Zero trust management of data flow between IoT edge nodes based on SDN by XIAO Jingxu, GUO Yuanbo, CHANG Chaowen, WU Ping, YANG Chenli

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Data augmentation based multi-view contrastive learning graph anomaly detection by LI Yifan, LI Jiayin, LIN Xingpeng, DAI Yuanfei, XU Li

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Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation by Zhan Wang, Mwamba Kasongo Dahouda, Hyoseong Hwang, Inwhee Joe

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Tendon Anomaly Identification in Prestressed Concrete Beams Based on an Advanced Monitoring MEMS and Data-Driven Detection of Structural Damage by Giorgio de Alteriis, Giulio Mariniello, Tommaso Pastore, Alessia Teresa Silvestri, Giuseppe Augugliaro, Ida Papallo, Canio Mennuti, Antonio Bilotta, Rosario Schiano Lo Moriello, Domenico Asprone

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Machine Learning-Based Detection of Anomalies, Intrusions, and Threats in Industrial Control Systems by Denis Benka, Dusan Horvath, Lukas Spendla, Gabriel Gaspar, Maximilian Stremy

Subjects: “…Anomaly detection…”
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Design of an integrated model with temporal graph attention and transformer-augmented RNNs for enhanced anomaly detection by Sai Babu Veesam, Aravapalli Rama Satish, Sreenivasulu Tupakula, Yuvaraju Chinnam, Krishna Prakash, Shonak Bansal, Mohammad Rashed Iqbal Faruque

Subjects: “…Anomaly detection…”
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Study of the anomaly detection on rail by a tachometer generator of a train by Gaku YOSHIKAWA

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Advancements and challenges in agriculture: a comprehensive review of machine learning and IoT applications in vertical farming and controlled environment agriculture by Binoy Sasmal, Gobinda Das, Preeti Mallick, Sneha Dey, Suman Ghorai, Subrata Jana, Chiranjibe Jana

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STGLR: A Spacecraft Anomaly Detection Method Based on Spatio-Temporal Graph Learning by Yi Lai, Ye Zhu, Li Li, Qing Lan, Yizheng Zuo

Subjects: “…anomaly detection…”
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<inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T: Deep Denoising Dictionary Tensor for Hyperspectral Anomaly Detection by Qiangqiang Shen, Zonglin Liu, Hanzhang Wang, Yanhui Xu, Yongyong Chen, Yongsheng Liang

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New Approach for Tracking, Monitoring, and Diagnosing Faults in a Photovoltaic System in Real Time: An Experimental and Case Study by Leila Boucerredj, Ali Khechekhouche, Nadir Benalia, Abderrahmane Khechekhouche, Antonio Marcos de Oliveira Siqueira, Julio Cesar Costa Campos

Subjects: “…Renewable energy, Photovoltaic installations, Real-time monitoring, Fault diagnosis, Energy yield, Anomaly detection.…”
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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

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End-to-End Methodology for Predictive Maintenance Based on Fingerprint Routines and Anomaly Detection for Machine Tool Rotary Components by Amaia Arregi, Aitor Barrutia, Iñigo Bediaga

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Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance by Sarfaraz Natha, Fareed Ahmed, Mohammad Siraj, Mehwish Lagari, Majid Altamimi, Asghar Ali Chandio

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Anomaly detection of large scale network based on data streams by ZHENG Jun, HU Ming-zeng, YUN Xiao-chun, ZHENG Zhong

Subjects: “…anomaly detection…”
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IoT Network Anomaly Detection in Smart Homes Using Machine Learning by Nadeem Sarwar, Imran Sarwar Bajwa, Muhammad Zunnurain Hussain, Muhammad Ibrahim, Khizra Saleem

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Detecting Anomaly Classification Using PCA-Kmeans and Ensembled Classifier for Wind Turbines by Prince Waqas Khan, Yung-Cheol Byun

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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

Subjects: “…Anomaly detection…”
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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

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Large Pretrained Foundation Model for Key Performance Indicator Multivariate Time Series Anomaly Detection by Xu Wang, Qisheng Xu, Kele Xu, Ting Yu, Bo Ding, Dawei Feng, Yong Dou

Subjects: “…Key Performance Indicator (KPI) anomaly detection…”
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