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Visual commonsense reasoning with directional visual connections Research Articles

Yahong Han, Aming Wu, Linchao Zhu, Yi Yang,yahong@tju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.2000722

Abstract: To boost research into cognition-level visual understanding, i.e., making an accurate inference based on a thorough understanding of visual details, (VCR) has been proposed. Compared with traditional visual question answering which requires models to select correct answers, VCR requires models to select not only the correct answers, but also the correct rationales. Recent research into human cognition has indicated that brain function or cognition can be considered as a global and dynamic integration of local neuron connectivity, which is helpful in solving specific cognition tasks. Inspired by this idea, we propose a to achieve VCR by dynamically reorganizing the that is contextualized using the meaning of questions and answers and leveraging the directional information to enhance the reasoning ability. Specifically, we first develop a GraphVLAD module to capture to fully model visual content correlations. Then, a contextualization process is proposed to fuse sentence representations with visual neuron representations. Finally, based on the output of , we propose to infer answers and rationales, which includes a ReasonVLAD module. Experimental results on the VCR dataset and visualization analysis demonstrate the effectiveness of our method.

Keywords：视觉常识推理；有向连接网络；视觉神经元连接；情景化连接；有向连接

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Dynamic aspects of domination networks Personal View

Yu-xian LIU, Ronald ROUSSEAU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4, Pages 635-648 doi: 10.1631/FITEE.1800553

Abstract: A dynamic quantitative theory and measurement of power or dominance structures are proposed. Such power structures are represented as directed networks. A graph somewhat similar to the Lorenz curve for inequality measurement is introduced. The changes in the graph resulting from network dynamics are studied. Dynamics are operationalized in terms of added nodes and links. Study of dynamic aspects of networks is essential for potential applications in many fields such as business management, politics, and social interactions. As such, we provide examples of a dominance structure in a directed, acyclic network. We calculate the change in the D-measure, which is a measure expressing the degree of dominance in a network when nodes are added to an existing simple network.

Keywords： Domination Power structure Digraphs Network dynamics

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Decentralized fault-tolerant cooperative control of multipleUAVs with prescribed attitude synchronization tracking performance under directed communication topology Regular Papers

Zi-quan YU, Zhi-xiang LIU, You-min ZHANG, Yao-hong QU, Chun-yi SU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 5, Pages 685-700 doi: 10.1631/FITEE.1800569

Abstract:

In this paper, a decentralized fault-tolerant cooperative control scheme is developed for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and a directed communication network. To counteract in-flight actuator faults and enhance formation flight safety, neural networks (NNs) are used to approximate unknown nonlinear terms due to the inherent nonlinearities in UAV models and the actuator loss of control effectiveness faults. To further compensate for NN approximation errors and actuator bias faults, the disturbance observer (DO) technique is incorporated into the control scheme to increase the composite approximation capability. Moreover, the prediction errors, which represent the approximation qualities of the states induced by NNs and DOs to the measured states, are integrated into the developed fault-tolerant cooperative control scheme. Furthermore, prescribed performance functions are imposed on the attitude synchronization tracking errors, to guarantee the prescribed synchronization tracking performance. One of the key features of the proposed strategy is that unknown terms due to the inherent nonlinearities in UAVs and actuator faults are compensated for by the composite approximators constructed by NNs, DOs, and prediction errors. Another key feature is that the attitude synchronization tracking errors are strictly constrained within the prescribed bounds. Finally, simulation results are provided and have demonstrated the effectiveness of the proposed control scheme.

