Research and Design of an Airfield Runway FOD Detection System Based on WSN by Li Ang

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Study on the burial depth calculation method for AC submarine cable based on the surface optical fiber monitoring temperature by Qishun Li, Yanpeng Hao, Peng Zhang, Haotian Tan, Lin Yang

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SecuNet 4D a comprehensive framework for distributed SDN security and resilience by Sumit Badotra, Mohan Gurusamy

“…In this research, we propose a unified framework, SecuNet-4D Detection, designed for defense, distribution, and dynamic adaptation in distributed SDN systems. …”
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Resource scheduling based on routing tree and detection matrix for Internet of things by Hongying Bai, Xiaotong Zhang, Yuxin Liu, Yingdong Xie

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Distribution, Occupancy, and Habitat of the Endangered Carolina Madtom: Implications for Recovery of an Endemic Stream Fish by W. Robert Cope, Thomas J. Kwak, Tyler R. Black, Krishna Pacifici, Jennifer M. Archambault, W. Gregory Cope

“…To provide critical information to guide Carolina Madtom conservation and recovery strategies, we surveyed 36 sites (75 locations) in both basins to (1) determine the current distribution of the Carolina Madtom, (2) develop occupancy models to estimate probability of detection and occurrence of the species throughout its range, and (3) determine its instream habitat use and suitability. …”
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Monitoring of the state of electromagnetic fuel injectors of gasoline engines with distributed fuel injection systems by G. N. Votinov, D. V. Maltsev, D. S. Repetsky

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Faulty feeder selection based on improved Hough transform in resonant grounded distribution networks by Xiaowei Wang, Xinyu Qu, Liang Guo, Zhihua Zhang, Yizhao Wang, Peng Wang

“…Secondly, using the Hough transform to detect IMFK, obtaining the fitted straight line and IMFK angle during the fault's initial stage. …”
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DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium by Anichur Rahman, Md. Jahidul Islam, Ziaur Rahman, Md. Mahfuz Reza, Adnan Anwar, M. A. Parvez Mahmud, Mostofa Kamal Nasir, Rafidah Md. Noor

“…Secured communication platform or channel has been highlighted as a key requirement for a reliable condominium which can be ensured by the utilization of the advanced techniques and platforms like Software-Defined Network (SDN), Network Function Virtualization (NFV) and Blockchain (BC). …”
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Epidemiological study of the serology and geographic distribution of abortion causative agents in aceh cows in Indonesia by Muhammad Hanafiah, Amalia Sutriana, Teuku Zahrial Helmi, Ruhul Fajriah, Happy Mulyana, Cut Nanda Sabila, Nadhira Dewantara

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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…In addition, by replacing the original CIOU loss function with the Focal–EIOU loss function, the problem of sample imbalance is solved and the detection performance of the model in complex scenarios is improved. …”
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Generative adversarial local density-based unsupervised anomaly detection. by Xinliang Li, Jianmin Peng, Wenjing Li, Zhiping Song, Xusheng Du

“…Existing generative adversarial nets (GANs)-based anomaly detection methods overlook the importance of local density, limiting their effectiveness in detecting anomaly objects in complex data distributions. …”
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Evidence of Interaction between Ion-scale Waves and Ion Velocity Distributions in the Solar Wind by Yogesh, Leon Ofman, Scott A. Boardsen, Kristopher Klein, Mihailo Martinović, Viacheslav M. Sadykov, Jaye L. Verniero, Niranjana Shankarappa, Lan K. Jian, Parisa Mostafavi, Jia Huang, K. W. Paulson

“…During PSP Encounter 17 (at 11.4 R _s ) on 2023 September 26, the PSP/FIELDS instrument detected enhanced ion-scale wave activity associated with deviations from local thermodynamic equilibrium in ion velocity distribution functions (VDFs) observed by the PSP/Solar Probe Analyzers-Ion. …”
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Spatial Cluster Detection Under Dependent Random Environmental Effects by Walguen Oscar, Jean Vaillant

“…The environmental effects here represents unobserved covariates, as opposed to observed covariates whose observations are used via the link function in the model. These random effects are modeled by means of spatial copula with margins distributed according to a Gamma distribution. …”
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SRM-YOLO for Small Object Detection in Remote Sensing Images by Bin Yao, Chengkun Zhang, Qingxiang Meng, Xiandong Sun, Xuyang Hu, Lu Wang, Xilai Li

“…Small object detection presents significant challenges in computer vision, often affected by factors such as low resolution, dense object distribution, and complex backgrounds, which can lead to false positives or missed detections. …”
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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…The latter constructs a prediction set on which a given guarantee for detection will be obtained. First, we define a loss function for each calibration sample to quantify detection error rates. …”
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Automatic detection and counting of wheat spike based on DMseg-Count by Hecang Zang, Yilong Peng, Meng Zhou, Guoqiang Li, Guoqing Zheng, Hualei Shen

“…Finally, the total loss function was constructed to optimize the model. The test results showed that the mean absolute error (MAE) and root mean square error (RMSE) of the proposed DMseg-Count model were 5.79 and 7.54, respectively, which were 9.76 and 10.91 higher than the standard distribution matching for crowd counting (DM-Count) model. …”
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A YOLO-Based Method for Head Detection in Complex Scenes by Ming Xie, Xiaobing Yang, Boxu Li, Yingjie Fan

“…Firstly, in complex scenes, head detection typically involves a large number of small objects that are randomly distributed. …”
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Change-Point Estimation and Detection for Mixture of Linear Regression Models by Wenzhi Zhao, Tian Cheng, Zhiming Xia

“…This paper studies the estimation and detection problems in the mixture of linear regression models with change point. …”
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Music Emotion Detection Using Hierarchical Sparse Kernel Machines by Yu-Hao Chin, Chang-Hong Lin, Ernestasia Siahaan, Jia-Ching Wang

“…For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…In industrial detection scenarios, achieving high accuracy typically relies on extensive labeled datasets, which are costly and time-consuming. …”
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