Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
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Generating Dark Matter Subhalo Populations Using Normalizing Flows by Jack Lonergan, Andrew Benson, Daniel Gilman

“…We present a comparative analysis of strong gravitational lensing signatures generated by dark matter subhalo populations using two different approaches. The first approach models subhalos using an empirical model, while the second employs the Galacticus semi-analytic model of subhalo evolution. …”
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Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System by Qiang Gao, Jilin Chen, Li Wang, Shiqing Xu, Yuanlong Hou

“…To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. …”
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Phase Space Similarity as a Signature for Rolling Bearing Fault Diagnosis and Remaining Useful Life Estimation by Fang Liu, Bing He, Yongbin Liu, Siliang Lu, Yilei Zhao, Jiwen Zhao

“…Secondly, the normalized cross-correlation (NCC) is employed to calculate the PSS between bearing data with different states. Based on the PSS, a fault pattern recognition algorithm, a bearing fault size prediction algorithm, and a RUL estimation algorithm are introduced to analyze the experimental signal. …”
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Postoperative outcome analysis of chronic rhinosinusitis using transfer learning with pre-trained foundation models based on endoscopic images: a multicenter, observational study by Wentao Gong, Keguang Chen, Xiao Chen, Xueli Liu, Zhen Li, Li Wang, Yuxuan Shi, Quan Liu, Xicai Sun, Xinsheng Huang, Xu Luo, Hongmeng Yu

“…Conclusion The transfer learning algorithm model based on pre-trained foundation models can provide accurate and reproducible analysis of postoperative outcomes in CRS, effectively addressing the issue of high subjectivity in postoperative evaluation. …”
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Shadow hamiltonian simulation by Rolando D. Somma, Robbie King, Robin Kothari, Thomas E. O’Brien, Ryan Babbush

“…Applications of this approach to quantum simulation problems include simulating the dynamics of exponentially large systems of free fermions or free bosons, the latter example recovering a recent algorithm for simulating exponentially many classical harmonic oscillators. …”
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Task offloading and resource allocation in vehicle heterogeneous networks with MEC by Haibo ZHANG, Qiuji LUAN, Jiang ZHU, Fangwei LI

“…Based on the advantages of high-bandwidth and low-latency brought by mobile edge computing (MEC),which could provide IT service environment and cloud computing capability,combined with the long-term evolution unlicensed (LTE-U) technology,the task offloading decision and resource allocation issues in vehicle heterogeneous network were studied.Considering the link differentiation requirements,which were the high capacity of vehicle-to-roadside unit (V2I) links and the super reliability of vehicle-to-vehicle (V2V) links,quality of service (QoS) was modeled as the combination of capacity and latency.Firstly,the improved K-means algorithm was used to cluster the request vehicles according to different QoS to determine the communication mode.Secondly,the LTE-U technology based on non-competition period (CFP) which was combined with carrier aggregation (CA) technology,and the distribution Q-Learning algorithm were adopted to allocate the channel and power.The simulation results show that the proposed mechanism can maximize the V2I link traversal capacity while ensuring the reliability of the V2I link.…”
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Service Composition and Optimal Selection for Industrial Software Integration with QoS and Availability by Yangzhen Cao, Shanhui Liu, Chaoyang Li, Hongen Yang, Yuanyang Wang

“…To efficiently solve the proposed model, a hybrid enhanced multi-objective Gray Wolf Optimizer (HEMOGWO) was developed. This algorithm integrated Tent chaotic mapping and a Levy flight-enhanced differential evolution (DE) strategy. …”
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Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy by Wen FAN, Lian GE, Xiaoting XIAO, Fangji GAN, Xin LAI, Hongxia DENG, Qi HUANG

“…A new fitness function combining differential evolution (DE) algorithm with gray wolf optimization (GWO) algorithm is proposed to form a new hybrid optimization algorithm, named DEGWO. …”
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Optimizing Ontology Alignment through Improved NSGA-II by Yikun Huang, Xingsi Xue, Chao Jiang

“…In this study, for further enhancing the performance of NSGA-II, we propose to incorporate into NSGA-II’s evolutionary process the monkey king evolution algorithm (MKE) as the local search algorithm. …”
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Research on concrete structure damage detection based on piezoelectric sensing technology and morphological fractal method by Hanqing Zhong, Liwei Shuai, Dongmin Deng

“…The research results show that the signal corrosion algorithm based on mathematical morphology can significantly enhance the contrast of the steepness characteristics of wave peaks at different damage stages, thereby more effectively capturing the self-similarity characteristics of signal waveforms. …”
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Numerical Simulation Study on the Strengthening Mechanism of Rock Materials under Impact Loads by Xin Liu, Kai Wang, Chunan Tang, Xikun Qian

“…The orthogonal design and range method are used to analyze the sensitivity of the dynamic damage constitutive parameters, and a differential evolution algorithm is used to invert the relevant parameters of the constitutive model. …”
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Modelling maintenance scheduling strategies for highway networks. by Bao Tong, Jianwei Wang, Xue Wang, Feihao Zhou, Xinhua Mao, Yaxin Duan

“…A simulated annealing algorithm and augmented Lagrange algorithm are employed to solve the two proposed models, respectively. …”
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Multi-Criteria Analysis of Steel–Concrete–Steel Slab Performance: Dynamic Response Assessment Under Post-Fire Explosion by Shijie Zhang, Zhenfu Chen, Yizhi Liu, Qiuwang Tao, Dan Wu, Pinyu Zou

“…This article uses ABAQUS 2020 finite element software and combines the different advantages of the implicit heat transfer algorithm and explosion display algorithm to establish a numerical simulation method for dynamic analysis of SCS slab under explosion after fire. …”
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Multi-Objective Optimization of Three-Stage Turbomachine Rotor Based on Complex Transfer Matrix Method by Hüseyin Tarık Niş, Ahmet Yıldız

“…Furthermore, it is noted that among the different optimization algorithms, ABC provided the best results for this multi-objective optimization problem.…”
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Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration by Wenbo Wang, Fei Hui, Kaiwang Zhang, Xiangmo Zhao, Asad J. Khattak

“…Additionally, the model parameters are calibrated using real vehicle data from urban roads combined with an improved salp swarm algorithm. Finally, the evolution rule of disturbance in the traffic flow under different states is analyzed using a time-space diagram, and the DIDM-CSCL model is compared with the classical IDM. …”
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Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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Primitive-Level vs. Implementation-Level DPA Security: a Certified Case Study by Charles Momin, François-Xavier Standaert, Corentin Verhamme

“… Implementation-level countermeasures like masking can be applied to any cryptographic algorithm in order to mitigate Differential Power Analysis (DPA). …”
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Implementation of MS Circle Map in Digital Image Encryption by Ichsani Mursidah, Suryadi MT, Sarifuddin Madenda, Suryadi Harmanto

“…The proposed method features a large key space, high key sensitivity, and strong resistance to brute force, statistical, and differential attacks. Performance evaluation through key space analysis, initial value sensitivity, entropy, correlation coefficient, NPCR, and UACI shows that the encrypted image using MS Circle Map has strong security properties. …”
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Host-symbiont-gene phylogenetic reconciliation by Menet, Hugo, Trung, Alexia Nguyen, Daubin, Vincent, Tannier, Eric

“…These interactions range from independence or conflict to cooperation and coevolution, which results in them having a common history. The evolution of such systems is approached by phylogenetic reconciliation, which describes the common patterns of diversification between two different levels, e.g. genes and species, or hosts and symbionts for example. …”
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