Adaptive DDoS Attack Detection: Entropy-Based Model With Dynamic Threshold and Suspicious IP Reevaluation by Juri Pebrianto, Vera Suryani

“…DDoS constitutes a significant andger to network security, frequently employing anomalous traffic patterns to impede services. DDoS detection can be executed by an entropy-based anomaly detection approach, which juxtaposes the entropy value with the threshold <inline-formula> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>. …”
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Traffic Scene Analysis using Hierarchical Sparse Topical Coding by P. Ahmadi, I. Gholampour, M. Tabandeh

“…Analyzing motion patterns in traffic videos can be exploited directly to generate high-level descriptions of the video contents. …”
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An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning by L. Ravi Kumar, Ravi Kumar Tata, T. R. Mahesh, Endris Mohammed Ali

“…Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the creation of labels with bounding boxes, and it will be evaluated by using accuracy scores. …”
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

“…For ARs, relevant patterns include elongated bands of high TMQ and eastward winds. …”
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Real-Time Object Detection Using Low-Resolution Thermal Camera for Smart Ventilation Systems by Jun-Hee Lee, Eung-Tea Kim

“…To address the scarcity of thermal data, we developed the TOI (Thermal Object Insertion) data augmentation technique, which generates new training data while preserving thermal pattern characteristics. A composite loss function combining box, classification, and confidence losses was implemented to enhance object detection performance. …”
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Deep learning-based debris flow hazard detection and recognition system: a case study by Fei Wu, Jianlin Zhang, Dunlong Liu, Andreas Maier, Vincent Christlein

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A Novel Phantom for Standardized Microcalcification Detection Developed Using a Crystalline Growth System by Dee H. Wu, Caroline Preskitt, Natalie Stratemeier, Hunter Lau, Sreeja Ponnam, Supriya Koya

“…Background/Objectives: The accurate detection of microcalcifications in mammograms is critical for the early detection of breast cancer. …”
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In-context learning for propaganda detection on Twitter Mexico using large language model meta AI by C.A. Piña-García

“…Hierarchical clustering and word frequency analyses reveal coordinated messaging patterns, reinforcing the role of social media as a tool for political discourse manipulation. …”
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Polarimetric Wide‐Angle Radar Detects Competing Signatures of Ice Fabric and Structural Firn Anisotropy by Falk M. Oraschewski, M. Reza Ershadi, Reinhard Drews

“…The degree of anisotropy evolves dynamically as ice crystals align during deformation into macroscopic patterns termed ice fabric. Radar polarimetry is an emerging tool to detect such patterns, particularly using nadir‐looking antenna geometries sensitive to horizontal anisotropy. …”
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CoAt-Set: Transformed coordinated attack dataset for collaborative intrusion detection simulationMendeley Data by Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno

“…The CoAt-Set dataset is a transformed dataset specifically designed for collaborative anomaly detection within Collaborative Intrusion Detection Systems (CIDS). …”
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Detection of genome-wide methylation changes in bladder cancer by long-read sequencing of urinary DNA by Anshita Goel, Benjamin J. Tura, Joanne D. Stockton, Nicholas Tovey, Luke Ames, Andrew D. Beggs, Maurice P. Zeegers, Nicholas D. James, K. K. Cheng, Richard T. Bryan, Douglas G. Ward, Roland Arnold

“…Conclusions Even at low-read depths, genome-wide methylation patterns in urinary DNA reflect the presence of BC, potentially permitting rapid, non-invasive and cost-effective BC detection.…”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…Methods currently used for identifying vulnerabilities in smart contracts mostly rely on static analysis methods that search for predefined vulnerability patterns. However, these patterns often fail to capture complex vulnerabilities, leading to a high rate of false negatives. …”
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Real-Time Financial Fraud Detection Using Adaptive Graph Neural Networks and Federated Learning by Milad Rahmati

“…Conventional fraud detection systems rely heavily on static machine learning models, which often struggle to adapt to emerging fraud patterns. …”
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Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques by Althaf Ali A, Rama Devi K, Syed Siraj Ahmed N, Ramchandran P, Parvathi S

“…By leveraging semantic analysis, lexical patterns, and metadata extraction, the proposed framework enhances the identification of suspicious patterns in web page content. …”
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Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks by Ayan Chatterjee, Vajira Thambawita, Michael A. Riegler, Pal Halvorsen

“…ADSiamNet effectively identifies localized patterns in time-series data and smooths detected anomalies using a quantile-based technique. …”
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Predictive maintenance based on anomaly detection in photovoltaic system using SCADA data and machine learning by Agussalim Syamsuddin, Andrew Cahyo Adhi, Amie Kusumawardhani, Toni Prahasto, Achmad Widodo

“…This paper aims to propose a predictive maintenance approach for PV systems using anomaly detection and fault diagnosis. In this study, the daily patterns of irradiance and corresponding AC output from a newly completed solar PV farm are investigated. …”
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Outlier Detection in VPN Authentication Logs for Corporate Computer Networks Access using CRISP-DM by Nilo Legowo, Wilyu Mahendra Bad

“…This necessitates a proactive approach from companies to safeguard data integrity, particularly by identifying abnormal access patterns and timestamps. This study aims to develop a model for detecting anomalous activities within authentication log data obtained from VPN usage. …”
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Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19. by Hamish Gibbs, Emily Nightingale, Yang Liu, James Cheshire, Leon Danon, Liam Smeeth, Carl A B Pearson, Chris Grundy, LSHTM CMMID COVID-19 working group, Adam J Kucharski, Rosalind M Eggo

“…We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. …”
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Detection of Steel Reinforcement in Concrete Using Active Microwave Thermography and Neural Network-Based Analysis by Barbara Szymanik, Maja Kocoń, Sam Ang Keo, Franck Brachelet, Didier Defer

“…Numerical simulations were developed to model the thermal response of reinforced concrete subjected to microwave excitation, generating synthetic thermal images representing the surface temperature patterns of reinforced concrete, influenced by subsurface steel reinforcement. …”
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A systematic review on sleep stage classification and sleep disorder detection using artificial intelligence by Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md Mehedi Hasan Shawon

“…Therefore, a sleep study that includes sleep patterns and disorders is crucial to enhancing our knowledge about individual health status. …”
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