Multivariate prediction of temper outbursts in a sample of youth enriched for irritability using ecological momentary assessment data: A registered report. by Dipta Saha, Reut Naim, Francisco Pereira, Melissa A Brotman, Charles Y Zheng

“…This work will potentially provide the foundation for the identification of features predictive of risk and future development of novel mobile-device-based interventions in youth affected with severe and impairing psychopathology.…”
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Probabilistic Multilayer Perceptrons for Wind Farm Condition Monitoring by Filippo Fiocchi, Domniki Ladopoulou, Petros Dellaportas

“…The model predicts the output power of the wind turbine under normal behaviour based on features retrieved from supervisory control and data acquisition (SCADA) systems. …”
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Facial expression recognition through muscle synergies and estimation of facial keypoint displacements through a skin-musculoskeletal model using facial sEMG signals by Lun Shu, Victor R. Barradas, Zixuan Qin, Yasuharu Koike

“…Muscle synergies are groups of muscles that show coordinated patterns of activity, as measured by their sEMG signals, and are hypothesized to form the building blocks of human motor control. We then trained two classifiers for the facial expressions based on extracted features from the sEMG signals and the synergy activation coefficients of the extracted muscle synergies, respectively. …”
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Teacher in the social space of a modern city by Boris Yu. Berzin, Aleksey V. Maltsev, Denis V. Shkurin

“…This is the reform of the educational system itself, improving the quality of the educational process, developing its material and technical base, issues of the material well-being of teachers. …”
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Interface-aware molecular generative framework for protein–protein interaction modulators by Jianmin Wang, Jiashun Mao, Chunyan Li, Hongxin Xiang, Xun Wang, Shuang Wang, Zixu Wang, Yangyang Chen, Yuquan Li, Kyoung Tai No, Tao Song, Xiangxiang Zeng

“…These features are integrated into a Conditional Wasserstein Generative Adversarial Network, which trains the model to generate compound representations targeting PPI interfaces. …”
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Concrete Spalling Severity Classification Using Image Texture Analysis and a Novel Jellyfish Search Optimized Machine Learning Approach by Nhat-Duc Hoang, Thanh-Canh Huynh, Van-Duc Tran

“…To characterize concrete surface condition, image texture descriptors of statistical measurement of color channels, gray-level run length, and center-symmetric local binary pattern are used. Based on these texture-based features, the support vector machine classifier optimized by the jellyfish search metaheuristic is put forward to construct a decision boundary that partitions the input data into two classes of shallow spalling and deep spalling. …”
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Text mining for improved exposure assessment. by Kristin Larsson, Simon Baker, Ilona Silins, Yufan Guo, Ulla Stenius, Anna Korhonen, Marika Berglund

“…Natural Language Processing (NLP) techniques were used to extract semantic and syntactic features relevant to chemical exposure text. Using these features, we trained a supervised machine learning algorithm to automatically classify PubMed abstracts according to the exposure taxonomy. …”
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Deep Learning Methods for Automatic Identification of Male and Female Chickens in a Cage-Free Flock by Bidur Paneru, Ramesh Bahadur Bist, Xiao Yang, Anjan Dhungana, Samin Dahal, Lilong Chai

“…Deep learning methods, such as You Only Look Once (YOLO) models, were innovated and trained (based on a comb size of up to 2500 images) for the identification of male and female chickens based on comb size and body features. …”
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Personal Data Recognition Using a Deep Learning Model by Nikita Babak

“…In this paper, deep learning models featuring different neural network architectures were implemented and compared against rule-based algorithms. …”
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A Generalized Method for Sentiment Analysis across Different Sources by Abubakar M. Ashir

“…A text is broken into number of tokens with each representing a sentence and then lexicon-dependent features are extracted from each token. The features are merged together using a combining function for a given text before being used to train a machine learning classifier. …”
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Convolutional Neural Networks to Facilitate the Continuous Recognition of Arabic Speech with Independent Speakers by Sally A. Sayed, Rania Ahmed Abdel Azeem Abul Seoud, Howida Y. Abdel Naby

“…The first uses a combination of convolutional neural network (CNN) and long short-term memory (LSTM) encoders, and an attention-based decoder, and the second is based on the Sphinx-4 recognizer, which includes pocket sphinx, base sphinx, and sphinx train, with various types and number of features to be extracted (filter bank and mel frequency cepstral coefficients (MFCC)) based on the CMU Sphinx tool, which generates a language model for different sentences spoken by different speakers. …”
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MAGECODE: Machine-Generated Code Detection Method Using Large Language Models by Hung Pham, Huyen Ha, van Tong, Dung Hoang, Duc Tran, Tuyen Ngoc Le

“…MageCode utilizes the pre-trained model CodeT5+ to extract semantic features from source code inputs and incorporates metric-based techniques to enhance accuracy. …”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…The classifier, trained on labeled data, recognizes and classifies specific events based on these features. …”
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Application of Artificial Intelligence in Tinnitus Diagnosis and Treatment: A Pilot Study by Yu Wang, Kaixiang Pan, Richard Tyler, Zhaoyi Lu, Shan Xiong, Yufei Xie, Tao Pan

“…AI models can learn intricate patterns between tinnitus features and treatments, as suggested by experts. In this study, we trained an AI model with an expert system to predict tinnitus treatment based on tinnitus symptoms. …”
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Functions of civic education: Teachers' priorities by V. V. Malenkov

“…The quantitative data provided can be used as an information base for the development of civic education programmes at various levels, as well as the design of curricula and content of disciplines of civic studies.…”
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Graph neural network structural limitation for thermal simulation and architecture optimization through rating system by Pierre Hembert, Chady Ghnatios, Julien Cotton, Francisco Chinesta

“…Abstract Graph neural networks are well suited for physics based simulation. Among other features, graphs can accurately represent thermal effects, with energy conservation operating on the nodes (vertices) and heat flow coursing through edges. …”
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c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease. by Sherlyn Jemimah, Ferial Abuhantash, Aamna AlShehhi

“…We trained the model with blood genotyping data, microarray, and clinical features from the Alzheimer's Neuroimaging Disease Initiative (ADNI). …”
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Classification of Biological Data using Deep Learning Technique by Azha Javed, Muhammad Javed Iqbal

“…The model extracted features from the protein sequences labels and learned through the dataset. …”
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Lexicon-enhanced transformer with spatial-aware integration for Chinese named entity recognition by Jiachen Huang, Shuo Liu

“…In recent years, pre-trained language and lexicon-based models have proven more powerful than the previous character-based models in CNER tasks. …”
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Deep Neural Networks for Estimating Regularization Parameter in Sparse Time–Frequency Reconstruction by Vedran Jurdana

“…This study introduces a novel approach using deep neural networks (DNNs) to predict regularization parameters based on Wigner–Ville distributions (WVDs). The proposed DNN is trained on a comprehensive dataset of synthetic signals featuring multiple linear and quadratic frequency-modulated components, with variations in component amplitudes and random positions, ensuring wide applicability and robustness. …”
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