data science

Intelligent Underwater Quantum Communications: A Review of AI-Enabled Channel Estimation, Noise Mitigation, and System Optimization

Underwater quantum communication (UQC) has emerged as a promising approach for secure information transfer in oceanic environments by exploiting fundamental quantum mechanical principles. However, realizing UQC in practice remains highly challenging due to the inherently dynamic nature of the underwater optical channel...

Data-Driven Optimization and Machine Learning-Powered Automation for Intervention Opportunity Management in Oil Wells

The document presents a data science workflow that leverages machine learning (ML) and artificial intelligence (AI) to promote innovative methodologies for automating and optimizing the selection of wells as workover candidates. It integrates multiple disciplines, including production, engineering, reservoir, and geo...

Sistem Pendukung Keputusan Aset TI Berbasis LLM dengan Guardrail Domain

Manajemen aset Teknologi Informasi (TI) memerlukan keputusan yang dapat dipertanggungjawabkan berdasarkan data aset, riwayat pemeliharaan, kebutuhan pengguna, dan data monitoring. Penelitian ini mengusulkan sistem pendukung keputusan aset TI yang mengintegrasikan large language model, aturan guardrail domain, dan verif...

Mapping Pre-Service Teachers’ Digital Competence Research, 2014-2026: A Bibliometric Analysis of Conceptual Structure and Thematic Evolution

Pre-service teachers’ digital competence has become central to teacher education, yet the field’s conceptual organization, international structure, and temporal development remain insufficiently integrated. This study maps the development of this research domain and identifies its publication patterns, collaboration ne...

Applying artificial intelligence and big data analysis in predicting the effectiveness of strategic decision-making in the green hotel standards

A capabilities approach to examining mathematics and science teachers’ reported experiences of lesson study professional development

This study examined teachers’ reported experiences of lesson study (LS) professional development (PD). A qualitative phenomenological design was employed, using face-to-face interviews conducted in 2018 with 15 mathematics and science teachers from several secondary schools in the Mangaung District, South Africa. Inter...

Scaling of sustainable development goals in science education using Thurstone’s pairwise comparison–based scaling technique

A lack of evidence-based guidelines on which sustainable development goals (SDGs) need to be focused on in educational settings can be regarded as the key deficiency that leads to an inefficient sustainability learning process. As sustainability-related issues become ever more acute, there is a necessity to determine w...

Lachnospiraceae in the Food–Gut Axis: A Critical Review of Dietary Modulation, Immune Regulation, and Translational Barriers

It is concluded that although Lachnospiraceae hold promise for immunomodulatory functional foods, current evidence does not support clinical or commercial claims.

Neural Boltzmann Equations

The Neural Boltzmann Equations framework is introduced, which is used to perform the most numerically precise calculation to date of the effective number of relativistic neutrino degrees of freedom, $N_\mathrm{eff}$, in the Standard Model.

Priors learned from legacy reconstructions inherit undetectable overconfidence

Where truths are scarce (e.g., seismic and medical imaging), learned priors in ill-posed inverse problems are trained on archives of legacy reconstructions---i.e., an older method's outputs---and their reported uncertainty is taken as data-driven. We show that this prior is, in the population limit, exactly the regular...

Diversified Multinomial Logit Contextual Bandits

A UCB-based algorithm that constructs assortments item-wise by maximizing optimistic marginal gains, avoids black-box optimization oracles, and offers a statistically and computationally efficient solution for diversity-aware assortment optimization under uncertainty is proposed.

Finite-Sample Performance of Gradient Descent in Logistic Regression with Gaussian Design

The main technical component is to show that the gradient of the logistic loss satisfies a certain approximate invertibility condition (AIC) and uniformly control the deviation of the gradient from its population counterpart by covering and peeling arguments, and then show that the population GD is a contraction by a d...