributed wireless channel access method under reliable multicast communication was proposed.Each source competes for the channel in a distributed manner, the winner source determines whether to access the shared channel by comparing the reliable multicast access rate with a pure threshold to complete the reliable multicast communication from the winner source to all the sinks.Theoretic optimality of the method was proved rigorously.A corresponding low-complexity algorithm was designed, which has a pure threshold structure and good engineering practicability.Numerical results show that the proposed channel access method can effectively improve the average throughput of the system.…”
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Graph neural network-based address classification method for account balance model blockchain by Zhiyuan LI, Binglei XU, Yingyi ZHOU

“…To regulate the transactional activities on the public blockchain involving account balance models, it is necessary to conduct research on address classification for transactions on such blockchains.A blockchain address classification method, named AJKGS-ABCM (attention jumping knowledge graph SAGE account-based blockchain classification model), was proposed to categorize blockchain addresses, providing effective support for blockchain transaction tracking.Blockchain transaction data was represented as a graph structure, with addressed as nodes and transactions as edges.The AJK-GraphSAGE algorithm was introduced to learn embedded representations of the graph, where the model’s input required only nodes and their sampled neighboring node sets.Simultaneously, attention mechanisms and skip-connection knowledge integration strategies were incorporated into the model, allowing for adaptive weight allocation across different layers and information sharing between various levels, thereby enhancing training speed and generalization capabilities.Finally, experimental comparisons are conducted, demonstrating superior performance in terms of accuracy, recall, and F1 score compared to other methods.…”
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An Evaluation Model for Tailings Storage Facilities Using Improved Neural Networks and Fuzzy Mathematics by Sen Tian, Jianhong Chen

“…This paper establishes a reasonable TSF safety evaluation index system and puts forward a new TSF safety evaluation model by combining the theories for the analytic hierarchy process (AHP) and improved back-propagation (BP) neural network algorithm. The varying proportions of cross validation were calculated, demonstrating that this method has better evaluation performance with higher learning efficiency and faster convergence speed and avoids the oscillation in the training process in traditional BP neural network method and other primary neural network methods. …”
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Research on New SMA Actuator and Bionic Hand by Zhiguang Wu

“…The experimental results show that the new polygon SMA actuator has small volume，light quality，drive a large displacement，through the double feedback current and temperature control algorithm，the precise control of output displacement is realized and the SMA actuator response speed under different environmental temperature is improved，by fetching experiments，the bionic hand grasping ability is verified. …”
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Research of the Virtual Test Method for Dynamic Load Simulation of Automatic Transmission by Zou Xihong, Gou Xun, Zheng Xiaomei, Zhao Jun

“…In order to achieve EM-CVT dynamic load simulation,the dynamic load simulation method is researched by using MATLAB/Simulink to establish the mathematical model of automatic transmission dynamic load simulation system and combining with the speed tracking control algorithm.The virtual test is carried out,which refers to a section of the NEDC city cycle,the EPA performance index is introduced to evaluate the system performance. …”
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FAULT FEATURE EXTRACTION OF ROLLING ELEMENT BEARINGS BASED ON ADAPTIVE MCKD by CHEN BingYan, SONG DongLi, ZHANG WeiHua, CHENG Yao, LI JiaYuan

“…Considering the shortcomings of the maximum correlated kurtosis deconvolution（MCKD） method that cannot automatically identify the period of bearing fault impulses,exists the resampling process and the multiple input parameters,an adaptive maximum correlated kurtosis deconvolution（AMCKD） method is proposed.The periodic modulation intensity（PMI） of envelope signal is used to identify the period of bearing fault impulses adaptively.Moreover,the period is constantly updated during searching for the optimal deconvolution filter iteratively,so that the real fault period is gradually approximated.Finally,the filtered signal with the largest correlated kurtosis is selected as the optimal deconvolution signal.Compared with MCKD method,AMCKD method can identify fault impulse period adaptively,avoid signal resampling process,and reduce the input parameters of the algorithm.Simulated and experimental results verify the effectiveness of this method in early fault feature extraction of rolling bearings,and the comparison with fast kurtogram method shows the superiority of AMCKD method in enhancing periodic impulse characteristics.…”
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Abnormal traffic detection method based on multi-scale attention feature enhancement by YANG Hongyu, ZHANG Haohao, CHENG Xiang

“…Firstly, an optimal feature set was selected from traffic data using a feature selection algorithm based on dynamic grouping. Secondly, Dense-CNN and a multi-scale attention feature extraction network were employed to extract local and global features of the traffic data. …”
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Recognition of non-drilled polar codes based on soft decision by Zhaojun WU, Zhaogen ZHONG, Limin ZHANG, Bo DAN

“…In order to solve the problem of the blind recognition of polar codes, the theorem 1 and theorem 2 were proved firstly, which reflects the relationship between length and rate of actual polar codes, and then theorem 3 which could distinguish frozen bit and information bit positions was also proved.Based on these three theorems, the codewords matrixes and Kronecker matrixes were constructed by traversing the possible code length values.Then the information bits were traversed to detect the check relationship between the codewords and the suspected dual space.In order to detect the check relationship, log likelihood ratio was introduced, based on its characteristics and optimal criteria, the code rate and information bit positions were estimated.The simulation results show that the conclusions of the three theorems are consistent with the results.At the same time, the proposed algorithm has a strong error tolerance.Under 6.5 dB and code length of 1024, the rate of recognition can reach more than 98%.…”
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Modeling Spatial Riding Characteristics of Bike-Sharing Users Using Hotspot Areas-Based Association Rule Mining by Chao Sun, Jian Lu

