Smart photonic wristband for pulse wave monitoring by Renfei Kuang, Zhuo Wang, Lin Ma, Heng Wang, Qingming Chen, Arnaldo Leal Junior, Santosh Kumar, Xiaoli Li, Carlos Marques, Rui Min

“…Several different speckle pattern processing algorithms and POFs with different core diameters were evaluated. …”
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Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks by Ihor Blinov, Virginijus Radziukynas, Pavlo Shymaniuk, Artur Dyczko, Kinga Stecuła, Viktoriia Sychova, Volodymyr Miroshnyk, Roman Dychkovskyi

“…Given the presence of anomalies and missing values in the operational data, a two-stage preprocessing algorithm incorporating DBSCAN clustering was applied for data cleansing and imputation. …”
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Discovering emergent connections in quantum physics research via dynamic word embeddings by Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg

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Modelling and Output Power Estimation of a Combined Gas Plant and a Combined Cycle Plant Using an Artificial Neural Network Approach by Vasileios Xezonakis, Olusegun David Samuel, Christopher Chintua Enweremadu

“…Researchers, academicians, and stakeholders have been unable to predict, ensure effective operation, and prevent power outages in COGAS due to the nonlinearity. …”
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Radiomics in pediatric brain tumors: from images to insights by Pranjal Rai, Sabha Ahmed, Abhishek Mahajan

“…By integrating radiomics with machine learning algorithms, studies have demonstrated strong performance in classifying tumor types such as medulloblastoma, ependymoma, and gliomas, and predicting molecular subgroups and mutations such as H3K27M and BRAF. …”
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Investigation of the Pathogenesis of Liver Fibrosis Associated with Type 2 Diabetes Mellitus via Bioinformatic Analysis by Zhiyu Xiong, Kan Shu, Yingan Jiang

“…The co-differentially expressed genes (co-DEGs) were identified and subsequently analyzed through functional enrichment, protein–protein interaction (PPI) network construction, transcription factor prediction, and drug prediction. Machine learning algorithms were then applied to identify key genes. …”
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Comparative Study and Real-World Validation of Vertical Load Estimation Techniques for Intelligent Tire Systems by Ti Wu, Xiaolong Zhang, Dong Wang, Weigong Zhang, Deng Pan, Liang Tao

“…Vertical load prediction algorithms are developed using Support Vector Machine (SVM) and linear regression, considering variables like contact length, vehicle speed, and tire pressure. …”
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DNA familial binding profiles made easy: comparison of various motif alignment and clustering strategies. by Shaun Mahony, Philip E Auron, Panayiotis V Benos

“…Various comparison metrics and alignment algorithms are evaluated (a total of 105 combinations). …”
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Digital solutions for risk management in sustainable development conditions of business ecosystems by Oleksii HNIEZDOVSKYI, Danylo DOMASHENKO, Svitlana DOMASHENKO, Denys MOROZOV, Serhii SHYLO

“…A prediction system that uses various machine learning algorithms was developed and tested. …”
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Network archaeology: uncovering ancient networks from present-day interactions. by Saket Navlakha, Carl Kingsford

“…To overcome this limitation, we propose several novel algorithms to reconstruct the growth history of a present-day network. …”
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Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis by Alikhan Anuarbekov, Jiří Kléma

“…By integrating RNA-seq data with prior interaction networks obtained experimentally or through in-silico predictions, researchers can discover novel interactions, validate existing ones, and improve interaction prediction accuracy. …”
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QoS Routing in Telecommunications Networks by N. I. Listopad, O. A. Lavshuk

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Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study by Zhong-Kai Ni, Tian-Han Zhou, Shu-Chao Kang, Ye-Hong Han, Hai-Min Jin, Shi-Fei Huang, Hai Huang

“…A predictive model for internal abdominal hernias was constructed based on a machine learning algorithm incorporating 7 different features. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Therefore, CNN is used as the fault prediction also. The model is implemented using Python programming language and demonstrated its effectiveness on test cases. …”
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Empirical Reduced-Order Modeling for Boundary Feedback Flow Control by Seddik M. Djouadi, R. Chris Camphouse, James H. Myatt

“…This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. …”
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GenAI-Based Jamming and Spoofing Attacks on UAVs by Burcu Sonmez Sarikaya, Serif Bahtiyar

“…Creating effective intrusion detection systems against such attacks has been a significant challenge since there is a lack of sufficient attack data that can be used to design an intrusion detection system with advanced computing algorithms. In this research, we propose a novel framework to create attacks data for UAVs by using generative artificial intelligence algorithms. …”
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A clustering fractional-order grey model in short-term electrical load forecasting by Xiang Yu, Lihua Lu, Jianming Qi, Yuchen Qian, Lisen Zhao, Chang Tan, Yangquan Chen, Zhigang Han

“…Hyper parameters of these equations are then sent to a global optimization algorithm to reduce predictive errors. Simulation results on two electricity datasets demonstrated that our algorithm can learn from datasets hyper parameters inside equations and produce forecast values efficiently. …”
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Investigating the Machining Behavior of the Additively Manufactured Polymer-Based Composite Using Adaptive Neuro-Fuzzy Learning by Anastasios Tzotzis, Dumitru Nedelcu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis

“…Multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm 2 (NSGA-II) algorithm was employed to minimize both <i>Ra</i> and <i>T</i> simultaneously. …”
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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

“…Among the tested models, the extra trees (ET) algorithm demonstrated superior performance, achieving an average absolute percent relative error (AAPRE) of approximately 3%, indicating its high reliability for Rs prediction. …”
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Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts by A. V. Nemenko, M. M. Nikitin

“…The paper provides the results of testing the proposed algorithm for predicting the yield of viable products using the proposed method based on interim measurements of defect characteristics during the treatment process. …”
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