Search · four archives
Search · four archives
14 papers · ranked by Valyu relevance
Habeeb Abolaji Babatunde, Owen M. McDougal, Timothy Andersen, Hongbin Pu
'Hongbin Pu'] The preprocessing of infrared spectra can significantly improve predictive accuracy for protein, carbohydrate, lipid, or other nutrition components, yet optimal preprocessing selection is typically empirical, tedious, and dataset specific. This study introduces a Bayesian optimization-based framework…
Nathan W. Churchill, Robyn Spring, Babak Afshin-Pour, Fan Dong + 2 more
'Stephen C. Strother' 'Jerzy Bodurka'] BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although…
Nathan W. Churchill, Grigori Yourganov, Anita Oder, Fred Tam + 3 more
'Simon J. Graham' 'Stephen C. Strother' 'Xi-Nian Zuo'] A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI…
Sai Prakash Challa, Melvin Alexis Lara de Leon, Jiri Koziorek, Ibrahim A. Hameed + 1 more
Machine vision and AI-based defect detection systems are increasingly deployed in manufacturing to support consistent product quality and high production efficiency. However, these automated inspection systems often suffer from sensitivity to imaging variability, dependence on large labeled datasets, and the need for…
Mathieu Dugré, Yohan Chatelain, Tristan Glatard
Magnetic resonance imaging (MRI) preprocessing is a critical step for neuroimaging analysis. However, the computational cost of MRI preprocessing pipelines is a major bottleneck for large cohort studies and some clinical applications. While high-performance computing and, more recently, deep learning have been adopted…
Gufran Ahmad Ansari, Salliah Shafi, Lamees Alhazzaa, Dechang Chen + 2 more
Background: Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due to late diagnosis. Although machine learning (ML) techniques have been widely applied for lung cancer classification, many studies lack a fully optimized end-to-end pipeline using routine clinical data. This…
Ben Blamey, Salman Toor, Martin Dahlö, Håkan Wieslander + 6 more
In this section we illustrate the utility of the toolkit in 2 real-world case studies chosen to demonstrate how the HASTE pipeline model can be realized in practice to optimize resource usage in 2 very different infrastructure and deployment scenarios. Table [tbl1] summarizes the objectives of the case studies. Case…
Ramona Leenings, Nils Ralf Winter, Lucas Plagwitz, Vincent Holstein + 14 more
'Jan Ernsting' 'Kelvin Sarink' 'Lukas Fisch' 'Jakob Steenweg' 'Leon Kleine-Vennekate' 'Julian Gebker' 'Daniel Emden' 'Dominik Grotegerd' 'Nils Opel' 'Benjamin Risse' 'Xiaoyi Jiang' 'Udo Dannlowski' 'Tim Hahn' 'Thippa Reddy Gadekallu'] PHOTONAI is a high-level Python API designed to simplify and accelerate machine…
Swapana S. Jerpoth, Robert Hesketh, C. Stewart Slater, Mariano J. Savelski + 1 more
of the Flushing Operations in Lubricant Manufacturing and Packaging Facilities Authors: ['Swapana\nS. Jerpoth' 'Robert Hesketh' 'C. Stewart Slater' 'Mariano J. Savelski' 'Kirti M. Yenkie'] Commercial lubricant industries use a complex pipeline network for the sequential processing of thousands of unique products…
Enbin Liu, Changjun Li, Yi Yang
There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the…
Seyed Hossein Abrehdari
Title: Review Highlights 1. • Technical diagrams (e.g., performance analysis) were depicted for process mining. 2. • An innovative approach was applied to optimize the time of process operations. 3. • A specialized map of the process mining was depicted using the particular event-logs.
Xuefeng Tang, Zhizhou Wang, Lei Deng, Xinyun Wang + 5 more
'Xin Jiang' 'Junsong Jin' 'Juchen Xia' 'Guozheng Quan'] The plastic forming process involves many influencing factors and has some inevitable disturbance factors, rendering the multi-objective collaborative optimization difficult. With the rapid development of big data and artificial intelligence (AI) technology…
Raúl Miñón, Josu Diaz-de-Arcaya, Ana I. Torre-Bastida, Juan López-de-Armentia + 4 more
'Juan López-de-Armentia' 'Gorka Zarate' 'Lander Bonilla' 'Asier Garcia-Perez' 'Jon Aguirre-Usandizaga'] Machine learning is already integrated in diverse domains enhancing their performance and decision support. For laboratories, this approach is normally sufficient. However, in real environments, these models can not…
Yuxiang Liu, Xinzhong Xia, Jingyang Zhang, Kun Wang + 11 more
'Mengmeng Wu' 'Jinchao Shi' 'Chao Ma' 'Ying Liu' 'Boyang Hu' 'Xinying Wang' 'Bo Wang' 'Ruzhi Wang' 'Bing Wang' 'Zeashan Hameed Khan'] This study presents a systematic approach to enhance the efficiency of monocrystalline silicon photovoltaic module assembly lines using advanced simulation modeling. The research focuses…