Keywords： Fault-tolerant control Decentralized control Prescribed performance Unmanned aerial vehicle Neural network Disturbance observer Directed topology

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Networking Architecture and Development Trend of Industrial Internet

Yu Xiaohui, Zhang Hengsheng, Peng Yan, Li Dong

Strategic Study of CAE 2018, Volume 20, Issue 4, Pages 79-84 doi: 10.15302/J-SSCAE-2018.04.013

Abstract:

As one of the three main function aspects of the industrial Internet, networks provide infrastructure for the all-round interconnection of industrial elements. The existing "two-layer and three-level" industrial network is difficult to meet the development needs of the new models and services of the industrial Internet. The emerging network technologies can promote the evolution of the network architecture. The intra-factory network is developing in directions of integration, openness, and flexibility. The services of the extra-factory network are universal, refined, and flexible. At the end, the paper describes the networking framework of the industrial Internet, and suggests that industrial enterprises build intra-factory networks according to requirements for business, real-time performance, transmission methods, etc., and build extra-factory external networks by selecting three dedicated lines and one networking mode according to development requirements of different services.

Keywords： intra-factory network extra-factory network openness integration

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The Dynamic Functional Network Connectivity Analysis Framework

Zening Fu, Yuhui Du, Vince D. Calhoun

Engineering 2019, Volume 5, Issue 2, Pages 190-193 doi: 10.1016/j.eng.2018.10.001

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Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9, Pages 1234-1246 doi: 10.1631/FITEE.2000426

Abstract:

It is necessary to construct an adaptive model to cope with process non-stationaries. In this study, a novel quality-related locally weighted soft sensing method is designed for non-stationary processes based on a Bayesian network with . Specifically, a is proposed where quality-oriented are extracted and further applied to a double-layer similarity measurement algorithm. The proposed soft sensing method tries to find a general approach for non-stationary processes via quality-related information where the concepts of local similarities and window confidence are explained in detail. The performance of the developed method is demonstrated by application to a numerical example and a debutanizer column. It is shown that the proposed method outperforms competitive methods in terms of the accuracy of predicting key quality variables.

Keywords：软测量；有监督贝叶斯网络；隐变量；局部加权建模；质量预测

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Industrial Wireless Control Networks: From WIA to Future

Haibin Yu, Peng Zeng, Chi Xu

Engineering 2022, Volume 8, Issue 1, Pages 18-24 doi: 10.1016/j.eng.2021.06.024

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Video summarization with a graph convolutional attention network Research Articles

Ping Li, Chao Tang, Xianghua Xu,patriclouis.lee@gmail.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6, Pages 902-913 doi: 10.1631/FITEE.2000429

Abstract: has established itself as a fundamental technique for generating compact and concise video, which alleviates managing and browsing large-scale video data. Existing methods fail to fully consider the local and global relations among frames of video, leading to a deteriorated summarization performance. To address the above problem, we propose a graph convolutional attention network (GCAN) for . GCAN consists of two parts, embedding learning and , where embedding learning includes the temporal branch and graph branch. In particular, GCAN uses dilated temporal convolution to model local cues and temporal self-attention to exploit global cues for video frames. It learns graph embedding via a multi-layer to reveal the intrinsic structure of frame samples. The part combines the output streams from the temporal branch and graph branch to create the context-aware representation of frames, on which the importance scores are evaluated for selecting representative frames to generate video summary. Experiments are carried out on two benchmark databases, SumMe and TVSum, showing that the proposed GCAN approach enjoys superior performance compared to several state-of-the-art alternatives in three evaluation settings.

Keywords：时序学习；自注意力机制；图卷积网络；上下文融合；视频摘要

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Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome Review

Peng Qi, Hua Ru, Lingyun Gao, Xiaobing Zhang, Tianshu Zhou, Yu Tian, Nitish Thakor, Anastasios Bezerianos, Jinsong Li, Yu Sun

Engineering 2019, Volume 5, Issue 2, Pages 276-286 doi: 10.1016/j.eng.2018.11.025

Abstract:

