MANAGING THE DEVELOPMENT OF AGRO-INDUSTRIAL CLUSTERS by D. V. Zavyalov, O. V. Saginova, N. B. Zavyalova

“…Among them the main are: lack of relevant strategy of agrarian and industrial complex, imperfection of methodology of formation of clusters and lack of motives of consolidation of subjects of small and medium business in this sphere; backwardness of production, logistic and innovative infrastructure; and also the low level of commercialization of scientific research in the agro-industrial sector. As one of the measures capable to refract a similar negative situation, development of the concept of management of agro-industrial clusters formed on the basis of an information system of "a digital cluster" which includes algorithms and methods of optimization of information, material and financial flows for achievement of desirable indicators of economic activity by all participants of cluster structure is recommended. …”
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Certainty of Linear Interrelation of Technical and Economic Parameters of Power Units of 300 МWt Thermal Power Stations by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, A. A. Rustamova

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Genetic association between celiac disease and chronic kidney disease: a two-sample Mendelian randomization study by Zhimin Chen, Zigui Zheng, Bingjing Jiang, Yanfang Xu

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Modeling the variables that influence substance consumption of people who experience homelessness in Colombia by Leandro González Támara, Sandra Patricia Barragán Moreno

“…By identifying age and homelessness duration as critical factors, the research contributes actionable knowledge for the development of evidence-based public policies. …”
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DATA MINING IN RELATIONAL SYSTEMS by Valentin Filatov, Valerii Semenets, Oleg Zolotukhin

“…The subject of the research is methods of relational database mining. …”
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Quantum-enabled topological optimization of distributed energy storage for resilient black-start operations by Yinchi Shao, Yu Gong, Xiaoyu Wan, Xianmiao Huang, Shanna Luo, Yuntao Cao, Tao Zhang

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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure by Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

“… Spatial epidemiology, defined as the study of spatial patterns in disease burdens or health outcomes, aims to estimate disease risk or incidence by identifying geographical risk factors and populations at risk (Morrison et al., 2024). Research in spatial epidemiology relies on both conventional approaches and Machine- Learning (ML) algorithms to explore geographic patterns of diseases and identify influential factors (Pfeiffer & Stevens, 2015). …”
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Wellcounter: Automated high‐throughput phenotyping for aquatic microinvertebrates by Claus‐Peter Stelzer, Dominique Groffman

“…Abstract Using phenotypic information extracted from digital images through automated computer vision analysis has become a promising avenue in ecological and evolutionary research. However, acquiring large quantities of high‐quality image data and processing them efficiently often remain a bottleneck. …”
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A Dataset of Real and Synthetic Speech in Ukrainian by Khrystyna Lipianina-Honcharenko, Hennadii Bohuta, Adam Ivaniush, Mariana Soia

“…Abstract This work is dedicated to the analysis and evaluation of the DRSSU dataset: A Dataset of Real and Synthetic Speech in Ukrainian, created to support research in the field of natural language processing and speech recognition. …”
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Enhancing Missing Data Imputation for Migrants Data: A Neutrosophic Set-Based Machine Learning Approach by Doaa A. Abdo, A. A. Salama, Alaa A. Abdelmegaly, Hanan Khadari Mahdi Mahmoud

“…These sets, which can represent uncertainty and ambiguity, are well-suited for managing the complex nature of missing information in sensitive fields like migration research. We test the effectiveness of KNN, SVM, decision tree, random forest, and Ada Boost algorithms on a migrant dataset, comparing their results using different imputation methods (mean/mode, model-based imputer (simple tree), and random values). …”
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Ein Bild sagt mehr als 1000 Worte? Visualisierungen in den Digital Humanities. by Gary S. Schaal, Kelly Lancaster

“…Digital Humanities is still lacking both an epistemological basis and a best practice for an (hermeneutic) interpretation of visualizations generated by algorithms. This paper will address precisely this research gap in raising the question whether, and to what extent, approaches to the hermeneutic interpretation of computer-generated visualizations in the natural sciences can be applied to analyses in the Digital Humanities. …”
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Current trends of international financial organizations during a large-scale war in Europe. New international security policies in the European Union by Paulina Kolisnichenko

“… Through a documentary research design, supported by open-ended interviews with two security and defense specialists, and within the theoretical framework of critical geopolitics and political economy, the objective of the research is to interpret (hermeneutically) the narratives and contexts that shape the new security policies in the European Union, in order to determine the meaning and scope of the current trends of its financial organizations during a large-scale war in Europe. …”
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Deep Learning Based on Facial Expression Recognition from Images to Videos by Deng Rui

“…The paper concludes with a summary of the latest advancements in the field of facial expression recognition and proposes potential directions for future research.…”
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Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry by Bowen Cai

“…Henceforth, there is a need to carry out a research of new energy. Soon, new energy vehicles will be the mainstream trend, which can not only reduce the burden of consumers due to rising fuel prices but also solve the air pollution problem caused by the exhaust emissions of fuel vehicles. …”
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Bibliometry of slow tourism through the software lens of VOSviewer and MS Excel by Ngoc Thu Vu, Hong Long Pham, Samuel Tietse

“…Future research could cross-reference multiple sources and methods to refine these initial findings.…”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

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Recent advances in machine learning applications for MXene materials: Design, synthesis, characterization, and commercialization for energy and environmental applications by Sodiq Abiodun Kareem, Makinde Akindeji Ibrahim, Justus Uchenna Anaele, Olajesu Favor Olanrewaju, Emmanuel Omosegunfunmi Aikulola, Michael Oluwatosin Bodunrin

“…Techniques such as genetic algorithms, evolutionary algorithms, and Bayesian optimization accelerate the discovery of novel MXene phases tailored for specific uses. …”
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Optimizing Inotropic Infusion With Cluster Specific AI Decision Models and Digital Twins by Vidya S Nair, G. D. Heshan Niranga, Aryalakshmi C.S, Dipu T. Sathyapalan, Thushara Madathil, Rahul Krishnan Pathinarupothi

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Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a “seek out” machine learning approach by Marianna Rania, Anna Procopio, Paolo Zaffino, Elvira Anna Carbone, Teresa Vanessa Fiorentino, Francesco Andreozzi, Cristina Segura-Garcia, Carlo Cosentino, Franco Arturi

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IoT BotScan: Ultra-Lightweight AI Defense Against Botnet Threats by Sapna Sadhwani, Urvi Kavan Modi, Raja Muthalagu, Pranav M. Pawar, Alavikunhu Panthakkan, Wathiq Mansoor

“…This research study examines the effectiveness of Deep Learning (DL) and Machine Learning (ML) algorithms in identifying BotNet attacks within network infrastructures. …”
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