Identification of unknown operating system type of Internet of Things terminal device based on RIPPER by Shichang Xuan, Dapeng Man, Wu Yang, Wei Wang, Jiashuai Zhao, Miao Yu

“…In this work, a passive operating system identification method based on RIPPER model is proposed. …”
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Agronomic character identification and ornamental value evaluation of dwarf ornamental tomato germplasm resources by ZHANG Zhongyan, HU Luwei, CHEN Jiawei, ZHU Zhujun, ZHU Biao

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Integrating experimental-based vulnerability mapping with intelligent identification of multi-aquifer groundwater salinization by Mohamed A. Yassin, Sani I. Abba, A.G. Usman, Syed Muzzamil Hussain Shah, Isam H. Aljundi, Shafik S. Shafik, Zaher Mundher Yaseen

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Rapid Identification Method for Concrete Defect Boundaries Based on Acoustic-Mode Gradient Analysis by Yong Yang, Peixuan Shen, Ziming Qi, Shiqi Liu

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Gastrointestinal Motility and Improvement Efficacy of Shenhuang Plaster Application on Shenque: Identification, Evaluation, and Mechanism by Yanan Shi, Jingming Xu, Bin Ding, Guiping Chen, Lu Jin, Liang Ke, Xiao Xu, JingXia Wang, Qiuhua Sun, Xiaohong Xu

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EXTRAPOLATION BY ATTRACTION METHOD FOR IDENTIFICATION OF TRACKS AND PLOTS IN SYSTEM OF SECONDARY RADAR INFORMATION PROCESSING by U. A. Aparovich, R. V. Bondarenko

“…The proposed extrapolation algorithm is based on the principle of gravity by analogy with the physical phenomena of charged particles attraction. Modeling shows that probabilities of correct identification calculated according to this algorithm significantly higher than the values calculated by the methods of linear and quadratic extrapolation. …”
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Damage identification in RC bridges by confronting two approaches: visual inspection and numerical analysis by Mohammed Ayad, Nadir Boumechra, Karim Hamdaoui

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Artificial Intelligence for Image-Based Identification of Osteoclasts and Assessment of Their Maturation—Using the OC_Identifier by Guofan Lv, Christiane Heinemann, Hans-Peter Wiesmann, Benjamin Kruppke

“…The developed AI used YOLOv5m models to analyze these cell types based on microscopic images. …”
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Intronic RNAscope probes enable precise identification of cardiomyocyte nuclei and cell cycle activity by Zhe Yu, Sen Zhang, Julius Bogomolovas, Ju Chen, Sylvia M. Evans

“…Abstract Cardiac regeneration studies have been plagued by technical challenges in unequivocally identifying cardiomyocyte (CM) nuclei in cardiac sections, crucial for accurate identification of cycling CMs. The use of antibodies to sarcomeric proteins is error-prone, the CM specificity of common nuclear markers is controversial, and utilizing genetically modified mouse models poses risk of inducing unintended cardiac phenotypes. …”
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Knowledge mapping and trend identification in UAV-enabled hybrid FSO/RF communication systems by Kamran Ali Memon, Khalid H. Mohammadani, Abdul Ghaffar, Khurrum Karim Qureshi, Muhammad Mahmood Ali

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Efficient slice anomaly detection network for 3D brain MRI Volume. by Zeduo Zhang, Yalda Mohsenzadeh

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Research on Parameter-Efficient Knowledge Graph Completion Methods and Their Performance in the Cybersecurity Field by Bin Chen, Hongyi Li, Ze Shi

“…As an advanced knowledge management and reasoning tool, knowledge graph technology can significantly enhance the efficiency of managing and analyzing cyberthreat intelligence, providing strong technical support for cybersecurity threat identification and situational awareness. …”
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Active identification and detection of external operator safety risk factors for smart grid based on deep learning by PENG Fang, LIU Tiantian, LU Weilong, PAN Jianhong, REN Junda

“…Aiming at the safety risk problems caused by the incorrect wearing of helmets, safety belts and illegal smoking of operators during the construction of power grid, this paper designs a detection and identification system for the safety risk caused by operators based on YOLOv7 deep learning model. …”
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Energy-Efficient Fall-Detection System Using LoRa and Hybrid Algorithms by Manny Villa, Eduardo Casilari

“…This study introduces a hybrid system that integrates a threshold-based model for preliminary detection with a deep learning-based approach that combines a CNN (Convolutional Neural Network) for spatial feature extraction with a LSTM (Long Short-Term Memory) model for temporal pattern recognition, aimed at improving classification accuracy. …”
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Learning efficient haptic shape exploration with a rigid tactile sensor array. by Sascha Fleer, Alexandra Moringen, Roberta L Klatzky, Helge Ritter

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Spatial spillover effects of swine insurance policy on swine production efficiency in China by Jingyue Feng, Wenbo Zhang, Lin Wang, Bo Hu, Fengjie Xie

“…China’s swine insurance policy serves as a key institutional mechanism for strengthening risk mitigation and resilience, rigorously evaluation of the policy’s impact on swine production efficiency is essential for optimizing agricultural insurance mechanisms and advancing sustainability in the swine industry.MethodsThis study treats the pilot implementation of the swine insurance policy as a quasi-natural experiment, drawing on panel data from 30 Chinese provinces over the years from 2005 to 2021, it employs a spatial difference-in-differences (SDID) model and a mediation effect model to empirically examine the impact of the swine insurance policy on swine production efficiency.ResultsThe results reveal that the swine insurance policy significantly improves swine production efficiency in the implementing provinces and generates substantial spatial spillover effects, the boundary of spatial effect decay is 250 km. …”
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Reinforcement learning for an efficient and effective malware investigation during cyber incident response by Dipo Dunsin, Mohamed Chahine Ghanem, Karim Ouazzane, Vassil Vassilev

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Advanced deep transfer learning techniques for efficient detection of cotton plant diseases by Prashant Johri, SeongKi Kim, Kumud Dixit, Prakhar Sharma, Barkha Kakkar, Yogesh Kumar, Jana Shafi, Muhammad Fazal Ijaz

“…After pre-processing the images of the dataset, their region of interest is obtained by applying feature extraction techniques such as the generation of the biggest contour, identification of extreme points, cropping of relevant regions, and segmenting the objects using adaptive thresholding.Results and DiscussionDuring experimentation, it is found that the EfficientNetB3 model outperforms in accuracy, loss, as well as root mean square error by obtaining 99.96%, 0.149, and 0.386 respectively. …”
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Leaf disease detection and classification in food crops with efficient feature dimensionality reduction. by Khasim Syed, Shaik Salma Asiya Begum, Anitha Rani Palakayala, G V Vidya Lakshmi, Sateesh Gorikapudi

“…This cost-effective approach can be integrated into precision agriculture systems, facilitating automated disease detection and monitoring, thereby enhancing crop yields and promoting sustainable farming practices. The proposed Efficient Labelled Feature Dimensionality Reduction utilizing CNN-BiLSTM (ELFDR-LDC-CNN-BiLSTM) model is compared to current models to show its effectiveness in reducing extracted features for leaf detection and classification tasks.…”
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Influence of high powder flow dynamics on the efficiency of laser-directed energy deposition by Hong Seok Kim, Sang Hu Park

“…A physics-based model is proposed to calculate powder incorporation efficiency into the melt pool as a function of feeding rate and key physical parameters—namely, the melting ratio of in-flight particles, melt pool size, and both the particle count and residence time on the melt pool surface. …”
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