TECHNOLOGY OF SELF-DETERMINED LEARNING AS A NEW FORMAT OF CONTINUING PROFESSIONAL EDUCATION OF TEACHERS by G. A. Ignatieva, O. V. Tulupova, S. V. Matchinа

“…The essence of such transformations generally consists in necessary rejection of a subject-information learning model and transition to designing the model of vocational self-development and self-determination.The aim of this research was to reveal the essence of teachers’ professional development as the process of positional self-determination and formation of managerial position. …”
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USING 5E INSTRUCTIONAL MODEL WITH ICT SUPPORT IN TEACHING LOWER SECONDARY STUDENTS ON THE TOPIC OF LIGHT REFLECTION by Frank Angelo Pacala

“…The study used a mixed-method design involving 24 students participating in a 5E-based intervention. …”
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Reinforcement Learning with Multi-Policy Movement Strategy for Weakly Supervised Temporal Sentence Grounding by Shan Jiang, Yuqiu Kong, Lihe Zhang, Baocai Yin

“…To better learn the alignment, we propose a Gaussian-based Dual-Alignment Module (GDAM) which combines the strengths of both scoring-based and reconstruction-based alignment methods, addressing the issues of negative sample bias and language bias. …”
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PCA-GWO-KELM Optimization Gait Recognition Indoor Fusion Localization Method by Xiaoyu Ji, Xiaoyue Xu, Suqing Yan, Jianming Xiao, Qiang Fu, Kamarul Hawari Bin Ghazali

“…Location-based services have important economic and social values. …”
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3D Reconstruction of Pedestrian Trajectory with Moving Direction Learning and Optimal Gait Recognition by Binbin Wang, Tingli Su, Xuebo Jin, Jianlei Kong, Yuting Bai

“…This paper used an optimal gait recognition algorithm to improve the accuracy of gait detection. Then a learning-based moving direction determination method was proposed. …”
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A Deep Reinforcement Learning Approach for Portfolio Management in Non-Short-Selling Market by Ruidan Su, Chun Chi, Shikui Tu, Lei Xu

“…Reinforcement learning (RL) has been applied to financial portfolio management in recent years. …”
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Machine Learning Forecasting of Commercial Buildings’ Energy Consumption Using Euclidian Distance Matrices by Connor Scott, Alhussein Albarbar

“…One key strategy for achieving this involves enhanced energy management in buildings, often using machine learning-based forecasting methods. However, such methods typically rely on extensive historical data collected via costly sensor installations—resources that many buildings lack. …”
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An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…However, traditional detection methods often suffer from false positives and missed detections, and they do not adequately account for complex weather conditions such as fog and snow. …”
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Multi-label classification with deep learning techniques applied to the B-Scan images of GPR by El Karakhi, Soukayna, Reineix, Alain, Guiffaut, Christophe

“…In this study, a multi-label classification (MLC) model based on transfer learning and data augmentation has been developed to generate multiple information elements on the same image and to realize classification. …”
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Multitarget Direct Localization Using Block Sparse Bayesian Learning in Distributed MIMO Radar by Bin Sun, Haowen Chen, Xizhang Wei, Xiang Li

“…Since the sparse representation coefficients exhibit block sparsity, we use a block sparse Bayesian learning (BSBL) method to estimate the locations of multitarget, which has many advantages over existing block sparse model based algorithms. …”
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Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…Extensive research has been conducted to evaluate the influence of machine learning on innovative anaesthesia methods. In 2023, Lopez et al. published a systematic review on how Artificial Intelligence could positively impact traditional anaesthesia practices.1 Various studies included in the review employed different models to achieve variable targets during the induction of anaesthesia. …”
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GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication by Vendi Ardianto Nugroho, Byung Moo Lee

“…These outcomes stem from a proposed data splitting method ensuring balanced label distribution, paired with a GPS preprocessing technique that extracts key positional features, and a DL architecture that maps sequential position data to beam index predictions. …”
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Leveraging learned monocular depth prediction for pose estimation and mapping on unmanned underwater vehicles by Marco Job, Marco Job, David Botta, Victor Reijgwart, Luca Ebner, Andrej Studer, Roland Siegwart, Eleni Kelasidi, Eleni Kelasidi, Eleni Kelasidi

“…The pipeline enables net-relative pose estimation for Unmanned Underwater Vehicles (UUVs) and depth prediction within net pens solely from visual data by combining deep learning-based monocular depth prediction with sparse depth priors derived from a classical Fast Fourier Transform (FFT)-based method. …”
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Preservice Teachers’ Shifting Perspectives of Individuals with Intellectual and Developmental Disabilities in Service-Learning Experiences by Stephanie Devine, Cynthia Massey, Kathryn Haughney, Akintomide Adebile

“…Conclusions position subsequent inquiry to explore service-learning outcomes and preservice teacher soft skill development. …”
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Preservice Teachers’ Shifting Perspectives of Individuals with Intellectual and Developmental Disabilities in Service-Learning Experiences by Stephanie Devine, Cynthia Massey, Kathryn Haughney, Akintomide Adebile

“…Conclusions position subsequent inquiry to explore service-learning outcomes and preservice teacher soft skill development. …”
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Preservice Teachers’ Shifting Perspectives of Individuals with Intellectual and Developmental Disabilities in Service-Learning Experiences by Stephanie Devine, Cynthia Massey, Kathryn Haughney, Akintomide Adebile

“…Conclusions position subsequent inquiry to explore service-learning outcomes and preservice teacher soft skill development. …”
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Nurse stress and patient safety in the ICU: physician-led observational mixed-methods study by Manju Mathew, Anjum John, Reshma Vazhakkalayil Ramachandran

“…A perceived need for a non-punitive, learning-oriented environment was identified for fostering patient safety culture. …”
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An interactive course program on nutrition for medical students: interdisciplinary development and mixed-methods evaluation by Gonza B. Ngoumou, Daniela A. Koppold, Laetitia Wenzel, Anne Schirmaier, Carolin Breinlinger, Lisa M. Pörtner, Stefan Jordan, Julia K. Schiele, Etienne Hanslian, Annika Koppold, Beate Stock-Schröer, Dimitra M. Varvarezou, Michael Jeitler, Miriam Ortiz, Andreas Michalsen, Wiebke Stritter, Georg Seifert, Christian S. Kessler

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Flash Flood Regionalization for the Hengduan Mountains Region, China, Combining GNN and SHAP Methods by Yifan Li, Chendi Zhang, Peng Cui, Marwan Hassan, Zhongjie Duan, Suman Bhattacharyya, Shunyu Yao, Yang Zhao

“…The performances of two classic machine learning methods (K-means and Self-organizing feature map) and three GNN methods (Deep Graph Infomax (DGI), Deep Modularity Networks (DMoN), and Dilation shrink Network (Dink-Net)) were compared for flash-flood regionalization, and the Dink-Net model outperformed the others. …”
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Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning by Xin Lei, Xing Wang, Guanlin Chen, Ce Liang, Quhuan Li, Huaiguang Jiang, Wei Xiong

“…Finally, we developed an integrated platform for generating promoters and predicting their strength.IMPORTANCEWe demonstrated that diffusion models are superior in accomplishing the promoter synthesis task compared to other state-of-the-art deep learning models. The effectiveness of our method was validated using data sets of Escherichia coli and cyanobacteria promoters, showing more stable and prompt convergence and more natural-like promoters than the variational autoencoder model. …”
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