Results 121 to 130 of about 4,787,648 (245)

An Adaptive Rank Aggregation-Based Ensemble Multi-Filter Feature Selection Method in Software Defect Prediction. [PDF]

Entropy (Basel), 2021
Balogun AO, Basri S, Capretz LF, Mahamad S, Imam AA, Almomani MA, Adeyemo VE, Kumar G.   +7 more
europepmc   +1 more source

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

Advanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan, Jiafen Song, Jinglong Li, Jiangtao Xiong, Tao Yang   +4 more
wiley   +1 more source

A Novel Unsupervised Method for Software Defect Prediction Based on Clustering Assumption

IEEE Access
Software 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, Xinlan Tie, Minggui Song, Qiao Yang   +3 more
doaj   +1 more source

Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques. [PDF]

J Healthc Eng, 2021
Khan B, Naseem R, Shah MA, Wakil K, Khan A, Uddin MI, Mahmoud M.   +6 more
europepmc   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM). [PDF]

PeerJ Comput Sci, 2021
Farid AB, Fathy EM, Sharaf Eldin A, Abd-Elmegid LA.   +3 more
europepmc   +1 more source

Enhancement of the Through‐Thickness Electrical Conductivity of Carbon‐Fiber‐Reinforced Plastics Using Large Graphite Particles

Advanced Engineering Materials, EarlyView.
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe, Yu Zhou, Shintaro Kamiyama, Takao Okada, Tomohiro Yokozeki, Ryoma Tokonami, Tatsuhiro Takahashi   +6 more
wiley   +1 more source

Impact of the Process Atmosphere During Hot Isostatic Pressing on the Near‐Surface Composition of an Additively Manufactured Austenitic High‐Interstitial Steel

Advanced Engineering Materials, EarlyView.
A high interstital austenitic steel is additively manufactured and postdensified by HIP to eliminate gas porosity. Thereby, the loss of N and Mn in Ar HIP atmosphere is investigated. Further, HIP using N2 atmosphere is investigated which led to excessive nitride formation.
F. Großwendt, J. Hahn, J. Kimm, S. Weber, J. Lentz   +4 more
wiley   +1 more source

incorporating qualitative and quantitative factors for software defect prediction

, 2012
Defect is an important quality attribute of software. Defect is injected in development process and depended on the maturity level of the processes. How many defects were detected is enough?
Chen Xichang, Wang Qing, Wang Dandan, Yang Ye, Zhang Liwen, Hong Zhenghua   +5 more
core   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source