Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis by Jinyan Kai, Jiaqi Su, Yinping You, Xiaoliang Liang, Haitao Huang, Jie Fang, Qiong Chen

“…The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. …”
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PM2.5 concentration 7-day prediction in the Beijing–Tianjin–Hebei region using a novel stacking framework by Xintong Gao, Xiaohong Wang, Fuping Li, Wenhao Jiang, Meng Zhe, Jiaxing Sun, Ao Zhang, Linlin Jiao

“…The findings of this study demonstrated that the integration of the LSTM-RF model with the fusion-based Stacking algorithm led to a substantial enhancement in the accuracy of PM2.5 predictions. …”
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RESULTS DESIGNING AND ANALYSIS WHEN INTRODUCING NEW BEVERAGE IDENTIFICATION CRITERIA by I. I. Ageikina, E. G. Lazareva, I. Yu. Mikhailova, V. K. Semipyatny

“…The article discusses an algorithm for constructing a flexible experimental design for the new identification criteria development, taking into account the laboratory research peculiarities in the beverage industry. …”
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A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems by Badreddine Kanouni, Abd Essalam Badoud, Saad Mekhilef, Ahmed Elsanabary, Mohit Bajaj, Ievgen Zaitsev

“…The computational cost of the overall system is rather low, making it feasible to construct using PLECS RT Box 1. The new MPPT algorithm quickly finds the maximum power point (MPP) and balances the voltage of capacitors in a number of different proton exchange membrane fuel cells. …”
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Exploration of the ubiquitination-related molecular classification and signature to predict the survival and immune microenvironment in colon cancer by Ji-Zhong Xu, Tian-Qi Wan, Jin-Song Su, Jun-Min Song

“…Quantitative scores for 28 immune cell infiltrates and the tumor microenvironment were computed using single-sample gene set enrichment analysis (ssGSEA) and the Estimate algorithm. Subtype feature genes were selected through Lasso logistic regression and SVM-RFE algorithm. …”
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Comparison of Deep Learning Sentiment Analysis Methods, Including LSTM and Machine Learning by Jean Max T. Habib, A. A. Poguda

“…In general, both deep classification algorithm. A combination of both approaches can also learning and feature-based selection methods can be used to solve be used to further improve the efficiency of the algorithm. some of the most pressing problems. …”
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Design of an intelligent optimization system for high-altitude photovoltaic power plant output power prediction and enhancement using GVSAO-CNN-BiGRU-Attention by Shuai Yuan, Hui Zhou, Kai Zhao

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A landslide area segmentation method based on an improved UNet by Guangchen Li, Kefeng Li, Guangyuan Zhang, Ke Pan, Yuxuan Ding, Zhenfei Wang, Chen Fu, Zhenfang Zhu

“…Therefore, this paper proposes an improved UNet-based landslide segmentation algorithm. Firstly, the feature extraction structure of the model was redesigned by integrating dilated convolution and EMA attention mechanism to enhance the model’s ability to extract image features. …”
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Advanced Investigation into Active Control Force Requirements for Seismic Damage Mitigation of Inelastic Structures by Ruben Iacob Munteanu, Vasile Calofir, Karol-Cristian Lemnaru, Cătălin Ponta

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Enhanced frame expansion via configuring filterbank topology for rapid processing of multi-sensor vibration data with applications to turbo-machinery fault diag... by Wangpeng He, Yunyi Yan, Lu An, Wei Sun, Baolong Guo

“…In this article, an enhanced frame expansion is constructed via filterbank topology approach, which addresses these problems but at the same time can be implemented via fast numerical algorithm. …”
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RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

“…Additionally, a critic learning optimal control algorithm is developed to determine the control law. …”
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Empowering entity synonym set generation using flexible perceptual field and multi-layer contextual information. by Subin Huang, Daoyu Li, Chengzhen Yu, Junjie Chen, Qing Zhou, Sanmin Liu

“…Secondly, we introduce a dynamic-weight-based algorithm for synthesizing entity synonym sets, leveraging a neural network classifier trained to generate entity synonym sets from the candidate entity vocabulary. …”
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ProvNavigator: shadow path guided attack investigation method by XI Hao, FAN Hao, YUAN Shenyang, ZHU Jinyu, CHEN Changhua, WAN Hai, ZHAO Xibin

“…However, existing log fusion techniques either rely on complex fusion rules or require reverse engineering of applications, necessitating algorithm adjustments when facing new applications, which limits their general applicability. …”
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Analysis of Pre- and during COVID-19 Mixed Load Models on Unbalanced Radial Distribution System Using a New Metaphor-Less Rao Optimization by Jitendra Singh Bhadoriya, A. R. Gupta, Baseem Khan

“…An unbalanced electrical distribution system (DS) with radial construction and passive nature suffers from significant power loss. …”
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Extraction and Analysis of Influencing Factors of Scientific and Technological Ability Improvement of University Teachers Based on Deep Learning Model by Aiqin Wang, Wei Yan

“…In order to improve the development and construction level of colleges and universities and help teachers improve their scientific and technological abilities, a model based on deep learning model for the extraction and analysis of factors affecting the improvement of college teachers’ scientific and technological abilities was proposed. …”
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Distributed robust planning for new power system considering uncertainty and frequency security by Xinxin Zheng, Dahai Zhang, Zhaohong Bie, Xue Wu

“…Firstly, establish a system frequency model that provides frequency support for a fast frequency response energy storage system, and propose an improved segmented linearization algorithm to transform the constructed frequency safety constraints. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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Research and application of water drainage borehole design method based on three-dimensional geological model by Zhenrong WANG

“…The mine roadway model is reconstructed through the roadway centerline with three - dimensional coordinates and relevant attributes; the coal seam model is constructed by triangulating point data and boundary data, and is dynamically updated based on the cross - layer point data during borehole construction; the hydrogeological model is constructed by processing spatial data points using the Delaunay triangulation algorithm, similar to the coal seam modeling method, and is also updated according to the control point data collected during borehole construction. …”
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Urban Land Use Classification Model Fusing Multimodal Deep Features by Yougui Ren, Zhiwei Xie, Shuaizhi Zhai

“…First, we divide the urban area into block units based on road network data and further subdivide these units using the fractal network evolution algorithm (FNEA). Next, the K-nearest neighbors (KNN) graph construction method with adaptive fusion coefficients is employed to generate both global and local graphs of the blocks and sub-units. …”
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A Machine Learning Approach for Predicting Particle Spatial, Velocity, and Temperature Distributions in Cold Spray Additive Manufacturing by Lurui Wang, Mehdi Jadidi, Ali Dolatabadi

“…To bypass the high cost of purely CFD-driven optimization, we construct a two-stage machine learning (ML) framework trained on 48 high-fidelity CFD simulations. …”
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