Vision-based detection algorithm for monitoring dynamic change of fire progression by Yongyoon Suh

“…To achieve this, a convolutional neural network (CNN) based on deep learning is applied to detect fire events through vision-based patterns. …”
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Yalbilinya Miya (learn together): community-led program to support Aboriginal and Torres Strait Islander women through their breastfeeding journey—a protocol by Smriti Nepal, Deanna Kalucy, Janice Nixon, Simone Sherriff, Natalie Smith, Michelle Dickson, Chelsea Rowley, Hilary Honeysett, Tarnie Brown, Megan Elliott-rudder, Summer M Finlay, Kristy Williams, Rachael Fikkers, Peta Larsen, Annika Honeysett

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The effect of peer coaching on teachers’ digital storytelling based teaching practices by Mustafa Emrullah Akbaba, Esma Genç

“…The research aims to explore the influence of peer coaching on the lesson planning and implementation processes based on the digital storytelling method. The case-study research involved 12 week peer coaching initiative focused on lesson planning and implementation based on the digital storytelling method with two teachers. …”
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AHP-MOORA framework for longitudinal evaluation of Pharm.D program learning outcomes: a tool for Saudi pharmacy programs accreditation and curriculum enhancement by Sultan M. Alshahrani

“…IntroductionAs pharmacy education in Saudi Arabia progresses in accordance with Saudi Vision 2030 and international competency-based standards, the necessity for systematic evaluation of Program Learning Outcomes (PLOs) has become essential. …”
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Lane Detection Based on CycleGAN and Feature Fusion in Challenging Scenes by Eric Hsueh-Chan Lu, Wei-Chih Chiu

“…Image-based deep learning is currently the most advanced method for lane detection. …”
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Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study by Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

“…We evaluated machine learning algorithms (random forest [RF], extra-trees classifier, and light gradient boosting machine) and selected the RF model as the final model based on its performance. …”
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Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…Anchor evaluation score, in continuous iterative learning, the model parameters, Anchor position coordinates and classification confidence are continuously optimized. …”
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The predictive effects of learner autonomy and academic engagement on willingness to communicate, foreign language learning self-esteem, and L2 grit in an EFL context by Ehsan Namaziandost, Fidel Çakmak, Tahereh Heydarnejad, Afsheen Rezai

“…Drawing upon a quantitative method, the current study delved into a university setting to investigate the impact of autonomy and academic engagement on willingness to communicate, foreign language learning self-esteem, and L2 grit in English as a Foreign Language (EFL). …”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

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Deep Fusion Intelligence: Enhancing 5G Security Against Over-the-Air Attacks by Mohammadreza Amini, Ghazal Asemian, Burak Kantarci, Cliff Ellement, Melike Erol-Kantarci

“…The ensemble module is optimized for the aggregation method and different learning parameters. Furthermore, to mitigate the false positive and false negative, a systematic approach, termed Temporal Epistemic Decision Aggregator (TEDA) is introduced, which elegantly navigates the time-accuracy tradeoff by seamlessly integrating temporal decisions, thereby enhancing decision reliability. …”
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Mapping Wetlands with High-Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand by Md. Saiful Islam Khan, Maria C. Vega-Corredor, Matthew D. Wilson

“…In this research, our motivation was to test whether high-spatial-resolution PlanetScope imagery can be used with pixel-based machine learning to support the mapping and monitoring of wetlands at a national scale. (2) Methods: This study compared four machine learning classification models—Random Forest (RF), XGBoost (XGB), Histogram-Based Gradient Boosting (HGB) and a Multi-Layer Perceptron Classifier (MLPC)—to detect and map wetland areas across New Zealand. …”
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A pose generation model for animated characters based on DCNN and PFNN by Boli Wang

“…The animation character generation method includes data collection and the application after data collection, which shows the various roles that deep learning technology can play in the field of computer graphics animation, and also provides excellent solutions for other computer graphics problems.…”
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Adaptive Warning Thresholds for Dam Safety: A KDE-Based Approach by Nathalia Silva-Cancino, Fernando Salazar, Joaquín Irazábal, Juan Mata

“…Traditional monitoring systems typically employ predictive models—based on techniques such as the finite element method (FEM) or machine learning (ML)—to compare real-time data against expected performance. …”
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Vitamin D and focal brain atrophy in PD with non-dementia: a VBM study by Yingying Xu, Erlei Wang, Qilin Zhang, Jing Liu, Weifeng Luo

“…The simple linear regression analyses between serum 25-hydroxyvitamin D levels and the scores of subtests that analyzed cognitive function showed that serum 25-hydroxyvitamin D levels were negatively correlated with Trail Making Test-A scores and positively correlated with Symbol Digit Modalities Test and Auditory Verbal Learning Test scores. …”
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Improved EEG-Based Emotion Classification via Stockwell Entropy and CSP Integration by Yuan Lu, Jingying Chen

“…Traditional entropy-based learning methods primarily extract the relevant entropy measures directly from EEG signals using sliding time windows. …”
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Airway-microbiome-driven mechanisms of disease during optimised self-management: a lesson learned from mechanistic study of the Colour-COPD trial by Alice M Turner, Daniella Spittle, Karl Staples, David Cleary

“…Since only half of exacerbations of chronic obstructive pulmonary disease (acute exacerbation of chronic obstructive pulmonary disease) are bacterial, and sputum colour has a good positive predictive value for bacterial presence, it is likely that our intervention will reduce antibiotic consumption. …”
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Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification by Zhaoxia Xue, Zhiwei Liu, Zhaohui Xue, Tingqiang Song

“…Extensive experiments on four benchmark HSI datasets—University of Pavia (PU), Salinas Valley (SA), WHU-Hi-HanChuan (WHU-HH), and WHU-Hi-LongKou (WHU-HL)—demonstrate SSCGNN’s superiority over state-of-the-art few-shot learning methods. With only 5 labeled samples per class, our model achieves overall accuracy (OA) values of: 93.36% (PU, +6.22% vs. baseline GCN), 98.37% (SA, +4.91% vs. spectral-spatial CNN), 84.68% (WHU-HH, +8.03% vs. meta-learning approaches), 95.87% (WHU-HL, +7.15% vs. graph attention networks).…”
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Dual conditional GAN based on external attention for semantic image synthesis by Gang Liu, Qijun Zhou, Xiaoxiao Xie, Qingchen Yu

“…Although the existing semantic image synthesis methods based on generative adversarial networks (GANs) have achieved great success, the quality of the generated images still cannot achieve satisfactory results. …”
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SOME ISSUES OF TEACHING AND LEARNING OF CORPORATE GOVERNANCE IN LAW INSTITUTIONS AND UNIVERSITIES IN THE CONTEXT OF THE INTERNATIONAL MASTER’S DOUBLE DEGREE PROGRAM «EUROPEAN AND I... by Sergey Yu. Marochkin, Marina I. Shunevich

“…The research is based on the dialectic method regulating legislative norms, including the corporate right and activity of managing subjects. …”
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Evaluation of high school-based dengue solution model in Southern Thailand: a community participatory action research by Charuai Suwanbamrung, Sandeep Kumar Mehraj, Melkamu Worku Kercho, Muhammad Haroon Stanikzai, Temesgen Anjulo Ageru, Jiraporn Jaroenpool, Panatda Pibul, Shamarina Shohaimi, Eskinder Israel

“…Conclusion This participatory action research not only improved students' understanding of dengue but also empowered them to be proactive in various community health initiatives. The positive correlation between educational attainment and students understanding of dengue solution and larval indices surveillance underscores the need for tailored educational interventions that address diverse learning needs within the community. …”
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