Optimization of variable-speed weighing detection and intelligent regulation device for seeding amount in rice seedling trays by Xihong HU, Xu MA, Yuwei WANG, Xicheng WANG, Lei ZHONG, Suiyan TAN

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An Efficient Aerial Image Detection with Variable Receptive Fields by Wenbin Liu, Liangren Shi, Guocheng An

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Intelligent Stress Detection Using ECG Signals: Power Spectrum Imaging with Continuous Wavelet Transform and CNN by Rodrigo Mateo-Reyes, Irving A. Cruz-Albarran, Luis A. Morales-Hernandez

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Application of Artificial Intelligence in Obsessive-Compulsive Disorder Detection and Response to Treatment: A Systematic Review by Faezeh Ghasemi, Ahmad Shalbaf, Ali Esteki

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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

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Monitoring and Interpretation of Process Variability Generated from the Integration of the Multivariate Cumulative Sum Control Chart and Artificial Intelligence by Edgar Augusto Ruelas-Santoyo, Vicente Figueroa-Fernández, Moisés Tapia-Esquivias, Yaquelin Verenice Pantoja-Pacheco, Edgar Bravo-Santibáñez, Javier Cruz-Salgado

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The Early Detection of Cardiac Fatigue: Could the HRV Be Used as a Physiological Biomarker by AI? by Giovanna Zimatore, Maria Chiara Gallotta, Marco Alessandria, Matteo Campanella, Marta Ricci, Leonarda Galiuto

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Design and motion analysis of a coal mine robot with variable wheel diameter by Liguo Han, Fei Ding, Lijuan Zhao, Peng Li, Chuanzong Li, Mingjun Liu, Liangliang Ren, Yuhao Li

“…This provides new ideas for the research of special detection robots and the intelligence of coal mines in the future.…”
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The dark tetrad as associated factors in generative AI academic misconduct: insights beyond personal attribute variables by Rongjian Sun, Minmin Tang, Minmin Tang, Junjun Zhou, Nguyen Thi Thuy Loan, Cheng-Yen Wang

“…Unlike traditional plagiarism, which typically involves copying existing text, generative artificial intelligence-generated content often appears sufficiently original to evade detection systems. …”
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Evaluating the Influence of Clinical Data on Inter-Observer Variability in Optic Disc Analysis for AI-Assisted Glaucoma Screening by Pourjavan S, Bourguignon GH, Marinescu C, Otjacques L, Boschi A

“…This study evaluated how consistently different eye specialists assess these photographs and what this variability means for developing artificial intelligence (AI) tools to detect glaucoma.The study involved 70 individuals screened for glaucoma using fundus photographs. …”
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Fleet‐Wide Data‐Driven Model Generation Process for Residual‐Based Fault Detection in Wind Energy by Théodore Raymond, Sylvie Charbonnier, Christophe Bérenguer, Alexis Lebranchu

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Influence of Sliding Time Window Size Selection Based on Heart Rate Variability Signal Analysis on Intelligent Monitoring of Noxious Stimulation under Anesthesia by Qiang Yin, Dai Shen, Qian Ding

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Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…Variable selection (VS) is a critical step in developing predictive binary classification (BC) models. …”
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Using Explainable Machine Learning Methods to Predict the Survivability Rate of Pediatric Respiratory Diseases by Roshan Kumar, V Srirama, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, Srikanth Prabhu, Rajagopala Chadaga

“…Large datasets of clinical variables are analyzed by machine learning (ML) to find patterns and co-relations that human clinicians might not be able to predict immediately. …”
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An intelligent recognition method for electrical work permits based on seed growth strategy and deep neural networks by LIAO Meiying, ZHOU Junhuang, ZHANG Yongjun

“…Then， during text recognition， the method combines DenseNet’s deep feature extraction capabilities with the CTC technique’s mechanism for aligning variable-length sequences， enhancing the recognition performance of character sequences. …”
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Exploring the impact of gender-related variables on health measures and perceived stress by Maria Picó-Pérez, Maria Picó-Pérez, Maria Picó-Pérez, Marisa S. Coelho, Marisa S. Coelho, Rita Vieira, Rita Vieira, Rita Vieira, Mafalda Machado-Sousa, Mafalda Machado-Sousa, Mafalda Machado-Sousa, Pedro Morgado, Pedro Morgado, Pedro Morgado

“…Regarding stress, it was positively associated with discrimination and work strain, while it was negatively associated with social support, emotional intelligence and risk-taking. Finally, discrimination and work strain were positively associated with mental health worsening and activity limitations, while social support was negatively associated with mental health worsening.DiscussionIn conclusion, by approaching gender from a multidimensional perspective we detected specific factors influencing health outcomes, showing that the relational aspects of gender are particularly relevant for mental health.…”
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Variable Selection Algorithm for Explaining Anomalies in Real-World Regenerative Thermal Oxidizers by Min-Ji Seo, Myung-Ho Kim

“…Using the most influencing variables based on our method, XAI correctly identified the main variables without considering unnecessary variables. …”
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Innovative Sandia Frequency Shift Islanding Detection for Microgrids Using Interval Type-II Fuzzy Logic and VP-PSO Optimization by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yeonwoo Lee, Sun-Kyoung Kang, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

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Artificial Intelligence in the Non-Invasive Detection of Melanoma by Banu İsmail Mendi, Kivanc Kose, Lauren Fleshner, Richard Adam, Bijan Safai, Banu Farabi, Mehmet Fatih Atak

“…While these techniques are useful, there is wide inter-user variability and minimal training for dermatology residents on how to properly use these devices. …”
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Identification of atrial fibrillation using heart rate variability: a meta-analysis by Ziwei Yin, Changxin Liu, Chenggong Xie, Zixing Nie, Jiaming Wei, Wen Zhang, Hao Liang

“…Recently, artificial intelligence (AI) algorithms have leveraged heart rate variability (HRV) patterns to enhance the accuracy of AF identification.MethodsWe conducted a systematic review of the literature by searching four major biomedical databases—PubMed, Web of Science, Embase, and Cochrane Library—spanning from their inception to December 13, 2024, following the PRISMA guidelines. …”
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