2LE-BO-DeepTrade: an integrated deep learning framework for stock price prediction by Zinnet Duygu Akşehir, Erdal Kılıç

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Exploring students’ perceptions of the design and use of the Moodle learning management system by Dimah Al-Fraihat, Abdulaziz M. Alshahrani, Maram Alzaidi, Aijaz A. Shaikh, Mohammed Al-Obeidallah, Manaf Al-Okaily

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Cword2vec: a novel morphological rule-based word embedding approach for Urdu text sentiment analysis by Saquib Khushhal, Abdul Majid, Syed Ali Abass, Rabia Riaz, Mohammad Babar, Shafiq Ahmad

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Editorial by Christian Gütl

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Numerical modelling of rope elasticity for heave compensation lifting in offshore crane operations by Bassey Asanga, Akanimo Ekpenyong, Aniekan Ikpe

“…Second, the performance of wire rope based on rope stiffness was evaluated when HCS was turned off (WOC) and on (WC). …”
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A semi-mechanistic mathematical framework for simulating multi-hormone dynamics in reproductive endocrinology by Alexandre Vallée, Anis Feki, Gaby Moawad, Jean-Marc Ayoubi

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RICE AlgebraBot: Lessons learned from designing and developing responsible conversational AI using induction, concretization, and exemplification to support algebra learning by Chenglu Li, Wanli Xing, Yukyeong Song, Bailing Lyu

“…The purpose of this study is to develop a ConvAI system that mitigates the potential ethical concerns and empirically evaluate the effect of such a system for math learning. …”
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Forecasting temperature and rainfall using deep learning for the challenging climates of Northern India by Syed Nisar Hussain Bukhari, Kingsley A. Ogudo

“…The major research focus is to develop and evaluate a model capable of capturing complex temporal dependencies in localized time-series weather data. …”
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Federated learning for digital twin applications: a privacy-preserving and low-latency approach by Jie Li, Dong Wang

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Using Text Mining to Search for Neolithic Vlaardingen Culture Sites in the Rhine-Meuse-Scheldt Delta by Lasse Van den Dikkenberg, Alex Brandsen

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Enhancing river and lake wastewater reuse recommendation in industrial and agricultural using AquaMeld techniques by J. Priskilla Angel Rani, C. Yesubai Rubavathi

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Uncertainty-Aware <i>δ</i>-GLMB Filtering for Multi-Target Tracking by M. Hadi Sepanj, Saed Moradi, Zohreh Azimifar, Paul Fieguth

“…In this study, the results indicate that the proposed heuristic ideas can improve the performance of filtering in the presence of uncertain observations. Experimental evaluations demonstrate that the proposed methods enhance track continuity and robustness, particularly in scenarios with low detection rates and high clutter, while maintaining computational feasibility.…”
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A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific Texts by Tsitsi Zengeya, Jean Vincent Fonou Dombeu, Mandlenkosi Gwetu

“…The proposed CenBERT-SEQ model was evaluated against the standard BERT base-uncased model using three Computer Science article datasets, namely, SemEval-2010, WWW, and KDD. …”
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Investigating the impact of generative AI integration on the sustenance of higher-order thinking skills and understanding of programming logic by Jemimah Nathaniel, Solomon Sunday Oyelere, Jarkko Suhonen, Matti Tedre

“…The intervention followed a one-group pretest-post-test structure over seven weeks with 25 computer science students with no prior C++ experience. …”
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Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil by Adriano Lages dos Santos, Maria Christina L. Oliveira, Enrico A. Colosimo, Robert H. Mak, Clara C. Pinhati, Stella C. Gallante, Hercílio Martelli-Júnior, Ana Cristina Simões e Silva, Eduardo A. Oliveira

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Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

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Comparative analysis of machine learning techniques in metabolomic-based preterm birth prediction by Ying-Chieh Han, Jane Shearer, Chunlong Mu, Donna M. Slater, Suzanne C. Tough, Gavin E. Duggan

“…Background: Machine learning (ML), with advancements in algorithms and computations, is seeing an increased presence in life science research. …”
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Biophysical characterization of TREM2 missense variants implicated in neurodegenerative disease by Joshua Pillai, Kijung Sung, Linda Shi, Chengbiao Wu

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AI-based nanotoxicity data extraction and prediction of nanotoxicity by Eunyong Ha, Seung Min Ha, Zayakhuu Gerelkhuu, Hyun-Yi Kim, Tae Hyun Yoon

“…Among toxicity assessment methods, computational models for predicting nanotoxicity are emerging as alternatives to traditional in vitro and in vivo assays, which involve high costs and ethical concerns. …”
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Assessment of NSCLC disease burden: A survival model-based meta-analysis study by Nataliya Kudryashova, Boris Shulgin, Nikolai Katuninks, Victoria Kulesh, Gabriel Helmlinger, Kirill Zhudenkov, Kirill Peskov

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