Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control by Takashi Watanabe, Yoshihiro Sugi

“…For FES application, the ISM was tested in learning off line using training data obtained by PID control of very slow movements. …”
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Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data by Masahiro Hata, Yuki Miyazaki, Kohji Mori, Kenji Yoshiyama, Shoshin Akamine, Hideki Kanemoto, Shiho Gotoh, Hisaki Omori, Atsuya Hirashima, Yuto Satake, Takashi Suehiro, Shun Takahashi, Manabu Ikeda

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SPACIER: on-demand polymer design with fully automated all-atom classical molecular dynamics integrated into machine learning pipelines by Shun Nanjo, Arifin, Hayato Maeda, Yoshihiro Hayashi, Kan Hatakeyama-Sato, Ryoji Himeno, Teruaki Hayakawa, Ryo Yoshida

“…Abstract Machine learning has rapidly advanced the design and discovery of new materials with targeted applications in various systems. …”
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Development and Validation of a Cost-Effective Machine Learning Model for Screening Potential Rheumatoid Arthritis in Primary Healthcare Clinics by Wu W, Hu X, Yan L, Li Z, Li B, Chen X, Lin Z, Zeng H, Li C, Mo Y, Wu Y, Wang Q

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Remote sensing-based winter wheat yield estimation integrating machine learning and crop growth multi-scenario simulations by Xin Du, Jiong Zhu, Jingyuan Xu, Qiangzi Li, Zui Tao, Yuan Zhang, Hongyan Wang, Haoxuan Hu

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Retrospective evaluation of a single surgeon’s experience in robot-assisted inguinal repair with the Dexter System™ during the learning curve by Hubert Mignot, Bineta Diack, Juliette Capitaine, Damien Emeriau

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Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models by Xiaoxue Yang, Yajie Zou, Jinjun Tang, Jian Liang, Muhammad Ijaz

“…Overall, the findings in this paper suggest that the proposed hybrid prediction approach is effective for both statistical and machine learning models in short-term speed prediction.…”
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Electrical brain activations in preadolescents during a probabilistic reward-learning task reflect cognitive processes and behavior strategies by Yu Sun Chung, Yu Sun Chung, Berry van den Berg, Kenneth C. Roberts, Armen Bagdasarov, Marty G. Woldorff, Marty G. Woldorff, Michael S. Gaffrey, Michael S. Gaffrey, Michael S. Gaffrey

Subjects: “…reinforcement learning…”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…These results highlight the effectiveness of combining deep learning-based feature extraction with optimization and machine learning classifiers. …”
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Enhancing Cybersecurity and Privacy Protection for Cloud Computing-Assisted Vehicular Network of Autonomous Electric Vehicles: Applications of Machine Learning by Tiansheng Yang, Ruikai Sun, Rajkumar Singh Rathore, Imran Baig

Subjects: “…machine learning…”
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Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population by Eun Kyung Choe, Hwanseok Rhee, Seungjae Lee, Eunsoon Shin, Seung-Won Oh, Jong-Eun Lee, Seung Ho Choi

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A hybrid particle swarm optimization algorithm for single machine scheduling with sequence-dependent setup times and learning effects by Payam Chiniforooshan, Dragan Marinkovic

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Modeling Soil Behavior with Machine Learning: Static and Cyclic Properties of High Plasticity Clays Treated with Lime and Fly Ash by Gebrail Bekdaş, Yaren Aydın, Sinan Melih Nigdeli, İnci Süt Ünver, Wook-Won Kim, Zong Woo Geem

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Enhanced Cognitive Load Detection in Air Traffic Control Operators Using EEG and a Hybrid Deep Learning Approach by Yueying Zhou, Junji Jiang, Lijun Wang, Shanshan Liang, Hao Liu

“…We then used one hybrid deep learning model based on the convolutional layers and a self-attention mechanism to extract the pertinent EEG features. …”
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Exploration of Key Factors in the Preparation of Highly Hydrophobic Silica Aerogel from Rice Husk Ash Assisted by Machine Learning by Yun Deng, Ziyan Sha, Xingxing Wang, Ke Duan, Weijie Xue, Ian Beadham, Xiaolan Xiao, Changbo Zhang

“…To expand the applications of hydrophobic silica aerogels derived from rice husk ash (HSA) through simple traditional methods (without adding special materials or processes), this paper employs machine learning to establish mathematical models to identify optimal conditions for extracting water glass and investigates how preparation conditions and heat treatment temperatures affect properties such as the porosity and hydrophobicity of HSA. …”
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Automatic Segmentation of Asphalt Cracks on Highways After Large-Scale and Severe Earthquakes Using Deep Learning-Based Approaches by Mehmet Yilmaz, Erkut Yalcin, Fatih Demir, Ahmet Munir Ozdemir, Muhammed Atar, Aysegul Gunes, Beyza Furtana Yalcin, Ertugrul Cambay

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Retracted: Predicting the Spread of Vessels in Initial Stage Cervical Cancer through Radiomics Strategy Based on Deep Learning Approach by Advances in Materials Science and Engineering

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Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models by Samira Mohammadi, Vahid Rahmanian, Sasan Sattarpanah Karganroudi, Mehdi Adda

Subjects: “…transfer learning…”
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Modulation of Cognition: The Role of Gnidia glauca on Spatial Learning and Memory Retention in High-Fat Diet-Induced Obese Rats by Wycliffe Makori Arika, Cromwell Mwiti Kibiti, Joan Murugi Njagi, Mathew Piero Ngugi

“…Chronic exposures to high-fat diets are linked to neuropathological changes that culminate in obesity-related cognitive dysfunction and brain alteration. Learning, memory performance, and executive function are the main domains affected by an obesogenic diet. …”
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Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning – ERRATUM by Gregory Duthé, Francisco de N Santos, Imad Abdallah, Wout Weijtjens, Christof Devrient, Eleni Chatzi

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