Results 181 to 190 of about 6,728 (248)

Rendering transparency to ranking in educational assessment via Bayesian comparative judgement

Review of Education, Volume 14, Issue 2, August 2026.
Abstract Transparency in educational assessment has become an increasingly pressing concern, particularly in the aftermath of the pandemic, as institutions seek more equitable, robust and defensible methods of evaluating student work. Comparative judgement (CJ) has gained traction as a promising alternative to traditional rubric‐based marking. However,
Andy Gray, Stephen Lindsay, Jen Pearson, Tom Crick, Alma Rahat   +4 more
wiley   +1 more source

Closed-Set Heterogeneous Domain Adaptation for IoT Intrusion Detection: An Anchor-Based Benchmark Across Single- and Multi-Source Transfer. [PDF]

Sensors (Basel)
Chizari M, Khan Ali Mirza Q, Alam A, Chizari H.   +3 more
europepmc   +1 more source

When GUI‐Based Testing of Web Applications Meets Code Review

Software Testing, Verification and Reliability, Volume 36, Issue 5, August 2026.
Summary of our findings on practices, challenges, information needs and future improvements for code review of GUI‐based testing artefacts. ABSTRACT Code review is a well‐established practice to ensure code quality, identify potential bugs, promote knowledge sharing and maintain coding standards within a team or organization.
Andreas Bauer, Tomas Helmfridsson, Emil Alégroth, Georg‐Daniel Schwarz   +3 more
wiley   +1 more source

Prototype-Based Classifiers and Vector Quantization on a Quantum Computer-Implementing Integer Arithmetic Oracles for Nearest Prototype Search. [PDF]

Entropy (Basel)
Engelsberger A, Pšeničkova M, Villmann T.   +2 more
europepmc   +1 more source

Rebalancing Software Defect Datasets via Mutation: Performance Insights From Prediction Models Based on Software Measures

Software Testing, Verification and Reliability, Volume 36, Issue 5, August 2026.
A mutation‐based approach (MBA) to rebalance defect datasets improves recall, particularly in cross‐project prediction, but increases false alarms and does not consistently enhance MCC or AUC. These findings highlight both the potential and limitations of mutation‐based rebalancing in software defect prediction.
Dinçer Güner, Görkem Giray, Onur Demirörs   +2 more
wiley   +1 more source

PETIMOT: a novel framework for inferring protein motions from sparse data using SE(3)‐equivariant graph neural networks

Acta Crystallographica Section D, Volume 82, Issue 8, Page 862-885, August 2026.
We present a new formulation for protein flexibility and learn protein motions from sparse experimental data.Proteins move and deform to ensure their biological functions. Despite significant progress in protein structure prediction, approximating conformational ensembles under physiological conditions remains a fundamental open problem.
Valentin Lombard, Julien Nguyen Van, Sergei Grudinin, Elodie Laine   +3 more
wiley   +1 more source

Protein abundance inference via expectation-maximization in fluorosequencing. [PDF]

Bioinform Adv
Kipen J, Smith MB, Blom T, Zhou SB, Marcotte EM, Jaldén J.   +5 more
europepmc   +1 more source

Are we there yet? Reliable occupancy modeling from AI‐labeled trail camera data

Conservation Science and Practice, Volume 8, Issue 8, August 2026.
Even low false‐positive rates in AI‐labeled camera‐trap data can bias occupancy estimates, particularly for rare species. Our results show that false positive informed occupancy models can substantially improve inference, underscoring the need to evaluate AI classifiers according to the assumptions of downstream ecological analyses.
Mohamed Khalil Meliane, Joseph M. Guthrie, E. Hance Ellington   +2 more
wiley   +1 more source

RELEAP: reinforcement-enhanced label-efficient active phenotyping for electronic health records. [PDF]

JAMIA Open
Yang Y, Pollak KI, Chakraborty B, Liu M, Zhou D, Hong C.   +5 more
europepmc   +1 more source

Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies

International Economic Review, Volume 67, Issue 3, Page 957-976, August 2026.
ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi, Junpei Komiyama, Shunya Noda   +2 more
wiley   +1 more source