Methodology for extracting narratives from social media big data by E. Yu. Petrov, A. Yu. Sarkisova, D. O. Dunaeva, A. S. Voronov, M. G. Myagkov

“…The calculation of the measure of proximity of keywords using the Python, partial manual markup and data validation were also carried out.Results: 4.5 million messages relevant to the topic of COVID-19 vaccination published in VKontakte from 01.01.2020 to 01.03.2023 were reduced to 237 stable narratives. …”
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When Two are Better Than One: Synthesizing Heavily Unbalanced Data by Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes

“…Fraud Detection systems are examples of such systems where Machine Learning algorithms leverage information to classify financial transactions as legitimate or illicit. …”
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Challenges of Water Resources Governance under the Impact of Climate Change and Water Transfer by Atabak Jaffari, Ahmad Sharafati, Amin reza Neshat, Seyed abbas Hosseini

“…Method: In this study, considering the integrated exploitation of surface and groundwater resources in the Qazvin study area and the use of transferred water from Taleghan Dam, the inflow to this dam and the status of the aquifer under climate change conditions were simulated using two optimization algorithms, the Fire Falcon and the Emperor Penguin, using the LSTM model. …”
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Factors affecting frequency discrimination of vibrotactile stimuli: implications for cortical encoding. by Justin A Harris, Ehsan Arabzadeh, Adrienne L Fairhall, Claire Benito, Mathew E Diamond

“…<h4>Background</h4>Measuring perceptual judgments about stimuli while manipulating their physical characteristics can uncover the neural algorithms underlying sensory processing. We carried out psychophysical experiments to examine how humans discriminate vibrotactile stimuli.…”
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Artificial intelligence in environmental monitoring: in-depth analysis by Emran Alotaibi, Nadia Nassif

“…In-depth analysis reveals advancements in AI/ML methodologies, including novel algorithms for soil mapping, land-cover classification, flood susceptibility modeling, and remote sensing image analysis. …”
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Dynamic Processes of Development Jointing of a Fractal Type: Models for a Solid-State Material of the Chamber in a Power Facility during its Operation by T. V. Ryzhova, D. N. Bukharov, M. M. Arakelyan, S. M. Arakelyan

“…Although the analysis carried out is a model in the general formulation with known representation algorithms, nevertheless it is based on relevant physical principles and has obvious practical significance in terms of determining trends and directions for assessing the reliability and durability of such installations. …”
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Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction by Omar Abdullatif Jassim, Mohammed Jawad Abed, Zenah Hadi Saied Saied

“…Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. …”
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Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression by Saad Alanazi, Rayan Alanazi

“…This paper presents a comprehensive solution for DR identification utilizing deep learning algorithms. To reduce class imbalance and strengthen this model, we first prepare unbalanced data utilizing the Synthetic Minority Oversampling Technique (SMOTE). …”
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FLORA: a novel method to predict protein function from structure in diverse superfamilies. by Oliver C Redfern, Benoît H Dessailly, Timothy J Dallman, Ian Sillitoe, Christine A Orengo

“…The majority of prediction algorithms employ local templates built on known or predicted functional residues. …”
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Issues, Challenges, and Solution Options for On-Grid Multi-Microgrid Game Theory: A Systematic Review by Dimas Jalaluddin Ahmad, Nanang Hariyanto, Umar Khayam

“…Research and future works recommendation related with on-grid MMG game theory subject is also described.…”
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Joint User Association and Resource Allocation for Hierarchical Federated Learning Based on Games in Satisfaction Form by Panagiotis Charatsaris, Maria Diamanti, Symeon Papavassiliou

“…Algorithms based on Reinforcement Learning (RL) and Best Response Dynamics (BRD) are, then, devised to conclude the SE and MESE points. …”
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Raising Awareness of Acute Kidney Injury: Unfolding the Truth by Aida Lydia

“…AKI is now considered as a common complication of COVID-19 and it is also associated with adverse outcomes, including development or worsening of comorbidities, yet little is known about the pathogenesis or optimal management of COVID-19-associated AKI. …”
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Investigating Trends and Costs Associated with Designing Concrete Mixes Using Different Methods by Computer Programs by Mohammed Abdul Qader, Ahmed Ibrahim, Al-Badr Alaidaros, Abdul Kareem Abdulkareem, Abdullah Alwuayl, Abdullah Alsaluli, Mamdooh Alwetaishi, Mishal Alsehli, Saleh Alghamdi

“…Hence, in this work, algorithms were developed and implemented for six mix design methods, which replaced the time-consuming hand calculations with error-free and fast ones, in a user-friendly fashion. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
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Critical considerations and computational tools in plant genome editing by Dipnarayan Saha, Alok Kumar Panda, Subhojit Datta

“…Computational tools and algorithms play a crucial role in construct design and gRNA selection to minimize off-target effects and also to optimize their delivery techniques. …”
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High-throughput image-based monitoring of cell aggregation and microspheroid formation. by Thomas Deckers, Toon Lambrechts, Stefano Viazzi, Gabriella Nilsson Hall, Ioannis Papantoniou, Veerle Bloemen, Jean-Marie Aerts

“…As opposed to existing algorithms, our methodology was not only able to automatically monitor compact spheroids but also the aggregation process of individual spheroids, and this in an accurate and high-throughput manner. …”
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Low-Complexity Adaptive Chromatic Dispersion Estimation Scheme Using Machine Learning for Coherent Long-Reach Passive Optical Networks by Jin Li, Danshi Wang, Min Zhang

“…To add comparisons, the performances of CD estimation schemes using other two well-known machine learning algorithms including the k-nearest neighbor (KNN) and the decision tree (DT) have also been investigated. …”
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Enhancing Efficiency and Security in MTC Environments: A Novel Strategy for Dynamic Grouping and Streamlined Management by Maloth Bhavsingh, K Samunnisa, A Mallareddy

“…It also introduces adaptive network management strategies to customize performance according to the needs of MTC networks. …”
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Hindcasting Maximum Water Depths in Coastal Watersheds: The Importance of Incorporating Off‐Channel Data and Their Uncertainties in Machine Learning Models by Maryam Pakdehi, Ebrahim Ahmadisharaf

“…This approach can be efficient for physics‐based models, which incorporate the underlying physical processes, but the efficiency for data‐driven models like machine learning (ML) algorithms is unclear. The existing off‐channel observations like high‐water marks (HWMs) are also subject to uncertainty. …”
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Artificial Intelligence in Digital Marketing: Towards an Analytical Framework for Revealing and Mitigating Bias by Catherine Reed, Martin Wynn, Robin Bown

“…Traditional AI centres on supervised learning algorithms to support and enable the application of data rules, predictive functionality and other AI-based features. …”
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