Multi-objective optimization of the heating oil circuit inside the calendering roller for the lithium battery pole piece by Shuangqiu Sun, Junqiang Wang, Rongying Zhang, Zhenchao Si, Zhijie Yang

“…Then, the improved NSGA-II algorithm is selected to execute the optimization loop. …”
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Lattice‐based hash‐and‐sign signatures using approximate trapdoor, revisited by Huiwen Jia, Yupu Hu, Chunming Tang

“…Due to the fact that the signature size and the concrete security are closely related to the Gaussian parameter of the sampling algorithm, this technique provides a tradeoff between them. …”
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Numerical characterization of hemodynamics conditions near aortic valve after implantation of left ventricular assist device by Annalisa Quaini, Sunčica Čanić, David Paniagua

“…The use of LVADs has been associated with thrombus formation next to the aortic valve and close to the anastomosis region,especially in patients in which the native cardiac function isnegligible and the aortic valve remains closed.Stagnation points and recirculation zones have been implicated as the main fluid dynamics factors contributing to thrombus formation.The purpose of the present study was to develop and use computer simulations based on afluid-structure interaction (FSI) solver to study flow conditions corresponding to different strategies inLVAD ascending aortic anastomosis providing a scenario with the lowest likelihood of thrombus formation.A novel FSI algorithm was developed to dealwith the presence of multiple structures corresponding to different elastic properties ofthe native aorta and of the LVAD cannula.A sensitivity analysis of different variables was performed to assess their impact of flow conditionspotentially leading to thrombus formation.It was found that the location of the anastomosis closest to the aortic valve(within 4 cm away from the valve)and at the angle of 30$^\circ$ minimizes the likelihood of thrombus formation.Furthermore, it was shownthat the rigidity of the dacron anastomosis cannula plays almost no role in generating pathologicalconditions downstream from the anastomosis.Additionally, the flow analysis presented in this manuscriptindicates that compliance of the cardiovascular tissue acts as a natural inhibitor of pathological flow conditions conducive to thrombus formationand should not be neglected in computer simulations.…”
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Enhancing Persian text summarization through a three-phase fine-tuning and reinforcement learning approach with the mT5 transformer model by Vahid Nejad Mahmood Abadi, Fahimeh Ghasemian

“…Subsequently, reinforcement learning via the PPO algorithm is integrated with the fine-tuned model. …”
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Analyzing urban public sports facilities for recognition and optimization using intelligent image processing by Zhongqian Zhang

“…The method incorporates an optimized Residual-Shuffle Network modified by a boosted variant of Spring Search Algorithm (BSSA) for efficient image recognition along with metaheuristics and super-efficiency data envelopment analysis (SE-DEA) model. …”
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Improved Support Vector Machine and Image Processing Enabled Methodology for Detection and Classification of Grape Leaf Disease by Arshiya S. Ansari, Malik Jawarneh, Mahyudin Ritonga, Pragti Jamwal, Mohammad Sajid Mohammadi, Ravi Kishore Veluri, Virendra Kumar, Mohd Asif Shah

“…Image denoising is conducted using the mean function, image enhancement is performed using the CLAHE method, pictures are segmented using the fuzzy C Means algorithm, features are retrieved using PCA, and images are eventually classed using the PSO SVM, BPNN, and random forest algorithms. …”
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Methods of forecasting stocks of construction materials during deliveries by Yu. A. Laamarti, E. G. Dedov, O. Yu. Kramlikh

“…Under such conditions, it is incorrect to predict inventories using the classical algorithm. The evolution of forecasting methods is characterized by a shift in emphasis from demand for goods to inventory management. …”
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Targeted Advertising in Social Media Platforms Using Hybrid Convolutional Learning Method besides Efficient Feature Weights by Seyed Mohsen Ebadi Jokandan, Peyman Bayat, Mehdi Farrokhbakht Foumani

