PCMINN: A GPU-Accelerated Conditional Mutual Information-Based Feature Selection Method by Nikolaos Papaioannou, Georgios Myllis, Alkiviadis Tsimpiris, Stamatis Aggelopoulos, Vasiliki Vrana

“…Conditional Mutual Information Nearest-Neighbor (CMINN) is an algorithm developed to address this challenge by using Conditional Mutual Information (CMI) to assess the relevance of individual features to the target variable, while identifying redundancy among similar features. …”
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Efficient collision-avoidance navigation strategy for autonomous surface vehicles in unstructured and constricted marine environments by Wenlong Meng, Rongdian Ku, Yanbo Pu, Xiaoxiao Shi, Ya Gong

“…Current path planning algorithms designed for unstructured environments, particularly those characterized by narrow spaces, often face difficulties in efficiently exploring the target area while producing high-quality paths. …”
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A quantum random access memory (QRAM) using a polynomial encoding of binary strings by Priyanka Mukhopadhyay

“…Abstract Quantum algorithms claim significant speedup over their classical counterparts for solving many problems. …”
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Adaptive Fast Refocusing for Ship Targets With Complex Motion in SAR Images by Xinqi Xu, Xiangguang Leng, Zhongzhen Sun, Xiangdong Tan, Kefeng Ji, Gangyao Kuang

“…This algorithm can adaptively adjust algorithm parameters based on SAR images from different SAR platforms, thereby more accurately determining the optimal rotation interval (ORI), reducing computational cost, and achieving adaptive fast refocusing. …”
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PP-QADMM: A Dual-Driven Perturbation and Quantized ADMM for Privacy Preserving and Communication-Efficient Federated Learning by Anis Elgabli

“…We provide a rigorous theoretical proof of convergence, showing that PP-QADMM converges to the optimal solution for convex problems while achieving a convergence rate comparable to standard ADMM, but with significantly lower communication and energy costs, and robust privacy protection. …”
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Exploration of Energy-Saving Chilling Landscape Design Based on Algo for Group Intelligence by Zhuo Li

“…With the development of electronic computers, the previously unachievable optimization of engineering structures is now possible, while the traditional optimization methods cannot meet the requirements of modern computing due to the implementation constraints. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…While synthetic data enables controlled algorithm comparison, real-world clinical validation remains essential before deployment.…”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. …”
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Prediction of Transformer Residual Flux Based on J-A Hysteresis Theory by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Mingchun Hou, Yu Xin, Dehua Xiong, Xiongying Duan

“…The problem of slow convergence speed and susceptibility to local optima in traditional particle-swarm optimization algorithms is solved by optimizing the velocity and position-update formulas of particles in this algorithm. …”
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Deployment and Operation of Battery Swapping Stations for Electric Two-Wheelers Based on Machine Learning by Yu Feng, Xiaochun Lu

“…This study developed a data-driven optimization model based on machine learning algorithms using Beijing’s battery swapping stations and point of interest (POI) dataset. …”
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RFID-Based Real-Time Salt Concentration Monitoring with Adaptive EKF by Renhai Feng, Xinyi Lin

“…The concentration dynamics are modeled as a hidden Markov process and tracked using an adaptive extended Kalman filter (AEKF). The AEKF algorithm avoids computationally expensive inversion of complex observation equations while automatically adjusting noise covariance matrices via innovation sequence. …”
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Graph attention networks based multi-agent path finding via temporal-spatial information aggregation. by Qingling Zhang, Peng Wang, Cui Ni, Xianchang Liu

“…An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. …”
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Short-term results of treatment of non-epithelial gastro-intestinal tumors complicated by bleeding by S. G. Shapovalyants, A. I. Mikhalev, Ye. D. Fedorov, R. V. Plakhov, L. M. Mikhaleva, Z. V. Galkova, Ye. V. Ivanova, A. E. Sergeyenko

“…According to suggested diagnostic algorithm detailed characteristic of patients with bleeding tumor was given, the optimal method of surgical intervention was chosen. …”
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MAARS: Multiagent Actor–Critic Approach for Resource Allocation and Network Slicing in Multiaccess Edge Computing by Ducsun Lim, Inwhee Joe

“…This paper presents a novel algorithm to address resource allocation and network-slicing challenges in multiaccess edge computing (MEC) networks. …”
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THE USE OF CORRELATION ANALYSIS OF TWO-DIMENSION STOCHASTIC PROCESS FOR HELICOPTER MAINTENANCE WORKABILITY ESTIMATION by Y. M. Chinyuchin, A. S. Solov’ev

“…The new calculated program complex which main task is to find the optimal algorithm of stochastic helicopter de- sign and assembling in terms of maintenance efficiency is described. …”
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Accurate extraction of electrical parameters in three-diode photovoltaic systems through the enhanced mother tree methodology: A novel approach for parameter estimation. by Mouncef El Marghichi, Abdelilah Hilali, Abdelkhalek Chellakhi, Mohamed Makhad, Azeddine Loulijat, Najib El Ouanjli, Abdelhak Essounaini, Vikash Kumar Saini, Ameena Saad Al-Sumaiti

“…This balance between exploration and exploitation allows the algorithm to dynamically and effectively identify optimal parameters. …”
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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Building upon the RT-DETR framework, this study proposes a Multiscale Separable Deformable (MSD) module that integrates depthwise convolution with deformable convolution to enhance feature extraction capabilities while reducing computational load. Additionally, a Deformable Agent Attention (DAA) mechanism is designed to optimize attention weights through sparse queries, effectively improving detection accuracy for small targets and enhancing inference speed in complex scenarios. …”
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A Task Offloading and Resource Allocation Strategy Based on Multi-Agent Reinforcement Learning in Mobile Edge Computing by Guiwen Jiang, Rongxi Huang, Zhiming Bao, Gaocai Wang

“…In addition, the drop rate of some baseline algorithms with 50 users can achieve 62.5% for critical tasks, while the proposed TOMAC-PPO only has 5.5%.…”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…Global FFT processing extracts real-time Doppler-SNR parameter pairs, while a KNN-based arbiter dynamically selects the optimal estimator by: (1) Projecting parameter pairs into historical performance space, (2) Identifying the accuracy-optimal algorithm for current beam conditions, and (3) Executing real-time switching to balance accuracy and robustness. …”
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An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base by Qingqing Yang, Shiming Li, Yuhe Wang, Guoxing Li, Yanbin Yuan

“…Then, in combination with the Selection covariance matrix adaptive evolution strategy (S-CMA-ES) algorithm, a parameter optimization method for the BRB-s model is designed, which expands the selective constraints on expert knowledge. …”
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