Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…Automated machine-learning algorithms that analyze biomedical signals have been used to identify sleep patterns and health issues. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Predicting student performance is crucial for providing personalized support and enhancing academic performance. Advanced machine-learning approaches are being used to understand student performance variables as educational data grows. …”
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Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…The performance of LSTM is compared with other machine learning algorithm such as Decision tree (DT), Linear regression (LR) and Gradient Boosting. …”
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Keywords, morpheme parsing and syntactic trees: features for text complexity assessment by Dmitry A. Morozov, Ivan A. Smal, Timur A. Garipov, Anna V. Glazkova

“…We conducted a comparison using four different machine learning algorithms and four annotated Russian-language text corpora. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…As part of this study, we compared the outputs generated by two unsupervised machine learning algorithms with a conventional image clustering technique. …”
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Design of an Electronic Nose System with Automatic End-Tidal Breath Gas Collection for Enhanced Breath Detection Performance by Dongfu Xu, Pu Liu, Xiangming Meng, Yizhou Chen, Lei Du, Yan Zhang, Lixin Qiao, Wei Zhang, Jiale Kuang, Jingjing Liu

“…Finally, the system is used for breath detection. We employ classical machine learning algorithms to classify breath samples from different health conditions with a classification accuracy of more than 90%, which is better than the accuracy achieved in other studies of this type. …”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…Future research should explore the integration of advanced sensors, machine learning algorithms, and predictive models to further optimize irrigation strategies, with an emphasis on scalability and environmental impact. …”
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Mapping forest types along ecological gradient in Pakistan by Naveed Ahmad, Syed Ghias Ali

“…This study suggests that mapping of forest types through machine learning algorithms may be improved by incorporating other explanatory variables such as microclimate, soil types, nutrients, anthropogenic, demographic factors and spectral indices.…”
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Assessing the association between ADHD and brain maturation in late childhood and emotion regulation in early adolescence by Kristóf Ágrez, Pál Vakli, Béla Weiss, Zoltán Vidnyánszky, Nóra Bunford

“…Whether the difference between an individual’s brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual’s chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. …”
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Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management by Anderson Jhones Passos Nascimento, Menaouar Berrehil El Kattel, Jose Antonio Fernandes de Macedo, Fernando Luiz Marcelo Antunes

“…The research employs time series techniques and clustering algorithms to identify atypical consumption profiles and regular patterns based on average monthly consumption and contracted power demand. …”
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Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area by Aibo Jin, Hui Li, Xiangrong Wang, Ziyao Wang

“…The XGBoost algorithm elucidates the multifaceted driving mechanisms, and geographically weighted regression (GWR) quantifies the spatial variability of these drivers. …”
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Luminescence-enabled three-dimensional temperature bioimaging by Liyan Ming, Anna Romelli, José Lifante, Patrizia Canton, Ginés Lifante-Pedrola, Daniel Jaque, Erving Ximendes, Riccardo Marin

“…The optimized neural network-based algorithm can extract this information and provide 3D thermal images of complex nanothermometer patterns. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit by Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo, Oliverio Cruz-Mejia, Jose-Manuel Mejia-Muñoz

“…<i>Methods</i>: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. …”
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A multimodal approach for ADHD with coexisting ASD detection for children by Jungpil Shin, Sota Konnai, Md. Maniruzzaman, Yoichi Tomioka, Yong Seok Hwang, Akiko Megumi, Akira Yasumura

“…The potentiality of these features was evaluated using Sequential Forward Floating Selection (SFFS)-based algorithm and support vector machine (SVM) was employed to evaluate the performance of ZL and PL tasks. …”
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Comprehensive analysis of mRNA and lncRNA expression for predicting lymph node metastasis in cervical cancer: a novel seven-gene signature approach by Jiahui Wei, Ming Wang, Yumei Wu

“…The differential expression of mRNAs and lncRNAs was identified using DESeq2. Subsequently, dual machine learning strategies—LASSO regression and the Boruta algorithm—were applied to select robust biomarkers. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…Abstract The existing coal-rock identification technology based on machine vision makes it difficult to accurately identify coal-rock images with low distinguishability. …”
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Hierarchical genetic structure in an evolving species complex: Insights from genome wide ddRAD data in Sebastes mentella. by Atal Saha, Matthew Kent, Lorenz Hauser, Daniel P Drinan, Einar E Nielsen, Jon-Ivar Westgaard, Sigbjørn Lien, Torild Johansen

“…We identified a SNP panel with only 21 loci to discriminate populations in mixed samples based on a machine-learning algorithm. This first SNP based investigation clarifies the population structure of S. mentella, and provides novel and high-resolution genomic tools for future investigations. …”
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The impact of artificial intelligence on financial auditing: the case of Algeria by Amira Benachour, Ramzi Kaddai, Hanane Abdelmalek, Fella Bochelgoum, Lamine Tarhlissia

“…It enables auditors to go beyond the limits of manual analysis, facilitating more accurate and data-driven decisions. AI algorithms can analyze vast volumes of transactions to detect anomalies that may indicate fraud, such as duplications, unexplained discrepancies, or unusual transaction patterns. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…These models utilize numerous technologies and sensors to monitor day-to-day work like movement, medication adherence, and sleep patterns, and provide valued perceptions of the user’s everyday life and entire health. …”
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