February 2026

Environmental, Social, and Governance (ESG) analytics increasingly uses knowledge graphs (KGs) to encode framework-grounded semantics, align partially overlapping standards, and attach provenance for auditable querying. Yet ESG evidence is mainly text-first (disclosures, regulations, policies, news, incident narratives), so quality depends on the KG–NLP interface. Research remains fragmented across topics, modalities, and pipelines, limiting reuse. To this end, we first introduce the ESG Research Focus Map (ESG-RFM), a vendor-agnostic pillar–theme–focus taxonomy crosswalked to major ESG frameworks and standards (MSCI, […]

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Since 2011, the mandatory adoption of Korean International Financial Reporting Standards (K-IFRS) by listed Korean firms has improved the consistency of financial reporting and enhanced comparability across firms and over time This institutional change has made it more feasible to construct long-horizon firm–year panel datasets and apply quantitative predictive analyses. The KoTaP dataset provides standardized firm–year panel data for Korean listed non-financial firms over 2011–2024, and this study empirically evaluates the feasibility of risk screening based on one-year-ahead […]

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In this study, a novel idea, Uncertainty Structure Estimation (USE), a lightweight, algorithm-agnostic procedure that emphasizes the often-overlooked role of unlabeled data quality is introduced for Semi-supervised learning (SSL). SSL has achieved impressive progress, but its reliability in deployment is limited by the quality of the unlabeled pool. In practice, unlabeled data are almost always contaminated by out-of-distribution (OOD) samples, where both near-OOD and far-OOD can negatively affect performance in different ways. We argue that the bottleneck does […]

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If you hang around startup circles in the Bay Area long enough, you’ll start hearing something unexpected between funding rounds and AI debates: founders quietly Googling “car rental in UAE” and checking flight prices to Dubai and Abu Dhabi. What started as curiosity has turned into a real trend. From San Francisco to the sands of the Arabian Peninsula, American tech talent is seriously eyeing the United Arab Emirates—and not just for a quick conference or a flashy […]

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This study focuses on the tendency of agents in long-horizon sequential tasks to rely on short-term states and to underutilize historical information, and proposes a cognitive modeling and learning framework with long-term memory and reasoning capabilities. The framework provides a unified cognitive description of the agent’s decision process. It introduces a structured long-term memory mechanism to support continuous storage and selective updating of cross-temporal key information. On this basis, a memory retrieval-driven reasoning module is constructed so that […]

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The rapid growth of course-based online platforms has expanded access to learning in non-formal educational contexts. However, many existing systems primarily emphasize content delivery and transactional functionality, with limited pedagogical coordination between activity tracking, assessment, and learner guidance. This paper proposes a multi-layered architectural framework for orchestrating course-based online learning through a structured separation of content management, learning activity tracking, competency modeling, adaptive support, and credentialing. A key contribution of the proposed model is the distinction between content […]

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This guide compares the 7 leading requirements management software solutions in 2026, from modern platforms like Jama Connect to legacy tools like IBM DOORS and lightweight options like Excel. The best choice depends on your product complexity, regulatory requirements, and team structure—but most organizations opt for modern tools like Jama Connect.

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Forecasting stock prices, market trends, and associated emotions remains a complex challenge due to the market’s inherent volatility, nonlinearity, susceptibility to factors such as news events, and the limited availability of financial data. Stock prices are noisy, unpredictable, and sensitive to investor sentiment cite{ko2021, dahal2023, kumarsh2025}. To account for this, this study considers three models that effectively capture both the spatial relationships (similar sector stocks) between stocks and the temporal trends in their price movements, thereby addressing limitations […]

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Background: Artificial intelligence (AI) has moved from research labs into the everyday work of clinicians and software engineers. In healthcare, AI systems now shape triage, imaging interpretation, risk prediction and documentation workflows, while in computer science and AI development, models are increasingly used to generate code, tests and even other AI systems [1–4,7,10,11,76–82]. Early governance frameworks framed “human oversight” as a high-level ethical injunction but provided limited operational guidance on how humans should interact with data-intensive, adaptive AI […]

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