A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification by Ruichen Li, Bei Wang, Tao Zhang, Takenao Sugi

“…However, the automatic staging model would have a relatively poor performance when working on unseen new data due to individual differences. …”
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A machine learning modelling for the seismicity in the region of Greece from 2000 and thereafter by Ambrosios-Antonios Savvides, Leonidas Papadopoulos, Dimitrios-Panagiotis Serris

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Gender Factor in Associative Links of Words: Dictionary and Distributive-Semantic Model Data by T. A. Litvinova, E. S. Kotlyarova, V. A. Zavarzina

“…The aim of the work is to make a comparative analysis of the associative links of full-meaning words from the upper zone of the frequency list, compiled on the basis of a research corpus of blog texts in Russian, in a psycholinguistic experiment and the distributivesemantic model Global Vectors (GloVe), trained on this corpus. …”
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Advanced neural network-based model for predicting court decisions on child custody by Mohammad Abrar, Abdu Salam, Faizan Ullah, Muhammad Nadeem, Hussain AlSalman, Muaadh Mukred, Farhan Amin

“…The working mechanism of our proposed model is performed in two phases. …”
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Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model by Sophie Charrasse, Titouan Poquillon, Charlotte Saint-Omer, Audrey Schunemann, Mylène Weill, Victor Racine, Abdel Aouacheria

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A Riemannian Dichotomizer Approach on Symmetric Positive Definite Manifolds for Offline, Writer-Independent Signature Verification by Nikolaos Vasilakis, Christos Chorianopoulos, Elias N. Zois

“…This work introduces, for the first time in the signature verification literature, a Riemannian dichotomizer employing Riemannian dissimilarity vectors (RDVs). …”
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A malware detection method with function parameters encoding and function dependency modeling by Ronghao Hou, Dongjie Liu, Xiaobo Jin, Jian Weng, Guanggang Geng

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Development and use of a cognitive system model for solving problems of purposeful behavior by A. A. Solodov, V. M. Trembach

“…The aim of the study is to formulate a formal definition of the cognitive system on the basis of a simplified representation of human cognitive activity and on this basis to develop methods for engineering design of the cognitive system model. The process of cognition is modeled as the interaction of several structures of the human personality. …”
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Real-time prediction of the rate of penetration via computational intelligence: a comparative study on complex lithology in Southwest Iran by Mohammad Najafi, Yousef Shiri

“…In this study, five methodologies, including three artificial intelligence models (artificial neural networks [ANNs], support vector regression [SVR], random forest [RF]), a physical model, and a hybrid model, were evaluated for their ability to estimate the ROP on the basis of drilling data from a complex lithological area. …”
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Conceptualizing of Rural Settlements Development by A. A. Satybaldin, A. T. Tleuberdinova, X. V. Kulik

“…The problem of territorial development is quite relevant for countries that cause a wide range of development issues: a low level of quality of life, underdeveloped infrastructure, migration of the working-age population to urban areas, etc. countryside. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…This research contributes to the field of machine learning by demonstrating that the selection of an anomaly detection algorithm should be a considered decision, taking into account the specific characteristics of the data and the operational context of its application. Future work should explore parameter optimization, the impact of dataset characteristics on model performance, and the application of these models to real-world datasets to validate their efficacy in practical anomaly detection scenarios.…”
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Anomaly detection using machine learning and adopted digital twin concepts in radio environments by Mohamed Hussien Moharam, Omar Hany, Ahmed Hany, Amenah Mahmoud, Mariam Mohamed, Sohila Saeed

“…Abstract Reliable and secure wireless communication is essential in Industry 4.0. This work presents an anomaly detection framework using Digital Twin (DT) technology to simulate and monitor dynamic radio environments. …”
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Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models by Izabela Cristina de Oliveira, Ricardo Gava, Dthenifer Cordeiro Santana, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Mayara Favero Cotrim, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro

“…The objectives of this work are (i) to classify soybean cultivars under different irrigation managements using hyperspectral data, looking for the best machine-learning algorithm for the classification and the input that improves the performance of the models. …”
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An integrative review of the combined use of mathematical and statistical models for estimating malaria transmission parameters by Alessandro Grosso, Niel Hens, Steven Abrams

“…Conclusion The present work argues that the interaction between mathematical and statistical models, although previously exemplified by others, is underappreciated when modelling malaria transmission. …”
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Phonosemantic component of bilingual mental lexicon: word recognition models and lexical selection mechanisms by S.O. Gaivoronskaya

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Identification of an unmanned aerial vehicle pilot-operator dynamics model under stochastic conditions by C. І. Осадчий, А. М. Івлієв, С. Ф. Колісніченко, Г. С. Тимошенко

“… The article is devoted to investigation of the new rules for identifying the pilot and his remnants dynamics models in the conditions of work as a part of a multidimensional closed-loop control system for an unmanned aerial vehicle. …”
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A Generic AI-Based Technique for Assessing Student Performance in Conducting Online Virtual and Remote Controlled Laboratories by Ahmed M. Abd El-Haleem, Mohab Mohammed Eid, Mahmoud M. Elmesalawy, Hadeer A. Hassan Hosny

“…The study confirmed that Artificial Neural Network (ANN) and Support Vector Machine (SVM) are the best models to be used for automatically evaluating student performance while conducting the online labs with a precision reaching up to 91%.…”
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Stacking modeling with genetic algorithm-based hyperparameter tuning for uniaxial compressive strength prediction by Tanveer Alam Munshi, Khanum Popi, Labiba Nusrat Jahan, M. Farhad Howladar, Mahamudul Hashan

“…The proposed stacking model achieved a high testing R2 of 0.9762, outperforming individual models. …”
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Comparative analysis of machine learning classifiers and deep learning models for categorization of Knee Osteoarthritis by Deo Arpit, Korde Manish, Khatri Amit, Jain Aman, Kumawat Ashish, Rathore Vineeta

“…The study evaluates two Machine Learning classifiers which were Support Vector Machine (SVM) and XGBoost which both are optimized through GridSearchCV for hyperparameter tuning and two deep learning models EfficientNetB6 and EfficientNetB7 which both were fine tuned. …”
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A Lightweight Deep Learning Model for Profiled SCA Based on Random Convolution Kernels by Yu Ou, Yongzhuang Wei, René Rodríguez-Aldama, Fengrong Zhang

“…The model is then processed by a classifier with an attention mechanism, which finally outputs the probability vector for the candidate keys. …”
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