This paper describes an approach to designing-fuzzy if-then rules for the fuzzy-controlled static var compensator (FCSVC) in a three-phase electric power system. In general, it is very difficult to control the rms lin...
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This paper describes an approach to designing-fuzzy if-then rules for the fuzzy-controlled static var compensator (FCSVC) in a three-phase electric power system. In general, it is very difficult to control the rms line voltage in the three-phase ac circuit. We propose the FCSVC system to control the voltage. FCSVC is an rms line voltage stabilizer using three static var compensators (SVC) which are controlled by a fuzzy logic controller (FLC). Moreover, we propose an easier and more efficient approach to designing the fuzzy if-then rules of FCSVC. The effectiveness of the FCSVC described in this paper is verified by the experimental results. (C) Elsevier Science Inc. 1997.
Audio-visual emotion recognition, integrating information from various sources, enhances the comprehensive understanding and analysis of human emotions. However, existing methods in this field primarily focus on featu...
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Audio-visual emotion recognition, integrating information from various sources, enhances the comprehensive understanding and analysis of human emotions. However, existing methods in this field primarily focus on feature fusion, often overlooking the equally crucial stage of feature extraction. Typically, these methods employ pre-trained models to extract features during the initial phase, complicating modality-specific feature extraction and increasing system complexity and coordination challenges, which hinder effective audio-visual feature fusion. To address these issues, we propose an end-to-end audio-visual emotion recognition model, EAVFormer. For the audio modality, we input raw audio signals along with a mix of mel spectrograms and Mel Frequency Cepstral Coefficients (MFCCs), employing a hierarchical transformer technique that facilitates both shallow local and deep global feature extraction to fully harness complementary acoustic information, significantly enhancing the acoustic modality’s contribution. For the visual modality, we input raw video frames and employ a hierarchical transformer feature extraction method that integrates three-dimensional convolution and spatio-temporal self-attention mechanisms to address spatial and temporal redundancies and dependencies, thereby enhancing the expression of dynamic visual information. In the modal fusion stage, we construct dual-modality representations and encode inter-modal information while preserving modality-specific and meaningful intra-modal features. Testing on three popular datasets RAVDESS, CREMA-D, and CMU-MOSEI demonstrates that EAVFormer surpasses existing state-of-the-art methods in audio-visual emotion recognition accuracy, achieving rates of 95.17%, 86.13%, and 78.22%, respectively.
In recent years, China has witnessed considerable achievements in the production of domesticallydesigned CPUs and DSPs. Owing to fifteen years of hard work that began in 2001, significant progress has been made in Chi...
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In recent years, China has witnessed considerable achievements in the production of domesticallydesigned CPUs and DSPs. Owing to fifteen years of hard work that began in 2001, significant progress has been made in Chinese domestic CPUs and DSPs, primarily represented by Loongson and Shen Wei *** parts of the CPU design techniques are comparable to the world’s most advanced designs. A special issue published in Scientia Sinica I nf ormationis in April 2015, is dedicated to exhibiting the technical advancements in Chinese domestically-designed CPUs and DSPs. The content in this issue describes the design and optimization of high performance processors and the key technologies in processor development; these include high-performance micro-architecture design, many-core and multi-core design, radiation hardening design, highperformance physical design, complex chip verification, and binary translation technology. We hope that the articles we collected will promote understanding of CPU/DSP progress in China. Moreover, we believe that the future of Chinese domestic CPU/DSP processors is quite promising.
Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural net...
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Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.
Smart grid is considered as a promising approach to solve the problems of carbon emission and energy crisis. In smart grid, the power consumption data are collected to optimize the energy ***, security issues in commu...
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Smart grid is considered as a promising approach to solve the problems of carbon emission and energy crisis. In smart grid, the power consumption data are collected to optimize the energy ***, security issues in communications still present practical concerns. To cope with these challenges, we propose EFFECT, an efficient flexible privacy-preserving aggregation scheme with authentication in smart grid. Specifically, in the proposed scheme, we achieve both data source authentication and data aggregation in high efficiency. Besides, in order to adapt to the dynamic smart grid system, the threshold for aggregation is adjusted according to the energy consumption information of each particular residential area and the time period, which can support fault-tolerance while ensuring individual data privacy during *** security analysis shows that our scheme can satisfy the desired security requirements of smart *** addition, we compare our scheme with existing schemes to demonstrate the effectiveness of our proposed scheme in terms of low computational complexity and communication overhead.
Designing safe controllers is crucial and notoriously challenging for input-constrained safety-critical control systems. Backup control barrier functions offer an approach for the construction of safe controllers onli...
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The x ad hoc network (xANET) termed as a family of ad hoc networks, including mobile ad hoc network (MANET), vehicular ad hoc network (VANET), flying ad hoc network (FANET) and satellite ad hoc network (SANET), has fo...
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Recent works on the application of Physics-Informed Neural Networks to traffic density estimation have shown to be promising for future developments due to their robustness to model errors and noisy data. In this pape...
CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computationa...
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CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.
With the rapid development in Internet of Thing technology, the security issues have become increasingly prominent. There are many problems and shortcomings in applying current security mechanisms to the Internet of T...
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With the rapid development in Internet of Thing technology, the security issues have become increasingly prominent. There are many problems and shortcomings in applying current security mechanisms to the Internet of Thing. In this article we build network security architecture by presenting combination of IBE and PKI/CA in the Internet acquisition and transport layer. With the KDC security certification, the node open parameters and the security of the private key of the node with the PKG distribution are implemented, and the nodes and node data transmission together are effectively protected. We also enable the secure authentication and encrypted transmission by PKI/CA in the middle of certification in aggregation nodes and network data processing. Moreover we propose the key management strategy of private key generator and realize the publication of PKG parameter and the fast distribution, update, and withdraw process of private key, which further ensure secure data network transmission.
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