Exploring Chinese Students’ Learning Experiences in a Private Higher Education Institution in the Philippines towards a Proposed Global Engagement Initiative Program by Shao Peng

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Machine learning-based analysis of sea fog’s spatial and temporal impact on near-miss ship collisions using remote sensing and AIS data by Dan Liu, Ling Ke, Zhe Zeng, Zhe Zeng, Shuo Zhang, Shanwei Liu, Shanwei Liu

“…To investigate the spatial and temporal effects of sea fog on vessel near-miss collisions, this paper proposes a general-purpose framework for analyzing the spatial and temporal correlations between satellite-derived large-scale sea fog using a machine learning model and the near-miss collisions detected by the automatic identification system through the Vessel Conflict Ranking Operator. …”
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Impact of water, sanitation, and hygiene (WASH) interventions on gender-specific school attendance and learning outcomes: A systematic review and meta-analysis protocol. by Dinaol Bedada Dibaba, Bezatu Mengistie Alemu, Sisay Abebe Debela

“…While there are strong evidences that reveal that WASH facilities do reduce the prevalence of infectious diseases and improve the learning environment, data remain thin and equivocal on the differential impacts of WASH facilities on education by gender. …”
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Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study by Yuanjun Guo, Zhile Yang, Shengzhong Feng, Jinxing Hu

“…This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. …”
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Analisis Interaksi Aktivitas Pembelajaran Daring Berdasarkan Data Log Aktivitas pada Learning Managemefnt System (LMS) Menggunakan Educational Process Mining by Novriani Dewi Anwar, Nanang Yudi Setiawan, Welly Purnomo

Subjects: “…Learning Management System…”
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Correction: Finding a safe space for learning and exploration: A qualitative study of recently diagnosed men's experiences of peer support for HIV in Sweden. by PLOS One Staff

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Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques by Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead

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Classification of Silicon (Si) Wafer Material Defects in Semiconductor Choosers using a Deep Learning ShuffleNet-v2-CNN Model by Rajesh Doss, Jayabrabu Ramakrishnan, S. Kavitha, S. Ramkumar, G. Charlyn Pushpa Latha, Kiran Ramaswamy

“…In this research, a deep-learning-based silicon wafer defect identification and classification model is proposed. …”
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Understanding Community Health Care Through Problem-Based Learning With Real-Patient Videos: Single-Arm Pre-Post Mixed Methods Study by Kiyoshi Shikino, Kazuyo Yamauchi, Nobuyuki Araki, Ikuo Shimizu, Hajime Kasai, Tomoko Tsukamoto, Hiroshi Tajima, Yu Li, Misaki Onodera, Shoichi Ito

“…We hypothesized that community-based problem-based learning (PBL) using real-patient videos could foster students’ understanding of community health care and encourage positive attitudes toward rural health care. …”
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Power Controlled Resource Allocation and Task Offloading via Optimized Deep Reinforcement Learning in D2D Assisted Mobile Edge Computing by Sambi Reddy Gottam, Udit Narayana Kar

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Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies. by Peter R McIlroy, Le Thanh Mai Pham, Thomas Sheffield, Maxwell A Stefan, Christine E Thatcher, James Jaryenneh, Jennifer L Schwedler, Anupama Sinha, Christopher A Sumner, Iris K A Jones, Stephen Won, Ryan C Bruneau, Dina R Weilhammer, Zhuoming Liu, Sean Whelan, Oscar A Negrete, Kenneth L Sale, Brooke Harmon

“…In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). …”
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Lessons Learned from Social Forestry Policy in Java Forest: Shaping the Way Forward for New Forest Status in ex-Perhutani Forest Area by Andita Aulia Pratama

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Advanced Efficient Feature Selection Integrating Augmented Extreme Learning Machine and Particle Swarm Optimization for Predicting Nitrogen Use Efficiency and Yield in Corn by Josselin Bontemps, Isa Ebtehaj, Gabriel Deslauriers, Alain N. Rousseau, Hossein Bonakdari, Jacynthe Dessureault-Rompré

Subjects: “…augmented extreme learning machine (AELM)…”
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Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model by Gopi Battineni, Nalini Chintalapudi, Francesco Amenta

“…To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model. …”
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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

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A deep-learning approach to parameter fitting for a lithium metal battery cycling model, validated with experimental cell cycling time series by Maria Grazia Quarta, Ivonne Sgura, Elisa Emanuele, Jacopo Strada, Raquel Barreira, Benedetto Bozzini

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Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets by Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Mina Iravani, Pejman Farhadi Ghalati, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert

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A comparative performance analysis of machine learning models for compressive strength prediction in fly ash-based geopolymers concrete using reference data by Muhammad Kashif Anwar, Muhammad Ahmed Qurashi, Xingyi Zhu, Syyed Adnan Raheel Shah, Muhammad Usman Siddiq

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Development and validation of a machine learning-based model to predict survival in patients with cirrhosis after transjugular intrahepatic portosystemic shuntResearch in context by Binlin Da, Huan Chen, Wei Wu, Wuhua Guo, Anru Zhou, Qin Yin, Jun Gao, Junhui Chen, Jiangqiang Xiao, Lei Wang, Ming Zhang, Yuzheng Zhuge, Feng Zhang

“…Summary: Background: Although numerous prognostic scores have been developed for patients with cirrhosis after Transjugular intrahepatic portosystemic shunt (TIPS) placement over years, an accurate machine learning (ML)-based model remains unavailable. The aim of this study was to develop and validate a ML-based prognostic model to predict survival in patients with cirrhosis after TIPS placement. …”
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Action-Oriented Study Circles Facilitate Efforts in Nursing Homes to “Go from Feeding to Serving”: Conceptual Perspectives on Knowledge Translation and Workplace Learning by Albert Westergren

“…Based on a collaborative learning perspective, AOSC manages to integrate evidence, context, and facilitation in the efforts to achieve knowledge translation in a learning organisation. …”
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