Results 41 to 50 of about 78,918 (265)
Cross-Project Defect Prediction Method Based on Manifold Feature Transformation
Future Internet, 2021 Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data.
Yu Zhao, Yi Zhu, Qiao Yu, Xiaoying Chen
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FEBS Letters, EarlyView.Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes +4 more
wiley +1 more source
Cross–Project Defect Prediction With Respect To Code Ownership Model: An Empirical Study
e-Informatica Software Engineering Journal, 2015 The paper presents an analysis of 83 versions of industrial, open-source and academic projects. We have empirically evaluated whether those project types constitute separate classes of projects with regard to defect prediction.
Marian Jureczko, Lech Madeyski
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Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
A Novel Unsupervised Method for Software Defect Prediction Based on Clustering Assumption
IEEE AccessSoftware defect prediction (SDP) is a very important technique used in the software testing. It helps to quickly predict the defects contained in software in the early stage of development.
Shiqi Tang +3 more
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Software Measurement and Defect Prediction with Depress Extensible Framework
Foundations of Computing and Decision Sciences, 2014 Context. Software data collection precedes analysis which, in turn, requires data science related skills. Software defect prediction is hardly used in industrial projects as a quality assurance and cost reduction mean. Objectives.
Madeyski Lech, Majchrzak Marek
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Cost-Sensitive Machine Learning for Predicting Production Defects: a Novel Approach Based on MetaCost [PDF]
پژوهش در مدیریت تولید و عملیاتPurpose: This paper aims to apply cost-sensitive machine learning (CSML) for predicting production defects in industrial processes to minimize the costs associated with false negatives.
Ahmad Jafarnejad +2 more
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FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
Machine Learning-Guided Optimization of Defects in In-Situ Alloyed Additively Manufactured Parts
Journal of Manufacturing and Materials ProcessingIn-situ alloying during laser powder bed fusion (LPBF) offers great compositional flexibility but is prone to process-induced defects. To address this problem, we developed a machine learning framework to predict and minimize major defects such as ...
Shaaf Shelesh Nezhad, Sravya Tekumalla
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FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source