Maintaining sustained attention during a prolonged cognitive task often comes at a cost: high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or exhaustion, and a disengagement from the task at hand; it manifests as impaired cognitive and behavioral performance. In order to effectively reduce the undesirable yet preventable consequences of mental fatigue in many real-world workspaces, a better understanding of the underlying neural mechanisms is needed, and continuous efforts have been devoted to this topic. In comparison with conventional univariate approaches, which are widely utilized in fatigue studies, convergent evidence has shown that multivariate functional connectivity analysis may lead to richer information about mental fatigue. In fact, mental fatigue is increasingly thought to be related to the deviated reorganization of functional connectivity among brain regions in recent studies. In addition, graph theoretical analysis has shed new light on quantitatively assessing the reorganization of the brain functional networks that are modulated by mental fatigue. This review article begins with a brief introduction to neuroimaging studies on mental fatigue and the brain connectome, followed by a thorough overview of connectome studies on mental fatigue. Although only a limited number of studies have been published
thus far, it is believed that the brain connectome can be a useful approach not only for the elucidation of underlying neural mechanisms in the nascent field of neuroergonomics, but also for the automatic detection and classification of mental fatigue in order to address the prevention of fatigue-related human error in the near future.

Keywords： Mental fatigue Functional connectivity Graph theoretical analysis Brain network

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Pricing Based Adaptive Call Admission Control Algorithm for Wireless Networks

Zhang Xue

Strategic Study of CAE 2006, Volume 8, Issue 4, Pages 32-38

Abstract:

In order to efficiently and effectively control the use of wireless network resources, in this paper, according to the characteristic of adaptive multimedia applications in which bandwidths can be adjusted dynamically, and the influence of pricing on the users' behavior, an adaptive admission control algorithm integrated with pricing is proposed. The algorithm, in with the price is adjusted dynamically based on the current network conditions, is fit for the multi-priorilies services. Attempt is tried to make best balance between the efficiency and simplicity for the pricing scheme. Comparison of the performance of the proposed approach is made with the corresponding results of conventional systems where pricing is not taken into consideration in CAC process. The performance results verify the considerable improvement achieved by the integration of pricing with CAC in wireless networks.

Keywords： wireless networks adaptive call admission control microeconomic theory pricing connection level QoS

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Secure connectivity analysis in unmanned aerial vehicle networks None

Xin YUAN, Zhi-yong FENG, Wen-jun XU, Zhi-qing WEI, Ren-ping LIU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 3, Pages 409-422 doi: 10.1631/FITEE.1700032

Abstract: The distinctive characteristics of unmanned aerial vehicle networks (UAVNs), including highly dynamic network topology, high mobility, and open-air wireless environments, may make UAVNs vulnerable to attacks and threats. In this study, we propose a novel trust model for UAVNs that is based on the behavior and mobility pattern of UAV nodes and the characteristics of inter-UAV channels. The proposed trust model consists of four parts: direct trust section, indirect trust section, integrated trust section, and trust update section. Based on the trust model, the concept of a secure link in UAVNs is formulated that exists only when there is both a physical link and a trust link between two UAVs. Moreover, the metrics of both the physical connectivity probability and the secure connectivity probability between two UAVs are adopted to analyze the connectivity of UAVNs. We derive accurate and analytical expressions of both the physical connectivity probability and the secure connectivity probability using stochastic geometry with or without Doppler shift. Extensive simulations show that compared with the physical connection probability with or without malicious attacks, the proposed trust model can guarantee secure communication and reliable connectivity between UAVs and enhance network performance when UAVNs face malicious attacks and other security risks.

Keywords： Unmanned aerial vehicle networks (UAVNs) Trust model Secure connectivity Doppler shift

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Reducing power grid cascading failure propagation by minimizing algebraic connectivity in edge addition Research Articles

Supaporn LONAPALAWONG, Jiangzhe YAN, Jiayu LI, Deshi YE, Wei CHEN, Yong TANG, Yanhao HUANG, Can WANG,11821132@zju.edu.cn,wcan@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3, Pages 382-397 doi: 10.1631/FITEE.2000596

Abstract: Analyzing under various circumstances is generally regarded as a challenging problem. Robustness against failure is one of the essential properties of large-scale dynamic network systems such as s, transportation systems, communication systems, and computer networks. Due to the network diversity and complexity, many topological features have been proposed to capture specific system properties. For s, a popular process for improving a network’s structural robustness is via the topology design. However, most of existing methods focus on localized network metrics, such as node connectivity and edge connectivity, which do not encompass a global perspective of cascading propagation in a . In this paper, we use an informative global metric because it is sensitive to the connectedness in a broader spectrum of graphs. Our process involves decreasing the in a by minimizing the increase in its . We propose a topology-based greedy strategy to optimize the robustness of the . To evaluate the , we calculate the using MATCASC to simulate cascading line outages in s. Experimental results illustrate that our proposed method outperforms existing techniques.

