Was Copernicus an Astrologer? by George Borski, Ivan Kolkov

“…However, apparently it was not rectified by the algorithms most popular at the time. The findings suggest the number-symbolic rather than astrological inclinations of Copernicus. …”
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Advances in the application of human-machine collaboration in healthcare: insights from China by Wuzhen Wang, Liangji Liu

“…“Human–machine collaboration” is based on an intelligent algorithmic system that utilizes the complementary strengths of humans and machines for data exchange, task allocation, decision making and collaborative work to provide more decision support. …”
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RETRACTED ARTICLE: Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnosti... by Zhang Zhang, Fangfang Chen, Xiaoxiao Deng

“…Furthermore, using machine learning algorithms, we constructed a clinical prognostic model and validated and optimized it via extensive clinical data. …”
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Advancing Hydrogel-Based 3D Cell Culture Systems: Histological Image Analysis and AI-Driven Filament Characterization by Lucio Assis Araujo Neto, Alessandra Maia Freire, Luciano Paulino Silva

“…<b>Background:</b> Machine learning is used to analyze images by training algorithms on data to recognize patterns and identify objects, with applications in various fields, such as medicine, security, and automation. …”
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An Enhanced Drone Technology for Detecting the Human Object in the Dense Areas Using a Deep Learning Model by Mohamad Reda A. Refaai, Dhruva R. Rinku, I. Thamarai, null S. Meera, Naresh Kumar Sripada, Simon Yishak

“…This study focused on detecting wildfires at the beginning stages in forest and wilderness areas, utilizing deep learning-based computer vision algorithms that control and then mitigate massive damages to human life and forest management.…”
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Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks by Tauqeer Safdar Malik, Mohd Hilmi Hasan

“…The channel selection is performed on the basis of reinforcement learning algorithms such as No-External Regret Learning, Q-Learning, and Learning Automata. …”
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Typical investigative situations in the initial phase of a war-related sexual violence investigation by O. O. Naumkin

“…A number of tasks that need to be solved by the pre-trial investigation body in order to obtain sufficient grounds for making a reasonable procedural decision determining the proper limits of the investigation have been identified. Algorithms of corresponding actions have been developed, which are reflected in a procedural form through the prism of the intellectual activity of an official, in particular, an inspection of the scene of the incident, questioning of the victim or witnesses, taking biological samples of a person, appointing forensic experts, taking measures to ensure criminal proceedings in the form of temporary access to things and documents for the purpose of extracting photo or video material in digital form, using OSINT technologies to identify the rapist through social networks Instagram, Facebook, VK, etc., conducting covert investigative (search) actions and operational-search activities in order to establish the location the suspect, etc.…”
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Modern air defense methods and countermeasures for use in operational-tactical missiles by Mykola Bondarenko, Mykhailo Vorobei

“…This article delves into the multifaceted realm of missile defense, scrutinizing a spectrum of methodologies from conventional anti-aircraft systems to cutting-edge artificial intelligence algorithms. The primary objective is to explore existing methodologies aimed at protecting military assets and countering high-precision weaponry. …”
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Role of PPARs in Progression of Anxiety: Literature Analysis and Signaling Pathways Reconstruction by Olga I. Rudko, Artemii V. Tretiakov, Elena A. Naumova, Eugene A. Klimov

“…Signal pathways were created according to previously developed algorithms. SNEA was performed in Pathway Studio. Current study revealed 14 PPAR-regulated proteins linked to anxiety. …”
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Optimization of joint strength in friction stir welded wood plastic composites using ANFIS and Cheetah Optimizer by Ammar H. Elsheikh, Mohamad Elmiligy, Ahmed M. El-Kassas

“…Three machine learning algorithms—multilayer perceptron (MLP), decision tree (DT), and adaptive neuro-fuzzy inference system (ANFIS)—were used to model the relationships between the input parameters and output responses. …”
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English Teaching Achievement Prediction by Big Data Analysis under Deep Intervention by Junfang Guo

“…First, data analysis methods and decision tree algorithms are analyzed. Second, in data mining technology, the C4.5 decision tree method is used to construct an English score prediction model. …”
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An Incremental Learning Ensemble Strategy for Industrial Process Soft Sensors by Huixin Tian, Minwei Shuai, Kun Li, Xiao Peng

“…The ability to handle large amounts of data incrementally and efficiently is indispensable for modern machine learning (ML) algorithms. According to the characteristics of industrial production process, we address an ILES (incremental learning ensemble strategy) that incorporates incremental learning to extract information efficiently from constantly incoming data. …”
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Considerations in the search for epistasis by Marleen Balvert, Johnathan Cooper-Knock, Julian Stamp, Ross P. Byrne, Soufiane Mourragui, Juami van Gils, Stefania Benonisdottir, Johannes Schlüter, Kevin Kenna, Sanne Abeln, Alfredo Iacoangeli, Joséphine T. Daub, Brian L. Browning, Gizem Taş, Jiajing Hu, Yan Wang, Elham Alhathli, Calum Harvey, Luna Pianesi, Sara C. Schulte, Jorge González-Domínguez, Erik Garrisson, Lorentz workshop on epistasis, Michael P. Snyder, Alexander Schönhuth, Letitia M. F. Sng, Natalie A. Twine

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A COMPARATIVE STUDY OF HEADWAY-BASED AND TRANSPORT SYSTEM-BASED ASSIGNMENTS OF PUBLIC TRANSPORT IN VISUM: THE CITY OF KRYVYI RIH CASE by Volodymyr SISTUK

“…This paper introduces a thorough comparison of algorithms involved in public transport assignment processes, using the transport model of the city of Kryvyi Rih in Ukraine. …”
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ON THE SIMULATION OF MODES ОF ELECTRIC POWER SYSTEMS WITH FACTS by E. D. Halilov

“…In regard with the introduction of FACTS devices in power systems, there is an arising need to develop appropriate algorithms and implement them in the form of software for analyzing and controlling the established modes of power systems. …”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. Distinct AU patterns were found for all five phases, with gradient boosting machine and random forest models achieving the highest predictive accuracy. …”
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Mapping urban green structures using object-based analysis of satellite imagery: A review by Shivesh Kishore Karan, Bjørn Tobias Borchsenius, Misganu Debella-Gilo, Jonathan Rizzi

“…Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. …”
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Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach by Sajadul Hassan Kumhar, Prabhakara Rao Kapula, Harveen Kaur, Radeep R. Krishna, Mudasir M Kirmani, Vijay Anant Athavale, Mohd Wazih Ahmad

“…Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. …”
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Impact and optimization of vehicle charging scheduling on regional clean energy power supply network management by Penghui Xu, Xiaobo Wang, Zhichao Li

“…The comprehensive model integrates electric vehicle charging stations, distributed photovoltaic power generation systems, wind farms, and battery energy storage devices and enables the charging process to be accurately controlled with real-time monitoring and intelligent algorithms. In particular, the demand forecasting model based on machine learning effectively solves the dilemma of matching the charging load with a clean energy supply. …”
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More Benefits of Adding Sparse Random Links to Wireless Networks: Yet Another Case for Hybrid Networks by Gunes Ercal

“…Further, we theoretically demonstrate that as long as k is polylogarithmic in the network size, G 1 has rapidly mixing random walks with high probability, which also exponentially improves upon the mixing time of the purely wireless random geometric graph, which yields direct improvement to the performance of distributed gossip algorithms as well as normalized edge connectivity. …”
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