Optimum Design of Braced Steel Space Frames including Soil-Structure Interaction via Teaching-Learning-Based Optimization and Harmony Search Algorithms by Ayse T. Daloglu, Musa Artar, Korhan Ozgan, Ali İ. Karakas

“…Optimum design of braced steel space frames including soil-structure interaction is studied by using harmony search (HS) and teaching-learning-based optimization (TLBO) algorithms. A three-parameter elastic foundation model is used to incorporate the soil-structure interaction effect. …”
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Corrections to “The Attention Mechanism Performance Analysis for Football Players Using the Internet of Things and Deep Learning” by Chuan Mou

“…Presents corrections to the paper, (Corrections to “The Attention Mechanism Performance Analysis for Football Players Using the Internet of Things and Deep Learning”).…”
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Experimental investigation on fresh, hardened and durability characteristics of partially replaced E-waste plastic concrete: A sustainable concept with machine learning approaches by Md. Hamidul Islam, Zannatun Noor Prova, Md. Habibur Rahman Sobuz, Nusrat Jahan Nijum, Fahim Shahriyar Aditto

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Harnessing Multi-Source Data and Deep Learning for High-Resolution Land Surface Temperature Gap-Filling Supporting Climate Change Adaptation Activities by Katja Kustura, David Conti, Matthias Sammer, Michael Riffler

“…Here, we propose a deep-learning-based methodology for LST estimation using multi-source data including Sentinel-2 imagery, land cover, and meteorological data. …”
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IMPLEMENTASI MODUL IPA BERBASIS ETNOSAINS MASYARAKAT BENGKULU MATERI PENGUKURAN MELALUI DISCOVERY LEARNING UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KRITIS MAHASISWA by Indra Sakti, Aprina Defianti, Nirwana Nirwana

“…Keywords: Classroom Action Research, Module, Ethnoscience, Discovery Learning, Critical Thinking Skills.   …”
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An improved soft voting-based machine learning technique to detect breast cancer utilizing effective feature selection and SMOTE-ENN class balancing by Indu Chhillar, Ajmer Singh

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A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity by Muhammad Islam, Farrukh Shehzad

“…Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. …”
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Intelligent in-cell electrophysiology: Reconstructing intracellular action potentials using a physics-informed deep learning model trained on nanoelectrode array recordings by Keivan Rahmani, Yang Yang, Ethan Paul Foster, Ching-Ting Tsai, Dhivya Pushpa Meganathan, Diego D. Alvarez, Aayush Gupta, Bianxiao Cui, Francesca Santoro, Brenda L. Bloodgood, Rose Yu, Csaba Forro, Zeinab Jahed

“…We developed a physics-informed deep learning model to reconstruct iAP waveforms from extracellular recordings recorded from NEAs and Microelectrode arrays (MEAs), demonstrating its potential for non-invasive, long-term, high-throughput drug cardiotoxicity assessments. …”
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Predictive model of acute kidney injury in critically ill patients with acute pancreatitis: a machine learning approach using the MIMIC-IV database by Shengwei Lin, Wenbin Lu, Ting Wang, Ying Wang, Xueqian Leng, Lidan Chi, Peipei Jin, Jinjun Bian

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A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

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Promoting Agency Among Upper Elementary School Teachers and Students with an Artificial Intelligence Machine Learning System to Score Performance-Based Science Assessments by Fatima Elvira Terrazas-Arellanes, Lisa Strycker, Giani Gabriel Alvez, Bailey Miller, Kathryn Vargas

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Book reviews: Back to the Future: Review of Positive Residential Practice: Learning the Lessons of the 1990s and Champions for Children: The Lives of Modern Child Care Pioneers by Ian Milligan

Do global health networks facilitate innovation, learning and sharing? A qualitative analysis of the Quality-of-Care Network in Bangladesh, Ethiopia, Malawi, and Uganda. by Kondwani Mwandira, Seblewengel Lemma, Albert Dube, Kohenour Akter, Asebe Amenu Tufa, Agnes Kyamulabi, Gloria Seruwagi, Catherine Nakidde, Kasonde Mwaba, Nehla Djellouli, Charles Makwenda, Tim Colbourn, Yusra Ribhi Shawar

“…The network also promoted coordination among stakeholders. Common sharing and learning approaches, such as learning collaborative sessions, were evident across QCN countries. …”
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Acute Bladder Necrosis after Pelvic Arterial Embolization for Pelvic Trauma: Lessons Learned from Two Cases of Immediate Postembolization Bladder Necrosis by Samuel Washington, E. Charles Osterberg, Sean P. Elliott, Adam B. Hittelman, Benjamin N. Breyer

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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study by Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao

“…Variables were trained in different machine learning models and traditional logistic regression models. …”
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The interventions of physical education by using augmented reality based mobile learning can significantly improve gross motor skills in elementary school students by Mohammad Faruk, Mohammad Ali, Rudi Susilana, Laksmi Dewi, Norlidah Alias, I Made Sri Undy Mahardika, Imam Syafi’i, Muchamad Samsul Huda, Achmad Rizanul Wahyudi, Laily Mita Andriana, Adi Pranoto

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Learning How to Use Input-Based and Output-Based Form-Focused Instruction: A Meta-Analytic Comparison of Korean and Persian EFL Learners by Andrew Schenck

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Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study by Yanfei Chen, Bing Wang, Yankai Shi, Wenhao Qi, Shihua Cao, Bingsheng Wang, Ruihan Xie, Jiani Yao, Xiajing Lou, Chaoqun Dong, Xiaohong Zhu, Danni He

“…This study aimed to develop a convenience, efficient prediction model for AD risk using machine learning techniques.Design and setting We conducted a cross-sectional study with participants aged 60 and older from the National Alzheimer’s Coordinating Center. …”
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Searching for efficient and informative instruments to digitally monitor fraction learning: putting tests for fraction subconstruct knowledge and informal fraction knowledge on the test bench by Constanze Schadl, Constanze Schadl, Anke Lindmeier

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