Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…This algorithm surpasses step control methods optimized through particle swarm optimization and outperforms traditional TD3 reinforcement learning methodologies. …”
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Pedagogical grammar as a frame concept for research in the field of foreign language teaching methods. Part 16. Problems of organising pedagogical grammar in teaching by L. Chernovaty

“…The article presents a comparative analysis of two approaches to teaching a foreign language in general and its grammar in particular – acquisition (mainly implicit learning, similar to the mastery of a first language) and learning (based on students’ awareness of the structure and conditions of use of the grammatical structures to be learnt). …”
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Development of problem orientation model and work organization in problem-based learning at Muhammadiyah Senior High School of Batu city by N. Nurwidodo, Siti Zaenab, Iin Hindun, Sri Wahyuni

“… The problem-based learning (PBL) model consists of five steps: orienting students to the problem, organizing work, guiding investigations, compiling work and presenting it, and evaluating the process and results. …”
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From pixels to letters: A high-accuracy CPU-real-time American Sign Language detection pipeline by Jonas Rheiner, Daniel Kerger, Matthias Drüppel

“…This increases generalization on unseen data and strengthens our evaluation. We employ a two-step training: The backbone is initialized through transfer learning and frozen for the initial training of the head. …”
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Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning by Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida, Hikaru Nakazawa, Sakiya Kawada, Hafumi Nishi, Koji Tsuda, Tomoshi Kameda, Mitsuo Umetsu

“…Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. …”
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Refining daily precipitation estimates using machine learning and multi-source data in alpine regions with unevenly distributed gauges by Huajin Lei, Hongyi Li, Hongyu Zhao

“…XDMF includes three critical steps: precipitation downscaling, identification, and estimation, focusing on simultaneously improving the spatial resolution, precipitation detection capability and estimation capability. …”
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Non-compulsory care for children and young people: learning from research on Section 25 arrangements. What next for Scotland? by Brandi Lee Lough Dennell, Robert B. Porter, Micky Anderson

Effect of a workplace-based learning program on clerkship students’ behaviors and attitudes toward evidence-based medicine practice by Hajime Kasai, Go Saito, Kenichiro Takeda, Hiroshi Tajima, Chiaki Kawame, Nami Hayama, Kiyoshi Shikino, Ikuo Shimizu, Kazuyo Yamauchi, Mayumi Asahina, Takuji Suzuki, Shoichi Ito

“…One hundred and nine fourth- and fifth-year medical students undergoing CC at a medical school in Japan attended a workplace-based learning program for EBM during CC (WB-EBM), which included the practice of the five steps of EBM. …”
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Protocol to analyze deep-learning-predicted functional scores for noncoding de novo variants and their correlation with complex brain traits by Enrique Mondragon-Estrada, Sarah U. Morton

“…We describe steps for score prediction, statistical comparison, phenotype correlation, and functional enrichment analysis. …”
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Experimental Dataset for Fiber Optic Specklegram Sensing Under Thermal Conditions and Use in a Deep Learning Interrogation Scheme by Francisco J. Vélez, Juan D. Arango, Víctor H. Aristizábal, Carlos Trujillo, Jorge A. Herrera-Ramírez

“…Finally, an implementation is presented for utilizing the dataset in a deep learning interrogation scheme.…”
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PENGEMBANGAN BAHAN AJAR PROBLEM BASED LEARNING UNTUK MENINGKATKAN KEMAMPUAN LITERASI MATEMATIKA CALON GURU MADRASAH IBTIDAIYAH by Siti Annisah, Yunita Wildaniati, Firma Andrian

“…Indonesian students have mathematical literacy skills that are far from the international average. Strategic steps that can be taken to improve students' mathematical literacy skills are to improve the mathematical literacy skills of prospective teachers at the elementary school or madrasah ibtidaiyah level by developing teaching materials based on Problem Based Learning (PBL). …”
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Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids by Yanfei Li, Juejing Liu, Xiaodong Zhao, Wenjun Liu, Tong Geng, Ang Li, Xin Zhang

“…Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. …”
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Inverse Kinematics of a 7-Degree-of-Freedom Robotic Arm Based on Deep Reinforcement Learning and Damped Least Squares by Shusheng Yu, Gongquan Tan

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Finding and following: a deep learning-based pipeline for tracking platelets during thrombus formation in vivo and ex vivo by Abigail S. McGovern, Pia Larsson, Volga Tarlac, Natasha Setiabakti, Leila Shabani Mashcool, Justin R. Hamilton, Niklas Boknäs, Juan Nunez-Iglesias

“…Our pipeline covers four steps: detection, tracking, estimation of tracking accuracy, and quantification of platelet metrics. …”
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Harnessing machine learning for high-throughput screening of high thermal conductivity polyimides: A multiscale feature engineering approach by Jiale Han, Chunhua Ying, Yue Cao, Wen Li, Yuan Feng, Masood Mortazavi, Pingfan Wu, Liang Peng, Jiechen Wang

“…In this study, we present a machine learning technique with novel multiscale feature engineering approach to predict and identify high thermal conductivity polyimide efficiently. …”
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Using Forensic Cases to Introduce First Year Pharmacy Students to Forensic Pharmacy and Strengthen Student Learning in Basic Sciences by Reza Karimi, Huy Hoang, Fawzy Elbarbry, Anita Cleven

“…Next steps: Faculty can generate elective courses to introduce pharmacy students to forensic pharmacy and use real-life forensic cases to strengthen student learning.   …”
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Impact of Sliding Window Overlap Ratio on EEG-Based ASD Diagnosis Using Brain Hemisphere Energy and Machine Learning by Bashar S. Falih, Mohannad K. Sabir, Ahmet Aydın

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An integrated approach using social support theory and technology acceptance model to investigate the sustainable use of digital learning technologies by Sultan Hammad Alshammari, Abeer F. Alkhwaldi

“…Abstract The present study explored the determinants influencing students’ intentions towards utilizing digital learning technologies (DLTs). It proposes a holistic view model for students’ utilization of digital learning technologies by integrating social support theory and the “Technology Acceptance Model” (TAM). …”
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The Development of Machine Learning-Assisted Software for Predicting the Interaction Behaviours of Lactic Acid Bacteria and <i>Listeria monocytogenes</i> by Fatih Tarlak, Jean Carlos Correia Peres Costa, Ozgun Yucel

“…The integration of machine learning-assisted software developed in this work into predictive microbiology demonstrates significant advancements by bypassing the conventional primary and secondary modelling steps, enabling a streamlined, precise characterization of microbial interactions in food products.…”
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Going Deeper With Deep Learning: Automatically Tracing Internal Reflection Horizons in Ice Sheets—Methodology and Benchmark Data Set by Hameed Moqadam, Daniel Steinhage, Adalbert Wilhelm, Olaf Eisen

“…Here, our goal is to present a complete pipeline for automatic tracing of internal reflection horizons (IRH) of intermediate to large depths in the ice sheet from radargrams using deep learning. We introduce IRHMapNet, which is a deep learning framework that uses a U‐Net‐based architecture to trace IRHs, based on airborne RES data with preprocessing steps such as noise removal and data augmentation, and postprocessing techniques such as morphological filtering and skeletonization. …”
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