Distributed semi-supervised partial multi-dimensional learning via subspace learning by Zhen Xu, Weibin Chen

“…Nowadays, however, the training data are typically distributed at multiple nodes within a network, making it challenging to transmit them to a fusion center for further processing. To address these issues, in this paper, we propose a novel algorithm called distributed semi-supervised partial multi-dimensional learning (dS $$^2$$ 2 PMDL), which is designed to handle distributed classification of a small proportion of partially multi-dimensional (PMD) data and a large proportion of unlabeled data across a network. …”
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Limits of competence of a forensic commodity expert in determining the characteristics of goods in cases of customs rules violation by S. О. Diachuk

“…Today, all goods, regardless of the country of origin, are subject to classification, that is, codes are determined for goods in accordance with the classification groupings specified in the UCC of the Economic and Monetary Union. …”
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Towards Greater Standardisation in Benthic Trait Research to Support Application to Environmental Management by Irene Susini, Heidi M. Tillin, Louise Anderson, Craig M. Robertson, Sian Rees, Kerry L. Howell

“…Secondly, three distinct trait classification frameworks are identified, of which one presents considerable internal variation; within‐framework trait classification also emerges as inconsistent. …”
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Transfer learning based hybrid feature learning framework for enhanced skin cancer diagnosis using deep feature integration by Maridu Bhargavi, Sivadi Balakrishna

“…Among the primary challenges in automated skin cancer classification are addressing differences in lesion appearance, occlusions, and data class imbalance that impact model performance and reliability. …”
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Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction by Svetlana Illarionova, Dmitrii Shadrin, Fedor Gubanov, Mikhail Shutov, Usman Tasuev, Ksenia Evteeva, Maksim Mironenko, Evgeny Burnaev

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Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals by Wenhan Zhang, Marwan Krunz, Gregory Ditzler

“…Machine learning (ML) has been successfully applied to classification tasks in many domains, including computer vision, cybersecurity, and communications. …”
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LONG-CHAIN POLYUNSATURATED ω-3 AND ω-6 FATTY ACIDS AS ESSENTIAL NUTRIENTS IN DIFFERENT PERIODS OF CHILDHOOD by S. G. Makarova, E. A. Vishneva

“…The authors present modern data on the issue of rational nutrition of children in different periods of childhood. …”
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Effect of Imputation Methods in the Classifier Performance by Pinar Cihan, Oya Kalıpsız, Erhan Gökçe

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Leveraging Machine Learning for Enhanced Bug Triaging in Open-Source Software Projects by Nitanta Adhikari, Rabindra Bista, Joao Carlos Ferreira

“…Bug triaging–the process of classifying and assigning software issues to appropriate developers–is a critical yet challenging task in large-scale software development. …”
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The importance of improving the legal regulation of animal treatment in terms of preventing cruelty by V. S. Seliukov

“…The issue of defining the concept of fauna in modern Ukraine is rather limited and does not correspond to the concept of modern interaction between humans and animals in many areas of public life. …”
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Mechanical safety assessment method for transmission towers based on improved reliability theory by Zhengdao Zhou, Linfeng Zhang, Zhiyu Shang, Wang Zhang, Qianwen Wang, Zhengfa Li

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Method for recycling waste generated in the production of fiberglass-reinforced plastic by Evgeniy G. Fedarovich, Alexander E. Levdanski, Anastasiya A. Kovaleva

“…A significant associated with large-scale production and application of these materials is the inevitable generation of waste, exerting a negative environmental impact. To address this issue, mechanical recycling of fiberglass waste is proposed, involving selective grinding in an impact-centrifugal mill followed by mechanical classification of the ground products. …”
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Grid structure optimization using slow coherency theory and holomorphic embedding method by Fei Tang, Mo Chen, Yuhan Guo, Jinzhou Sun, Xiaoqing Wei, Jiaquan Yang, Xuehao He

“…This paper addresses the issue of complex fault oscillation modes and weak voltage points in large power systems by proposing a network structure optimization method that balances system synchrony and node voltage stability. …”
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Speech Emotion Recognition Using Transfer Learning: Integration of Advanced Speaker Embeddings and Image Recognition Models by Maros Jakubec, Eva Lieskovska, Roman Jarina, Michal Spisiak, Peter Kasak

“…Transfer learning is a machine learning technique that helps address this issue by utilizing knowledge from pre-trained models to improve performance on a new task in a target domain, even with limited data. …”
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<italic>DiverseNet:</italic> Decision Diversified Semi-Supervised Semantic Segmentation Networks for Remote Sensing Imagery by Wanli Ma, Oktay Karakus, Paul L. Rosin

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Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning by Aristotelis Ballas, Vasileios Papapanagiotou, Christos Diou

“…Self-Supervised Learning (SSL), particularly contrastive learning, has shown promise in mitigating the issue of data scarcity by leveraging unlabeled data to enhance model robustness and effectiveness. …”
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Cross-scale observation of riparian vegetation: Testing the potential of satellite-UAV-Field integrated observations for large-scale herbaceous species by Weiwei Jiang, Chenyu Li, Henglin Xiao

“…This framework employs Support Vector Machine (SVM) technology to eliminate non-vegetation interferences, adopts object-based rather than traditional pixel-based units for supervised classification, and incorporates rich spatial information beyond spectral data, significantly enhancing the accuracy of dominant species identification with F1 scores improved by 10 % to 50 %. …”
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Classification of Apples (<i>Malus × domestica</i> <span style="font-variant: small-caps">borkh.</span>) According to Geographical Origin, Variety and Production Method Using Liqui... by Jule Hansen, Iris Fransson, Robbin Schrieck, Christof Kunert, Stephan Seifert

“…Since the classification models largely use different parts of the data, which is shown by variable selection, this method is very well suited to answer different authentication issues with one analytical approach.…”
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Checking the stability of correlation of chronologies over time: an example on Pinus pinea L. rings widths by Sergio Camiz, Francesco Spada

“…An exploratory study concerning the variation over time of multidimensional time series allows to check to what extent factors and dendrograms issued by ordination and classification methods, keep stable over time or change – even dramatically. …”
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LUCID: A Framework for Reducing False Positives and Inconsistencies Among Container Scanning Tools by Md Sadun Haq, Ali Saman Tosun, Turgay Korkmaz

“…To address the security issues, scanning tools that scan containers for preexisting vulnerabilities have been developed, but they suffer from false positives. …”
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