Indoor Positioning Systems in Logistics: A Review by Laura Vaccari, Antonio Maria Coruzzolo, Francesco Lolli, Miguel Afonso Sellitto

“…Geometric methods, particularly multilateration, proved to be the most effective for positioning and are supported by advanced filtering techniques like the Extended Kalman Filter and machine learning models such as Convolutional Neural Networks. …”
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Micro-electrical Discharge Machining of Micro-holes Based on Integrated Orthogonal Experiments and CNN Methods by Yuandong MO, Yazhi WANG, Shuqi HUANG, Jiajun ZHONG

“…Objective To improve the precision of the micro-electrical discharge machining (micro-EDM) of micro-holes, a pioneering approach is undertaken in this study. Deep learning is applied innovatively to micro-hole micro-EDM, weaving together orthogonal experiments and deep learning to present an intricate methodology, i.e., an integrated fusion of orthogonal experiments and convolutional neural networks (CNNs). …”
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Improving medical students’ learning strategies, management of workload and wellbeing: a mixed methods case study in undergraduate medical education by Christopher-James Harvey, Kathleen E. Leedham-Green, Cristina Koppel, Arti Maini, Susan F. Smith, Mary J. Morrell, Michael Emerson

“…Passive study methods often fail, while evidence-based strategies like retrieval practice, active learning, and growth mindset foster success. …”
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Extreme Learning Machine and Moving Least Square Regression Based Solar Panel Vision Inspection by Heng Liu, Caihong Zhang, Dongdong Huang

“…In this work, for solar panel vision inspection, we present an extreme learning machine (ELM) and moving least square regression based approach to identify solder joint defect and detect the panel position. …”
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UAV Autonomous Navigation Based on Deep Reinforcement Learning in Highly Dynamic and High-Density Environments by Yuanyuan Sheng, Huanyu Liu, Junbao Li, Qi Han

“…Autonomous navigation of Unmanned Aerial Vehicles (UAVs) based on deep reinforcement learning (DRL) has made great progress. …”
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Acoustic Source Localization Using Kernel-based Extreme Learning Machine in Distributed Microphone Array by Rong WANG, Zhe CHEN, Fuliang YIN

“…During the training phase, by the implementation of kernel function, the output weights of the classifier are calculated and do not need to be tuned. After the kernel-based extreme learning machine (K-ELM) is well trained, the measured generalized cross correlation data are fed into the K-ELM classifier, and the output is the estimated acoustic source position. …”
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Students Perceptions, Satisfactions and Challenges on Problem-Based Learning (PBL): A Survey Study Among Final Year Pharmacy Students by Engku Nuraishah Huda E. Zainudin, Fakhira Damia Khaidir, May Khin Soe, Nurul Asyiqin Yusof, Khairool Azizul Mohammad

“… Introduction: Problem-based learning (PBL) is being adopted more frequently in pharmacy education to enhance skills such as problem-solving, and self-directed learning. …”
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Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu, Ying Mao, Xiaoting Hua, Yan Jiang, Yi Zou, Zhichao Wang, Zubi Liu, Hongrui Zhang, Lingling Lu, Yunsong Yu

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Lessons Learned from the COVID-19 Pandemic: Simulation of the Tuberculosis Epidemic as a Function of Population Coverage with Screening by A. A. Starshinova, I. F. Dovgalyuk, N. N. Osipov, D. A. Kudlay

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PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification by Bo Ren, Chaoyue Hua, Biao Hou, Jian Lv, Chen Yang, Licheng Jiao, Jocelyn Chanussot

“…The design process for polarimetric contrastive learning involves the construction of positive samples, the establishment of a PolSAR-based network architecture for contrastive learning, and the formulation of the loss function. …”
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Capability level and development priority of learning environment and diversity of learners’ domain by Saturnino Dalagan Jr., Maria Kristina Atugan

“…Creating a conducive learning environment has been a target to build a supportive and peaceful classroom where diverse learners were engaged for them to learn better. …”
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Composite Learning-Based Inverse Optimal Fault-Tolerant Control for Hierarchy-Structured Unmanned Helicopters by Qingyi Liu, Ke Zhang, Bin Jiang, Yushun Tan

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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…This paper introduces a distributed heterogeneous multi-agent deep reinforcement learning algorithm, named HMDRL-UC, which is specifically designed to address the cluster-based spectrum sharing problem in heterogeneous UAV swarms. …”
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Starting driving style recognition of electric city bus based on deep learning and CAN data by Dengfeng Zhao, Zhijun Fu, Chaohui Liu, Junjian Hou, Shesen Dong, Yudong Zhong

“…In this article, a starting driving style recognition method of electric city bus is firstly proposed based on deep learning with in-vehicle Controller Area Network (CAN) bus data. …”
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Crystal’s Self-Alignment for High Power Laser Facility Based on Machine Learning by Yaohan Kang, Daizhong Liu, Xiuqing Jiang, Lei Gong, Xingqiang Lu, Mingying Sun

“…The proposed scheme comprises two modules: a rectangular spiral spot scanning search method module and an automatic spot aligning method module based on the open-source Machine-Learning Online Optimization Package (M-LOOP) algorithm. …”
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Co-designing and testing the learn together guidance to support patient and family involvement in patient safety investigations: a mixed-methods study by Jane O’Hara, Lauren Ramsey, Siobhan McHugh, Joseph Langley, Justin Waring, Ruth Simms-Ellis, Gemma Louch, Jenni Murray, Carl Macrae, John Baker, Rebecca Lawton, Daisy Halligan, Olivia Rogerson, Penny Phillips, Debra Hazeldine, Sarah Seddon, Joanne Hughes, Rebecca Partridge, Katherine Ludwin, Laura Sheard

“…Our guidance was found to be feasible, with stakeholders being positive about involvement and the impact on organisational learning. …”
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Transformer-Based Detection and Clinical Evaluation System for Torsional Nystagmus by Ju-Hyuck Han, Yong-Suk Kim, Jong Bin Lee, Hantai Kim, Jong-Yeup Kim, Yongseok Cho

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Problem-based Learning (PBL) Using Resource Mining as a Teaching Approach: An Action Research by Tomas Jr Diquito, Aia Sept Franco, Maria Ericka Caballes

“…Problem-Based Learning (PBL) is a teaching approach wherein learners are immersed in different issues to create real-life solutions. …”
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Insights into simulation-based learning: student and faculty experiences in a PharmD program in Saudi Arabia by Reem Binsuwaidan, Najla A. Altwaijry, Alnada A. Ibrahim, Rawan A. Alghamdi, Razan Bin Humaid, Alaa A. AlSharif, Alaa A. AlHubaishi, Elshaymaa I. Elmongy, Lina I. Alnajjar, Ghadah H. Alshehri

“…Abstract Background Simulation-based learning is a highly effective and increasingly popular method of teaching in medical education. …”
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Problem Based Learning Model Integrated Islamic Values with Mind Mapping Assessment to Improve Students' Creative Thinking Skills by Uyumatul Ummah, Evi Roviati, Mujib Ubaidillah

“…The study aims to describe student learning activities, analyze students' creative thinking skills, and describe student responses by applying a the problem-based learning (PBL) model that integrates Islamic values with mind-mapping assessments. …”
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