Learning to Live Through Loss: When Job Loss Triggers Grief by Carolyn S. Wilken

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Federated learning based reference evapotranspiration estimation for distributed crop fields. by Muhammad Tausif, Muhammad Waseem Iqbal, Rab Nawaz Bashir, Bayan AlGhofaily, Alex Elyassih, Amjad Rehman Khan

“…Efforts have been made to simplify the (ETo) estimation using machine learning models. The existing approaches are limited to a single specific area. …”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…The proposed system works on three stages: pre-processing, feature extraction, and classification with machine learning algorithms including NB, KNN, ADA, DT, and CNN deep learning. …”
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Peran Interaktivitas dalam Penggunaan E-learning: Perluasan Model UTAUT by Yuni Marlina Saragih, Erwin Setiawan Panjaitan, Roni Yunis

“…STMIK Mikroskil had introduced E-learning, specifically Moodle, prior to covid-19. However, during the COVID-19 epidemic, the usage of E-learning exploded, and because the enormous number of transactions carried out in online learning activities could not be supported, STMIK Mikroskil chose Microsoft Teams as an online learning medium. …”
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Short-term solar irradiance forecasting using deep learning models by Syed Saad Ahmed, Chang Wei Bin, Nisar Humaira, Riaz Hannan Naseem, Yeap Kim Ho, Zaber Nursaida Mohamad

“…In this paper, short-term solar forecasting models are proposed using deep learning to reliably predict the amount of solar irradiance for optimal power generation. …”
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Machine Learning Algorithm for Estimating Surface PM2.5 in Thailand by Pawan Gupta, Shanshan Zhan, Vikalp Mishra, Aekkapol Aekakkararungroj, Amanda Markert, Sarawut Paibong, Farrukh Chishtie

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Research and Application of Heart Disease Prediction Model Based on Machine Learning by Bao Yongli

“…This study aims to improve the accuracy and efficiency of heart disease prediction through Machine learning (ML) methods to help medical diagnosis. A heart disease dataset was used in the study, and multiple ML models were used to analyze multiple key health features, and the model performance was verified through a test set. …”
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Double layer federated security learning architecture for artificial intelligence of things by ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin

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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

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An Overview of Application of Machine Learning Models in Urban Flood Simulation and Forecasting by CHEN Zeming, FANG Xuhong, LI Jiaye, WANG Mengyao, CHEN Aifang, YIN Ling

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MASC: Wearable Design for Infectious Disease Detection Through Machine Learning by Sumaiya Afroz Mila, Bhagawat Baanav Yedla Ravi, Md Rafiul Kabir, Sandip Ray

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Knowledge Management in Road Accident Detection Based on Developed Deep Learning by Bvss Subbarao, Ramana K

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Policy design labs and uncertainty: can they innovate, and retain and circulate learning? by Jenny M. Lewis

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LANGUAGE LEARNING STRATEGIES EMPLOYED BY EFL LEARNERS IN A RURAL AREA by Yanik Lailinas Sakinah, Putu Dian Danayanti Degeng, Sahiruddin Sahiruddin

Subjects: “…Language Learning Strategies…”
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Designing a system of learning materials to explain climate change to children by Lucy Blackwell

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Machine Learning-Based Classification of Turkish Music for Mood-Driven Selection by Nazime Tokgöz, Ali Değirmenci, Ömer Karal

“…This study seeks to employ machine learning-based methods to classify four different music genres using a minimal set of features. …”
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Interactive Arabic E-Learning for Prospective Students Studying in the Middle East by Mohammad Zaelani Musonif, Hanik Mahliatussikah, Kholisin Kholisin

Subjects: “…Arabic E-learning…”
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From data to diagnosis: leveraging deep learning in IoT-based healthcare by Miracle A. Atianashie, Chukwuma Chinaza Adaobi

“… In the evolving landscape of healthcare, the integration of deep learning within the Internet of Things (IoT) presents transformative potentials for medical diagnostics and patient care. …”
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The Learning Continuum: A Model for Sustained Participation with Hard-to-Serve Clients by Elizabeth B. Bolton

“… This report, The Learning Continuum: A Model for Sustained Participation with Hard-to-Serve Clients, is part of the UF/IFAS Welfare-to-Work Initiative (Grant #A6218) funded by the Florida Agency for Workforce Innovation (formerly Florida Department of Labor and Employment Security). …”
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Incorporating Machine Learning in Capture-Recapture Estimation of Survey Measurement Error by Maaike Walraad, Jonas Klingwort, Joep Burger

“…Results show that machine learning clearly outperforms the regression models, but the obtained CRC point estimates remain largely unaffected. …”
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