Results 221 to 230 of about 84,005 (291)

Explainable artificial intelligence (XAI)‐powered design framework for lightweight strain‐hardening ultra‐high‐performance composites (SH‐UHPC)

open access: yesStructural Concrete, EarlyView.
Abstract Lightweight strain‐hardening ultra‐high‐performance concrete composite (SH‐UHPC) is an outstanding alternative for engineering applications and infrastructure thanks to its outstanding strength, toughness, ductility, and low density. The integration of artificial intelligence (AI)‐based modeling strategies into engineering problems can ...
Metin Katlav, Kazim Turk
wiley   +1 more source

SecAgent: Efficient Mobile GUI Agent with Semantic Context

open access: green
Yiping Xie   +9 more
openalex   +1 more source

Search based GUI Test Generation in Java - Comparing Code-based and EFG-based Optimization Goals

open access: gold, 2017
Mathias Menninghaus   +3 more
openalex   +1 more source

FDI and Performance: A Comparative Analysis Between Emerging and Developed Economies

open access: yesThunderbird International Business Review, EarlyView.
ABSTRACT This study investigates the nuanced relationship between foreign direct investment (FDI) and firm performance, addressing the heterogeneity of FDI's impact across countries with different levels of development. While FDI is widely recognized as a catalyst for economic growth, technology transfer, and enhanced competitiveness, particularly in ...
Cintya Lanchimba, Mamadou Ndione
wiley   +1 more source

FEC Check: Development of a decision support tool to aid interpretation of gastrointestinal nematode faecal egg counts in sheep

open access: yesVeterinary Record, EarlyView.
Abstract Background Gastrointestinal nematode infections are ubiquitous in grazing livestock worldwide impacting animal health and production. Faecal egg count (FEC) is an accessible diagnostic test that can guide the need for treatment. However, interpretation of FECs can be challenging.
Eilidh Geddes   +7 more
wiley   +1 more source

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

open access: yesWildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin   +4 more
wiley   +1 more source

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