Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…We used sentence-level classification to categorize sentences including terrorist attacks, national news, sports, entertainment, politics, safety, earthquakes, fraud and corruption, sexual assault, weather, accidents, forces, inflation, murder and death, education, and international news. Deep learning, transformer-based and machine learning classifiers are used for event classification. …”
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An explainable AI-based approach for predicting undergraduate students academic performance by Fatema Tuz Johora, Md Nahid Hasan, Aditya Rajbongshi, Md Ashrafuzzaman, Farzana Akter

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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

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Industrial heat island and carbon emissions: machine learning-based environmental impact assessment in Cilegon, Indonesia by Agus Suprijanto, Yumin Tan, Muhammad Kamran Lodhi, Rodolfo Domingo Moreno Santillan, Isiaka Lukman Alage, Gonzalo Rodolfo Pena Zamalloa

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Modeling the unconfined compressive strength of lateritic soil treated with FGD gypsum as a partial cement replacement by Chidananda M Linganagoudar, Shiva Kumar G, M S Ujwal, G Rohith, A Vinay, Poornachandra Pandit

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A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems by Saiprasad Potharaju, Ravi Kumar Tirandasu, Swapnali N. Tambe, Devyani Bhamare Jadhav, Dudla Anil Kumar, Shanmuk Srinivas Amiripalli

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Predicting adverse drug reactions in oncology: A critical review of machine learning approaches and future directions by Abid Yahya, Phatsimo Lobelo, Afiya Eram, Sana Althaf Hussain, Irfan Anjum Badruddin, Lory Liza D. Bulay-og, Dionel O. Albina

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Applying machine learning to decode built environment thresholds for public and active transport distances in the global south by Ali Shkera, Domokos Esztergár-Kiss

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Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review by Shalini Dhananjay Balgude, Shilpa Gite, Biswajeet Pradhan, Chang-Wook Lee

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Predicting graduation grades using Machine Learning: A case study of Can Tho University students by Minh Khiem Nguyen, Van Tu Huynh, Hung Dung Nguyen

“…The capacity to forecast academic performance at the time of graduation holds profound importance for universities, especially in discerning the influential factors that contribute to a student's successful completion of their educational pursuits. This study employs multiple machine learning algorithms, including K-nearest neighbor, Neural network, Decision tree, Random forest, and Gradient boosting, to prognosticate the graduation outcomes of 7,837 undergraduate students from Can Tho University during the academic year 2022. …”
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Predicting graduation grades using Machine Learning: A case study of Can Tho University students by Minh Khiem Nguyen, Van Tu Huynh, Hung Dung Nguyen

“…The capacity to forecast academic performance at the time of graduation holds profound importance for universities, especially in discerning the influential factors that contribute to a student's successful completion of their educational pursuits. This study employs multiple machine learning algorithms, including K-nearest neighbor, Neural network, Decision tree, Random forest, and Gradient boosting, to prognosticate the graduation outcomes of 7,837 undergraduate students from Can Tho University during the academic year 2022. …”
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Machine Learning for Early Detection of Cognitive Decline in Parkinson’s Disease Using Multimodal Biomarker and Clinical Data by Raziyeh Mohammadi, Samuel Y. E. Ng, Jayne Y. Tan, Adeline S. L. Ng, Xiao Deng, Xinyi Choi, Dede L. Heng, Shermyn Neo, Zheyu Xu, Kay-Yaw Tay, Wing-Lok Au, Eng-King Tan, Louis C. S. Tan, Ewout W. Steyerberg, William Greene, Seyed Ehsan Saffari

“…Accurate CD prediction is crucial for timely intervention and tailored management of at-risk patients. This study used machine learning (ML) techniques to predict the CD risk over five-year in early-stage PD. …”
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Estimation of the air conditioning energy consumption of a classroom using machine learning in a tropical climate by Liliana Ortega-Diaz, Julian Jaramillo-Ibarra, German Osma-Pinto

“…In this study, three machine learning models were used to predict the air conditioning energy demand in a classroom of an educational building in a hot tropical climate. …”
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The Role of Simulation Science in Public Health at the Agency for Toxic Substances and Disease Registry: An Overview and Analysis of the Last Decade by Siddhi Desai, Jewell Wilson, Chao Ji, Jason Sautner, Andrew J. Prussia, Eugene Demchuk, M. Moiz Mumtaz, Patricia Ruiz

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Machine learning training data: over 500,000 images of butterflies and moths (Lepidoptera) with species labels by Friederike Barkmann, Andreas Lindner, Ronald Würflinger, Helmut Höttinger, Johannes Rüdisser

“…Abstract Deep learning models can accelerate the processing of image-based biodiversity data and provide educational value by giving direct feedback to citizen scientists. …”
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Modeling student satisfaction in online learning using random forest by Jinlei Li, Xiaowei Chen

“…This study contributes theoretically by integrating cognitive-affective dimensions, methodologically by demonstrating the utility of machine learning in modeling nonlinear interactions, and practically by providing actionable insights for platform optimization. …”
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Decoding lake water eutrophication using an innovative dynamic model pool framework in Erhai Lake by Wei Si, Zhixiong Chen, Chi Yung Jim, Ngai Weng Chan, Mou Leong Tan, Bingbing Liu, Dong Liu, Lifei Wei, Shaoyong Wang, Fei Zhang

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Semi-Supervised Learning of Statistical Models for Natural Language Understanding by Deyu Zhou, Yulan He

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Exploring association between ambient air pollution and glaucoma in China: a nationwide analysis with predictive modeling based on the China Health and Retirement Longitudinal Stud... by Xiang Li, Xiang Li, Zhan-Yang Luo, Sen Lei, Zhi-Jie Zhang, Jia-feng Tang, Yi-qing Sun, Yi-qing Sun

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Application of gesture recognition based on domain transfer learning and SimSiam network in education management by Xiaoxu He

“…In view of the problems of negative transfer and poor model generalization in single-source domain transfer learning, which have great impact on gesture recognition, this paper proposes a new novel gesture recognition method based on domain transfer learning and SimSiam network. …”
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