Transition state structure detection with machine learningś by Yitao Si, Yiding Ma, Tao Yu, Yifan Wu, Yingzhe Liu, Weipeng Lai, Zhixiang Zhang, Jinwen Shi, Liejin Guo, Oleg V. Prezhdo, Maochang Liu

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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…Notably, TCDA-NE achieves a maximum improvement of up to 0.1 in the normalized mutual information (NMI) index compared to state-of-the-art methods, highlighting its effectiveness in temporal community detection.…”
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An overview of ahead geological detection technologies in tunnels by Dingchao Chen, Xiangyu Wang, Jianbiao Bai, Yuan Chu, Xian Wang, Jiaxin Zhao, Menglong Li

“…This paper examines the evolution of geological detection methods in tunnel construction, and categorizing them into traditional ahead geological detection methods and ahead detection while excavation (DWE) methods. …”
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Advances in HIV-1 resistance detection technology by SHEN Kuiling, YAN huimin, LI Lin, LI Hanping

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Deep Learning-Based Atmospheric Visibility Detection by Yawei Qu, Yuxin Fang, Shengxuan Ji, Cheng Yuan, Hao Wu, Shengbo Zhu, Haoran Qin, Fan Que

“…Traditional visibility detection methods, primarily manual and instrumental, have been costly and imprecise. …”
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A one-stage anchor-free keypoints detection model for fast electric vehicle charging port detection and pose extraction by Feifei Hou, Qiwen Meng, Xinyu Fan, Yijun Wang

“…A key breakthrough lies in developing efficient methods to identify and locate charging ports. However, challenges such as high sensor costs, compromised robustness in complex environments, and stringent computational demands remain. …”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…These results highlight the effectiveness of swarm intelligence methods in enabling energy-efficient, performance-optimized deployment of electronic information sensing systems in intelligent WSNs.…”
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Research on Optimization of Magnetic Ranging by Mechanism & Intelligence by QIAN Hongyu, CHE Yang, WANG Xiufang, FENG Fuping, JIANG Chunlei

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From Accuracy to Vulnerability: Quantifying the Impact of Adversarial Perturbations on Healthcare AI Models by Sarfraz Brohi, Qurat-ul-ain Mastoi

“…Unlike prior studies, we conducted a quantitative evaluation on the impact of a Fast Gradient Sign Method (FGSM) attack on an optimized DL model designed for breast cancer detection to demonstrate how minor perturbations reduced the model’s accuracy from 98% to 53%, and led to a substantial increase in the classification errors, as revealed by the confusion matrix. …”
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Diagnosis of array antennas based on near-field data using Faster R-CNN by Boguang Yang, Yulun Wei, Jixiang Shi, Tao Hong, Liangyu Li, Kai-Da Xu

“…In this paper, a source reconstruction method for detecting failures in array antenna elements using near-field data based on Faster region-convolutional neural network (Faster R-CNN) is introduced. …”
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Optimization of helicopter and UAV coordinated SAR time by Ming Zhang, Ying Huo, Hanzhi Zhang, Jiale Duan, Faqiang Wen

“…The helicopter-UAV rescue time optimization, in which UAV is responsible for low-altitude detection task, include the remote TAL site selection model for UAV, the SAR task allocation model of UAV, and helicopter-UAV coordinated SAR time optimization model. …”
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Detection of Dental Anomalies in Digital Panoramic Images Using YOLO: A Next Generation Approach Based on Single Stage Detection Models by Uğur Şevik, Onur Mutlu

“…This study aims to develop and rigorously validate an advanced deep learning model to enhance diagnostic accuracy and efficiency in pediatric dentistry, providing an objective tool to support clinical decision-making. <b>Methods</b>: An initial comparative study of four state-of-the-art YOLO variants (YOLOv8, v9, v10, and v11) was conducted to identify the optimal architecture for detecting four common findings: Dental Caries, Deciduous Tooth, Root Canal Treatment, and Pulpotomy. …”
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Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence–Driven Clinical Prediction Model: Protocol fro... by Rutger van Mierlo, Bart Scheenstra, Joost Verbeek, Anke Bruninx, Petros Kalendralis, Inigo Bermejo, Andre Dekker, Arnoud van 't Hof, Marieke Spreeuwenberg, Laura Hochstenbach

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Optimization of the treatment of patients with severe chronic urticaria by Ye.M. Dytiatkovska, N.O. Nedohybchenko

“…All patients underwent a general clinical examination, quality of life indicators using the SKINDEX-29 questionnaire were studied; blood tryptase level once before the start of treatment using ImmunoCAP was determined, the level of total IgE in blood serum using an immunochemical method with electrochemiluminescence detection before and after the end of treatment was determined. …”
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Determination of optimal imaging parameters of hyperspectral images using the identification module by Chilikin Andrey, Pupin Daniil

“…The presented device is used for imaging process to detect fruit diseases at an early stage. Hyperspectral monitoring is a proven non-invasive method for detecting foetal damage. …”
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DAGIP: alleviating cell-free DNA sequencing biases with optimal transport by Antoine Passemiers, Stefania Tuveri, Tatjana Jatsenko, Adriaan Vanderstichele, Pieter Busschaert, An Coosemans, Dirk Timmerman, Sabine Tejpar, Peter Vandenberghe, Diether Lambrechts, Daniele Raimondi, Joris Robert Vermeesch, Yves Moreau

“…Our method improves cancer detection and copy number alteration analysis by alleviating the sources of variation that are not of biological origin. …”
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Gradient Boosting Feature Selection for Integrated Fault Diagnosis in Series-Compensated Transmission Lines by Rab Nawaz, Abdul Wadood, Khawaja Khalid Mehmood, Syed Basit Ali Bukhari, Hani Albalawi, Aadel Mohammed Alatwi, Muhammad Sajid

“…By optimizing each phase of data processing from feature extraction to model learning, the proposed system effectively addresses fault detection, classification, and localization as a multi-classification problem. …”
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Occurrence of Uncultured <i>Legionella</i> spp. in Treated Wastewater Effluent and Its Impact on Human Health (SCA.Re.S Project) by Osvalda De Giglio, Giusy Diella, Francesco Bagordo, Antonella Francesca Savino, Angelantonio Calabrese, Mariavirginia Campanale, Francesco Triggiano, Francesca Apollonio, Valentina Spagnuolo, Marco Lopuzzo, Tiziana Grassi, Maria Clementina Caputo, Silvia Brigida, Federica Valeriani, Vincenzo Romano Spica, Maria Teresa Montagna

“…<i>Legionella</i> was detected only with the molecular methods (except in one sample of effluent positive for <i>L. pneumophila</i> serogroup 6), which showed viable <i>Legionella pneumophila</i> and <i>L.…”
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Research on demodulation technology of fiber Bragg grating sensor based on generalized regression neural network by XIA Xiang, LI Xianliang, PAN Hua, YAN Dong, ZHANG Xiaofeng, ZHANG Yunhui

“…Aiming at the problems of large error and poor stability of traditional wavelength demodulation of fiber Bragg grating sensor, a wavelength peak detection method of fiber Bragg grating sensor based on generalized regression neural network and improved particle swarm optimization algorithm is proposed. …”
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On the Resolution of an Inverse Problem by Shape Optimization Techniques by Chahnaz Zakia Timimoun

“…We study the inverse problem of reconstructing ω using shape optimization methods by defining the Kohn-Vogelius cost functional. …”
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