Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

“…In this paper, we construct a data set for strong gravitational lensing searches that consist of known lenses and lens candidates from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys (the DESI Legacy Imaging Surveys) and the Dark Energy Survey (DES) and non-lenses from the Legacy Surveys Data Release 9 (DR9). We apply the YOLOX algorithm as the basic framework and improve it by selecting the optimal optimizer, activation function, attention mechanism, and loss function. …”
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Collision-Free Path Planning for Multiple Drones Based on Safe Reinforcement Learning by Hong Chen, Dan Huang, Chenggang Wang, Lu Ding, Lei Song, Hongtao Liu

“…To this end, this paper proposes an end-to-end planning method based model-free RL framework with optimization, which can achieve better learning performance with a safety guarantee. …”
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Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control by Yong Wang, Jiachen Li, Mingzhu Ji, Xiwen Qiao, Yang Wang

“…According to the mechanical characteristic of the inerter, the acceleration-velocity switch (AVS) control strategy is proposed to adjust the inertance of the SA-FO inerter. The dynamic model of the SA-FOIB suspension with AVS control is established, its dynamic response under road harmonic excitation is obtained using the averaging method, the dynamic performance under road harmonic and random excitations is analyzed and evaluated by the vehicle body acceleration, suspension dynamic deflection and wheel dynamic load, the optimized structural parameters are obtained using the genetic algorithm optimization method. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
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A Passive Radar System for Monitoring of Coastal Areas Ship Traffic Using Satellite Illumination Signals by Nguyen Van Quan

“…During development and implementation of the systems, there are a number of problems related to the search of highly efficient processing algorithms, to the optimization of structure and functioning modes when the system is a part of a complex multi-position monitoring system in coastal areas. …”
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High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor by Ji-wang Zhang, Ke-qin Ding, Guang Chen

“…A new denoising and shaping algorithm based on ensemble empirical mode decomposition (EEMD) was introduced for the errors caused by background noise. …”
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Research on the ordering strategy problem in supply chain with profit allocation under two-level price-fluctuation sales. by Minchao Zheng, Ying Yu, Jiayang Xu, Yunzhi Mu

“…A discrete algorithm is proposed to approximate the optimal solution, with its convergence rigorously proven. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. …”
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Automatic Quality Assessment of Speech-Driven Synthesized Gestures by Zhiyuan He

“…At the same time, in terms of performance, the model has an improvement of about 20% compared to before the algorithm adjustment.…”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…The qualitative and quantitative evaluation results show that MCSP is superior to two classical cost calculation methods and shows good transferability and applicability in the popular disparity estimation algorithms, which can significantly enhance the definition of the edges of the ground objects and improve the quality of the disparity estimation in the shadow occlusion areas.…”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…Accurately predicting the remaining useful life (RUL) of rolling bearings is crucial for ensuring optimal equipment operation and timely maintenance. …”
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A plug and play fuzzy mask extraction module for single image deraining by Mingdi Hu, Yao Song, Songxin Zhang, Zejian Xie, Bingyi Jing

“…Comprehensive experiments show that combining the rain removal network with our proposed model not only improves the rain removal effect of the algorithm, but also gives clearer background details of the image. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Existing methods, including post-processing optimization, specific model based improvements, and body part feature based methods, have limitations such as inaccurate handling of heavily occluded positive samples, high computational complexity, and susceptible to background noise. …”
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Machine Learning and Neural Networks for IT-Diagnostics of Neurological Diseases by U. A. Vishniakou, Y. W. Xia, Ch. Y. Yu

“…Among them are the GridSearchCV algorithm for optimizing the hyperparameters of the random forest classifier for recognizing Alzheimer’s disease (recognition accuracy is 87.6 %) and the KNN algorithm for training and testing on publicly available datasets of speech change features in patients with Parkinson’s disease. …”
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Vulnerability Assessment in Karst Aquifers with EPIK and COP Indices Calibration by Hamid Kardan Moghadam, Amir Reza Nemati Mansour, Abbas Akbarzadeh, Ali Mirarabi

“…In order to calibrate the GQI qualitative index with the zoning of the springs in the region, whale optimization algorithms were used. In this calibration, the weights and ranks of the two vulnerability indices were determined. …”
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Multiple Interface Parallel Approach of Bioinspired Routing Protocol for Mobile Ad Hoc Networks by L. J. García Villalba, D. Rupérez Cañas, A. L. Sandoval Orozco, T.-H. Kim

“…The simulation results indicate that PAntOR and PAntOR-MI improve performances of AntOR, whilst it is also noticed that PAntOR-MI is the most suitable for highly dynamic environments.…”
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Analytical framework for household energy management: integrated photovoltaic generation and load forecasting mechanisms by Zhenping Xie, Yansha Li

“…To address the challenges associated with the intermittent and variable nature of solar energy, an innovative hybrid model is proposed. Specifically, this research integrates the K-nearest neighbor (KNN) classification method and genetic algorithm (GA) to optimize a backpropagation neural network (BPNN). …”
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