Online Three-Dimensional Fuzzy Multi-Output Support Vector Regression Learning Modeling for Complex Distributed Parameter Systems by Gang Zhou, Xianxia Zhang, Hanyu Yuan, Bing Wang

“…In this paper, an innovative online three-dimensional (3D) fuzzy multi-output support vector regression learning method is proposed for DPS modeling. The proposed method employs spatial fuzzy basis functions from the 3D fuzzy model as kernel functions, enabling direct construction of a comprehensive fuzzy rule base. …”
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A novel end-to-end learning framework for inferring lncRNA-disease associations based on convolution neural network by Shunxian Zhou, Sisi Chen, Jinhai Le, Yangtai Xu, Lei Wang

“…And then, by combining these hidden features of diseases and lncRNAs with known lncRNA-disease associations, we designed five different loss functions. Next, based on errors obtained by these loss functions, we would perform back propagation to fit parameters in CNMCLDA, and complete those missing values in lncRNA-disease relational matrix according to these fitted parameters. …”
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A KWS System for Edge-Computing Applications with Analog-Based Feature Extraction and Learned Step Size Quantized Classifier by Yukai Shen, Binyi Wu, Dietmar Straeussnigg, Eric Gutierrez

“…The filter bank is behaviorally modeled, making use of second-order band-pass transfer functions, simulating the analog front-end (AFE) processing. …”
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Balancing Data Privacy and 5G VNFs Security Monitoring: Federated Learning with CNN + BiLSTM + LSTM Model by Abdoul-Aziz Maiga, Edwin Ataro, Stanley Githinji

“…The cloudification of telecommunication network functions with 5G is a novelty that offers higher performance than that of previous generations. …”
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How adolescents learn to build social bonds: A developmental computational account of social explore-exploit decision-making by Kathy T. Do, Sophie G. Paolizzi, Michael N. Hallquist

“…Building social bonds is a critical task of adolescence that affords opportunities for learning, identity formation, and social support. Failing to develop close relationships in adolescence hinders adult interpersonal functioning and contributes to problems such as loneliness and depression. …”
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A peptide mimetic targeting trans-homophilic NCAM binding sites promotes spatial learning and neural plasticity in the hippocampus. by Igor Kraev, Christian Henneberger, Clara Rossetti, Lisa Conboy, Lene B Kohler, Martina Fantin, Alistair Jennings, Cesar Venero, Victor Popov, Dmitri Rusakov, Michael G Stewart, Elisabeth Bock, Vladimir Berezin, Carmen Sandi

“…However, NCAM is a structurally and functionally complex molecule with multiple domains engaged in a variety of actions, which raise the question as to which NCAM fragment should be targeted. …”
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In Silico Discovery and Sensory Validation of Umami Peptides in Fermented Sausages: A Study Integrating Deep Learning and Molecular Modeling by Haochen Geng, Chunming Xu, Huijun Ma, Youxu Dai, Ziyou Jiang, Mingyue Yang, Danyang Zhu

“…Deep learning has great potential in the field of functional peptide prediction. …”
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Interpretable Active Learning Identifies Iron‐Doped Carbon Dots With High Photothermal Conversion Efficiency for Antitumor Synergistic Therapy by Tianliang Li, Bin Cao, Yitong Wang, Lixing Lin, Lifei Chen, Tianhao Su, Haicheng Song, Yuze Ren, Longhan Zhang, Yingying Chen, Zhenzhen Li, Lingyan Feng, Tong‐yi Zhang

“…ABSTRACT Active learning (AL) is a powerful method for accelerating novel materials discovery but faces huge challenges for extracting physical meaning. …”
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DeepRNAac4C: a hybrid deep learning framework for RNA N4-acetylcytidine site prediction by Guohua Huang, Guohua Huang, Runjuan Xiao, Runjuan Xiao, Chunying Peng, Jinyun Jiang, Weihong Chen

“…RNA N4-acetylcytidine (ac4C) is a crucial chemical modification involved in various biological processes, influencing RNA properties and functions. Accurate prediction of RNA ac4C sites is essential for understanding the roles of RNA molecules in gene expression and cellular regulation. …”
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Natural Language Processing-Based Deep Learning to Predict the Loss of Consciousness Event Using Emergency Department Text Records by Hang A. Park, Inyeop Jeon, Seung-Ho Shin, Soo Young Seo, Jae Jun Lee, Chulho Kim, Ju Ok Park

“…To address class imbalance in LOC labeling, deep learning models were trained with weighted loss functions, achieving a high area under the curve (AUC) of 0.91. …”
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Investigating and learning lessons from early experiences of implementing ePrescribing systems into NHS hospitals: a questionnaire study. by Kathrin Cresswell, Jamie Coleman, Ann Slee, Robin Williams, Aziz Sheikh, ePrescribing Programme Team

“…Implementations in English hospitals are in the early stages and there is a lack of standards guiding the procurement, functional specifications, and expected benefits. We sought to provide an updated overview of the current picture in relation to implementation of ePrescribing systems, explore existing strategies, and identify early lessons learned.…”
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Una herramienta automática para el aprendizaje de los conectores discursivos / An automatic tool for the learning of discourse connectors by Iria da Cunha, M.ª Ángeles Escobar

“…The main goal of this article is to describe the development of an automatic tool that helps to write texts in Spanish and contributes to the learning of discourse connectors. The tool includes discourse-level functionalities. …”
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Learning computer-aided manufacturing from demonstration: a case study with probabilistic movement primitives in robot wood carving by Daniel Schäle, Martin F. Stoelen, Erik Kyrkjebø

“…The ProMP model is then exposed in Grasshopper, where it functions as a translator from drawing input to toolpath output. …”
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Integrated bioinformatics analysis and machine learning approach for the identification of immune-related genes in the diagnosis of aortic valve calcification with periodontitis by Duolikun Mutailifu, Abudousaimi Aini, Abudunaibi Maimaitiaili

“…The study included functional enrichment, protein-protein interaction (PPI) network construction, and immune infiltration analyses. …”
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Machine-Learning-Based Depression Detection Model from Electroencephalograph (EEG) Data Obtained by Consumer-Grade EEG Device by Kei Suzuki, Tipporn Laohakangvalvit, Midori Sugaya

“…At present, a sufficient score has not been achieved.; <b>Methods:</b> To improve the score of depression detection, we quantified various EEG indices to train models such as power spectrum, asymmetry, complexity, and functional connectivity. In addition, feature selection was performed to ensure that the model learns only promising EEG indices for depression detection. …”
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Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic by Muhammed Ballı, Asli Ercan Dogan, Sevin Hun Senol, Hale Yapici Eser

“…The findings emphasize the critical roles of personality functioning, mood, and anxiety in shaping suicidal ideation. …”
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Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities by Munya A. Arasi, Hussah Nasser AlEisa, Amani A. Alneil, Radwa Marzouk

“…They are efficient in certifying functions of detection of actions, observing crucial functions, and tracking. …”
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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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Mental and speech development of children after cochlear implantation as a rehabilitation factor in the learning process: modern concepts and approaches by V. O. Kazitseva, E. V. Gutkevich

“…This has enabled the formulation of a position that views these processes as targets for effective learning and socialisation of the child as a whole. …”
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An interdisciplinary complex problem as a starting point for learning: Impact of the PBL method in second-year Environmental engineering students by E. Saez de Camara, A. Lopez-Urionabarrenechea, M. N. Azpiazu, P. Ruiz de Arbulo, G. Insunza

“…Regarding students’ opinion, it should be emphasized that they perceive that this method is functional and encouraging. A high percentage of the students describe the experience as positive or very positive. …”
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