Asynchronous bearing only tracking management approach in distributed multi-function integrated sensors by ZHANG Wei, YANG Qiu, LI Hao

“…The distributed multi-function system requires only one integrated sensor to switch to electronic support measure (ESM) mode within each tracking cycle to update the angle measurement information of target radiation source, while the other integrated sensors still work in the original planned mode and task. …”
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From fish to fiber: 3D-nanoprinted optical neuromast for multi-integrated underwater detection by Liangye Li, Xuhao Fan, Geng Chen, Yueqi Liu, Fujun Zhang, Zhuolin Chen, Zhi Zhang, Wangyang Xu, Shixiong Zhang, Yuncheng Liu, Zongjing Li, Hui Gao, Zhijun Yan, Wei Xiong, Qizhen Sun

“…Abstract Fish possess high sensitivity to acoustic, vibrational, and hydrodynamic stimuli through unique sensing cells, providing unparalleled paradigms for developing underwater detection methods. However, artificial perception devices face challenges in replicating comparable sensitivity and multi-dimensional integration of fish in function and scale. …”
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The Process of Using Power Supply Technical Solutions for Electronic Security Systems Operated in Smart Buildings: Modelling, Simulation and Reliability Analysis by Michał Wiśnios, Michał Mazur, Sebastian Tatko, Jacek Paś, Adam Rosiński, Jarosław Mateusz Łukasiak, Wiktor Koralewski, Janusz Dyduch

“…The operational tasks of ESSs in SBs require a continuous power supply from various sources, including renewable energy sources. The authors conducted an analysis of the power supply for selected ESSs used in SBs, which enabled the development of a power supply model. …”
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Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices by Hikaru Sugimoto, Ken-ichi Hironaka, Tomoaki Nakamura, Tomoko Yamada, Hiroshi Miura, Natsu Otowa-Suematsu, Masashi Fujii, Yushi Hirota, Kazuhiko Sakaguchi, Wataru Ogawa, Shinya Kuroda

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Enhancing Human Detection in Occlusion-Heavy Disaster Scenarios: A Visibility-Enhanced DINO (VE-DINO) Model with Reassembled Occlusion Dataset by Zi-An Zhao, Shidan Wang, Min-Xin Chen, Ye-Jiao Mao, Andy Chi-Ho Chan, Derek Ka-Hei Lai, Duo Wai-Chi Wong, James Chung-Wai Cheung

“…VE-DINO enhances detection accuracy by incorporating body part key point information and employing a specialized loss function. …”
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Relationships between vegetation indices and surface reflectance: Implications for detecting and monitoring sandification in arid regions by Yifan Yue, Wenzhi Zhao, Rentao Liu

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Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms by Roberta Puglisi, Caterina Testa, Sara Scuderi, Valentina Greco, Giuseppe Trusso Sfrazzetto, Manuel Petroselli, Andrea Pappalardo

“…Fluorescence titrations and density functional theory (DFT) calculations reveal and explain the high binding affinity of this receptor toward selected amines, demonstrating its potential as an effective tool for amine detection.…”
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Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

“…Compared to various lightweight architectures and advanced detection models, this method demonstrates excellent accuracy, lower computational costs, and better real-time performance, providing a feasible coal mine pedestrian-vehicle detection method for resource-constrained coal mine scenarios, meeting the deployment requirements of coal mine video surveillance and enabling real-time alerts for intelligent inspection of coal mine pedestrian-vehicles.…”
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Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

“…Although various technologies with wearables and vision systems that utilize artificial intelligence (AI) have been developed to detect falls, many AI models are complex and resource-intensive. …”
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Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

“…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

“…To address this problem, machine learning (ML) based intrusion detection systems (IDSs) have been proposed. However, existing IDSs suffer from low detection accuracy, limited real-time response, and high resource requirements. …”
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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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DNA-Based Nanobiosensor for the Colorimetric Detection of Dengue Virus Serotype 2 Synthetic Target Oligonucleotide by Michael Sandino C. Flores, Evangelyn C. Alocilja, Divina M. Amalin, Mae Joanne B. Aguila, Marynold V. Purificacion, Florinia E. Merca, Ma. Carmina C. Manuel, Mark Pierre S. Dimamay, Ma. Anita M. Bautista, Lilia M. Fernando

“…Being a developing country, most of the high-risk areas in the Philippines are resource-limited and cannot afford equipment for detection and monitoring. …”
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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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Effect of Cs atoms adsorption on the work function of the LaB6 (100) surface by Huaqing Zheng, Xin Zhang, Jun Hu, Yuhong Xu, Guangjiu Lei, Sanqiu Liu, Heng Li, Zilin Cui, Yiqin Zhu, Xiaolong Li, Xiaoqiao Liu, Shaofei Geng, Xiaochang Chen, Haifeng Liu, Xianqu Wang, Hai Liu, Jun Cheng, Changjian Tang

“…These results provide some reference for the selection of fusion plasma gird materials and the production of hydrogen negative ion sources for neutral beam injection.…”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data. by Qihai Liu, Kevin H Lee, Hyun Bin Kang

“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

“…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
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