Optimization of reconfigurable SM2 algorithm over prime filed by Bin LI, Qinglei ZHOU, Xiaojie CHEN, Feng FENG

“…Aiming at the problems of inefficient of software, low utilization of hardware resources and poor scalability of SM2 algorithm, a reconfigurable optimization method of SM2 algorithm over prime filed was proposed.Through in-depth analysis of the SM2 algorithm, starting from different computation stages and characteristics, respectively using KOA fast multiplication, fast modular reduction and Barrett algorithm to achieve recommended or arbitrary parameters of the modular multiplication operation, and the radix-4 extended Euclidean algorithm was optimized and improved to accelerate the modular inverse operation.Then, in the standard projective coordinate system, the Montgomery method was used to improve the efficiency of point multiplication, and the data flow of point addition and double point was optimized to shorten the operation cycle to 12 clocks.At the same time, fast coordinate system conversion was realized inside the FPGA.Finally, the parallel scheduling management of multi-SM2 was designed and implemented to meet the computational requirements of multiple applications.The experimental results show that the optimized SM2 makes full use of FPGA resources and shortens the cycle of point multiplication.The maximum number of calculations per second is 352.48 times higher than the CPU (Intel i5-8300), which improves the performance and scalability.…”
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Network Optimization Algorithm Based on Power Control and Channel Assignment by Yue Liu, Xiaolei Guo, Xun Zhang

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Target Image Matching Algorithm Based on Binocular CCD Ranging by Dongming Li, Wei Su, Jinhua Yang, Lijuan Zhang

“…Secondly, we deduced the algorithm which was named improved cross-correlation matching algorithm and cubic surface fitting algorithm for target images matched, and it could achieve a subpixel level matching for binocular CCD ranging images. …”
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Efficient routing algorithm for opportunistic networks based on network coding by Zhi REN, Zhi-hu LIU, Yu-kun YAO, Qian-bin CHEN

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Fuzzy logic applied to tunning mutation size in evolutionary algorithms by Krzysztof Pytel

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Negative feedback scheduling algorithm based on historical information in SDN by Yingying LYU, Yunfei GUO, Zhenpeng WANG, Guozhen CHENG, Yawen WANG

“…In the current SDN architecture,the controllers suffer from lots of potential attacks.For example,malicious flow rule attacks may introduce fake flow rules to confuse the host.A negative feedback scheduling algorithm based on historical information was proposed,in which hypothesis testing was used to judge the behavior of the attacker and the result will be used as a basis for scheduling.Simulation results and analysis show that,compared with the traditional scheduling methods,the proposed algorithm can increase the attacker’s time cost to a certain extent,so as to effectively defend the attacker’s probe attack.In addition,the more types of controllers,the more difficult it is to break the system.…”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…These algorithms were evaluated for their effectiveness in adapting to seasonal variations in electricity consumption data. …”
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Energy-Efficient Train Operation Using Nature-Inspired Algorithms by Kemal Keskin, Abdurrahman Karamancioglu

“…A train operation optimization by minimizing its traction energy subject to various constraints is carried out using nature-inspired evolutionary algorithms. The optimization process results in switching points that initiate cruising and coasting phases of the driving. …”
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Nonparametric Bayesian dictionary learning algorithm based on structural similarity by Daoguang DONG, Guosheng RUI, Wenbiao TIAN, Jian KANG, Ge LIU

“…Though nonparametric Bayesian methods possesses significant superiority with respect to traditional comprehensive dictionary learning methods,there is room for improvement of this method as it needs more consideration over the structural similarity and variability of images.To solve this problem,a nonparametric Bayesian dictionary learning algorithm based on structural similarity was proposed.The algorithm improved the structural representing ability of dictionaries by clustering images according to their non-local structural similarity and introducing block structure into sparse representing of images.Denoising and compressed sensing experiments showed that the proposed algorithm performs better than several current popular unsupervised dictionary learning algorithms.…”
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Improvement of identity adaptive recognition algorithm in visual sensor network by Na LI, Xiaoning ZHANG, Fang’e ZHU

“…When recognizing the identity in visual sensor network，it’s easily to be interfered with facial expression，illumination condition and shelter，so as to reduce the recognition accuracy.An identity adaptive recognition algorithm based on the improved minimum gray difference tree in visual sensor network was put forward.After gray processing，the minimum gray difference was used to enhance the quality of the image；cost function based on gray level was defined，the match price of each corresponding pair of gray of the image to be recognized and the specified face image were achieved，minimum gray difference tree model was set up，after two image similarity were calculated，the nearest neighbor matching algorithm was directly applied to obtain the image identity corresponding to minimum matching cost in the visual sensor network registration gallery，it was viewed as the identity to be recognized，the adaptive identity recognition was achieved in visual sensor network.Simulation results show that the proposed algorithm has high identification accuracy.…”
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A TSN traffic scheduling algorithm combined with enqueue shaping by Wenxuan HAN, Hailong ZHU, Xinxin HE, Yanjue LI, Changchuan YIN

“…Most of the existing studies on the scheduling of mixed traffic in time-sensitive network (TSN) focus on how to ensure low-latency of stream reservation (SR) traffic.However, SR traffic blocks best-effort (BE) traffic for a long time will lead to excessive delay in BE traffic, which is not conducive to the state maintenance of network and the management of system.In order to reduce the maximum end-to-end delay of BE messages, a traffic scheduling algorithm which combines with enqueue shaping was proposed.It reduced the blocking of BE traffic by reducing the reserved bandwidth of SR traffic.The algorithm first added enqueue buffers in front of SR queues.Then, the reserved bandwidth ratio among the same priority traffic was adjusted by setting the number of frames in each enqueue buffer entering the SR queue during enqueue shaping.Finally, it jointed egress shaping to reserve bandwidth resources for each SR flow to match its latency requirement.Simulation results showed that combining enqueue shaping can reduce the maximum end-to-end delay of BE messages by 9.66%～75.76%.…”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

Subjects: “…differential evolutionary algorithm…”
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Neutrosophic Clustering Algorithm Based on Sparse Regular Term Constraint by Dan Zhang, Yingcang Ma, Hu Zhao, Xiaofei Yang

“…Clustering algorithm is one of the important research topics in the field of machine learning. …”
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Image Encryption Using a Lightweight Stream Encryption Algorithm by Saeed Bahrami, Majid Naderi

“…In this paper, we consider a simple and lightweight stream encryption algorithm for image encryption, and a series of tests are performed to confirm suitability of the described encryption algorithm. …”
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RETRACTED: Correction of the movement of the mobile robot using the modified algorithm by Alferov Gennady, Korolev Vladimir, Fedorov Viktor, Khokhriakova Anastasiia

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Two-stage community detection algorithm based on label propagation by Xueliang SUN, Wei WANG, Junheng HUANG, Guodong XIN, Bailing WANG

“…Community detection is an important research topic of complex network analysis.The detection results help to understand the community structure of complex networks and provide support for downstream tasks, such as content recommendation, link detection.Considering the challenge of community detection in complex networks, a two-stage community detection algorithm based on label propagation (TS-LPA) was proposed.The TS-LPA algorithm quantified the propagation capability of nodes based on the extended neighborhood.Then a new evaluation index was proposed to measure the probability of influence between nodes using the information of nodes and the weight of edges in the network.Based on the calculation of node centrality, the algorithm determined the updating sequence of node labels and the selection strategy of seed nodes, which eliminated the instability of the algorithm in the updating process.The TS-LPA algorithm used the breadth-first propagation idea and introduced the second-stage label propagation method to improve the quality of community detection.When label began to spread, all neighboring nodes had an influence on the label of the related node.Meanwhile, the influence of neighboring seed nodes was added to complete label updating, in order to reduce the dominance of neighboring nodes on the updated node.The experimental results of different real data sets and synthetic data sets show that TS-LPA algorithm can eliminate randomness and show strong stability while effectively improving the quality of community detection.…”
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Application of Random Forest Algorithm in Xijiang River Flood Forecasting by LIU Hechang, ZHAO Bohua, SUN Bo

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Microplastic Identification Using Impedance Spectroscopy and Machine Learning Algorithms by Juan Sarmiento, Maribel Anaya, Diego Tibaduiza

“…As a contribution to the solution of this problem, this work presents a microplastic detection and classification methodology that uses an electronic tongue system, impedance spectroscopy, and machine learning algorithms for detecting and classifying microplastics. …”
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Wireless virtual network embedding algorithm based on link reliability by Juan LUO, Chuan-chuan LIU, Ren-fa LI

“…According to the problem of the poor reliability of wireless network links affectting wireless virtual network embedding,a wireless virtual network embedding algorithm based on link reliability named WVNEA-LR was proposed.This algorithm through the physical network topology pretreatment and the method of allowing multiple virtual nodes in the same virtual request mapping to the same physical nodes,improved the success rate of virtual networks construction and saved the physical link resources.The problem that low success ratio of virtual networks construction results from topology sparse was also improved with Q fact.Besides，node embedding of WVNEA-LR made the preparation for link embedding and this algorithm ensured virtual network embedded with high reliability via choosing high reliable paths during link embedding.Simulation results show the better success rate of virtual networks construction and higher resource utility can be acquired.…”
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Bounding box based distributed search localization algorithm for WSN by Ying-biao YAO, Rong ZENG, Zhi-qiang YI

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