Results 71 to 80 of about 1,295,192 (344)

Review of Machine Learning Approaches to Semantic Web Service Discovery

Journal of Advances in Information Technology, 2010
A Web service can discover and invoke any service anywhere on the Web, independently of the language, location, machine, or other implementation details.
Shalini Batra, Seema Bawa
doaj   +1 more source

Diagnosis of Breast Cancer Using Radiomics Models Built Based on Dynamic Contrast Enhanced MRI Combined With Mammography

Frontiers in Oncology, 2021
ObjectiveTo build radiomics models using features extracted from DCE-MRI and mammography for diagnosis of breast cancer.Materials and Methods266 patients receiving MRI and mammography, who had well-enhanced lesions on MRI and histologically confirmed ...
You-Fan Zhao, Zhongwei Chen, Yang Zhang, Jiejie Zhou, Jeon-Hor Chen, Jeon-Hor Chen, Kyoung Eun Lee, Freddie J. Combs, Ritesh Parajuli, Rita S. Mehta, Meihao Wang, Min-Ying Su, Min-Ying Su   +12 more
doaj   +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

Quadratic hyper-surface kernel-free large margin distribution machine-based regression and its least-square form

Machine Learning: Science and Technology
ε -Support vector regression ( ε -SVR) is a powerful machine learning approach that focuses on minimizing the margin, which represents the tolerance range between predicted and actual values.
Hao He, Kuaini Wang, Yuzhu Jiang, Huimin pei   +3 more
doaj   +1 more source

Supervised Transfer Learning for Product Information Question Answering

, 2019
Popular e-commerce websites such as Amazon offer community question answering systems for users to pose product related questions and experienced customers may provide answers voluntarily.
Bui, Trung, Lai, Tuan Manh, Li, Sheng, Lipka, Nedim   +3 more
core   +1 more source

Machine-learning-based EDFA gain estimation [Invited]

IEEE\/OSA Journal of Optical Communications and Networking, 2021
Optical transmission systems with high spectral efficiency require accurate quality of transmission estimation for optical channel provisioning. However, the wavelength-dependent gain effects of erbium-doped fiber amplifiers (EDFAs) complicate precise ...
Jiakai Yu, Shengxiang Zhu, Craig L. Gutterman, G. Zussman, D. Kilper   +4 more
semanticscholar   +1 more source

Machine learning approach to reconstruct density matrices from quantum marginals

Machine Learning: Science and Technology
Abstract In this work, we propose a machine learning (ML)-based approach to address a specific aspect of the Quantum Marginal Problem: reconstructing a global density matrix compatible with a given set of quantum marginals. Our method integrates a quantum marginal imposition technique with convolutional denoising autoencoders.
Daniel Uzcategui-Contreras, Antonio Guerra, Sebastian Niklitschek, Aldo Delgado   +3 more
openaire   +3 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Peritumoral features for assessing invasiveness of lung adenocarcinoma manifesting as ground-glass nodules

Scientific Reports
We evaluated the predictive value of radiomics features from different peritumoral ranges for the invasiveness of ground-glass nodular lung adenocarcinoma using various machine learning models.
Xiao Wang, Hui Xue, Wei Ding, Fei Huang, Yu Zhang, Xin Pang   +5 more
doaj   +1 more source

MP15-09 MACHINE LEARNING AND AUTOMATED PERFORMANCE METRICS TO PREDICT POSITIVE SURGICAL MARGINS AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY [PDF]

, 2021
Ryan S. Lee, Runzhuo Ma, Jessica H. Nguyen, Stephanie Pham, Jacqueline Maya-Silva, Manju Aron, Siamak Daneshmand, Steven Cen, Andrew J. Hung   +8 more
openalex   +1 more source