Fast access authentication scheme for mobile IPv6 hierarchical network by Shan-shan SONG, Tao SHANG, Jian-wei LIU

“…Firstly, the scheme used the vector network address coding method to improve the home registration performance. …”
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Role of the Plenum of Russian Supreme Court in the judicial practice formation by Yu. S. Pestereva, I. G. Ragozina, E. I. Chekmezova

“…The issue related to the function of the decisions of the Plenum of Russian Supreme Court in the formation of a single vector of judicial practice has been and remains debatable. …”
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A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…Another potential FD vector is the mosaic leafhopper, Orientus ishidae, commonly found in agroecosystems. …”
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Machine Learning-Based Non-Invasive Prediction of Metabolic Dysfunction-Associated Steatohepatitis in Obese Patients: A Retrospective Study by Jie Chen, Bo Zhang, Yong Cheng, Yuanchen Jia, Biao Zhou

“…Various ML models, including K-nearest neighbors, linear support vector machine, radial basis function support vector machine, Gaussian process, random forest, multilayer perceptron, adaptive boosting, and naïve Bayes, were developed through cross-validation and hyperparameter tuning. …”
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Analysis of social networks content to identify fake news using stacked combination of deep neural networks by Yujie Li, Yushui Xiao, Yong Huang, Rui Ma

“…Both models generate individual predictions from the input features presented to them, and the predicted labels and the posterior probability vector for each of the models are combined to output a vector to be forwarded to the meta-learner (a MLP model). …”
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Elevating metaverse virtual reality experiences through network‐integrated neuro‐fuzzy emotion recognition and adaptive content generation algorithms by Oshamah Ibrahim Khalaf, Dhamodharan Srinivasan, Sameer Algburi, Jeevanantham Vellaichamy, Dhanasekaran Selvaraj, Mhd Saeed Sharif, Wael Elmedany

“…An inventive method that combines natural language processing adaptive content generation algorithms and neuro‐fuzzy‐based support vector machines natural language processing (SVM‐NLP) is proposed by researchers to meet this demand. …”
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Optimization of Calculating Invariants in Petri Nets to Support the Creation of Integration Testing Scenarios by M. G. Dorrer, V. V. Kurokhtin

“…The article describes a method of finding business process invariants basing on a given model in eEPC notation. …”
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Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…In addition, One-Class SVMs can be run smoothly on unspecialized hardware, removing the need for Graphics Processing Unit (GPU) usage. In cases where time and processing power are valuable resources, One-Class SVMs are able to minimize time spent on transit detection tasks while maximizing performance and efficiency.…”
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Approximate Schur Complement Preconditioners for Half-Quadratic Image Restoration With Zero Boundary Conditions by Chaojie Wang, Shuen Sun, Jie Chen, Biling Liu

“…In order to accelerate this process, we have proposed a preconditioning method based on approximations of the Schur complement and the blurring matrix. …”
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Deep learning for compressed sensing based sparse channel estimation in FDD massive MIMO systems by Yuan HUANG, Yigang HE, Yuting WU, Tongtong CHENG, Yongbo SUI, Shuguang NING

“…For FDD massive multi-input multi-output (MIMO) downlink system, a novel deep learning method for compressed sensing based sparse channel estimation was proposed, which was called convolutional compressed sensing network (ConCSNet).In the ConCSNet, the convolutional neural network was utilized to solve the inverse transformation process from measurement vector y to signal h and solve the underdetermined optimization problem through data-driven method without sparsity.Simulation results show that the algorithm can recover the channel state information in massive MIMO Systems with unknown sparsity more quickly and accurately.…”
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Research of Forming Trajectory of Multi-branches Rose Curve of Double Eccentric Sets Transmission for Orbital Forming Press Head by Gong Xiaotao, Geng Pei

“…The formation process of multi- branches rose curve trajectory motion are analyzed,the branch numbers of multi- branches rose curve and the law of the its trajectory are studied.…”
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Assessing the ability of output gap estimates to forecast inflation in emerging countries by Nwabisa Florence Ndzama

