Pedestrian-Crossing Detection Enhanced by CyclicGAN-Based Loop Learning and Automatic Labeling by Kuan-Chieh Wang, Chao-Li Meng, Chyi-Ren Dow, Bonnie Lu

“…The proposed system may be integrated with in-vehicle assistance platforms as a supportive tool for pedestrian-crossing detection in data-scarce environments, contributing to improved driver awareness and road safety.…”
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Uncovering mathematical activities and concepts in Batik Pendekar of Madiun City through the lens of ethnomathematics by Ika Krisdiana, Titin Masfingatin, Wasilatul Murtaifiah, Febriana Nor Fadhilla, Gerald DG. Mabuti

“…Additionally, anthropological aspects, such as local wisdom, social values, and symbolic meanings, are integral to these activities. The study concludes that Batik Pendekar serves as a rich ethnomathematical resource, offering opportunities to bridge mathematics learning with local culture and enhance contextual understanding in mathematics education. …”
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Empowering designers to create life cycle informed products: heuristics for extracting insights from LCA reports by Nicole Goridkov, Ye Wang, Kosa Goucher-Lambert

“…As AI-driven tools become increasingly integrated into design workflows, there is an opportunity to improve access to sustainability data. …”
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Assessing disparities in access, use, and potential benefits of weather and climate information services among farmers in Guatemala’s Dry Corridor by Maya Moore, Geneva List, Max Mauerman, Dante Salazar Ballesteros, Walter Baethgen

“…Raising awareness of LTACs and ACBs through locally trusted channels such as radio broadcasts and effective outreach by climate intermediaries, can enhance accessibility. Integrating scientific data with farmers’ traditional knowledge and priorities, while ensuring their meaningful end-to-end participation in the LTAC process, is key to creating actionable, context-relevant recommendations. …”
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Empowering minority voices: how inclusive teaching and support foster multicultural learning by Awal Mohammed Alhassan, Margrethe Hall Christensen, Ksenia Solheim, Beate Mellemsether

“…This study investigates how instructional and emotional support from teachers influence minority students’ perceptions of inclusivity and their academic and emotional engagement.MethodsA mixed-methods approach was employed, involving survey responses from 305 minority students and participant observations across multiple educational settings. Quantitative data were analyzed to identify correlations, while qualitative observations provided contextual depth.ResultsApproximately 7% of students reported receiving little to no instructional or emotional support from teachers. …”
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Handling Semantic Relationships for Classification of Sparse Text: A Review by Safuan, Ku Ruhana Ku-Mahamud

“…These challenges stem from high-dimensional data and scarce relevant features because sparse text can result from noisy, short, or contextually limited inputs. …”
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Mapping Peatlands Combing Deep Learning With Sparse Spectral Unmixing Based on Zhuhai-1 Hyperspectral Images by Yulin Xu, Xiaodong Na

“…A multihead attention mechanism based on the transformer encoder captures global contextual information by correlating patches in the image, facilitating precise hyperspectral data reconstruction. …”
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AI-Based Linguistic Frameworks for Monitoring Physical Health, Sports Performance, and Educational Contexts by Rakhimov Vladimir, Saidnazarov Ulugbek, Mustafaev Ispandiyar

“…As little is known about where computational linguistics-based health inference is gaining momentum beyond clinical diagnostics and performance analytics, the purpose of this study is to map in what clusters of application domains it is perceived to gain traction. Drawing on data from network-based visualizations and structural equation models in multimodal datasets, we identify a long tail of embedded constructs and relational dependencies in which a total of 76 unique conceptual nodes operate, including predictors such as lexical calibration, contextual sentiment attribution, and semantic load dispersion. …”
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INTERNALIZATION OF THE READING HABIT CHARACTER THROUGH THE DOLAN LITERACY PROGRAM FOR ELEMENTARY SCHOOL-AGED CHILDREN by Hesti Awandani Pangestu, Aldo Redho Syam, Lilis Sumaryanti

“…The program is designed as a form of literacy education based on enjoyable, contextual, and inclusive activities, integrated with a character-building approach. …”
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Hybrid AI for Predictive Cyber Risk Assessment: Federated Graph-Transformer Architecture With Explainability by Jaime Govea, Rommel Gutierrez, William Villegas-Ch, Alexandra Maldonado Navarro

“…This paper proposes a hybrid model for predictive cyber risk assessment that integrates Graph Neural Networks (GNNs) for relational pattern modeling, a Transformer-based language model (CyberBERT) for semantic representation of logs and traffic data, and a Federated Learning framework to preserve data privacy during training. …”
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How does teacher self-efficacy mediate the relationship between student outcomes and principal leadership for learning? Results from meta-analytic structural equation modelling (MA... by Mehmet Ozdogru, Tijen Tulubas, Turgut Karakose, Sedat Kanadlı, Abdurrahman Kardas, Stamatios Papadakis

