Character-word level ensemble integrated model for power transformer defect recording text mining method by LI Yuan, LI Rui, LIN Jinshan, JIN Lingfeng, SHAO Xianjun, ZHANG Guanjun

“…By applying natural language processing technology to precise power equipment defect recoding text classification and efficient fault recognition, data resources are awakened, and the intelligent management level of power transformers is significantly improved.…”
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Imbalanced feature generation based on bootstrap power spectral curve for estimating respiratory rate by Soojeong Lee, Gyanendra Prasad Joshi, Gangseong Lee

“…However, machine learning algorithm-related errors are unsuitable for medical decision-making processes because some data have a much larger sample size in the training set than in other sets. …”
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A Cross-Spatial Differential Localization Network for Remote Sensing Change Captioning by Ruijie Wu, Hao Ye, Xiangying Liu, Zhenzhen Li, Chenhao Sun, Jiajia Wu

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Quenching of the weak axial coupling derived from the scattering of stopped-pion neutrinos on 127I by M. Hellgren, J. Suhonen

“…The need for quenching of the weak axial-vector coupling in calculations involving weak processes in nuclei is a well-known and long-standing problem arising from several contributing factors. …”
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DRKG: Faithful and Interpretable Multi-Hop Knowledge Graph Question Answering via LLM-Guided Reasoning Plans by Yan Chen, Shuai Sun, Xiaochun Hu

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Drying of Nettle Using Concentrated Air Collector and Concentrated Photovoltaic Thermal Supported Drying System and Modeling with Machine Learning by Mehmet Onur Karaagac

“…This study examines the performance of a solar assisted drying system in the nettle drying process. The drying process works by using thermal energy obtained from solar air collectors and PV modules. …”
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Modeling of development trajectories in the multidimensional space: socio-geographic interpretation by Kostyantyn Niemets, Kateryna Sehida, Lyudmyla Niemets, Ievgeniia Telebienіeva, Kateryna Kravchenko

“…Comparison of the real trajectory with the optimal, determining the pro-jection of the vector of development on the optimal trajectory, deviations from the optimal trajectory contain information on the pe-culiarities of the process. …”
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THE COMPLEX TERRITORIAL, SOCIAL AND ECONOMIC SYSTEM EURASEC: EVOLUTIONARY DEVELOPMENT by L. M. Borch, Y. N. Vorobyov, D. D. Burkaltseva, S. V. Gerasimova

“…It is noted that creation of the Eurasian Economic Community (EurAsEC) lays foundations for evolutionary international development which makes it possible to use constructivism in existing financial markets, define a vector of development, change models and control mechanisms with the purpose to increase the impact on macroeconomic processes in the EurAsEC member states. …”
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Recommending Actionable Strategies: A Semantic Approach to Integrating Analytical Frameworks with Decision Heuristics by Renato Ghisellini, Remo Pareschi, Marco Pedroni, Giovanni Battista Raggi

“…The approach employs <b>vector space representations</b> and <b>semantic similarity calculations</b> to map framework parameters to heuristic patterns, supported by a computational architecture that combines deep semantic processing with constrained use of Large Language Models. …”
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Identifying Persons of Interest in Digital Forensics Using NLP-Based AI by Jonathan Adkins, Ali Al Bataineh, Majd Khalaf

“…It also relies on different toolsets and an analyst’s expertise to parse enormous amounts of user-generated data to find clues that help crack a case. This process of investigative analysis is often done manually. …”
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Aspects of Developing A Methodology for Managing Digital Financial Assets by A. Yu. Proskuryakov

“…Problems of modeling processes in economic systems are considered, the problem of optimal control is defined. …”
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Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches by Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen

“…This study aims to solve this problem by creating a detailed process and training models using machine learning, deep learning, and large language models (LLMs). …”
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Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration by Choongseop Lee, Geunbo Yang, Jaewoo Baek, Yuntae Park, Mingyu Cheon, Jongkil Park, Cheolsoo Park

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Low-Complexity Adaptive Chromatic Dispersion Estimation Scheme Using Machine Learning for Coherent Long-Reach Passive Optical Networks by Jin Li, Danshi Wang, Min Zhang

“…In the coherent long-reach passive optical networks (LRPON), it is crucial to propose cost-effective digital signal processing (DSP) technologies to reduce the overall complexity and power consumption. …”
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SpectroFusionNet a CNN approach utilizing spectrogram fusion for electric guitar play recognition by Ganesh Kumar Chellamani, Aishwarya N, Chandhana C, Kanwaljeet Kaur, Rakesh Thoppaen Suresh Babu

“…These spectrograms are then individually processed using lightweight models (MobileNetV2, InceptionV3, ResNet50) to extract discriminative features of different guitar sounds, with ResNet50 yielding better performance. …”
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Machine learning for early detection of plant viruses: Analyzing post-infection electrical signal patterns by Elham Ghasemi, Esmaeil Ebrahimie, Ali Niazi

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Implementation of a Conditional Latent Diffusion-Based Generative Model to Synthetically Create Unlabeled Histopathological Images by Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, Ahmad Kamal Nasution, Muhammad Alqaaf, Md. Altaf-Ul-Amin, Shigehiko Kanaya

“…Initially, these images were embedded into a lower-dimensional latent space using a Vector Quantized Generative Adversarial Network (VQ-GAN). …”
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The Evolution of Machine Learning in Vibration and Acoustics: A Decade of Innovation (2015–2024) by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

“…In the context of these processes, a review of machine learning techniques was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), autoencoders, support vector machines (SVMs), decision trees (DTs), nearest neighbor search (NNS), K-means clustering, and random forests. …”
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Estimation of Polarization and Spatial Parameters of a Radio Source Signal Using Triorthogonal Antenna by G. S. Gribov

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Accurate and Efficient Fluid Flow Regime Classification Using Localized Texture Descriptors and Machine Learning by Manimaran Renganathan, Palani Thanaraj Krishnan, C. Christopher Columbus, T. Sunil Kumar

“…These features are then classified using various machine learning models, namely Random Forest (RF), Support Vector Machines (SVM), and k-Nearest Neighbors (k-NN). …”
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