Review of Multivariate Time Series Clustering Algorithms by ZHENG Desheng, SUN Hanming, WANG Liyuan, DUAN Yaoxin, LI Xiaoyu

“…Initially, based on classification standards such as feature extraction methods, similarity measurement algorithms, and clustering partition frameworks, this paper conducts a comparative analysis of existing multivariate time series clustering algorithms. …”
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Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…Our data preprocessing included bandpass filtering and feature extraction through Mel-Frequency Cepstral Coefficients (MFCCs). …”
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Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…The study highlights the effectiveness of feature engineering and model optimization in enhancing DDoS detection accuracy, making machine learning a viable solution for real-time cybersecurity applications.…”
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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

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Assessing the impact of stimulation environment and error probability on ErrP EEG response, detection and subject attention: an explorative study by Andrea Farabbi, Luca Mainardi

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Fact or Fake? How News Title, Sentiment and Writing Style help AI to detect COVID-19 Fake News? by Chen-Shu Wang, Bo-Yi Li, Kai-Wen Wang, Zhi-Chi Lin

“…This research presents a sophisticated model aimed at detecting COVID-19 related misinformation in Traditional Chinese, a critical response to the swift spread of fake news during the pandemic. …”
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Inertial-Based Gait Metrics During Turning Improve the Detection of Early-Stage Parkinson’s Disease Patients by Lin Meng, Jun Pang, Yifan Yang, Lei Chen, Rui Xu, Dong Ming

“…We explored the factor effect of group and gait tasks on gait parameters using a two-way mixed analysis of variance. The discriminating ability of gait parameters between PD and the control group was evaluated using receiver operating characteristic analysis. …”
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A Novel Detection Scheme for Motor Bearing Structure Defects in a High-Speed Train Using Stator Current by Qi Sun, Juan Zhu, Chunjun Chen

“…This approach employs a hybrid signal preprocessing algorithm that integrates adaptive notch filtering (ANF) with envelope spectrum analysis (ESA) to effectively sparse the stator current and extract relevant fault features. …”
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Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Recent advancements in Natural Language Processing (NLP) methodologies enable the automated extraction of informative speech features, which has been leveraged for early psychosis detection and assessment of symptomology. …”
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Developing transferable and universal IR biomarkers for intraoperative colorectal cancer diagnosis via FTIR spectroscopy by Ran Li, Heather C. Allen

“…Abstract Histological staining has long been the gold standard for cancer detection, but it is limited by subjectivity and delayed results. …”
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Boost-Classifier-Driven Fault Prediction Across Heterogeneous Open-Source Repositories by Philip König, Sebastian Raubitzek, Alexander Schatten, Dennis Toth, Fabian Obermann, Caroline König, Kevin Mallinger

“…Moreover, a comprehensive feature-importance analysis shows that files with long lifespans (high age), frequent edits (revision count), and widely scattered changes (entropy metrics) are especially vulnerable to defects. …”
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A Deep Learning Framework for Healthy Lifestyle Monitoring and Outdoor Localization by Mehrab Rafiq, Naif S. Alshammari, Haifa F. Alhasson, Dina Abdulaziz Alhammadi, Mohammed Alshehri, Ahmad Jalal, Hui Liu

“…Kernel Fisher Discriminant Analysis was applied for feature optimization, and a deep neural network was utilized for feature classification. …”
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Multi-Modal Dynamic Fusion for Defect Detection in Electronic Products: A Novel Approach Based on Energy and Deep Learning by Yulin Liu, Yang Gao

“…To address these shortcomings, this study introduces a dynamic multi-modal fusion framework that leverages data from sensors, visual imagery, and component attributes to enhance detection performance. Specifically, Transformer architectures are employed for sensor data analysis, Convolutional Neural Networks (CNNs) are applied to process image data, and Multi-Layer Perceptrons (MLPs) are used to represent part-level features. …”
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Trait-focused low-cost and stereo-based 3D plant modeling for phenotyping via deep neural detection by M. Wattad, S. Filin

“…To facilitate the reconstruction, we adapt an anchor-free detection deep neural network and integrate low- and high-level features to accurately detect our plant traits of interest. …”
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Detecting Serbia’s Settlement Patterns: A Fuzzy Logic-Based Approach to Rural–Urban Area Delimitation for Spatial Planning by Aleksandra Gajić Protić, Nikola Krunić, Branko Protić

“…In addition, such an approach detects settlements that have functional significance in the settlement system. …”
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Automatic Fracture Detection Convolutional Neural Network with Multiple Attention Blocks Using Multi-Region X-Ray Data by Rashadul Islam Sumon, Mejbah Ahammad, Md Ariful Islam Mozumder, Md Hasibuzzaman, Salam Akter, Hee-Cheol Kim, Mohammad Hassan Ali Al-Onaizan, Mohammed Saleh Ali Muthanna, Dina S. M. Hassan

“…Accurate detection of fractures in X-ray images is important to initiate appropriate medical treatment in time—in this study, an advanced combined attention CNN model with multiple attention mechanisms was developed to improve fracture detection by deeply representing features. …”
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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…Seasonal discrepancies in power generation are analyzed using theoretical and actual power analysis. Further, distributions of features are realized via kernel density estimation and efficiency metrics in order to identify performance inefficiencies. …”
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Opportunities and Challenges Surrounding the Use of Wearable Sensor Bracelets for Infectious Disease Detection During Hajj: Qualitative Interview Study by Noha Maddah, Arpana Verma, John Ainsworth

“…Semistructured in-depth interviews were used to capture perspectives on using wearable sensor bracelets for infectious disease detection during hajj. Thematic analysis of interview transcripts was conducted. …”
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“Detection and characterization of fractures in the Eocene Thebes formation using conventional well logs in October field, Gulf of Suez, Egypt” by M. Gamal, A.A. El-Araby, A.N. El-Barkooky, Alaa Hassan

“…Despite their necessity, detecting and characterizing natural fractures still represents a difficult challenge. …”
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Enhanced Ground Fissure Detection in Mining Areas Based on Visible–Infrared Image Fusion and YOLOv5 by Yixin Zhao, Liangchen Zhao, Jihong Guo, Kangning Zhang, Chunwei Ling, Shirui Wang, Hua Bian

“…This article proposes FisFusionYOLO, a novel method that integrates visible–infrared image fusion with a YOLOv5 deep learning network to enhance fissure detection accuracy and efficiency. By combining complementary information from visible and infrared images, the fusion strategy improves the representation of fissure features, which are then processed by the YOLOv5 network for precise and efficient object detection. …”
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