Steering nonlocality in high-speed telecommunication system without detection loophole by Qiang Zeng, Huihong Yuan, Haoyang Wang, Lai Zhou, Zhiliang Yuan

“…Abstract Nonlocal correlation represents the key feature of quantum mechanics, and is an exploitable resource in quantum information processing. However, the loophole issues and the associated applicability compromises hamper the practical applications. …”
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CNN based 2D object detection techniques: a review by Badri Raj Lamichhane, Gun Srijuntongsiri, Teerayut Horanont

“…The findings reveal that while 2-stage and hybrid methods achieve superior accuracy and detection precision, 1-stage methods offer faster processing and lower computational complexity, making them advantageous in specific real-time applications.…”
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TSHD: Topic Segmentation Based on Headings Detection (Case Study: Resumes) by Majd E. Tannous, Wassim H. Ramadan, Mohanad A. Rajab

“…They contain various segments such as personal information, experience, and education. Manually processing resumes to find the most suitable candidates for a particular job is a difficult task. …”
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GNSS-Based Multi-Target RDM Simulation and Detection Performance Analysis by Jinxing Li, Qi Wang, Meng Wang, Youcheng Wang, Min Zhang

“…This paper proposes a novel Global Navigation Satellite System (GNSS)-based remote sensing method for simulating Radar Doppler Map (RDM) features through joint electromagnetic scattering modeling and signal processing, enabling characteristic parameter extraction for both point and ship targets in multi-satellite scenarios. …”
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Development of a Nanostructured Electrochemical Genosensor for the Detection of the K-ras Gene by Luis Fernando Garcia-Melo, Miguel Morales-Rodríguez, Eduardo Madrigal-Bujaidar, Eduardo O. Madrigal-Santillán, José Antonio Morales-González, Rosa Natali Pineda Cruces, Jorge Alfredo Campoy Ramírez, Pablo Damian-Matsumura, Alexandro Tellez-Plancarte, Nikola Batina, Isela Álvarez-González

“…In the scientific literature, it has been documented that electrochemical genosensors are novel analytical tools with proven clinical diagnostic potential for the identification of carcinogenic processes due to genetic and epigenetic alterations, as well as infectious diseases due to viruses or bacteria. …”
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Early Fault Detection in Nuclear Systems: A Digital Engineering Approach by Maria Coelho, Kaleb Houck, Logan Browning, Piyush Sabharwall, Christopher Folmar, Jack Cavaluzzi, Patrick McClure, Jack Dunker

“…The present work proposes a comprehensive digital engineering approach that leverages digital twins, digital threads, model-based systems engineering, artificial intelligence, and immersive extended reality to support early fault detection in nuclear systems. Through a series of case studies, we highlight specific gaps in the fault detection mechanisms of traditional nuclear design and operation processes, then demonstrate a suite of solutions we are working to implement to address these shortcomings in similar projects. …”
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Frequency-informed transformer for real-time water pipeline leak detection by Fengnian Liu, Ding Wang, Junya Tang, Lei Wang

“…To address these limitations, this paper introduces a Frequency-Informed Transformer model, which integrates the Fast Fourier Transform and self-attention mechanisms to enhance water pipe leak detection accuracy. Experimental results show that FiT achieves 99.9% accuracy in leak detection and 98.7% in leak type classification, surpassing other models in both accuracy and processing speed, with an efficient response time of 0.25 seconds. …”
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Using convolutional neural networks for image semantic segmentation and object detection by Shuangmei Li, Chengning Huang

“…The experimental results show that the model exhibits excellent performance in object detection and segmentation tasks. This study provides a more effective strategy for processing complex images by optimizing network structure and enhancing feature fusion.…”
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Attention dual transformer with adaptive temporal convolutional for diabetic retinopathy detection by Mishmala Sushith, Ajanthaa Lakkshmanan, M. Saravanan, S. Castro

