Inter layer up-sampling filtering scheme applied in SVC by WANG Zhang1, LIU Jian2, YAN Guo-ping2

“…An efficient inter layer up-sampling filtering algorithm in scalable video coding （SVC） was proposed. …”
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On Some Types of Multigranulation Covering Based on Binary Relations by Ashraf Nawar, E. A. Elsakhawy

“…Then, we put forward an algorithm to illustrate the method of reduction based on the presented model. …”
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Genetic analysis of a serologically weak D phenotype caused by the p. R191G variant of the RHAG gene by ZHANG Xu, LI Xiaofeng, LI Jianping

“…R191Q) mutation was predicted to be “probably damaging”, “deleterious” and “affected” by PolyPhen2, PROVEAN and Mutation Taster algorithms, respectively. …”
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Application of machine learning in forensic geochemistry using presalt oil samples from the Santos basin by Gil Marcio Avelino Silva, Fernando Pellon de Miranda, Jarbas Vicente Poley Guzzo, Wagner Leonel Bastos, Ygor Rocha, Igor Viegas Alves Fernandes de Souza, Italo Oliveira Matias, Sarah Barron Torres, Francisco Fabio de Araujo Ponte

“…A dataset comprising 2200 presalt oil samples and 75 attributes from the Santos Basin underwent preprocessing and exploratory analysis, resulting in 2137 samples and 62 predictive attributes. Seven machine learning algorithms were evaluated, with the random forest model achieving the highest classification accuracy of 91%. …”
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Visualizing fatigue mechanisms in non-communicable diseases: an integrative approach with multi-omics and machine learning by Yusuke Kobayashi, Naoki Fujiwara, Yuki Murakami, Shoichi Ishida, Sho Kinguchi, Tatsuya Haze, Kengo Azushima, Akira Fujiwara, Hiromichi Wakui, Masayoshi Sakakura, Kei Terayama, Nobuhito Hirawa, Tetsuo Isozaki, Hiroaki Yasuzaki, Hajime Takase, Yuichiro Yano, Kouichi Tamura

“…LightGBM, a gradient boosting algorithm, was used for fatigue prediction, and model performance was evaluated using the F1-score, accuracy, and receiver operating characteristic area under the curve using leave-one-out cross-validation. …”
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Q-Learning-Based Medium Access Technology for Minimizing AoI in LoRa Wireless Relay Networks by Dowon Kim, Geonha Hwang, Ohyun Jo, Kyungseop Shin

“…Simulations demonstrate significant performance improvements over baseline algorithms, achieving average AoI reductions of 23% in high-density scenarios and 31% in high data transfer environments. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Recent advancements in artificial intelligence (AI) and machine learning (ML) have significantly improved the ability to analyze complex datasets, predict molecular properties, and design new compounds. …”
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Features of Breast Cancer Progression after Comprehensive Treatment, Prognosis of Metastatic Spread by Yu. Chuprovska, V. Bodiaka, O. Ivashchuk, Ch. Tsagkaris

“…Still, there are no clear criteria and algorithms for predicting the occurrence of this complication. …”
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Contrastive Disentangled Variational Autoencoder for Collaborative Filtering by Woo-Seong Yun, Seong-Min Kang, Yoon-Sik Cho

“…Recommender systems aim to accurately predict user preferences in order to provide potential items of interests. …”
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A localization strategy combined with transfer learning for image annotation. by Zhiqiang Chen, Leelavathi Rajamanickam, Jianfang Cao, Aidi Zhao, Xiaohui Hu

“…The optimal K value is obtained experimentally and used to determine the number of predicted labels, thereby solving the empty label set problem that occurs when the predicted label values of images are below a fixed threshold. …”
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A novel machine learning-based approach to thermal integrity profiling of concrete pile foundations by Javier Sánchez Fernández, Agustín Ruiz López, David M.G. Taborda

“…This is followed by a regression algorithm that predicts the defect size and its location within the cross-section. …”
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Optimizing the learning rate for adaptive estimation of neural encoding models. by Han-Lin Hsieh, Maryam M Shanechi

“…Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…The effectiveness of sulfur removal was predicted by analyzing five important factors: temperature, concentration, surface area, fuel/adsorbent, and time. …”
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An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion by Kavita Rawat, Trapti Sharma

“…The model achieved promising results with high accuracy (98.54%) and sensitivity (97.77%) in predicting mental problems, including neurological and psychiatric conditions. …”
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Spatial Evaluation of <i>Salurnis marginella</i> Occurrence According to Climate Change Using Multiple Species Distribution Models by Jae-Woo Song, Jaho Seo, Wang-Hee Lee

“…This distribution currently covers approximately 9.53% of the global land area; however, the model predicted this distribution would decrease to 6.85%. …”
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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. …”
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Clinically validated graphical approaches identify hepatosplenic multimorbidity in individuals at risk of schistosomiasis by Yin-Cong Zhi, Simon Mpooya, Narcis B. Kabatereine, Betty Nabatte, Christopher K. Opio, Goylette F. Chami

“…Co-occurrence graphs were clinically uninformative with low predictive capacity. Graph learning algorithms with statistical assumptions, e.g. graphical lasso, enabled accurate and clinically valid multimorbidity representations. …”
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Financing Mechanisms and Preferences of Technology-Driven Small- and Medium-Sized Enterprises in the Digitalization Context by Jing Hu, Lianming Huang, Weifu Li, Hongyi Xu

“…Additionally, six machine learning (ML) algorithms were employed to predict financing preferences. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…This improvement highlights the effectiveness of ensemble learning in integrating different algorithmic perspectives to enhance predictive performance. …”
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Monitoring the Concentrations of Na, Mg, Ca, Cu, Fe, and K in <i>Sargassum fusiforme</i> at Different Growth Stages by NIR Spectroscopy Coupled with Chemometrics by Sisi Wei, Jing Huang, Ying Niu, Haibin Tong, Laijin Su, Xu Zhang, Mingjiang Wu, Yue Yang

“…The effects of four spectral pretreatment methods and three wavelength selection methods, including the synergy interval partial least squares (SI-PLS) algorithm, genetic algorithm (GA), and competitive adaptive reweighted sampling method (CARS) on the model optimization, were evaluated. …”
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