“…The multivariate Hodrick–Prescott filter and the structural vector autoregressive model produce the smallest forecast errors in most cases among the four output gap models considered. …”
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Vers une approche individu-centrée pour modéliser et simuler l’expression spatiale d’une maladie transmissible : la peste à Madagascar by Dominique Badariotti, Arnaud Banos, Vincent Laperrière

“…Since the introduction of plague in Madagascar by European settlers, research on the Madagascar epidemiologic cycle has been focusing upon the comprehension of the transmission process between the main host, rats, and the secondary one, humans, via a vector, fleas. …”
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Automatic detection method of software upgrade vulnerability based on network traffic analysis by Jinhui TENG, Yan GUANG, Hui SHU, Bing ZHANG

“…During the software upgrade process,the lack of authentication for upgrade information or packages can lead to remote code execution vulnerabilities based on man-in-the-middle attack.An automatic detection method for upgrading vulnerabilities was proposed.The method described the upgrade mechanism by extracting the network traffic during the upgrade process,then matched it with the vulnerability feature vector to anticipate upgrading vulnerabilities.In a validation environment,the man-in-the-middle attack using the portrait information was carried out to verify the detection results.In addition,an automatic vulnerability analysis and verification system based on this method was designed.184 Windows applications samples was test and 117 upgrade vulnerabilities were detected in these samples,which proved validity of the method.…”
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Transition énergétique et hydrogène : le Living Lab ou l’ébauche d’une recherche participative by Rudy Amand, Pauline Ducoulombier, François Millet

“…Engaging institutional actors, participants, but also organizers and researchers in a process approaching participatory research, this initiative was supposed to facilitate a "common" ownership of hydrogen through the development of use scenarios mobilizing this energy vector and their prototyping. …”
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Research Progress on Digestive Behavior and Release Characteristics of Protein-Flavone Delivery System by Hao MA, Zhiyuan YANG, Huiying DU, Wenya MENG, Yuru WU, Jing LI, Kang LIU

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MiR-2284b regulation of α-s1 casein synthesis in mammary epithelial cells of dairy goats by Jinxing Hou, Wenfei Li, Xiaolong Xu, Ao Sun, Ganggang Xu, Zefang Cheng, Haoyuan Zhang, Xiaopeng An

“…Using GMECs (goat mammary epithelial cells) as the research object, the CHECK2 vector of the CSN1S1 gene and the overexpression vector of pcDNA 3.1 were constructed, and the mimics of miR-2284b and the interfering RNA of CSN1S1 were synthesized. …”
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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…To fill this research gap, this study developed 15 models comprising five machine learning methods: regression trees, support vector regression, Gaussian process regression, bagged trees, and boosted trees, and three optimization algorithms: random search, grid search, and Bayesian optimization. …”
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Two-dimensional QSAR-driven virtual screening for potential therapeutics against Trypanosoma cruzi by Naseer Maliyakkal, Sunil Kumar, Ratul Bhowmik, Harish Chandra Vishwakarma, Prabha Yadav, Bijo Mathew

“…In our study, we developed a standardized and robust machine learning-driven QSAR (ML-QSAR) model using a dataset of 1,183 Trypanosoma cruzi inhibitors curated from the ChEMBL database to speed up the drug discovery process. Following the calculation of molecular descriptors and feature selection approaches, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest (RF) models were developed and optimized to elucidate and predict the inhibition mechanism of novel inhibitors. …”
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Machine learning in assessing the association between the size and structure of the ascending aortic wall in patients with aortic dilatation of varying severity by V. E. Uspenskiy, V. L. Saprankov, V. I. Mazin, D. G. Zavarzina, A. B. Malashicheva, O. B. Irtyuga, O. M. Moiseeva, M. L. Gordeev

“…Standard paraclinical investigations and pathological examination of the VA wall were used. Statistical processing was carried out in the SPYDER 4.1.5 environment (Python 3.8), and included univariate correlation analysis, logistic regression analysis, as well as supervised machine learning (ML) methods (support vector machine, k-nearest neighbor method, random forest).Results. …”
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