Results 71 to 80 of about 4,787,648 (245)

Software Defect Prediction Techniques in Automotive Domain: Evaluation, Selection and Adoption [PDF]

, 2015
Software is becoming an increasingly important part of automotive product development. While software in automotive domain enables important functionality and innovations, it also requires significant effort for its verification & validation to meet ...
Rana, Rakesh
core   +1 more source

Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to characterize specific physiologic defects in anorectal dysfunction in systemic sclerosis (SSc) using anorectal manometry (ARM), evaluate associations with gastrointestinal (GI) and extraintestinal clinical phenotypes, and explore potential serologic markers for risk stratification.
Timothy Kaniecki, Alireza Amindarolzarbi, Tsion Abdi, John Clarke, Michael Hughes, Ami A. Shah, Zsuzsanna H. McMahan   +6 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Thermodynamic Pathways of Nonequilibrium Solidification in Wire‐Arc Additive Manufacturing Fe‐Based Multicomponent Alloy Structures

Advanced Engineering Materials, EarlyView.
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios, Anthony Gonzalez, Aleksander Aleman, Tyler Dolmetsch, Tanaji Paul, Arvind Agarwal   +5 more
wiley   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Outlier Detection through Connectivity-based Outlier Factor for Software Defect Prediction

Outlier Detection through Connectivity-based Outlier Factor for Software Defect ...
Andreea Vescan (10035377), Andrada-Mihaela-Nicoleta Moldovan (17666220)   +1 more
core   +1 more source

data unpredictability in software defect-fixing effort prediction

, 2010
National Laboratory for Parallel and Distributed Processing; The University of Hong KongThe prediction of software defect-fixing effort is important for strategic resource allocation and software quality management.
Wang Qing, Yang Ye, He Zhimin, Zhang Wen, Shu Fengdi   +4 more
core   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

Software defect prediction based on association rule classification. [PDF]

In software defect prediction, predictive models are estimated based on various code attributes to assess the likelihood of software modules containing errors. Many classification methods have been suggested to accomplish this task.
Vanthienen, Jan, Baojun, Ma, Baesens, Bart, Dejaeger, Karel   +3 more
core  

Toward Reduction in False Positives Just-In-Time Software Defect Prediction Using Deep Reinforcement Learning

IEEE Access
Deep Q-Network (DQN) is a popular deep reinforcement learning algorithm that has demonstrated promising results across a variety of domains. DQN presents a promising solution to the challenge of lowering false positives in software defect prediction ...
Ahmad Muhaimin Ismail, Siti Hafizah Ab Hamid, Asmiza Abdul Sani, Nur Nasuha Mohd Daud   +3 more
doaj   +1 more source