Robust fault detection in electrochemical energy storage systems under label noise: applications to lithium-ion batteries and transformer windings by Tao He, Wei Liu, Xin Wu, Yu Wei

“…However, the performance of machine learning-based fault diagnosis models is often degraded in practice due to label noise in training data, caused by sensor inaccuracies, ambiguous fault transitions, and imperfect labeling processes. This paper proposes a lightweight and effective kernel-based data rectification framework to improve the robustness of fault detection under noisy label conditions. …”
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Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

“…This enhanced predictive capability offers potential for optimizing machining processes and reducing material waste in polymer manufacturing.…”
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Theoretical background for the bionic substantiation of parameters of the stubble cultivator working bodies by L. F. Babitsky, I. V. Sobolevsky, V. A. Kuklin

“…Use of the serrated shape of the cutting edge is consistent with the bionic principle of multi-contact exposure and leads to the fact that the tops of the teeth become stress concentrators and, with a significantly smaller indentation force, cause soil destruction processes, which reduces the energy costs of cutting the soil layer. …”
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Machine learning with analysis-of-variance-based method for identifying rice varieties by Nabin Kumar Naik, M. Venkata Subbarao, Prabira Kumar Sethy, Santi Kumari Behera, Gyana Ranjan Panigrahi

“…Implementing this methodology in real-world scenarios could significantly enhance the efficiency and accuracy of the rice variety identification processes, benefiting both producers and consumers.…”
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Effects of Motor Preparation on Walking Ability in Active Ankle Dorsiflexion by Hiroki Ito, Hideaki Yamaguchi, Ryosuke Yamauchi, Ken Kitai, Kazuhei Nishimoto, Takayuki Kodama

“…Conclusions: These findings highlight that the motor preparation processes of the brain during active ankle dorsiflexion are involved in walking ability and can be used to predict it. …”
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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

“…However, if the feature extraction and selection processes are optimized when using ML for WBC classification, its performance is improved. …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

“…This research examined the performance of eleven machine learning models for this purpose: Ridge Regression, Lasso Regression, K-Nearest Neighbors, Gradient Boosting, Support Vector Regression, Multi-Layer Perceptron, XGBoost, CatBoost, LightGBM, Gaussian Processes for Regression(GPR) and Extra Trees Regressor, considering real historical data from Colorado. …”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…To further validate our results, we employ a support vector machine model, utilizing multiscale entropy values as feature inputs. …”
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Identification of potential shared core biomarkers in type 2 diabetes and sarcopenia by Ping Zhang, Yijun Du, Xing Zhong, Yue Wang, Tianrong Pan

“…Key modules in each condition highlighted 30 shared genes, which were enriched in biological processes and pathways related to metabolic and immune functions. …”
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The Institution of Mediation in the Legislation of the Republic of Kazakhstan: Prospects for Regional Adaptation by N. S. Chimarov, S. Yu. Chimarov

“…The involvement of the state in international processes, as well as the desire to adapt a greater number of “conciliation” procedures, lead to a unique context in which mediation has its own special conceptual and functional features, but is also limited by the existence of other forms of alternative dispute resolution. …”
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Advances in machine learning for the detection and characterization of microplastics in the environment by M. Maksuda Khanam, M. Khabir Uddin, Julhash U. Kazi

“…Recent advances in machine learning (ML) have revolutionized the field of microplastic research by automating and enhancing detection processes. In particular, algorithms such as support vector machines, random forests, and convolutional neural networks have demonstrated considerable success in classifying microplastics based on chemical signatures and visual characteristics. …”
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Development of Fast Analytical Method for the Detection and Quantification of Honey Adulteration Using Vibrational Spectroscopy and Chemometrics Tools by Omar Elhamdaoui, Aimen El Orche, Amine Cheikh, Brahim Mojemmi, Rachid Nejjari, Mustapha Bouatia

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Algoritmo robusto para el diagnóstico de fallas eléctricas en el motor de inducción trifásico basado en herramientas espectrales y ondeletas. by Francisco Javier Villalobos-Piña, Ricardo Alvarez-Salas

“…The main objective of the work is to perform a non invasive electric fault diagnosis to avoid economical losses in the industrial process using the advantages of spectral and wavelet tools. …”
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Filtering and Overlapping Data for Accuracy Enhancement of Doppler-Based Location Method by Rafał Szczepanik, Jan M. Kelner

“…This paper proposes enhancements to the SDF method through advanced signal processing techniques, including dedicated filtering and a novel two-level overlapping approach, which significantly improve localization accuracy. …”
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TECHNIQUE OF VIBRATION MONITORING by B. A. Chichkov

“…Particularly, the simultaneous three-axial estimation of vibration acceleration and a vibration vector with the graphic and character data presentation in real-time mode and more archiving and operative data processing opportunities, is executed.…”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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Operator Integrated – Concept for Manufacturing Intelligence by Konrad Wegener, Sascha Weikert, Joseph Mayr, Markus Maier, Vahid Ostad Ali Akbari, Martin Postel

“…It is necessary to point out, that not only intelligent mastering of process and machine becomes more and more important but communications among machine tools enabling process chain overarching intelligent approaches and creating intelligent factories.…”
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A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware by Fandi Kurniawan, Deris Stiawan, Darius Antoni, Mohd Yazid Idris, Rahmat Budiarto

“…The dataset used consists of 2,084 Android applications, including 1,314 malware samples and 770 benign applications, obtained through a reverse engineering process. Data pre-processing, feature extraction, and training using supervised learning are carried out to optimize detection accuracy. …”
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MAPPING OF AREAS OF MODEL SPECIES OF ANIMAL POPULATION OF THE REPUBLIC OF DAGESTAN by Asiyat M. Mukhtarova, Vitalij V. Bratkov, Nailya M. Biktimirova, Gulnara M. Mukhtarova, Patimat A. Bekshokova, Gyulnara M. Nakhibasheva

“…Processing of the materials and creation of maps were carried out using such software platforms as ArcGIS, MapInfo and Adobe Illustrator CC. …”
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Evaluation of an interferon-gamma release assay for early detection of lumpy skin disease virus infection and vaccination in cattle by Nina Kresic, Wannes Philips, Andy Haegeman, Nick de Regge

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