Case report: Detection and treatment of a rare submucosal gland duct adenoma of the esophagus by Yu Zhou, Daoxing He, Zhigang Huang, Zhaoyi Chen, Zheng Zhou, Hui Duan, Jie Xu

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SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices by Chao Wang, Zhizhong Wu, Xi Li, Xuehai Zhou, Aili Wang, Patrick C. K. Hung

“…The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server’s main task is to detect anomalies using state-of-art detection algorithms. …”
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Evaluation of Post Hoc Uncertainty Quantification Approaches for Flood Detection From SAR Imagery by Jakob Ludwig, Ronny Hansch

“…In particular when these predictions are used by human decision makers in high stake scenarios, e.g., during detection and monitoring of natural disasters, trustworthiness is a necessary feature. …”
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Replica attack detection method for vehicular ad hoc networks with sequential trajectory segment by Yan Xin, Xia Feng

“…In terms of semi-supervised support vector machine, we establish a detection model using spatio-temporal trajectories of different identities as input samples, which include features of both conspiracy and non-conspiracy attack scenarios. …”
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Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning by Berk Özel, Muhammad Shahab Alam, Muhammad Umer Khan

“…In this article, we conduct a comprehensive review of articles from 2013 to 2023, exploring how these technologies are applied in fire detection and extinguishing. We delve into modern techniques enabling real-time analysis of the visual data captured by cameras or satellites, facilitating the detection of smoke, flames, and other fire-related cues. …”
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Validation of a Novel Data-Driven Algorithm to Detect Atypical Prescriptions in Radiation Therapy by Connor Thropp, MS, Jaroslaw Hepel, MD, Timothy Leech, Eric E. Klein, PhD, Qiongge Li, PhD

“…In that study, prototype analysis was conducted within a single institution with a single treatment site. …”
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Detecting the fractal physical activity pattern in aged adults with cerebral small vessel disease by Hóngyi Zhào, Hóngyi Zhào, Wei Wei, Fang Lv, Jie Shen, Yonghua Huang

“…Furthermore, these MRI markers were summed in a score of 0–4, representing all cSVD features combined. Detrended fluctuation analysis (DFA) was used to evaluate the fractal physical activity fluctuations at multiple time scales. …”
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Type 2 Diabetes Detection With Light CNN From Single Raw PPG Wave by Serena Zanelli, Mounim A. El Yacoubi, Magid Hallab, Mehdi Ammi

“…Recent studies have demonstrated the utility of PPG analysis for carrying out large-scale screening to prevent and detect diabetes. …”
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AI-Powered System for an Efficient and Effective Cyber Incidents Detection and Response in Cloud Environments by Mohammed Ashfaaq M. Farzaan, Mohamed Chahine Ghanem, Ayman El-Hajjar, Deepthi N. Ratnayake

“…Unlike conventional methods, our system employs advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to provide accurate, scalable, and seamless integration with platforms like Google Cloud and Microsoft Azure. Key features include an automated pipeline that integrates Network Traffic Classification, Web Intrusion Detection, and Post-Incident Malware Analysis into a cohesive framework implemented via a Flask application. …”
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Abnormal Power Fluctuation Detection of Wind Turbines Based on Subband Processing and Correlation Coefficient by CHEN Gang, HU Kaikai, CHEN Yanan, ZHANG Jiayou, XIONG Wenhao

“…Wind turbine power signals are nonlinear and non-stationary signals, and their abnormal fluctuation Frequencies are uncertain, which makes it difficult to extract and detect abnormal power fluctuation features. This paper proposes a method for detecting abnormal power fluctuations of wind turbine based on subband processing and correlation coefficient. …”
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An improve fraud detection framework via dynamic representations and adaptive frequency response filter by Juncheng Yang, Shuxia Li, Zijun Huang, Junhang Wu

“…Consequently, we introduce the Dynamic Pattern with Adaptive Filter Graph Learning framework for telecom fraud detection. With the sequential network, we capture users’ dynamic behavioral features for LSN input. …”
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Evaluating YOLO Models for Efficient Crack Detection in Concrete Structures Using Transfer Learning by Muhammad Sohaib, Muzamal Arif, Jong-Myon Kim

“…This work introduces a comprehensive analysis of various YOLO models for detecting cracks in concrete structures, aiming to assist in the selection of an optimal model for future detection and segmentation tasks. …”
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Diagnostic Methods Used in Detecting Multiple Myeloma in Paleopathological Research—A Narrative Review by Kinga Brawańska-Maśluch, Cyprian Olchowy, Grzegorz Mikita, Marta Wanat, Ada Świątko, Michał Krotliński, Martyna Byrska, Joanna Grzelak, Krzysztof Data, Paweł Dąbrowski

“…The diagnostic process is shaped by factors such as preservation, context, and access to technology; despite these variables, characteristic features of lesions were consistently recognized. Conclusion: This review highlights how macroscopic analysis remains central to diagnosis in paleopathology, with radiological and microscopic methods increasingly enhancing accuracy and interpretive depth. …”
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Explainable AI supported hybrid deep learnig method for layer 2 intrusion detection by Ilhan Firat Kilincer

“…In the last part of the study, the effect of the features in the CL2-IDS dataset on the classification is interpreted with SHapley Additive exPlanations (SHAP), an Explainable Artificial Intelligence (XAI) method. …”
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A Novel Framework for Financial Cybersecurity and Fraud Detection Using XAI-RNN-SGRU by Smarajit Ghosh

“…This model enhances financial data prediction and cybersecurity through advanced preprocessing for handling missing values and data imbalance, and it also normalizes numerical features and encodes categorical variables. Enhanced Principal Component Analysis (EPCA) and Improved Fast Random Opposition-based learning Aphid Ant Optimization (AAO) are utilized for feature extraction and desired feature selection. …”
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Advanced Deep Learning Models for Melanoma Diagnosis in Computer-Aided Skin Cancer Detection by Ranpreet Kaur, Hamid GholamHosseini, Maria Lindén

“…An image segmentation network based on deep learning is then used to extract lesion regions for detailed analysis and calculate the optimized classification features. …”
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Dielectrophoresis-Enhanced Microfluidic Device with Membrane Filter for Efficient Microparticle Concentration and Optical Detection by Young-Ho Nam, Seung-Ki Lee, Jae-Hyoung Park

“…These results highlight the device’s potential for precise and efficient microparticle concentration and detection.…”
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DADNet: text detection of arbitrary shapes from drone perspective based on boundary adaptation by Jun Liu, Jianxun Zhang, Ting Tang, Shengyuan Wu

“…To address this issue, we propose a drone-based text detection method based on boundary adaptation. We first conduct an in-depth analysis of text characteristics from a drone’s perspective. …”
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Streamlined Bearing Fault Detection Using Artificial Intelligence in Permanent Magnet Synchronous Motors by Javier de las Morenas, Lidia M. Belmonte, Rafael Morales

“…However, bearing faults remain a critical issue, necessitating robust fault detection strategies. This paper proposes an edge–fog–cloud architecture for bearing fault detection with a specific focus on implementing an efficient and non-intrusive edge-based solution. …”
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Federal Deep Learning Approach of Intrusion Detection System for In-Vehicle Communication Network Security by In-Seop Na, Anandakumar Haldorai, Nithesh Naik

“…This approach is commonly employed for spatial extraction of features, permitted the model to detect patterns that may indicate possible attacks. …”
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