“…The bike-sharing trajectory-based kernel density algorithm is employed to explore the optimum analysis locations and the analysis areas with the relatively high demand. …”
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Attack detection model based on stacking ensemble learning for Internet of vehicles by XU Huibin, FANG Long, ZHANG Sha

“…Firstly, the adaptive synthetic sampling (ADASYN) algorithm was adopted to generate more similar samples through the nearest neighbor sampling strategy in order to balance the training samples of different categories, and form a relatively symmetric dataset. …”
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The Robust Semantic SLAM System for Texture-Less Underground Parking Lot by Chongjun Liu, Jianjun Yao

“…The traditional visual-based simultaneous location and mapping (SLAM) algorithm suffers from localization loss because of inaccurate mapping results. …”
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GAD:topology-aware time series anomaly detection by Qi QI, Runye SHEN, Jingyu WANG

“…To solve the problems of anomaly detection,intelligent operation,root cause analysis of node equipment in the network,a graph-based gated convolutional codec anomaly detection model was proposed for time series data such as link delay,network throughput,and device memory usage.Considering the real-time requirements of network scenarios and the impact of network topology connections on time series data,the time dimension features of time series were extracted in parallel based on gated convolution and the spatial dependencies were mined through graph convolution.After the encoder composed of the spatio-temporal feature extraction module encoded the original input time series data,the decoder composed of the convolution module was used to reconstruct the time series data.The residuals between the original data and the reconstructed data were further used to calculate the anomaly score and detect anomalies.Experiments on public data and simulation platforms show that the proposed model has higher recognition accuracy than the current time series anomaly detection benchmark algorithm.…”
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Novel identity-based fully homomorphic encryption scheme from lattice by Yong-li TANG, Ming-xing HU, Kun LIU, Qing YE, Xi-xi YAN

“…The previous identity-based homomorphic encryption schemes from lattice was analyzed.That the high complexity in previous schemes was mainly caused by trapdoor generation and preimage sampling was pointed out.A new solution was proposed.A novel identity-based encryption scheme from lattice by combining new trapdoor function and dual-LWE algorithm organically was constructed,and it was transformed to an identity-based fully homomorphic encryption scheme from lattice by employing the idea of eigenvector.Comparative analysis shows that the scheme’s complexity of trapdoor generation has a significant reduction,the complexity of preimage sampling has a nearly three-fold reduction,and the SIVP approximation factor has a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <msqrt> <mi>m</mi> </msqrt> </mrow></math></inline-formula> times reduction.The security of the proposed scheme strictly reduces to the hardness of decisional learning with errors problem in the standard model.…”
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Evaluation and protection of multi-level location privacy based on an information theoretic approach by Wenjing ZHANG, Qiao LIU, Hui ZHU

“…A privacy metric based on mutual information was proposed to measure the privacy leakage occurred when location data owner trust data users at different levels and need to publish the distorted location data to each user according to her trust level,based on which an location privacy protection mechanism (LPPM)was generated to protect user’s location privacy.In addition,based on mutual information,a metric was proposed to measure the privacy leakage caused by attackers obtaining different levels of distorted location data and then performing inference attack on the original location data more accurately.Another privacy metric was also proposed to quantify the information leakage occurred in the scenario based on mutual information.In particular,the proposed privacy mechanism was designed by modifying Blahut-Arimoto algorithm in rate-distortion theory.Experimental results show the superiority of the proposed LPPM over an existing LPPM in terms of location privacyutility tradeoff in both scenarios,which is more conspicuous when there are highly popular locations.…”
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Improved embedded wideband speech codec fitting EV-VBR standard by XIN Jie, BAO Chang-chun, JIA Mao-shen, LIU Xin

“…Based on the International Telecommunication Union Telecommunication Standardization Sector（ITU-T） recommendation for EV-VBR coding standard and the candidate codec designed by Speech and Audio Signal Processing Laboratory（SASPL） of Beijing University of Technology,an improved embedded variable bit rates wideband speech codec was proposed.In the improved codec,ACELP coding was implied to the first two coding layers.The middle sub-frame spectral parameters were computed and quantized.Three pulses depth first tree search algorithm was designed.On the higher three coding layers embedded TCX coding was reconstructed by accumulating frequency coefficients vectors.Addition-ally,VAD and DTX functions were implemented in the improved codec.Test results show that the improved codec achieves better speech quality and much lower coding complexity than the original codec.The speech quality and coding efficiency are comparable with G.718 of a new ITU-T speech coding standard and the low delay feature is retained.…”
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Design and Optimization of the Master Manipulator of Minimally Invasive Surgery Robots by Liu Fen, Song Liqiang, Huang Fang, Han Rui, Sang Hongqiang

“…The Jacobian matrix of the master manipulator is solved, the comprehensive performance index of the master manipulator is defined based on the global performance dexterity index and the workspace utilization ratio, and the key link scale parameters are optimized by the genetic algorithm. The results show that the comprehensive performance index of the master manipulator after optimization is 18.41% higher than that before optimization, and the master manipulator is more compact, has better performance besides meeting the design requirements of the workspace.…”
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