Machine Learning-Based Mooring Failure Detection for FPSOs: A Two-Step ANN Approach by Omar Jebari, Do-Soo Kwon, Sung-Jae Kim, Chungkuk Jin, Moohyun Kim

“…This study presents a two-step artificial neural network (ANN) approach for detecting mooring failures in a spread-moored floating production storage and offloading (FPSO) vessel using platform motion data. …”
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XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems by Yousif Hosain, Muhammet Çakmak

“…Abstract The Internet of Medical Things (IoMT) has transformed healthcare delivery but faces critical challenges, including cybersecurity threats that endanger patient safety and data integrity. Intrusion Detection Systems (IDS) are essential for protecting IoMT networks, yet conventional models often struggle with class imbalance, lack interpretability, and are unsuitable for real-world deployment in sensitive healthcare settings. …”
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A decentralized privacy-preserving framework for diabetic retinopathy detection using federated learning and blockchain by Omar Dib

“…This GDPR/HIPAA-compliant solution offers a practical and trustworthy approach to decentralized DR detection in real-world telemedicine settings.…”
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Fluorescence-based methods for detecting caries lesions: systematic review, meta-analysis and sources of heterogeneity. by Thais Gimenez, Mariana Minatel Braga, Daniela Procida Raggio, Chris Deery, David N Ricketts, Fausto Medeiros Mendes

“…STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND DIAGNOSTIC METHODS: The eligibility criteria were studies that: (1) have assessed the accuracy of fluorescence-based methods of detecting caries lesions on occlusal, approximal or smooth surfaces, in both primary or permanent human teeth, in the laboratory or clinical setting; (2) have used a reference standard; and (3) have reported sufficient data relating to the sample size and the accuracy of methods.…”
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Extreme R-CNN: Few-Shot Object Detection via Sample Synthesis and Knowledge Distillation by Shenyong Zhang, Wenmin Wang, Zhibing Wang, Honglei Li, Ruochen Li, Shixiong Zhang

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A comparative study of machine learning models for automated detection and classification of retinal diseases in Ghana. by Gifty Duah, Eric Nyarko, Anani Lotsi

“…The preprocessing techniques employed included data augmentation, resizing, and one-hot encoding. …”
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The effect of fixational eye movements on fixation identification with a dispersion-based fixation detection algorithm by Pieter Blignaut, Tanya Beelders

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Detection of actionable mutations in circulating tumor DNA for non-small cell lung cancer patients by Paul van der Leest, Pim Rozendal, Naomi Rifaela, Anthonie J. van der Wekken, Hanneke Kievit, Vincent D. de Jager, Grigory Sidorenkov, Léon C. van Kempen, T. Jeroen N. Hiltermann, Ed Schuuring

“…In the absence of tumor tissue NGS data (n = 48), five therapeutically relevant mutations are detected. …”
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A Statistical Framework to Detect and Quantify Operator-Learning Curves in Medical Device Safety Evaluation by Ssemaganda HC, Davis SE, Govindarajulu US, Koola JD, Mao J, Westerman DM, Perkins AM, Speroff T, Ramsay CR, Sedrakyan A, Ohno-Machado L, Matheny ME, Resnic FS

“…Correctly attributing safety signals to learning or device effects allows for appropriate corrective actions and recommendations to improve patient safety.Objective: To develop and assess the statistical performance of an analytic framework to detect the presence of LE and quantify the learning curve (LC).Design and Setting: We generated synthetic datasets based on observed clinical distributions and complex feature correlations among patients hospitalized at US Department of Veterans Affairs facilities. …”
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SDR Based Energy Detection Spectrum Sensing in Cognitive Radio for Real Time Video Transmission by Rupali B. Patil, K. D. Kulat, A. S. Gandhi

