Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…Dynamic clustering algorithms play a crucial role in numerous real-world applications by continuously adapting to evolving data patterns and identifying changes within the underlying cluster structure. …”
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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

“…This systematic literature review evaluates predictive models in education, focusing on their role in forecasting student performance, identifying at-risk students, and personalising learning experiences. …”
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A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…Erosion is episodic and varies both spatially and temporarily; hence, forecasting erosion patterns to identify vulnerable infrastructure is immensely challenging. …”
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Exploring the Early Neolithic in the Arabian Gulf: A newly discovered 8,400-year-old stone-built architecture on Ghagha Island, United Arab Emirates. by Kevin Lidour, Noura Al Hameli, Rémy Crassard, Fabian D'Silva, Ahmed Al Haj

“…The architectural remnants reveal patterns of continuity and adaptation across both phases. …”
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Mapping the Evolution of Corporate Social Responsibility Research (2015–2024): A Bibliometric Analysis Based on Scopus by Cristyano Cristyano, Suryadi Suryadi, Riyanto Riyanto

“…The objective is to map the intellectual evolution of CSR scholarship by identifying key thematic shifts, dominant theoretical frameworks, and methodological patterns. Using VOSviewer as the primary visualization tool, the study explores research networks, keyword co-occurrences, and temporal transitions in CSR literature over the past decade. …”
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Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

“…However, essential individual features can be extracted by examining human skeletal movements’ progression and temporal patterns. This paper presents a novel multimodal spatio-temporal fistfight detection model (MSTFDet) that integrates RGB images and human skeletal data to identify violent behaviors accurately. …”
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Tourist Destination Recommendations Using Deep Learning by Amarita Ritthipakdee, Chartchai Leenawong

“…The model employs Neural Collaborative Filtering (NCF), utilizing deep neural networks to capture complex, non-linear patterns between users and destinations, surpassing the limitations of traditional matrix factorization methods. …”
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Optimizing Supply Chain Resilience Using Advanced Analytics and Computational Intelligence Techniques by Jie Xu, Lixing Bo

“…LSTM’s strength in capturing complex temporal patterns is utilized to predict demand with high precision, while PSO is employed to optimize various supply chain components, including inventory management, transportation, and production planning. …”
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Architecture-Aware Augmentation: A Hybrid Deep Learning and Machine Learning Approach for Enhanced Parkinson’s Disease Detection by Madjda Khedimi, Tao Zhang, Hanine Merzougui, Xin Zhao, Yanzhang Geng, Khamsa Djaroudib, Pascal Lorenz

“…We compare the accuracy of Vision Transformer (ViT) with K-Nearest Neighbors (KNN), Convolutional Neural Networks (CNN) with Support Vector Machines (SVM), and Residual Neural Networks (ResNet-50) with Logistic Regression, evaluating their performance on both augmented and non-augmented data. …”
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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…We evaluate the method on two PhysioNet datasets, TwoLeadECG and variable projection networks (VPNet). …”
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Comparing acoustic representations for deep learning-based classification of underwater acoustic signals: A case study on orca (Orcinus orca) vocalizations by Fabio Frazao, Ruth Joy, Michael Dowd

“…The spectrogram is well-suited for many such pattern recognition algorithms, including those developed for computer vision, such as convolutional neural networks. …”
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Environmental impacts shape the density-size relationship of benthic macroinvertebrates in Amazonian streams (Serra dos Carajás, Pará, Brazil) by Maria Eduarda Cabral Liberal, Camila Pinto Leão, Jaqueline Silva de Oliveira, Francisco Valente-Neto, Bruno Spacek Godoy

“…These changes suggest a simplification of trophic networks and decreased energy transfer efficiency. …”
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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…The model employs a hybrid architecture combining Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks, enriched with attention mechanisms to capture both local and global dependencies. …”
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Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes by Guillermo Edinson Guzman Gómez, Luis Eduardo Burbano Agredo, Veline Martínez, Oscar Fernando Bedoya Leiva

“…We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). …”
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A deep reinforcement learning approach for wind speed forecasting by Shahab S. Band, Ting Jia Lin, Sultan Noman Qasem, Rasoul Ameri, Danyal Shahmirzadi, Muhammad Shamrooz Aslam, Hao-Ting Pai, Ely Salwana, Amir Mosavi

