Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…Additionally, precipitation displayed a U-shaped relationship with BD risk in both the Subtropical Semi-Humid and Plateau Cold Climate Zones.ConclusionThis study developed a climate zone-specific predictive model for BD, systematically evaluating the interactions between environmental factors and BD dynamics. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The developed machine learning models with high predictive accuracy, suggest the potential of Kinect-based gait assessment as a real-time and cost-effective screening tool for older adults with depressive symptoms.…”
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Forecasting COVID-19 cases based on mobility by Mehmet Şahin

“…In this context, various machine learning algorithms are implemented to obtain accurate predictions. …”
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A method for measuring carbon emissions from power plants using a CNN-LSTM-Attention model with Bayesian optimization by Jiacheng Chen, Li Zheng, Wenyan Che, Li Liu, Hui Huang, Jun Liu, Chang Xing, Penghua Qiu

“…Accurate measurement of CO2 emissions from coal-fired power plants is crucial for achieving China's “carbon neutrality” goal; however, traditional CO2 emission measurement methods have several limitations, and emerging prediction models rarely utilize real-time monitoring data from power plants at the micro level. …”
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Conceptualizing an AI-based Police Robot for Preventing Online Child Sexual Exploitation and Abuse: by Nina Sunde, Inger Marie Sunde

“…Given the advancements in machine learning algorithms, PrevBOT may provide predictions concerning age and gender behind online aliases engaged in sexualized speech with children and assist the police in identifying former CSEA offenders who resume the criminal activity online. …”
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Energy Consumption Optimization for an Electric Delivery Vehicle by Andrzej Łebkowski

“…This publication proposes an electronic Energy Consumption Optimizer (ECO) that predictively uses information about the shape of the route and speed limits on its individual sections to control the motor speed and gear changes in the gearbox. …”
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Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment by Na Zhang

“…Through the BP of mobile human-computer interaction equipment, hereditary, genetic algorithms, and Hi-PLS regression method in the artificial neural network, the psychological pressure of college students is identified, evaluated, and predicted from three dimensions such as learning, life, and personal events. …”
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Confidence-Guided Frame Skipping to Enhance Object Tracking Speed by Yun Gu Lee

“…The proposed method determines the need for intervention by the robust algorithm based on the predicted confidence level. …”
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Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry by Bowen Cai

“…With the rapid development of science and technology, deep learning continues to make breakthroughs, and, in the field of economy with huge information data, we have more powerful weapons available to predict and research important economic data with infinite value, which can not only provide reference information to policy makers but also help enterprises and even economic markets to develop more healthily and sustainably. …”
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Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields by Gengming Zhang, Lihua Zhang, Yitao Wang, Chunyu Kang, Yinfei Zhou, Xiaodong Ma, Zeyuan Dai, Shaxige Wu

“…The result is subsequently incorporated into the sonar equation to develop a noise-considerate concealment effectiveness model, which serves as input for a noise-considerate A* path planning algorithm. Comparative analyses of path planning results demonstrate that, within the studied maritime domain, the noise-prioritized path exhibits a statistically significant reduction in the median detection range by approximately 17%, a 50% reduction in the minimum detection range, and a 20% reduction in the maximum detection range, relative to alternative paths planned with a fixed noise level assumption.…”
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Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule by Fanfan Wang, Fanfan Wang, Jianting Wen, Jianting Wen, Jian Liu, Jian Liu, Ling Xin, Yanyan Fang, Yanyan Fang, Yue Sun, Mingyu He, Mingyu He

“…Bioinformatics prediction, MeRIP-qPCR, RIP, and RNA pull-down assays were employed to identify the m6A modification sites of ENST00000619282 and their interactions with FTO/YTHDF1. …”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…ConclusionThe dual-brain synergy mechanism is based on the integration of mechanisms and data, which ensures model accuracy while enhancing prediction speed, computational efficiency, and fault diagnosis accuracy. …”
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Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa a... by Shaun Scholes, Jennifer S Mindell, Mari Toomse-Smith, Annibale Cois, Kafui Adjaye-Gbewonyo

