Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection by S. V. Kochergin, S. V. Artemova, A. A. Bakaev, E. S. Mityakov, Zh. G. Vegera, E. A. Maksimova

“…The obtained research results indicate the advantages of using a combination of machine learning algorithms to ensure the reliable protection of smart networks from cyberattacks taking into account the nature of the electrical load.…”
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Elephant Flows Detection Using Deep Neural Network, Convolutional Neural Network, Long Short-Term Memory, and Autoencoder by Getahun Wassie Geremew, Jianguo Ding

“…Specifically, DNN, CNN, LSTM, and Deep autoencoder are used to build elephant detection models that achieve an average accuracy of 99.12%, 98.17%, and 98.78%, respectively. Deep autoencoder is also one of the promising algorithms that do not require human class labeler. …”
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Decentralized electrochemical biosensors for biomedical applications: From lab to home by Pramod K. Kalambate, Vipin Kumar, Dhanjai

“…Furthermore, the integration of these devices with the Internet-of-Things (IoT), Internet-of-Medical-Things (IoMT), artificial intelligence (AI), and machine learning (ML) algorithms has demonstrated breakthrough technological solutions for healthcare management, disease prognosis, and patient care. …”
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Overcoming the challenges of data integration in ecosystem studies with machine learning workflows: an example from the Santos project by Gustavo Fonseca, Danilo Candido Vieira

“…Furthermore, these workflows lay the foundation for implementing long-term learning algorithms, a pivotal increment for monitoring initiatives. …”
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Hardware-software simulator for modeling indoor temperature and humidity processes by О.M. Yevseienko

“…The results of the simulation of the developed control system in interaction with the prototype stand are also presented. The conclusions confirm that the developed model aims to reduce costs for the development and testing of the control system and has proven its effectiveness. …”
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DEVELOPMENT OF A SOFTWARE MODULE FOR OPERATIONAL DISPATCH CONTROL OF PRODUCTION BASED ON CYBER-PHYSICAL CONTROL SYSTEMS by Igor Nevliudov, Vladyslav Yevsieiev, Nataliia Demska, Sergiy Novoselov

“…Conclusions: the proposed models and methods will not only automate the process of managing the development of CPPS from scratch, but will also make it possible to automate the process of managing the development of the cybernetic component for the modernization and improvement of existing CPPS.…”
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YOLO-GML: An object edge enhancement detection model for UAV aerial images in complex environments. by Zhihao Zheng, Jianguang Zhao, Jingjing Fan

“…Experimental results show that Compared with YOLO11s, YOLO-GML can improve AP50 by 2.3% to 73.6% on the challenging UAV detection dataset HazyDet, achieving a better balance between accuracy and inference efficiency compared to the most advanced detection algorithms. YOLO-GML also showed good performance improvement in the SODA-A and VisDrone-2019 datasets, demonstrating the generalization of the model.…”
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Heterogeneous AI Music Generation Technology Integrating Fine-Grained Control by Hongtao Wang, Li Gong

“…As artificial intelligence algorithms continue to advance, researchers have increasingly harnessed their capabilities to generate music that resonates with human emotions, offering a novel means of alleviating the escalating pressures of contemporary life. …”
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Classification of <i>Verticillium dahliae</i> Vegetative Compatibility Groups (VCGs) with Machine Learning and Hyperspectral Imagery by Sudha GC Upadhaya, Chongyuan Zhang, Sindhuja Sankaran, Timothy Paulitz, David Wheeler

“…Multiple machine learning algorithms, including random forest and artificial neural networks (ANNs), were trained and evaluated on previously unseen isolates. …”
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Monte Carlo approximation of the logarithm of the determinant of large matrices with applications for linear mixed models in quantitative genetics by Matias Bermann, Alejandra Alvarez-Munera, Andres Legarra, Ignacio Aguilar, Ignacy Misztal, Daniela Lourenco

“…We compared the restricted likelihood with (approximated) and without (exact) the approximation of the log-determinant for different values of heritability for a single-trait model. We also compared estimated variance components using exact expectation–maximization (EM) and average information (AI) REML algorithms, against two derivative-free approaches using the restricted likelihood calculated with the log-determinant approximation. …”
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Intelligent UAV health monitoring: Detecting propeller and structural faults with MEMS-based vibration by Temel Sonmezocak

“…For fault detection, the performance of Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Decision Tree (DT), and Neural Network (NN) algorithms was evaluated. The model achieved a maximum accuracy of 99.40 % in detecting the severity of propeller damage. …”
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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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A Comprehensive Review of Blockchain and Machine Learning Integration for Peer-to-Peer Energy Trading in Smart Grids by Sameen Fatima, Muhammad Junaid Arshad

“…This evolution emphasizes decentralization, efficiency, and sustainability in energy systems. However, it also introduces numerous risks, including cyber-physical system vulnerabilities and challenges in energy trading. …”
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Enhancing multivariate post‐processed visibility predictions utilizing Copernicus Atmosphere Monitoring Service forecasts by Mária Lakatos, Sándor Baran

“…Recent studies demonstrated that the application of classification algorithms can successfully improve the skill of such discrete forecasts; however, a frequently emerging issue is that certain spatial and/or temporal dependencies could be lost between marginals. …”
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Structural Magnetic Resonance Imaging Brain Age Investigation in Athletes with Persistent Postconcussion Syndrome by Samuel Guay, Camille Charlebois-Plante, Sophie-Andrée Vinet, Marie-Eve Bourassa, Louis De Beaumont

“…Brain age prediction algorithms using structural magnetic resonance imaging (MRI) estimate the biological age of the brain by comparing it to a normal aging trajectory, allowing for the identification of deviations that may indicate slower or accelerated biological aging. …”
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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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Predicting Kinematic Viscosity and Cetane Number of Diesel- Biodiesel Blend Using Neural Network and Empirical Models by M. yari, Gh. Moradi, M. Abdolmaleki, Sh. Bashiri

“…In this regard, a three-layer feed-forward network with varying input parameters, training algorithms, transfer functions, and hidden neurons has been examined to predict the KV and CN of the diesel-biodiesel blend. …”
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PtWAVE: a high-sensitive deconvolution software of sequencing trace for the detection of large indels in genome editing by Kazuki Nakamae, Saya Ide, Nagaki Ohnuki, Yoshiko Nakagawa, Keisuke Okuhara, Hidemasa Bono

“…Results In this study, we introduced a new software called PtWAVE that can detect a wide range of indel sizes, up to 200 bp. PtWAVE also offers options for variable selection and fitting algorithms to prevent uncertainties in the model. …”
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Methods of early diagnosis and pharmacological prevention of pancreatitis after endoscopic papillosphincterotomy by T. R. Spiridonov, E. D. Novikova, T. O. El'cov

“…Thus, we can conclude that despite the ongoing research and the search for effective algorithms for the prevention and early diagnosis of PEP, their data often contradict each other or simply do not confirm their effectiveness. …”
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Refining Software Clustering: The Impact of Code Co-Changes on Architectural Reconstruction by Adelina Diana Stana, Ioana Sora

“…Version control systems are essential for tracking and managing changes in software code. They also provide information about the relationships between software entities: when multiple entities (e.g., classes or interfaces) are frequently modified together, it may indicate an underlying connection between them. …”
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