DETERMINATED SIGNALS MATHEMATICAL MODELS ON THE BASIS OF PRIMITIVE FUNCTION SYSTEMS by V. N. Isakov

“…The module interface is designed for module private use (for example, as a computer reference guide) or for the external program application, for example, as a window to provide a signal type and signal parameters setting selection for users. …”
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Research on Transmission Error of Hypoid Gear based on Real Tooth Surface by Yimin Mo, Renjie Mo, Qiming Li, Jie Liu, Junjian Yang, Yecai Huang

“…Aiming at the inconsistency evaluation standards caused by using the gear designed by theory for simulation and using the gear produced by actual production for roll inspection certificate test，by using the NURBS surface fitting method，the real tooth surface is reconstructed and the construct of the 3D model in CATIA software is carried out. …”
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Multi-view graph neural network for fraud detection algorithm by Zhuo CHEN, Miao ZHU, Junwei DU

“…Aiming at the problem that in the field of fraud detection, imbalance labels and lack of necessary connections between fraud nodes, resulting in fraud detection tasks not conforming to the hypothesis of homogeneity of graph neural networks, multi-view graph neural network for fraud detection (MGFD) algorithm was proposed.First, A structure-independent encoder was used to encode the attributes of nodes in the network to learn the difference between the fraud node and the normal node.The hierarchical attention mechanism was designed to integrate the multi-view information in the network, and made full use of the interaction information between different perspectives in the network to model the nodes on the basis of learning differences.Then, based on the data imbalance ratio sampled subgraph, the sample was constructed according to the connection characteristics of fraud nodes for classification, which solved the problem of imbalance sample labels.Finally, the prediction label was used to identify whether a node is fraudulent.Experiments on real-world datasets have shown that the MGFD algorithm outperforms the comparison method in the field of graph-based fraud detection.…”
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Nonlinear Dynamics of Helicopter Planetary Gear-rotor System Caused by Stiffness Variation by Lanlan Hou, Mingqiang Li, Guosheng Wang, Lingyun Lai, Hao Chen, Yuping Huang

“…The research provides a reference of undesirable torsional behaviors in dynamic designing and vibration controlling for planetary gears-rotor systems in helicopter main reducer transmission.…”
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Ensemble Classification Approach for Sarcasm Detection by Jyoti Godara, Isha Batra, Rajni Aron, Mohammad Shabaz

“…The four ensemble classifiers are designed with the objective of detecting the sarcasm. …”
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An intrusion detection method based on depthwise separable convolution and attention mechanism by Zhifei ZHANG, Feng LIU, Yiyang GE, Shuo LI, Yu ZHANG, Ke XIONG

“…In order to improve the accuracy of multi-classification in network intrusion detection, an intrusion detection method was proposed based on depthwise separable convolution and attention mechanism.By constructing a cascade structure combining depthwise separable convolution and long-term and short-term memory networks, the spatial and temporal features of network traffic data can be better extracted.A mixed-domain attention mechanism was introduced to enhance the detection performance.To solve the problem of low detection rate in some samples, a data balance strategy based on the combination of the variational auto-encoder (VAE) the generative adversarial network (GAN) and was designed, which can effectively cope with imbalanced datasets and improve the adaptability of the proposed detection method.The experimental results show that the proposed method is able to achieve 99.80%, 99.32%, and 83.87% accuracy on the CICIDS-2017, NSL-KDD and UNSW-NB15 datasets, which is improved by 0.6%, 0.5%, and 2.3%, respectively.…”
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Event Related Potentials and Serial List Picture Memory in Parkinson’s Patients by M. S. Korsnes, I. Reinvang

“…The subjects were tested for recognition of abstract spatial designs and words after a 5 s retention interval. …”
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Fault Diagnosis Method Based on MTF-ResDSCNN Two-dimensional Image by Hu Mengnan, Yang Xiwang, Huang Jinying, Hu Hongjun, Wang Cheng

“…In order to effectively capture the fault features contained in the vibration signals of the rotating machinery and complete the fault diagnosis task efficiently, a fault diagnosis model combining two-dimensional image features and lightweight neural network is designed. Firstly, the collected one-dimensional vibration signals are decomposed by modified ensemble empirical mode decomposition (MEEMD) to obtain the intrinsic mode function (IMF) components, and the corresponding IMF components are selected for sum reconstruction to enhance the amplitude fluctuation of vibration signals. …”
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Comparative evaluation between two hybrid local anesthetics in lower third molar extraction: A retrospective study by Sourav Kumar, Nayak Dipti, Kumar Shashank, Khan Musaab, Kumari Shalini, Chauhan Pranshu

“…Aims: This study was designed to compare pain, swelling, and mouth opening in 4% articaine with dexamethasone and 2% lignocaine and dexamethasone. …”
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Data quality optimized online task allocation method for mobile crowdsensing by Wei ZHANG, Zhuo LI, Xin CHEN

“…Optimization of the perceived quality and the recruitment of user are two important issues of mobile crowdsensing.As the amount of data increases rapidly,perceived data becomes redundant,and perceived quality is at risk of decreasing.A mechanism of task assignment based on the perceptive quality optimization was proposed to improve the perceived quality under the condition of full coverage.The clustering algorithm was used to evaluate the truth value of the task and quantify the quality of the user data.Based on Thompson sampling algorithm and greedy algorithm,a user recruitment strategy was designed and implemented to optimize the perceived quality on the basis of ensuring the spatial coverage of the task.The performance of Thompson based user recruit (TSUR) algorithm was simulated and analyzed that compared with the existing algorithms of BBTA and basic user recruitment (BUR).Experiments show that in the same area,compared with bandit-based task assignment (BBTA) algorithm and BUR algorithm,the quality of the cumulative sensing data was improved by 16% and 20%,and the spatial coverage was improved by 30% and 22%.…”
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Services selection based on trust evolution and union for cloud computing by HU Chun-hua1, LIU Ji-bo1, LIU Jian-xun3

“…It was difficult for the service consumers to obtain high-quality composite services because of the existence of false or malicious service nodes in cloud computing environment.A novel cloud service-composition method based on the trust span tree was proposed.The trust relationship could be built after many times credible interaction between ser-vices requester and provider,and the trust union would be formed through the credible relationship evolution.So that the uncertain or malicious service should be excluded from the trust span tree,and the service composition would be carried out in a trust environment.At the same time,the measuring strategy of trust relationship among cloud services based on information entropy was designed,which could resolve the deficiencies of the trust parameter analysed by simply weighted angle in the previous studies.The experimental result shows that the method proposed in this paper is more su-perior in credibility and security,comparing to the traditional services selection methods.…”
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Un modèle-outil pour représenter le savoir technopédagogique disciplinaire des enseignants by Sylviane Bachy

“…In order to establish the different profiles of teachers we designed a questionnaire to test the component and the relationships. …”
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Iterative rake equalization method for low-complexity OTSM in high-speed mobile environment by Guojun LI, Kun LONG, Changrong YE, Jiawen LIANG

“…Aiming at the problems of poor anti-noise performance and high computational complexity of the existing orthogonal time sequency multiplexing (OTSM) equalization methods, a low-complexity iterative rake equalizer based on maximum ratio combining (MRC) was proposed.The main idea was to use MRC to iteratively extract and coherently combine the received multipath components of the transmitted symbols in the delay-time domain to improve the signal-to-noise ratio of the combined signal.In order to speed up the convergence of the MRC iterative algorithm, a single-tap time-frequency equalizer was designed to provide an initial estimate, and then combined with an external error correction code to further improve the bit error performance.The simulation results show that the performance of the iterative rake equalizer based on MRC is significantly better than that of the LMMSE linear equalizer, and the performance and computational complexity are greatly improved compared with the currently widely used Gauss-Seidel (GS) iterative equalizer.…”
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Fixed-Time Trajectory Tracking Control of Autonomous Surface Vehicle with Model Uncertainties and Disturbances by Jiawen Cui, Haibin Sun

“…The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). …”
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Research on 5G MEC security assessment system and method by Qiucheng LU, Jinhui TANG, Congying BAO, Hao WU, Yusun FU

“…Multi-access edge computing (MEC) is deployed at the edge of the network, enabling efficient and fast data processing in mobile networks, while also undertaking important security functions, making MEC a prime target for attackers.Therefore, MEC nodes will face huge security risks.How to accurately evaluate and quantify MEC security capabilities is an urgent issue to be solved.For accurately evaluating and quantifying MEC security capabilities, the MEC safety assessment system was proposed in combination with MEC safety risks.The assessment indicators selected in the assessment system comprehensively reflect the basic characteristics of MEC and its complete safety capability.Based on this evaluation system, the MEC security evaluation method was designed by using the analytic hierarchy process (AHP) and fuzzy evaluation, the MEC vulnerability scoring system was creatively proposed, and the evaluation indicators were provided based on the results of MEC vulnerability scoring system, the MEC security capability quantification value was finally calculated.The experimental result proves the effectiveness of the method.…”
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DOES HEALTH EXPENDITURE IMPACTS ON ECONOMIC GROWTH IN NIGERIA? by BENEDICT AZU, SHEDRACK ONYEKA AGBOBU

“… A nation with healthy people is considered a wealthy nation. This study is designed to evaluate the impact of health expenditure on education attainment and economic growth in Nigeria. …”
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Block-chain abnormal transaction detection method based on adaptive multi-feature fusion by Huijuan ZHU, Jinfu CHEN, Zhiyuan LI, Shangnan YIN

“…Aiming at the problem that the performance of intelligent detection models was limited by the representation ability of original data (features), a residual network structure ResNet-32 was designed to automatically mine the intricate association relationship between original features, so as to actively learn the high-level abstract features with rich semantic information.Low-level features were more transaction content descriptive, although their distinguishing ability was weaker than that of the high-level features.How to integrate them together to obtain complementary advantages was the key to improve the detection performance.Therefore, multi feature fusion methods were proposed to bridge the gap between the two kinds of features.Moreover, these fusion methods can automatically remove the noise and redundant information from the integrated features and further absorb the cross information, to acquire the most distinctive features.Finally, block-chain abnormal transaction detection model (BATDet) was proposed based on the above presented methods, and its effectiveness in the abnormal transaction detection is verified.…”
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Regularized Multioutput Gaussian Convolution Process for Chemical Contents Data Imputation in Sintering Raw Materials by Wei Liu, Cailian Chen, Junpeng Li, Xinping Guan

“…Moreover, the penalization terms are designed to weaken the false relationship between these outputs. …”
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Service customized networking by Yun-jie LIU, Tao HUANG, Jiao ZHANG, Jiang LIU, Hai-peng YAO, Ren-chao XIE

“…Today's Internet faces many challenges,two of which need to be addressed urgently.One is that most band-width is taken by OTT services,and the other one is that the content in the Internet is highly redundant.To address these two problems,a novel future Internet architecture,named as service customized networking (SCN),is proposed to pro-vide differentiated services.SCN is designed based on the software-defined networking (SDN) technology.It inherits the two advantages of SDN,that is,separation of control and data plane and programmable networking.Besides,SCN adds the function of network virtualization,and intelligent content scheduling.SCN avoids OTT services taking too much bandwidth through employing the network virtualization technology to provide differentiated services.Besides,SCN ef-fectively eliminates content redundancy by intelligent content scheduling.The results of experiments conducted on a real small-scale testbed indicate that SCN indeed provides differentiated services for different users and largely reduces con-tent redundancy.…”
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Objective assessment of communication speech interference effect based on feature fusion by Yun LIN, Huaitao XU, Sen WANG, Sicheng ZHANG, Long ZHUANG

“…In view of the objective assessment problem of the effect of communication speech interference, methods based on multi-measurements and multimodal fusion were proposed.First, the interfered speech was preprocessed by the endpoint detection algorithm and time warping algorithm.Then, the content of speech was extracted and performed measurement calculated with the standard speech to obtain five kinds of measure.After the fusion of five measures, random forest model was used to assessed the quality level.Finally, a neural network model based on residual structure was designed combined multimodal fusion technique, which fused the graph domain and measure domain features of the interfered speech data and performed quality level assessment.Experimental results show that the accuracy of two methods have reached more than 90%.Among them, the multimodal assessment method improves the accuracy by about 3.269% compared with the existing research methods, which proves that it has a better performance.…”
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