“…Laboratory- and non–laboratory-based World Health Organization (WHO) and Globorisk algorithms were used to calculate the predicted 10-year total (fatal and nonfatal) CVD risk. …”
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Ga-based MPC for satellite’s attitude and orbit control by Prasitthichai Naronglerdrit, Manukid Parnichkun

“…We propose a novel method that utilizes a nonlinear control strategy optimized by a Genetic Algorithm (GA) in conjunction with Model Predictive Control (MPC), focusing on managing both attitude and orbit simultaneously. …”
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Clinical utility of artificial intelligence–augmented endobronchial ultrasound elastography in lymph node staging for lung cancerCentral MessagePerspective by Yogita S. Patel, BSc, Anthony A. Gatti, PhD, Forough Farrokhyar, MPhil, PhD, Feng Xie, PhD, Waël C. Hanna, MDCM, MBA

“…NeuralSeg was able to predict 98 of 143 true negatives and 34 of 44 true positives, resulting in an overall accuracy of 70.59% (95% CI, 63.50-77.01), sensitivity of 43.04% (95% CI, 31.94-54.67), specificity of 90.74% (95% CI, 83.63-95.47), positive predictive value of 77.27% (95% CI, 64.13-86.60), negative predictive value of 68.53% (95% CI, 64.05-72.70), and area under the curve of 0.820 (95% CI, 0.758-0.883). …”
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Differential Evolution for Optimizing Model Parameters in Simulation of Direct Dimethyl Carbonate Synthesis by Outi Ruusunen, Riitta Keiski, Mika Ruusunen

“…When validated with data of a real-world batch process, the model accurately predicted evolution of reaction composition ratios in time, offering a tool for predictive optimization. …”
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Synergistic feature selection and distributed classification framework for high-dimensional medical data analysis by D. Dhinakaran, L. Srinivasan, S. Edwin Raja, K. Valarmathi, M. Gomathy Nayagam

“…In order to overcome these drawbacks, the new integrated algorithm is presented here: Synergistic Kruskal-RFE Selector and Distributed Multi-Kernel Classification Framework (SKR-DMKCF). …”
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Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators by Qin Yan, Jinxin Wang, Tao Lin, Archie James Johnston

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A Capacitated Vehicle Routing Model for Distribution and Repair with a Service Center by Irma-Delia Rojas-Cuevas, Elias Olivares-Benitez, Alfredo S. Ramos, Samuel Nucamendi-Guillén

“…<i>Results:</i> The model was applied to a real-world case study, achieving a 40% reduction in fuel costs, a reduction from 5 to 3 routes, and a sustainable logistics operations model with potential reductions of greenhouse gas emissions and item disposals. …”
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Channel estimation method of massive MIMO-OFDM system based on adaptive compressed sensing by Yiyang HU, Lina QI

“…Massive multiple-input multiple-output (MIMO) is a solution for efficiently providing connection services for a variety of machine equipment in the Internet of things (IoT), and efficient connection services require accurate channel estimation.Aimed at the problems of high pilot overhead and poor performance of normalized mean square error (NMSE) estimation in downlink channel estimation of massive MIMO systems, based on the compressed sensing (CS) theory, the common sparsity of the channel space domain was combined while using the feature of lower sparsity of adjacent time slot differential channel impulse response (CIR), which leaded to a significant reduction in pilot overhead.In the reconstruction algorithm, a two-stage differential estimation algorithm, which divided the channel estimation in consecutive time slots with time correlation into two stages, was proposed and the idea of adaptive compressed sensing was combined to achieve fast and accurate CIR estimate.The simulation results show that the proposed two-stage differential channel estimation algorithm not only has a significant improvement in the estimated NMSE performance and data transmission rate compared to the existing CS-based multiple measurement vector (MMV) algorithm, but also show a certain reduction in runtime complexity.…”
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