Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

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Redefining the high variable genes by optimized LOESS regression with positive ratio by Yue Xie, Zehua Jing, Hailin Pan, Xun Xu, Qi Fang

“…Results We developed a robust feature selection algorithm that leverages optimized locally estimated scatterplot smoothing regression (LOESS) to precisely capture the relationship between gene average expression level and positive ratio while minimizing overfitting. …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…The algorithm enhances cancer detection while ensuring data privacy. …”
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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

“…Correspondingly, unique circuits were engineered for each algorithm.To enhance the sensitivity of the sensor while simplifying the circuit's complexity and dimensions, the lm324 Op-Amp was used in the interrupt-based sensor circuit. …”
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Multiuser computation offloading for edge-cloud collaboration using submodular optimization by Bing LIANG, Wen JI

“…A computation offloading scheme based on edge-cloud computing was proposed to improve the system utility of multiuser computation offloading.This scheme improved the system utility while considering the optimization of edge-cloud resources.In order to tackle the problems of computation offloading mode selection and edge-cloud resource allocation,a greedy algorithm based on submodular theory was developed by fully exploiting the computing and communication resources of cloud and edge.The simulation results demonstrate that the proposed scheme effectively reduces the delay and energy consumption of computing tasks.Additionally,when computing tasks are offloaded to edge and cloud from devices,the proposed scheme still maintains stable system utilities under ultra-limited resources.…”
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Research on multi-condition optimization of centrifugal compressor impeller meridian profile. by Ning Yu, Xiaohan Yu, Zhi Cai, Xinle Yang, Liyong Tian, Song Li

“…The optimization goal is to improve the overall average efficiency while maintaining the high pressure ratio based on the prototype scheme. …”
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Cooperative Control and Intelligent Optimization for Air-Sea Heterogeneous Unmanned Systems by Can KE, Huifang CHEN, Lei XIE

“…Simulation results demonstrate that the air-sea heterogeneous unmanned system can achieve formation control while avoiding obstacles and reducing communication overhead, and the proposed algorithm has better convergence and global search ability than the traditional multi-objective quantum-behavior particle swarm optimization algorithm.…”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
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Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…The performance of several machine learning and deep learning models, including Long Short-Term Memory, Autoregressive Integrated Moving Average, Multilayer Perceptron, Random Forest, XGBoost, Support Vector Regression, and a hybrid CNN-LSTM model, is evaluated for daily solar radiation forecasting. To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Improving the Integrity of a Voting Process with Biometric Authentication and Data Encryption by Walter M. Molina, Lino R. Mac Kay, Daniel Subauste

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MODEL FOR THE FORMATION OF A PROJECT TEAM COMPOSITION BASED ON DISCRETE OPTIMIZATION METHODS by S.M. Beketov, M.V. Dergachev, S.G. Redko

“…The problem lies in the need to improve the efficiency and effectiveness of projects by optimizing the composition of teams. …”

Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…To manage this complexity, a novel optimization algorithm was implemented to perform multi-objective optimization. …”
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An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO by Xiaohu Liang, Shuguo Pan, Shitong Du, Baoguo Yu, Shuang Li

“…Compared to the non-dominated sorting genetic algorithm II (NSGA-II), the convergence speed increases by 33.33% and 36.99%, while optimization accuracy improves by 36.84% and 29.41%. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Beamforming Optimization for Information Enhancement Transmission in MISO SWIPT with NOMA System by Qing Miao, Longtao Zhou, Jiongqi Wang

“…Detailed simulation experiments indicate that the algorithm improves the performance of NOMA downlink beamforming under the condition of enhancing information and eliminating network interference.…”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

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