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data science

2,617 papers

#data science Review Oct 2026

Exploring the Impact of Course-Based Research Experiences on Student Engagement in STEM at HBCUs

This study evaluates the impact of course-based undergraduate research experiences (CUREs) on learning and retention in science, technology, engineering, and mathematics (STEM) fields among engineering students at Tennessee State University (TSU), a public historically Black college and university (HBCU). It examines...

Jing Yan, Li Yang, Kaiqi Xiong et al. · 0 citations
#data science Review Open access Sep 2026

Fine wine, art, and medical physicist bibliometrics: Things that improve with age.

Scholarly productivity in radiation therapy medical physics faculty at leading cancer centers is strongly dependent on career age, with peak output occurring near the end of a typical career before declining modestly near retirement.

Sundari Mehta, J. Lucido, Douglas Moseley et al. · 0 citations
#data science Review Open access Oct 2026

Enhancing indigenous language education: evaluating the effectiveness of Kadazandusun language teaching methods among primary school teachers in Sabah

This study aimed to examine the effectiveness of Kadazandusun language teaching and learning methods employed by primary school teachers specializing in the instruction of the Kadazandusun language. The research focused on the implementation of systematic pedagogical approaches that incorporate a variety of instruction...

Suziani Jeserah Binti Junaidih, Rosliah Kiting · 0 citations
#data science Review Open access Oct 2026

THE POTENTIAL OF STEAM-BASED SCIENCE LEARNING WITHIN A DEEP LEARNING FRAMEWORK FOR THE TOPIC OF ENVIRONMENTAL POLLUTION

This study aimed to analyze the potential for implementing an integrated STEAM–Deep Learning model on the topic of Environmental Pollution at the junior secondary school level, prior to full-scale implementation. A descriptive quantitative survey approach was employed, involving science teachers and a Grade IX class as...

Wartoyo Wartoyo, F. Roshayanti, Muhammad Syaipul Hayat · 0 citations
#data science Open access Oct 2026

The positive side of stress: exploring the factors that influence Generation Z's survival in tertiary education

Eustress, a constructive form of stress, supports performance and health and is becoming increasingly important in academia. This research aims to examine the relationships among peer pressure, financial status, academic responsibility, and stress among Generation Z students in Negeri Sembilan. It is therefore necessar...

Nurmadihah Mohd Rashdi, Nursyazana Najwa Jais, Nur Zafifa Kamarunzaman · 0 citations
#data science Review Oct 2026

A clinical review of REVOLAX™ : mechanisms, safety, efficacy and clinical applications

It is demonstrated that REVOLAX™ represents a valuable treatment option within the expanding field of minimally invasive aesthetic medicine when used appropriately by trained healthcare practitioners when used appropriately by trained healthcare practitioners.

Kirsten Horsfield · 0 citations
#data science Review Open access Oct 2026

GFZ SDS Level-2/-3 Overview

This presentation will give an overview of GFZ's activities within the GRACE-FO Science Data System (SDS) including the current status of Level-2 and Level-3 products. It will also provide a high-level summary of the ongoing RL07 reprocessing campaign. First GFZ RL07 Level-2 products are expected to be published shortl...

C. Dahle, M. Hauk, M. Murböck et al. · 0 citations
#data science Open access Oct 2026

GRACE-FO: mission status, science performance and outlook

Since 2018, the GRACE Follow-On satellite mission, a partnership between NASA (US) and GFZ (Germany), is continuing the unique essential climate data record of mass change in the Earth system initiated in 2002 by the GRACE mission (2002-2017). The combined GRACE & GRACE-FO data records now span over 22 years and provid...

F. Landerer, A. Eicker, H. Save et al. · 0 citations
#data science Open access Oct 2026

From GRACE Science to Climate Service: Operational TWSA and GWSC Products in the Copernicus Climate Change Service (C3S)

Over nearly 25 years, GRACE and GRACE-FO have matured from a novel observing system into an operational-grade data source, with terrestrial water storage anomaly (TWSA) and, derived from this, groundwater storage change (GWSC) products now feeding directly into drought, flood, and water-availability assessments. Despit...

J. Haas, E. Boergens, C. Dahle et al. · 0 citations
#data science Open access Oct 2026

GRACE-C Implementation Status - Update

GRACE-Continuity (GRACE-C) is a joint NASA (US) & DLR (Germany) mission, scheduled for launch in Dec-2028. It will continue the essential data record of Earth system gravity and mass change initiated by the original GRACE mission (2002-2017) and currently enabled by the GRACE-FO mission (2018 – present). The GRACE-seri...

F. Landerer, D. Wiese, W. Klipstein et al. · 0 citations
#data science Open access Oct 2026

Testing mascon regularization strategies for simulated future gravity-field recovery

Mascon solutions estimate mass changes directly on predefined surface elements, rather than only representing them by spherical harmonic coefficients. They are useful for regional water storage, ice-mass, and ocean applications, and are already provided by several groups such as GSFC, JPL and CSR. In the framework of G...

J. Wilms, C. Dahle, M. Hauk et al. · 0 citations
#data science Open access Oct 2026

GRACE and satellite altimetry to measure ocean mass and density changes between 2002 and 202

From GRACE and GRACE-FO we get time variable information from the Earth’s gravity field since 2002. The monthly time series obtained from science centers can be represented as a surface water layer. By sampling the oceans at mascons we obtain a mass against time signal which represents the barystatic component of the s...

E. Schrama, W. van der Wal · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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