Results 111 to 120 of about 82,951 (280)

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Computer-Aided Civil and Infrastructure Engineering, EarlyView.
Abstract Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)‐based models. For example, developing AI‐driven dynamic traffic system models that accurately capture high‐resolution traffic ...
H. Wang, Y. Wang, W. Li, A. B. Subramaniyan, G. Zhang   +4 more
wiley   +1 more source

SQLJ Part 0, now known as SQL/OLB (Object-Language Bindings) [PDF]

, 1998
Andrew Eisenberg, Jim Melton
openalex   +1 more source

Inflamed or Infected Molluscum Contagiosum Lesions: Pediatrician Perceptions and the Risk of Antibiotic Overuse

Pediatric Dermatology, EarlyView.
ABSTRACT Background/Objectives Molluscum contagiosum (MC) is a common pediatric skin infection caused by the molluscum contagiosum virus. Lesions often become inflamed prior to self‐resolving. This phenomenon can mimic bacterial superinfection, although true superinfection of MC lesions is thought to be rare.
Trevor Young, Jenny Wei, Joy Wan, Albert C. Yan   +3 more
wiley   +1 more source

Tempus: An Evolutionary Mutation Testing System on Event‐Based Systems With Profile‐Based Individual Generation

Software Testing, Verification and Reliability, Volume 35, Issue 5, August 2025.
Tempus is a testing system that enhances Evolutionary Mutation Testing (EMT) by using ProfileBased individual generation (PBig). PBig generates new individuals based on previous knowledge from other programs about which operators are more likely to produce strong mutants.
Lorena Gutiérrez‐Madroñal, Antonio García‐Domínguez, Inmaculada Medina‐Bulo   +2 more
wiley   +1 more source

Self-report quality of life measure for people with schizophrenia: The SQLS [PDF]

, 2000
Greg Wilkinson, Bernadette Hesdon, D Wild, Ron Cookson, Carole Farina, Vimal Sharma, Ray Fitzpatrick, Crispin Jenkinson   +7 more
openalex   +1 more source

OpenIVM: a SQL-to-SQL Compiler for Incremental Computations

Companion of the 2024 International Conference on Management of Data
This demonstration presents a new Open Source SQL-to-SQL compiler for Incremental View Maintenance (IVM). While previous systems, such as DBToaster, implemented computational functionality for IVM in a separate system, the core principle of OpenIVM is to make use of existing SQL query processing engines and perform all IVM computations via SQL.
Ilaria Battiston, Kriti Kathuria, Peter Boncz   +2 more
openaire   +2 more sources

Addressing Inequalities in Long Covid Healthcare: A Mixed‐Methods Study on Building Inclusive Services

Health Expectations, Volume 28, Issue 4, August 2025.
ABSTRACT Background Long Covid (LC) significantly impacts health, economic and social activities. Women, deprived, learning disability, homeless and some minority ethnic populations have high prevalence rates but low access to support, indicating health inequities in LC care.
Ghazala Mir, Jordan Mullard, Amy Parkin, Cassie Lee, Jonathan Clarke, Johannes H. De Kock, Denys Prociuk, Julie L. Darbyshire, Sophie Evans, Manoj Sivan, LOCOMOTION Consortium   +10 more
wiley   +1 more source

Incremental maintenance of recursive views using relational calculus/SQL [PDF]

, 2000
Guozhu Dong, Jianwen Su
openalex   +1 more source

Expressive power of SQL

Theoretical Computer Science, 2001
AbstractIt is a folk result in database theory that SQL cannot express recursive queries such as reachability; in fact, a new construct was added to SQL3 to overcome this limitation. However, the evidence for this claim is usually given in the form of a reference to a proof that relational algebra cannot express such queries. SQL, on the other hand, in
openaire   +3 more sources

Differential dementia detection from multimodal brain images in a real‐world dataset

Alzheimer's &Dementia, Volume 21, Issue 7, July 2025.
Abstract INTRODUCTION Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high‐quality benchmark databases, but not real‐world data in hospitals. METHODS We describe a deep learning model specially trained for disease detection in heterogeneous clinical images from electronic ...
Matthew Leming, Hyungsoon Im
wiley   +1 more source