RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review by Md Nasim Reza, Kyu-Ho Lee, Eliezel Habineza, Samsuzzaman, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…Machine vision and image processing algorithms enable for the real-time detection of subtle changes in pig appearance and behavior that may signify potential health issues. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…By extracting novel characteristics from diverse medical data sources, advanced identification techniques known as multimodal learning may be applied, enabling algorithms to analyze data from various sources and eliminating the need to train each modality. …”
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Investigating Performance of an Embedded Machine Learning Solution for Classifying Postural Behaviors by Bruno Andò, Salvatore Baglio, Mattia Manenti, Valeria Finocchiaro, Vincenzo Marletta, Sreeraman Rajan, Ebrahim Ali Nehary, Valeria Dibilio, Mario Zappia, Giovanni Mostile

“…Postural instability is one of the main critical aspects to be monitored in the case of degenerative diseases, and is also a predictor of potential falls. …”
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Design of Onboard Real-Time Networks Based on SDN Technology by Vasily V. Balashov, Valery A. Kostenko, Tatiana I. Ermakova

“…An important direction for future work is development of algorithms for dynamic creation of virtual link routes in course of OEC reconfiguration. …”
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Integrated production-distribution planning optimization models: A review in collaborative networks context by Beatriz Andres, Raquel Sanchis, Jaques Lamothe, Leila Saari, Frederic Hauser

“…In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. …”
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ON THE QUESTION OF MASS-ENERGY CHARACTERISTICS OF VARIOUS AVIATION SOURCES OF ELECTRICITY by A. V. Kechin

“…The main work done abroad and on the territory of the Russian Federation aimed at solving this problem are analyzed. …”
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Multi-Objective Optimization of Independent Automotive Suspension by AI and Quantum Approaches: A Systematic Review by Muhammad Waqas Arshad, Stefano Lodi, David Q. Liu

“…The optimization of independent automotive suspension systems, which is one of the main pillars of the vehicle performance and comfort, is currently going through a revolutionary change due to the development of artificial intelligence and quantum computing. …”
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Scientific Workflow-Based Synthesis of Optimal Microgrid Configurations by Olga Edeleva, Alexei Edelev, Mikhail Voskoboinikov, Alexander Feoktistov

“…They provide a higher level of energy supply compared to the main grids and enhance their reliability and resilience. …”
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Developing a Predictive Model for Stroke Disease Detection Using a Scalable Machine Learning Approach by Assefa Senbato Genale, Tsion Ayalew Dessalegn

“…It was also shown that the main risk factor for stroke disease is diabetes, which is followed by hypertension. …”
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On First-Principle Robot Building in Undergraduate Robotics Education in the Robotic System Levels Model by Bryan Van Scoy, Peter Jamieson, Veena Chidurala

“…However, robotics is inherently multi-disciplinary and requires knowledge of controls and automation, embedded systems, sensors, signal processing, algorithms, and artificial intelligence. This makes training the future robotics workforce a challenge. …”
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Diagnostic efficacy of serological and epigenetic methods of screening diagnostics of colorectal cancer by O. I. Kit, D. V. Burtsev, A. Yu. Maksimov

“…Development of adequate screening and diagnostic algorithms on colorectal cancer detection.Material and methods. …”
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Review on the Application of Remote Sensing Data and Machine Learning to the Estimation of Anthropogenic Heat Emissions by Lingyun Feng, Danyang Ma, Min Xie, Mengzhu Xi

“…This paper reviews the main approaches for estimating anthropogenic heat emissions. …”
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A hybrid extraction model for semantic knowledge discovery of water conservancy big data by Yanna Feng, Feng Zhang, Yongheng Zhang, Jiangang Dong, PengJu Wang

“…To address the growing demand for efficient public opinion analysis in water conservancy and related domains, as well as the inefficiencies and limited scalability of existing automated web data extraction algorithms for multi-source datasets, this research integrates advanced technologies including big data analytics, natural language processing, and deep learning. …”
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Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek by Kosmas Kosmidis, Vassiliki Apostolouda, Anthi Revithiadou

“…Traditional approaches modify existing words, risking unintended recognition. Modern algorithmic methods use high-frequency <i>n</i>-grams or syllable deconstruction but often require specialized expertise. …”
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Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods by Zhishui You, Yuzhu Guo, Xiulei Zhang, Yifan Zhao

“…However, despite the significant strides made, the paucity of EEG data has emerged as the main bottleneck, preventing generalization of decoding algorithms. …”
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Modern Methods for Diagnosing Faults in Rotor Systems: A Comprehensive Review and Prospects for AI-Based Expert Systems by Oleksandr Roshchupkin, Ivan Pavlenko

“…Some techniques like the vibration signal analysis method, spectral analysis, thermography, ultrasound diagnosis, and machine learning algorithms for predicting failure are of particular interest among them. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…Seven methods are considered for evaluation: two in the time domain, two in the frequency domain and three in the time–frequency domain. The main problem is to extract and select the right features to use in the classification stage. …”
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A Literature Review on Security in the Internet of Things: Identifying and Analysing Critical Categories by Hannelore Sebestyen, Daniela Elena Popescu, Rodica Doina Zmaranda

“…From leveraging machine learning and blockchain for anomaly detection and real-time threat response to optimising lightweight algorithms for resource-limited devices, researchers propose innovative and adaptive solutions to address emerging threats. …”
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Spectral Method of Measuring of Changes in Time Intervals between Periodic Pulse Sequences by A. A. Sheinikov, A. V. Isaev, V. V. Zelenko, Yu. V. Sukhodolov

“…Methods of measuring delay time between periodic sequences of pulses are mostly based on the considered parameter direct measurement. The main disadvantage of this approach is the difficulty of ensuring the measurements accuracy in the noise conditions. …”
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Automatic Fault Classification in Photovoltaic Modules Using Denoising Diffusion Probabilistic Model, Generative Adversarial Networks, and Convolutional Neural Networks by Carlos Roberto da Silveira Junior, Carlos Eduardo Rocha Sousa, Ricardo Henrique Fonseca Alves

“…Deep convolutional neural networks (CNNs) are machine learning algorithms that perform tasks involving images, such as image classification and object recognition. …”
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