Results 171 to 180 of about 131,766 (331)
Software-defined self-learning control system for industrial robots by using reinforcement learning. [PDF]
Moon J, Kim M, Lee T, Um J.
europepmc +1 more source
Comprehensible software fault and effort prediction: A data mining approach
Julie Moeyersoms +4 more
openalex +2 more sources
Bistable Mechanisms 3D Printing for Mechanically Programmable Vibration Control
This work introduces a 3D‐printed bistable mechanism integrated into tuned mass dampers (TMDs) for mechanically adaptive passive vibration suppression. Through optimized geometry, the bistable design provides adaptable vibration reduction across a broad range of scenarios, achieving effective vibration mitigation without complex controls or external ...
Ali Zolfagharian +4 more
wiley +1 more source
BugPrioritizeAI for multimodal test case prioritisation using bug reports, code changes, and test metadata. [PDF]
Kalyani P +4 more
europepmc +1 more source
Predicting Software Fault Proneness Using Machine Learning [PDF]
Context: Continuous Integration (CI) is a DevOps technique which is widely used in practice. Studies show that its adoption rates will increase even further. At the same time, it is argued that maintaining product quality requires extensive and time consuming, testing and code reviews.
openaire
Leveraging meta-heuristic algorithms for effective software fault prediction: a comprehensive study [PDF]
Zhizheng Dang, Hui Wang
openalex +1 more source
Laser surface texturing significantly improves the corrosion resistance and mechanical strength of 3D‐printed iron polylactic acid (Ir‐PLA) for marine applications. Optimal laser parameters reduce corrosion by 80% and enhance tensile strength by 25% and ductility by 15%.
Mohammad Rezayat +6 more
wiley +1 more source
Optical Microscopy for High-Resolution IPMC Displacement Measurement. [PDF]
Minas D +5 more
europepmc +1 more source
Software Fault Prediction Using Machine Learning Algorithms
D. Himabindu, K. Pranitha Kumari
openalex +2 more sources
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 +8 more
wiley +1 more source

