Robust fault detection and severity classification in rotating machinery using VMD-LSTM for limited data scenarios by Ammar Mrabti, Ramdane Younes, Nouredine Ouelaa, Tarek Kebabsa, Zakarya Ouelaa

“…VMD decomposes signals into intrinsic mode functions (IMFs), while LSTM classifies fault types and severity levels based on time-domain features extracted from the IMFs. Tested on the Case Western Reserve University Dataset (CWRUDS) for bearing defects and the Laboratory of Mechanics and Structures Dataset (LMSDS) for combined gear and bearing defects, the method outperforms vibratory analysis and conventional classifiers such as MLP, 1D-CNN, 2D-CNN, and standalone LSTM. …”
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NeuroFuzDetect–A Neural and Fuzzy Inference System for Fake News Classification by Borra Vineetha, Munirathinam Nirmala

“…NeuroFuzDetect leverages advanced computational reasoning to analyze uncertainty and ambiguity in textual data by evaluating critical linguistic features, including credibility, emotional tone, and language patterns, ensuring interpretability by providing justifications for its predictions. …”
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Urban change detection with airborne LiDAR for hostilities’ impact estimation: a case study of Kharkiv by Sergiy V. Kostrikov, Denys S. Serohin

“…This research demonstrates the application of LiDAR for urban change detection (CD), focusing on distinguishing between CD-patterns of normal urban development and from those caused by military hostilities. …”
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A framework of partial discharge detection for gas-insulated switchgear based on LSTM and multi-head attention by YANG Zhengsheng, LIU Fang

“…ObjectivesTo achieve long-term stable operation of electrical equipment， a framework for anomaly detection and classification of partial discharge （PD） in gas insulated switchgear （GIS） based on long short-term memory （LSTM） networks and a multi-head attention mechanism was proposed.MethodsFirstly， phase resolved partial discharge （PRPD） analysis was used as the input sequence， and LSTM was employed to learn the temporal correlations in PRPD signals. …”
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Detection of Foodborne Pathogens Through Volatile Organic Compounds Sensing via Metal Oxide Gas Sensors by Shiv Dutta Lawaniya, Anjali Awasthi, Prashanth W. Menezes, Kamlendra Awasthi

“…This review systematically explores recent advancements in gas sensing technologies utilizing metal oxide‐based sensors for the detection of foodborne pathogens through the analysis of volatile organic compounds (VOCs). …”
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An Intelligent Framework for Multiscale Detection of Power System Events Using Hilbert–Huang Decomposition and Neural Classifiers by Juan Vasquez, Manuel Jaramillo, Diego Carrión

“…Features are extracted using empirical mode decomposition (EMD) and Hilbert spectral analysis, enabling accurate representation of the signals’ non-stationary and nonlinear characteristics. …”
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Detecting muscle fatigue during lower limb isometric contractions tasks: a machine learning approach by Jiaqi Sun, Cheng Zhang, Guangda Liu, Wenjie Cui, Yubing Sun, Chunyan Zhang

“…Electromyography (EMG) serves as an effective tool for monitoring muscle activity, with EMG signal analysis playing a crucial role in assessing muscle fatigue. …”
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IoT-Based Pest Detection in Agriculture Using Raspberry Pi and YOLOv10m for Precision Farming by Zarboubi Mohamed, Bellout Abdelaaziz, Chabaa Samira, Dliou Azzedine, Zeroual Abdelouhab

“…The Ubidots dashboard encompasses features like data analysis, historical trends, and notification alerts for elevated pest densities. …”
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Early warning value of multiple serum indicators combined with ultrasound detection in girls with central precocious puberty by Xiaolong Song, Jianping Zhou, Tiantian Han, Zhifeng Lin, Xu Chen, Yufang Li, Yufang Li

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Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms by Chunxia Huang, Qiong Ma, Xiao Zeng, Jiawei He, Fengming You, Xi Fu, Yifeng Ren