“…From evaluation results, one can see that the proposed system can indicate the frequency band occupancy by setting the detection output. Detection output changes to one with start of video transmission. …”
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Comparative study of Taqman-based qPCR assay for the detection of Anisakis simplex and Pseudoterranova decipiens. by Mi-Gyeong Kim, Min Ji Hong, Doo Won Seo, Hyun Mi Jung, Hyun-Ja Han, Seung Hwan Kim, Insun Joo

“…Parasite-specific primer/probe sets were selected based on the data from domestic and foreign detection methods. …”
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Research on Detection Method for Wind Turbine Rotor Imbalance at 1P Frequency Based on PLC by LIU Feng, DING Guilin, LUO Zhihui, CHEN Gang, GUO Yanyifu, ZHAI Dayong

“…The amplitude of root-mean-square (RMS) values from real-time generator speed monitoring was preprocessed, including the elimination of outliers and first-order differencing. The processed data were then employed for the peak detection of the generator speed differences. …”
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Quantifying solid volume of stacked eucalypt timber using detection-segmentation and diameter distribution models by Gianmarco Goycochea Casas, Zool Hilmi Ismail, Mathaus Messias Coimbra Limeira, Carlos Pedro Boechat Soares, José Marinaldo Gleriani, Daniel Henrique Brada Binoti, Carlos Alberto Araújo Júnior, Mohd Ibrahim Shapiai, Leonardo Ippolito Rodrigues, Tassius Menezes Araújo, Helio Garcia Leite

“…The results indicate that the model generalizes well to new data, with high accuracy in both validation and test sets. …”
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RiceNet: Efficient CNN for High-Throughput Image-Based Rice Panicle Detection and Counting by Kushwaha Ragini, Balkrishna Sutar Manisha

“…The time complexity of the model is made small enough to efficiently analyze large image data sets with high throughput. RiceNet achieves high accuracy and computational efficiency over traditional image processing and other CNN architectures on diverse rice field images of different rice varieties and stages of growth. …”
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Securing the internet of things: A comprehensive review of ransomware attacks, detection, countermeasures, and future prospects by Peizhi Yan, Tala Talaei Khoei

“…Additionally, we propose a multi-layered defensive strategy integrating technological, legal, and policy measures to address the complexities of ransomware in IoT settings. Looking ahead, our study highlights potential research directions such as advancing real-time detection, leveraging blockchain for enhanced security and fostering cross-sector collaboration to bolster collective threat intelligence. …”
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Real-Time Object Detection in Tap Water Utilizing YOLOv8 for Comprehensive Contamination Monitoring by Glajemir E. Bautista, Paula Angelyn D. Gargar, Ramon G. Garcia

“…The presence of these pollutants poses significant risks to water quality and public health, particularly in urban settings. To address these concerns, a high-precision object detection system was implemented to monitor and analyze water samples effectively. …”
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A Multihead Attention Deep Learning Algorithm to Detect Amblyopia Using Fixation Eye Movements by Dipak P. Upadhyaya, MS, Gokce Cakir, MD, Stefano Ramat, PhD, Jeffrey Albert, PhD, Aasef Shaikh, MD, PhD, Satya S. Sahoo, PhD, Fatema Ghasia, MD

“…The model's ability to identify amblyopia using eye movements alone demonstrates the feasibility of using eye-tracking data in clinical settings to perform objective classifications and complement traditional amblyopia evaluations. …”
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Hybrid CNN and random forest model with late fusion for detection of autism spectrum disorder in Toddlers by Pushpmala Nawghare, Jayashree Prasad

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Detection of Oil Mineral Pollution in Tigris River from Aldora Refined using Absorbance Spectroscopy by Thamer Mahmood Mohammed, Ahmed K. Ahmed

“…The experiments were conducted in a lab setting with a broadband source (200-800 nm) to measure the absorbance of dissolved element salts and precisely identify the lowest concentration up to 2 ppm. …”
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Performance Analysis of Eye Movement Event Detection Neural Network Models with Different Feature Combinations by Birtukan Adamu Birawo, Pawel Kasprowski

“…Event detection is the most important element of eye movement analysis. …”
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