Keywords： Network robustness Cascading failure Average propagation Algebraic connectivity Power grid

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Research on Nonlinear Combination Forecasting Approach Based on BP-AGA

Wang Shuo,Zhang Youfu,Jin Juliang

Strategic Study of CAE 2005, Volume 7, Issue 4, Pages 83-87

Abstract:

A nonlinear combination forecasting model was established by using neural network and accelerating genetic algorithm (AGA) in the paper. AGA was used to optimize the network parameters as BP approach was slow with training network. Optimization results of AGA were taken as original values of BP approach, the network was trained with BP approach. Network convergence rate was increased with running BP approach and AGA alternately. Meanwhile the part least problem was improved. Examples were presented finally, as a result, the forecasting precision high in evidence.

Keywords： neural network accelerating genetic algorithm nonlinear combination forecasting forecasting precision

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Designing a novel consensus protocol formultiagent systemswith general dynamics under directed networks Article

Hao-liang LI, Ren-nong YANG, Qiu-ni LI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8, Pages 1071-1081 doi: 10.1631/FITEE.1601422

Abstract: The consensus problem for general linear multi-agent systems (MASs) under directed topology is investigated. First, a novel consensus protocol based on proportional-integral-derivative (PID) control is proposed. Second, the consensus problem is converted into an asymptotic stability problem through transformations. Third, through a state projection method the consensus condition is proved and the explicit expression of the consensus function is given. Then, a Lyapunov function is constructed and the gain matrices of the protocol are given based on the linear matrix inequality. Finally, two experiments are conducted to explain the advantages of the method. Simulation results show the effectiveness of the proposed algorithm.

Keywords： Multi-agent Consensus PID control Linear matrix inequality

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Analysis of Sound Radiation of Two ConnectedElastic Rectangular Enclosure

Yao Haoping,Zhang Jianrun,Chen Nan,Sun Qinghong

Strategic Study of CAE 2007, Volume 9, Issue 3, Pages 41-46

Abstract:

The model of sound radiated from two connected rectangular enclosures consisting of one elastically supported flexible panel and five rigid panels is deduced by using Hamiltonian function and Rayleigh -Ritz method in this paper. By means of artificial springs along connected points of flexible panels, this model allows the consideration of a wide variety structure joint conditions. Numerical results on the radiation of sound are presented. These results are intended to investigate two main issues:one is that the direct force affects the radiation of sound more than the indirect force does, the other is that the translational stiffness at connected points affects the radiation of sound more than the rotational stiffness does.

Keywords： the radiation of sound connection rectangular enclosure coupling

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Title Author Date Type Operation

Visual commonsense reasoning with directional visual connections

Yahong Han, Aming Wu, Linchao Zhu, Yi Yang,yahong@tju.edu.cn

Journal Article

Dynamic aspects of domination networks

Yu-xian LIU, Ronald ROUSSEAU

Journal Article

Decentralized fault-tolerant cooperative control of multipleUAVs with prescribed attitude synchronization tracking performance under directed communication topology

Zi-quan YU, Zhi-xiang LIU, You-min ZHANG, Yao-hong QU, Chun-yi SU

Journal Article

Networking Architecture and Development Trend of Industrial Internet

Yu Xiaohui, Zhang Hengsheng, Peng Yan, Li Dong

Journal Article

The Dynamic Functional Network Connectivity Analysis Framework

Zening Fu, Yuhui Du, Vince D. Calhoun

Journal Article

Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network with latent variables

Journal Article

Industrial Wireless Control Networks: From WIA to Future

Haibin Yu, Peng Zeng, Chi Xu