“…Using accuracy, recall, F-measure, and precision metrics, we compared our algorithm to standard techniques such as SVM, Logistic regression, Naïve Bayes, and CNN. …”
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Randomized and Efficient Time Synchronization in Dynamic Wireless Sensor Networks: A Gossip-Consensus-Based Approach by Nan Xiong, Minrui Fei, Taicheng Yang, Yu-Chu Tian

“…This paper proposes novel randomized gossip-consensus-based sync (RGCS) algorithms to realize efficient time calibration in dynamic wireless sensor networks (WSNs). …”
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A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization by Shaolong Chen, Renyu Yang, Renhuan Yang, Liu Yang, Xiuzeng Yang, Chuangbiao Xu, Baoguo Xu, Huatao Zhang, Yaosheng Lu, Weiping Liu

“…As a novel swarm intelligence algorithm, chicken swarm optimization (CSO) has attracted much attention owing to its good global convergence and robustness. …”
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Pediatric Ovarian Growing Teratoma Syndrome by Rebecca M. Rentea, Aaron Varghese, Atif Ahmed, Alexander Kats, Michelle Manalang, Tazim Dowlut-McElroy, Richard J. Hendrickson

“…We review in detail the history, diagnostic algorithm, and previous reported pediatric cases as well as treatment options for pediatric patients with GTS.…”
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Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…The results showed that a DNN algorithm for regression exhibits the highest accuracy in estimating the slope of the HFF.…”
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About probability of error detection of unauthorized impacts on pipeline with active vibroacoustic method of control by A. A. Fedotov, Yu. G. Malinovskiy

“…The conclusion is made about the consistency of the proposed algorithm for identifying the type of unauthorized exposure.…”
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Expert Detection In Question Answer Communities by Hamed Salimian, Mohammad Amin Fazli, Jafar Habibi

“…We used some ideas such as profile making for users, categorize users’ expertise, A-Priori algorithm and showed that neural networks method results the best for the purpose of expert detection.…”
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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

“…By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …”
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Compressive sampling–based ultrasonic computerized tomography technique for damage detection in concrete-filled steel tube in a bridge by Binbin Li, Bo Liu, Fan Xu, Yang Liu, Wentao Wang, Tao Yang

“…And in the imaging phase, ℓ 1 -norm minimization optimization algorithm is used to reconstruct the internal damage, rendering the sparest solution related to the physical damages. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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Application of Two-Dimensional Compressive Sensing to Wavelet Method of Moments for Fast Analysis of Wide-Angle Electromagnetic Scattering Problems by Yi Liu, Qi Qi, Xinyuan Cao, Mingsheng Chen, Guoqing Deng, Zhixiang Huang, Xianliang Wu

“…Finally, after completing the other side of the bilateral sparse transform, the wide-angle problems can be solved rapidly by two times of recovery algorithm with prior knowledge. The basic principle is elaborated in detail, and the effectiveness is demonstrated by numerical experiments.…”
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Application of the Professional Psychological Quest in the Professional Training of Police Officers by N. E. Miloradova, N. Ye. Tverdokhliebova

“…It is noted that the basis of the police quest is the situational method, the content of which is aimed at mastering the algorithm of actions by the cadets associated with the implementation of the service tasks of the police. …”
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Design Optimization of a Multistage Axial Flow Compressor Based on Full-Blade Surface Parameterization and Phased Strategy by Jinxin Cheng, Shengfeng Zhao, Zhaohui Dong, Chengwu Yang

“…The method mainly contains three aspects: full-blade surface parametrization can significantly reduce the number of control variables per blade row and increase the degrees of freedom of the leading edge blade angle compared with the traditional semiblade parametric method; secondly, the artificial bee colony algorithm improved initialization and food source exploration and exploitation mechanism to enhance the global optimization ability and convergence speed, and a distributed optimization system is built on the supercomputing platform based on this method; finally, a phased optimization strategy based on the “synchronous change in multirow blades” is proposed, and expert experience is introduced to achieve a better balance between exploration and exploitation. …”
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