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作者： He, Yefeng Ma, Wenping Ministry of Education Key Lab. of Computer Network and Information Security Xidian University Xi'an 710071 China School of Communication and Information Engineering Xi'an Institute of Post and Telecommunications Xi'an 710121 China

ISBN: (纸本)9789881701282

In order to respond to algebraic attacks, it is important to construct Boolean functions with high algebraic immunity of the graphs. In this paper, the complicated problem of algebraic immunity of the graph is converted to the simpler problem of annihilators of the single-output assistant function. Based on this, we propose a new method for constructing single-and multi-output Boolean functions with high algebraic immunity of the graphs. This method can also give many more general single-output Boolean functions with maximum algebraic immunity.

关键词： Boolean functions

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QoS-based data aggregation technology in wireless sensor networks

QoS-based data aggregation technology in wireless sensor net...

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2011 WASE Global Conference on Science Engineering, GCSE 2011

作者： Chen, Zhengyu Yang, Geng Li, Guohua Xu, Jian Key Lab. of Broadband Wireless Communication and Sensor Network Technology Ministry of Education College of Computer Science and Technology Nanjing University of Post and Telecommunications Nanjing 210046 China School of Information Technology Jinling Institute of Technology Nanjing 211169 China

ISBN: (纸本)9783037852903

The main goal of data-aggregation algorithms in wireless sensor networks (WSNs) is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this article, we focus on QoS-based data-aggregation problems in WSNs. Firstly, we provide a definition of the different QoS parameters for data aggregation, such as energy efficiency, network lifetime, data latency and data quality. Then, we compare the different algorithms on each QoS parameter, describe the main features of each algorithm, and highlight the trade-offs between each parameter. Finally, we conclude with possible future research directions on QoS-based data aggregation in WSNs.

关键词： Wireless sensor networks

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Android malware detection based on permission and behavior analysis

Android malware detection based on permission and behavior a...

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International Conference on Cyberspace Technology, CCT 2014

作者： Qin, Zhongyuan Xu, Yuqing Di, Yuxing Zhang, Qunfang Huang, Jie School of Information Science and Engineering Southeast University Nanjing Jiangsu China Key Lab of Information Network Security Ministry of Public Security Shanghai China Communication Department Nanjing Institute of Artillery Corps Nanjing Jiangsu China Computer Department Nanjing Institute of Artillery Corps Nanjing Jiangsu China

ISBN: (纸本)9781849199285

The development of mobile Internet and application store accelerates the spread of malicious applications on smartphones, especially on Android platform. In this paper, we propose an integrated Android malware detection scheme, combining permission and behavior analysis. For APK files which had been detected, their MD5 values are extracted as signature for detection. For APK files which had not been detected, detection is carried based on permission and behavior analysis. Behavior analysis contained taint propagation analysis and semantic analysis. Experiment results show that this system can detect the malware of privacy stealing and malicious deduction successfully.

关键词： Android malware

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The Proof is in the Pudding: Decision-Oriented Machine-Type Wireless Video Transmission

The Proof is in the Pudding: Decision-Oriented Machine-Type ...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Song, Jie Gao, Yun Wu, Dan Zhou, Liang Qian, Yi Nanjing University of Posts and Telecommunications Ministry of Education Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing China