Conflict Resolution Strategy Based on Flight Conflict Network Optimal Dominating Set by Minggong Wu, Wenda Yang, Kexin Bi, Xiangxi Wen, Jianping Li

“…In the process of solving the optimal dominating set of the network, we introduce the immune mechanism based on the particle swarm algorithm (PSO) and ensure the priority deployment of a critical aircraft and high-risk conflicts by setting two types of antigens, nodes and connected edges. …”
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Multi-node cooperative distributed offloading strategy in V2X scenario by Dun CAO, Yingbao ZHANG, Dian ZOU, Jin WANG, Qiang TANG, Baofeng JI

“…In order to cope with the dynamic changes of the offloading environment for computing resource-intensive and separable tasks in Internet of vehicle and deal with the problem that different collaborative nodes had different communication and computing resources, a distributed offloading strategy that multiple collaborative nodes had serial offloading mode and parallel computing mode in vehicle to everything (V2X) scenario was proposed.Utilizing the predictable motion trajectories of vehicle, the tasks were split into unequal parts, finally each part was computed on itself, mobile edge server, and vehicles in parallel.Then an optimization problem of the system time delay minimization was established.To solve the optimization problem, an offloading scheme based on the game theory was designed to determine the serial offloading execution order of the cooperative nodes.Considering the dynamic characteristics of Internet of vehicles, a sequential quadratic programming (SQP) algorithm was adopted to optimally split tasks.Finally, the simulation results show that the proposed strategy can effectively reduce system delay, and when multiple cooperative nodes offload in parallel, the proposed strategy can still maintain the stable system performance under the different parameter conditions.…”
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Hybrid Fingerprinting-EKF Based Tracking Schemes for Indoor Passive Localization by Salar Bybordi, Luca Reggiani

“…Additionally, in order to improve accuracy of ranging, we investigate the impact of a priori knowledge related to the clusters impulse responses and other features; the applied so called soft ranging algorithm for time of arrival (TOA) estimation is modified in order to take advantage of this a priori information and to make its decision variables more accurate. …”
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Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System by Guo Tong, Wang Jiawen, Liang Yingnan, Peng Buyu, Liu Tao, Liu Yiqun

“…The fmincon function was used to realize the sequential quadratic programming (SQP) algorithm, which is one of the most effective methods to solve the constrained nonlinear optimization problems, for the optimal design. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…This paper systematically reviews the growth of image classification technology, beginning with the introduction of commonly used datasets such as CIFAR-10, ImageNet, and MNIST, and exploring their impact on algorithm development. Subsequently, the paper provides an in-depth analysis of image classification methods based on machine learning, including traditional algorithms such as Support Vector Machine (SVM), Random Forest, and Decision Tree. …”
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Research on unsupervised domain adaptive bearing fault diagnosis method by WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun

“…Aiming at the problem that the bearing fault diagnosis algorithm based on deep learning has poor diagnosis performance when the fault samples are lack of labels in different working conditions and real environmentsly, an unsupervised domain adaptive bearing fault diagnosis method was proposed to realize the unsupervised fault diagnosis of bearings under different working conditions. …”
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Suppression of MRI Truncation Artifacts Using Total Variation Constrained Data Extrapolation by Kai Tobias Block, Martin Uecker, Jens Frahm

“…The assumption translates into a total variation minimization problem, which can be solved with a nonlinear optimization algorithm. In the presence of substantial noise, a modified approach offers edge-preserving denoising by allowing for slight deviations from the measured data in addition to supplementing data. …”
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Swarming Computational Procedures for the Coronavirus-Based Mathematical SEIR-NDC Model by Suthep Suantai, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Watcharaporn Cholamjiak

“…The swarming procedure based on the particle swarm optimization (PSO) works as a global search, while the sequential quadratic programming (SQP) is used as a local search algorithm. A merit function is constructed by using the nonlinear dynamics of the SEIR-NDC mathematical system based on its 7 classes, and the optimization of the merit function is performed through the PSOSQP. …”
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Circular Antenna Array Synthesis Using Multiverse Optimizer by Ahmet Emre Taser, Kerim Guney, Erhan Kurt

“…Since achieving a desired antenna radiation pattern is a mathematical problem, in the literature, there are various optimization algorithms applied to the synthesis process of different kinds of antenna arrays. …”
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Efficient high‐speed framework for sparse representation‐based iris recognition by Michael Melek, Mohamed F. Abu‐Elyazeed, Ahmed Khattab

“…To considerably improve classification performance, SRC is proposed, using a greedy compressed‐sensing recovery algorithm, as opposed to employing the traditional computationally expensive ℓ1 minimisation. …”
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ROLLER BEARING FAULT RECOGNITION METHOD BASED ON CYCLIC AUTOCORRELATION AND MULTI-DOMAIN KERNEL LIMIT LEARNING MACHINE by WANG XiaoHui, WANG GuangBing, XIANG JiaWei, HUANG Zhen, SUI GuangZhou

“…According to characteristics of the bearing signal,the second-order cyclic demodulation information was introduced into machine learning,and a multi-domain kernel extreme learning machine（MKELM） based on the combination of cyclic autocorrelation（CAF） frequency domain features and time domain features（TD） was proposed to accurately identify the bearing status.The algorithm constructed a CAF function based on the second-order cyclic characteristics of the bearing signal to extract the cyclic frequency domain features of the samples,then combined them with the time domain feature quantities of the samples.The matching factors of multi-domain feature vectors was designed to fuse TD and CAF feature vectors; finally,the fused CAF-TD sample features was input into the kernel extreme learning machine for cluster regression.The spindle bearing experimental results show that the cyclic frequency domain statistics extracted based on CAF can sensitively reflect the signal characteristics.Compared with the classic classifier,the CAF-TD multi-domain kernel extreme learning machine can extract more feature information from limited samples and obtain more accurate diagnostic result.…”
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Pneumomediastinum, Pneumopericardium, and Epidural Pneumatosis following Adenotonsillectomy: A Very Rare Complication by Feride Fatma Görgülü, Ayşe Selcan Koç, Orhan Görgülü

“…The possible mechanism, the algorithm of treatment, and precautions in such cases will be discussed.…”
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Study on the Rolling Bearing Fault Diagnosis based on the Hilbert Envelope Spectrum Singular Value and IPSO-SVM by Qin Bo, Sun Guodong, Zhang Liqiang, Liu Yongliang, Zhang Chao, Wang Jianguo

“…Firstly,the rolling bearing signal is divided by EMD,it selects IMFs that contains main characteristics of signal for Hilbert demodulation envelope analysis to obtain envelope matrix and the singular value decomposition is carried out. Secondly,the IPSO algorithm is used to optimize the penalty coefficient and the structural parameters of SVM to set up the rolling bearing fault classification model. …”
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Bayesian Classifier with Simplified Learning Phase for Detecting Microcalcifications in Digital Mammograms by Imad Zyout, Ikhlas Abdel-Qader, Christina Jacobs

“…Followed by an estimation of the classifier's decision function parameters, a mammogram is segmented into the identified targets (MCs) against background (healthy tissue). The proposed algorithm has been tested using 23 mammograms from the mini-MIAS database. …”
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Exploring the potential of blockchain technology for citizen engagement in smart governance [version 4; peer review: 1 approved, 3 approved with reservations] by Rebecca Marconi, Edna Pasher, Niccolò Testi

“…By examining the benefits of BCT in various aspects of smart city systems, such as data security and privacy, the paper highlights the advantages of implementing consortium blockchain architecture and the Proof of Authority (PoA) consensus algorithm and discusses the challenges of scalability and security concerns. …”
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Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets by Sajid Mahmood, Muhammad Shahbaz, Aziz Guergachi

“…In this paper, we propose an algorithm for discovering positive and negative association rules among frequent and infrequent itemsets. …”
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Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering Methodology by J. M. Urquiza, I. Rojas, H. Pomares, J. Herrera, J. P. Florido, O. Valenzuela

“…In the present work, a new approach is proposed to construct a PPI predictor training a support vector machine model through a mutual information filter-wrapper parallel feature selection algorithm and an iterative and hierarchical clustering to select a relevance negative training set. …”
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Adaptive Dynamic Programming-based Tracking Controls of Multi-Motor Driven Systems by LYU Yongfeng, JIAN Long

“…The optimal feedback controls are obtained with an approximate dynamic programming algorithm, which can be used to research the saddle point and minimized the performance index. …”
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Enhancing Time-Domain Interference Alignment for Underwater Acoustic Networks with Cross-Layer Design by Qiao Xiao, Zhicheng Bi, Chaofeng Wang

“…The simulation results validate the QIA framework’s superiority over the traditional TDIA and genetic algorithm benchmarks.…”
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Tooth Flank Mismatch Meshing Analysis for Spiral Bevel Gear Based on Tilt Cutting Method by Shaowu Nie, Sicheng Tang, Juhua Huang, Hua Zhang, Changfa Lai, Yong Xu

“…Compared with the traditional tooth flank meshing analysis method，the proposed method not only reduces the number of equations，but also makes the algorithm more stable. The Ease off topology can visually display the whole tooth flank mesh state and improve the current TCA output.…”
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