“…The conventional wind forecasting methods often struggle to handle the non-stationary and inconsistent wind patterns. This paper presents a hybrid method of  Empirical Wavelet Transform (EWT) and Deep Reinforcement Learning (DRL) for wind speed modeling to overcome the forecasting challenges. …”
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The dialog between mother and newborn: insights from immune mediator crosstalk elicited by antenatal SARS-COV-2 exposure by Maria Eduarda Canellas-de-Castro, Maria Eduarda Canellas-de-Castro, Maria Eduarda Canellas-de-Castro, Lizandra Moura Paravidine Sasaki, Lizandra Moura Paravidine Sasaki, Geraldo Magela Fernandes, Geraldo Magela Fernandes, Geraldo Magela Fernandes, Felipe Motta, David Alves de Araújo Júnior, Heidi Luise Schulte, Ângelo Pereira da Silva, Caroline de Oliveira Alves, Rosana Maria Tristão, José Alfredo Lacerda de Jesus, Karina Nascimento Costa, Luiz Claudio Gonçalves de Castro, Luiz Claudio Gonçalves de Castro, Otávio de Toledo Nóbrega, Laila Salmen Espindola, Jordana Grazziela Alves Coelho-dos-Reis, Joaquim Pedro Brito-de-Sousa, Ismael Artur da Costa-Rocha, Vitor Hugo Simões Miranda, Ana Carolina Campi-Azevedo, Vanessa Peruhype-Magalhães, Andréa Teixeira-Carvalho, Ciro Martins Gomes, Ciro Martins Gomes, Ciro Martins Gomes, Alberto Carlos Moreno Zaconeta, Cleandro Pires de Albuquerque, Cleandro Pires de Albuquerque, Licia Maria Henrique da Mota, Licia Maria Henrique da Mota, Licia Maria Henrique da Mota, Olindo Assis Martins-Filho, Alexandre Anderson de Sousa Munhoz Soares, Alexandre Anderson de Sousa Munhoz Soares

“…GoalThe present study intended to evaluate whether the profile of soluble immune mediators observed in cord blood samples resembles the pattern identified for mother serum samples.MethodsFor this purpose, parallel analysis of chemokines, cytokines, and growth factors was carried out in mother–newborn paired samples from acute and convalescent COVID-19 subgroups (Early, Intermediate, and Late) as well as healthy controls (HC).ResultsData demonstrated that increased levels of CCL11, IFN-γ, IL1-Ra, and G-CSF were observed in cord blood samples from most COVID-19 subgroups, with fold change magnitude from 1.6× to 8.2× as compared with HC. …”
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IRGL-RRI: interpretable graph representation learning for plant RNA–RNA interaction discovery by Qingquan Liao, Xuchong Liu, Wei Zhao, Yu Tong, Fangzheng Xu, Xinxin Liu, Yifan Chen

“…The model enriches sample information by extracting features of different bases from plant RNA data and reconstructs these features using an algorithmic hierarchy approach to capture more complex patterns. A graph representation based on a masking strategy and regularization enhances RNA feature extraction. …”
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FetalMovNet: A Novel Deep Learning Model Based on Attention Mechanism for Fetal Movement Classification in US by Musa Turkan, Emre Dandil, Furkan Erturk Urfali, Mehmet Korkmaz

“…The model integrates convolutional neural networks (CNN) for feature extraction and an attention mechanism to capture spatio-temporal patterns, significantly improving classification performance of fetal movements. …”
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Intercomparison of Surface Currents Obtained Using SCHISM and the HF Radar Data in Galveston Bay and Sabine Lake, Texas by Cletus O. Ogbodo, Rosa M. Fitzgerald, Christopher Fuller, Jungwoo Lee, Roberto Perea, Javier Polanco-Gonzalez

“…One-month HF radar data, in April 2023, were extracted from the two newly installed HF radar networks comprising two and three HF radar stations at Sabine Lake and Galveston Bay, respectively. …”
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Educational Reforms and Healthcare Competitiveness through Data-Driven Analysis by Artem Artyukhov, Olha Yeremenko, Nadiia Artiukhova, Artur Lapidus, Olena Churikanova, Kseniia Bliumska-Danko

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