E-Module in TVET: unveiling brazing and riveting methods through VAK learning by Hashim, Suhaizal, Mohamad Ali, Nur Alianni, Masran, Saiful Hadi

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Discrete differential geometry driven methods for architectural geometry by Yao, Sidan

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Data-driven methods to predict the stability metrics of catalytic nanoparticles by Prabhu, Asmee M., Choksi, Tej S.

“…In this review we discuss the recent advances in data-driven methods to predict stability metrics of nanoparticles.…”
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A novel tuning method for implementing dynamic matrix control on a water tank system by Sudarshan, Srinivasa Ramanujam.

“…The novel NlStar tuning technique was found to provide the same level of performance as the Shridhar-Cooper tuning method with greater ease to tune manually.…”
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A comparative analysis of vitrification and two slow freezing methods for gonocyte-containing neonatal calf testicular tissue and subsequent in vitro culture by Tang, S, Jones, C, Davies, J, Lane, S, Coward, K

A data-driven method for automated data superposition with applications in soft matter science by Lennon, Kyle R., McKinley, Gareth H., Swan, James W.

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A transparent data-driven method for stability-constrained load restoration considering multi-phase load dynamics by Xie, Dunjian, Xu, Yan, Nadarajan, Sivakumar, Viswanathan, Vaiyapuri, Gupta, Amit Kumar

“…A transparent data-driven method based on optimal decision trees is developed to address all the short-term stability criteria (including frequency, voltage, and transient stability) considering the inrush phase of load dynamics. …”
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Psychotropic taxonomies: constructing a therapeutic framework for psychiatry by McCutcheon, RA, Cowen, P, Nour, MM, Pillinger, T

“…Finally, we consider how data-driven methods might address the issue of classification at an intermediate level, based around transdiagnostic neurobiological and psychopathological markers.…”

Soft computing based controllers for automotive air conditioning system with variable speed compressor. by Ng, Boon Chiang.

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Transfer learning on UR robots by Yu, Xiwei

“…As neural networks and deep learning develop, researchers are continually exploring the capabilities and potential of using data-driven methods to control robots. As a data-driven approach, training neural networks requires substantial data support, making the collection of sufficient data to create datasets crucial. …”
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Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Nik Mohd Zaitul Akmal, Mustapha, Shahrizal, Saat

“…The effectiveness of the FOPID controller tuning method based on MPA was assessed by evaluating the performance criteria in terms of convergence curve of the average fitness function, statistical results, and Wilcoxon’s rank test. …”
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Study on designer surface plasmon resonators by Gao, Fei

“…Chapter 2 introduces a dispersion tuning method on designer surface plasmon resonators. …”
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AI Analytics for Carbon-Neutral City Planning: A Systematic Review of Applications by Cong, Cong, Page, Jessica, Kwak, Yoonshin, Deal, Brian, Kalantari, Zahra

“…We also consider the importance of interdisciplinary collaboration, responsible AI governance, and community engagement in guiding data-driven methods and suggest how AI can contribute to supporting carbon-neutrality goals.…”
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Weakly supervised learning on road area extraction via classification labels by Liu, Xuanyi

“…Since annotating roads at pixel level is labor intensive, several data-driven methods have been proposed for this task also, including both unsupervised methods and fully supervised methods. …”
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A Data Mining-Based Model for Assessing Guangzhou's Higher Vocational Colleges 'New Energy Automobile Majors' Vocational Skills by He, Ling, Hamid, Hashima

“…The findings show the positive aspects of using modern data-driven methods to more closely match educational institutions with the constantly evolving needs of the AS. …”
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Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance by Sadat-Nejad, Y, Vandewouw, MM, Cardy, R, Lerch, J, Taylor, MJ, Iaboni, A, Hammill, C, Syed, B, Brian, JA, Kelley, E, Ayub, M, Crosbie, J, Schachar, R, Georgiades, S, Nicolson, R, Anagnostou, E, Kushki, A

“…To address this gap, data-driven methods can be used to discover groups of individuals with shared biological patterns. …”

Advanced data analytics for future smart grid stability assessment by Ren, Chao

“…The main contributions through this Ph.D. research are as follows: Firstly, the temporal-adaptive data-driven methods are proposed based on optimized hybrid ensemble learning mechanism for online STVS assessment. …”
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Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel by Zhao, Hongbo, Deng, Haitao Dean, Cohen, Alexander E, Lim, Jongwoo, Li, Yiyang, Fraggedakis, Dimitrios, Jiang, Benben, Storey, Brian D, Chueh, William C, Braatz, Richard D, Bazant, Martin Z

“…Experimental characterizations of such materials by operando microscopy produce rich image datasets3,4,5,6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation7. …”
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Lattice strain and atomic replacement of CoO₆ octahedra in layered sodium cobalt oxide for boosted water oxidation electrocatalysis by Sun, Lan, Dai, Zhengfei, Zhong, Lixiang, Zhao, Yiwei, Cheng, Yan, Chong, Shaokun, Chen, Guanjun, Yan, Chunshuang, Zhang, Xiaoyu, Tan, Huiteng, Zhang, Long, Dinh, Khang Ngoc, Li, Shuzhou, Ma, Fei, Yan, Qingyu

“…In this work, electrochemical desodiation tuning method is explored on intralayer Ag, Cu, Ce-doped Na0.7CoO2 for highly active OER catalysts. …”
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Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data by Liu, Hui, Zhang, Fan, Mishra, Shital Kumar, Zhou, Shuigeng, Zheng, Jie

“…However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. …”
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