“…These results reiterate the significance of principals' leadership for learning to facilitate student outcomes and suggest that the integrated practice of leadership in accordance with contextual requirements could leverage the effectiveness and improvement of schools.…”
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Perspectives of undergraduate module convenors at a South African academic institution on medical student training in evidence-based health care: a qualitative study by Taryn Young, Anke Rohwer, Jimmy Volmink, Mike Clarke

“…Faculty convening medical undergraduate teaching modules were purposively sampled. Data collection was done using focus-group or individual interviews. …”
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The Evolution of Education, Birth Rate, and Drug Dependence and their Implications for the National Security by Moraru Teodora-Ioana

“…The research findings support the need for integrated public policies in the fields of education, health, and security, based on contextual diagnosis and preventive intervention.…”
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Leveraging Machine Learning for Enhanced Bug Triaging in Open-Source Software Projects by Nitanta Adhikari, Rabindra Bista, Joao Carlos Ferreira

“…Our primary contribution is the development of an Augmented Bidirectional LSTM model that integrates enriched textual features and contextual metadata. …”
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Research on a denoising model for entity-relation extraction using hierarchical contrastive learning with distant supervision by Ayiguli Halike, Aishan Wumaier, Kahaerjiang Abiderexiti, Tuergen Yibulayin

“…Specifically, a three-layer learning architecture is designed, which incorporates interactions at different levels and employs a multi-head self-attention mechanism to generate denoised context-aware representations, referred to as multi-granular re-contextualization. Additionally, a dynamic gradient adversarial perturbation data augmentation strategy is introduced to provide pseudo-positive samples for contrastive learning, further enhancing the model’s capabilities in recognizing rare relations. …”
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A Participatory Governance Model for Comprehensive Conservation of Historical Buildings and Urban Fabric: A Grounded Theory Approach by Somayyeh Ghadimzadeh, Elnaz Abizadeh, Mahdiyeh Rahnemay Toori

“…In the selective coding phase, these subcategories were integrated to form 26 main categories, which were then structured into 5 sections within the paradigm model: causal conditions (4 categories), contextual conditions (5 categories), intervening conditions (5 categories), strategies (7 categories), and consequences (5 categories).   …”
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Top 10 Research Lessons Learned From a Digital Child-Rearing Program in Low- and Middle-Income Countries: Multicase Study by Haley M LaMonica, Victoria Loblay, Adam Poulsen, Gabrielle Hindmarsh, Mafruha Alam, Mahalakshmi Ekambareshwar, Qaisar Khan, Yun J C Song, Jacob J Crouse, Chloe Wilson, Madelaine Sweeney-Nash, Olivia Iannelli, Aila Naderbagi, Iqthyer U Zahed, Adam Yoon, Mujahid Torwali, Jakelin Troy, Ian B Hickie

“…Data analysis for each case occurred over 3 phases, including qualitative data analysis and reporting, data synthesis to inform the transfer of learnings to the program, and, finally, a secondary analysis relating to program theory, stakeholder engagement, and the refinement of the program as they related to, interacted with, and were influenced by context. …”
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At the Southern limit: the Arenal Central site and the Guaraní occupation of the Paraná Delta (Argentina) by Daniel Loponte, Mirian Carbonera, Fernanda Schneider, Neli Machado, Aline Bertoncello, Maicon Telles Szczygel, Alejandro Acosta, Barbara Mazza, Sheila Alí, Isabel Capparelli

“…The results are integrated with previously known data to examine key aspects of Guaraní colonization, including chronology, subsistence strategies, resource acquisition, hunting ranges, and settlement spatial distribution, contributing to a new synthesis of Guaraní archaeology at the southernmost extent of their expansion in South America. …”
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ModFus-PD: synergizing cross-modal attention and contrastive learning for enhanced multimodal diagnosis of Parkinson’s disease by Xiangze Teng, Xiangze Teng, Xiangze Teng, Xiang Li, Xiang Li, Xiang Li, Benzheng Wei, Benzheng Wei, Benzheng Wei

“…The framework comprises three key components: (1) a contrastive learning-based feature alignment module that projects MRI data and clinical text prompts into a unified embedding space via pretrained image and text encoders; (2) a bidirectional cross-modal attention module in which textual semantics guide MRI feature refinement for improved sensitivity to PD-related brain regions, while MRI features simultaneously enhance the contextual understanding of clinical text; (3) a hierarchical classification module that integrates the fused representations through two fully connected layers to produce final PD classification probabilities. …”
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Semi-Supervised Salient Object Detection for Side-Scan Sonar Images via Entropy-Based Uncertainty and Contrastive Learning by Shenao Yuan, Zhen Wang, Fu-Lin He, Shan-Wen Zhang

“…Our method aims to improve the quality of pseudo-labels and the overall performance of the model using a small amount of labeled data. Specifically, we design an uncertainty map evaluation module that effectively extracts global contextual information through an entropy-based partition loss and a contrastive learning mechanism, integrated with the uncertainty map to handle the complex underwater background. …”
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