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

Get full text

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. …”
Get full text

<italic>DiverseNet:</italic> Decision Diversified Semi-Supervised Semantic Segmentation Networks for Remote Sensing Imagery by Wanli Ma, Oktay Karakus, Paul L. Rosin

Get full text

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 %. …”
Get full text

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. …”
Get full text

A cross-sectional study on the correlation between exercise frequency and mental health among university students based on international physical activity questionnaire-short form... by Xingbin Du, Xingbin Du, Fugao Jiang, Shuping Yuan, Shuping Yuan

Get full text

Identifying Human Factor Causes of Remotely Piloted Aircraft System Safety Occurrences in Australia by John Murray, Steven Richardson, Keith Joiner, Graham Wild

“…Examining an RPAS accident database from 2008–2019 for HF-caused accidents and coding to the Human Factors Analysis and Classification System (HFACS) taxonomy, an exploration of RPAS HFs is carried out and the predominant HF issues for RPAS pilots identified. …”
Get full text

Управленческий учет и проблемы классификации затрат

“…The article is devoted to topical issues of classification of costs-the cost price of production in conditions of market economy development in Russia. …”
Get full text

What disabilities make it possible to take up employment? Case studies by industry by Monika MAZUR-MITROWSKA

“…The issues of employment opportunities for people with disabilities are included in all descriptions including the information about occupations developed in the PO WER project „Developing, supplementing and updating information about occupations and its dissemination using modern communication tools – INFODORADCA +”. …”
Get full text

Advances and Challenges in Deep Learning for Automated Welding Defect Detection: A Technical Survey by Abdulrahim Mohammed, Muhammad Hussain

“…This paper presents a comprehensive review of state-of-the-art Deep Learning (DL) models tailored for welding defect detection, segmentation, and classification, emphasizing technical advancements and persistent challenges. …”
Get full text

Bridging Disciplinary Gaps in Studies of Human-Environment Relations: A Modelling Framework by Michael Hauhs, Baltasar Trancón y Widemann, Georg Klute

“…It can be tested on various other classification schemes in a number of disciplines. In each application, the categories of classification can be translated and then the patterns of the four logic types can be compared with the phenomenology of each case. …”
Get full text

A novel deep learning technique for multi classify Alzheimer disease: hyperparameter optimization technique by A. S. Elmotelb, Fayroz F. Sherif, A. S. Abohamama, A. S. Abohamama, Mahmoud Fakhr, Amr M. Abdelatif

Get full text

Evolution of paradigms in the study of depression: from a unitary concept to a biopsychosocial model and interdisciplinary approaches by A. N. Kornetov

“…The existing limitations in the study of depressive disorders in psychiatry and clinical psychology and the issues of interdisciplinary integration and interdisciplinary barriers are considered in detail. …”
Get full text

Identifying student help-seeking behavior patterns and help-seeking tendencies from student problem-solving and help-seeking behavior data: An educational data mining approach by Chih-Yueh Chou, Wei-Han Chen

Get full text

Experimental statistical analysis of radar signals reflected from weather hazards by E. S. Boyarenko, E. A. Bolelov, O. V. Vasiliev, S. S. Korotkov

“…The results obtained can be used to correct the classification criteria of weather hazards to subsequently increase the justification and reliability of the weather hazard classification. …”
Get full text

Conceptual principles of formation and functioning of vertically integrated structures by V.A. Topilo, V.K. Danylko

“…Despite the significant scientific contribution of the authors to the study of this topic, there is a number of unresolved issues regarding the selection of areas, forms, types of vertical integration that need further study and clarification. …”
Get full text

Sb-PiPLU: A Novel Parametric Activation Function for Deep Learning by Ayan Mondal, Vimal K. Shrivastava, Ayan Chatterjee, Raghavendra Ramachandra

“…Due to its flexibility and robustness, Sb-PiPLU is particularly well-suited for complex image classification tasks.…”
Get full text

Synergizing human insight and machine learning: A dual-lens approach to uncovering healthcare research and innovation outcomes by Stijn Horck, Sanne Steens, Jermain Kaminski

Get full text

Rapid Diagnosis of Distributed Acoustic Sensing Vibration Signals Using Mel-Frequency Cepstral Coefficients and Liquid Neural Networks by Haitao Liu, Yunfan Xu, Yuefeng Qi, Haosong Yang, Weihong Bi

“…Distributed Acoustic Sensing (DAS) systems face increasing challenges in massive data processing and real-time fault diagnosis due to the growing complexity of industrial environments and data volume. To address these issues, an end-to-end diagnostic framework is developed, integrating Mel-Frequency Cepstral Coefficients (MFCCs) for high-efficiency signal compression and Liquid Neural Networks (LNNs) for lightweight, real-time classification. …”
Get full text

Leveraging generative adversarial networks for data augmentation to improve fault detection in wind turbines with imbalanced data by Subhajit Chatterjee, Yung-Cheol Byun

“…The paramount task of ensuring the effective monitoring and fault classification of WTs is indispensable for the stability of wind farm systems. …”
Get full text