“…Abstract An Attention Dual Transformer with Adaptive Temporal Convolutional (ADT-ATC) model is proposed in this research work for enhanced detection of Diabetic Retinopathy (DR) from retinal fundus images. …”
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Screening of G-quadruplex DNA ligands by fluorescence detection of peptide displacement by Valentina Arciuolo, Simona Marzano, Rossella Buono, Nicola Grasso, Anna Di Porzio, Antonio Randazzo, Bruno Pagano, Jussara Amato

“…G-quadruplexes (G4s) are noncanonical DNA/RNA structures involved in key cellular processes, and their interactions with proteins are emerging as therapeutic targets. …”
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Recent advances in detection techniques for vitamin analysis: A comprehensive review by Xiangrui Li, Huan Lv, Wencan Luo, WenJia Yang, Linghong Kong, Qiujin Zhu, Lu Zeng

“…However, vitamins are highly susceptible to degradation by light, heat, oxygen, and interactions with other food components during processing and storage. Additionally, insufficient intake or malabsorption can lead to vitamin deficiencies, resulting in various diseases. …”
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Automatic Detection of Electric Motorcycle Based on Improved YOLOv5s Network by Yinggang He

“…Considering that common monitoring systems typically have limited data processing capabilities, this study proposes an electric motorcycle detection model based on improved You Only Look Once version 5s (YOLOv5s). …”
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A dataset for vineyard disease detection via multispectral imagingZenodo by Alessio Saccuti, Filippo Graziosi, Dario Lodi Rizzini

“…The present dataset is a collection of multispectral images designed for development of detection algorithms for grapevine diseases like Flavescence dorée (FD) and Esca (ED). …”
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Human Body Tracking Method Based on YOLOV5s Object Detection by Shaymaa Tarkan Abdullah, Bashar Talib AL-Nuaimi, Hazim Noman Abed

“…That is replacing typical processing procedures like roboflow with an alternative that can function without the Internet. …”
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Detecting Dynamic States of Temporal Networks Using Connection Series Tensors by Shun Cao, Hiroki Sayama

“…Many temporal networks exhibit multiple system states, such as weekday and weekend patterns in social contact networks. The detection of such distinct states in temporal network data has recently been studied as it helps reveal underlying dynamical processes. …”
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Mathematical model of detection of intra-erythrocyte pathologies using optoacoustic method by D. A. Kravchuk

“…Therefore, a simple, fast, accurate and affordable diagnostic system for the early detection of this disease is necessary for the timely administration of antimalarial drugs.The malarial parasite, during its intra-erythrocyte development, processes a significant amount of hemoglobin, which in this case turns into a hem form called hemozoin. …”
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SCR-Net: A novel lightweight aquatic biological detection network. by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…Marine biological detection is critical to environmental conservation and the use of marine resources. …”
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ROLE OF MAGNETIC RESONANCE IMAGING IN DETECTING KNEE INJURIES IN BASKETBALL PLAYERS by Intesar-Victoria M. Houech, I. Peltekova

“…MR is a reliable diagnostic tool that successfully allows the detection of knee contusions. MR could also help in evaluating the athlete’s condition in preseason. …”
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Mitigating Online Banking Fraud Using Machine Learning and Anomaly Detection by Sheunesu Makura, Caden Dobson, Seani Rananga

“…Online banking fraud has become increasingly prevalent with the widespread adoption of digital financial services, necessitating advanced security solutions capable of detecting both known and emerging threats. This paper presents a robust machine learning framework that integrates anomaly detection with network packet analysis to mitigate fraudulent activities, focusing particularly on Distributed Denial of Service (DDoS) attacks. …”
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Fault Detection in MV Switchgears Through Unsupervised Learning of Temperature Conditions by Grazia Iadarola, Alessandro Mingotti, Virginia Negri, Susanna Spinsante

“…Furthermore, onboard temperature processing eliminates the need for data transmission to remote servers, reducing latency and communication overhead while improving system responsiveness. …”
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