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Hybrid Contrastive Learning With Attention-Based Neural Networks for Robust Fraud Detection in Digital Payment Systems by Md Shahin Alam Mozumder, Mohammad Balayet Hossain Sakil, Md Rokibul Hasan, Md Amit Hasan, K. M Nafiur Rahman Fuad, M. F. Mridha, Md Rashedul Islam, Yutaka Watanobe

“…Additionally, SHAP-based analysis reveals the importance of key features such as transaction amount and PCA-derived components in model decisions, enhancing explainability. …”
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Hybrid Graph Representation Learning for Carotid Artery Stenosis Detection Based on Multimodal Retinal OCTA Images by Wenting Lan, Jinkui Hao, Shengjun Zhou, Jingfeng Zhang, Shaodong Ma, Yitian Zhao

“…We construct a hybrid graph representation by combining arterial and venous features, with the aim of improving the model’s ability to extract and integrate diverse anatomical information for more accurate CAS detection. …”
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An Automated Framework for Lane Closure Detection on Highway Using Connected Vehicle Data and Machine Learning Models by Ashutosh Dumka, Raghupathi Kandiboina, Aparna Joshi, Skylar Knickerbocker, Neal Hawkins, Anuj Sharma

“…We employ two machine learning models—support vector machines (SVMs) and k-nearest neighbors (K-NN)—trained on features extracted from these metrics to detect lane closures and provide insights into location and time of start and end. …”
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Enhancing Detection of Control State for High-Speed Asynchronous SSVEP-BCIs Using Frequency-Specific Framework by Yufeng Ke, Jiale Du, Shuang Liu, Dong Ming

“…The FS framework sequentially incorporated task-related component analysis (TRCA)-based SSVEP identification and a classifier bank containing multiple FS control state detection classifiers. …”
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Detection of Streptococcus pneumoniae serotypes causing invasive and non-invasive infections using whole-genome sequencing by Mironov К.O., Gaponova I.I., Korchagin V.I., Mikhailova Yu.V., Shelenkov A.A., Chagaryan A.N., Ivanchik N.V., Platonov A.E., Kozlov R.S., Akimkin V.G.

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Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades by Min Meng, Xiangyuan Zheng, Zhonghui Wu, Hanyu Hong, Lei Zhang

“…This paper presents the analysis of time-domain features of microwave signals, which facilitates the identification of both the icing state and the corresponding thickness. …”
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Impurity rates detection for pepper harvesting based on YOLOv8n-Seg-ASB and random forest by Lijian Lu, Jin Lei, Chenming Cheng, Shiguo Wang, Chengfu Wang, Xinyan Qin

“…To address the inaccuracies and inefficiencies of pepper impurity rates detection caused by complex material compositions and variable harvesting environments, this paper proposes a detection technique based on deep and machine learning algorithms. …”
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Edge-based detection and localization of adversarial oscillatory load attacks orchestrated by compromised EV charging stations by Khaled Sarieddine, Mohammad Ali Sayed, Sadegh Torabi, Ribal Atallah, Chadi Assi

“…The edge-based detection relies on the behavioral characteristics of the power grid in the presence of interconnected EVCS while combining cyber and physical layer features to implement deep learning algorithms for the effective detection of oscillatory load attacks at the EVCS. …”
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Detection and characterization of the Dezidougou virus (genus Negevirus) in mosquitoes (Ochlerotatus caspius) collected in the Republic of Sakha (Yakutia) by Marina A. Stepanyuk, Stanislav S. Legostaev, Kristina V. Karelina, Nina F. Timofeeva, Ksenia F. Emtsova, Olesia V. Ohlopkova, Oleg S. Taranov, Vladimir A. Ternovoi, Albert V. Protopopov, Valery B. Loktev, Victor A. Svyatchenko, Alexander P. Agafonov

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Enhanced fire hazard detection in solar power plants: an integrated UAV, AI, and SCADA-based approach by Andrii Lysyi, Anatoliy Sachenko, Pavlo Radiuk, Mykola Lysyi, Oleksandr Melnychenko, Oleksii Ishchuk, Oleg Savenko

“…The Subject of this research is the development of an intelligent, integrated system for the early detection and causal analysis of fire hazards in large-scale solar power plants (SPPs). …”
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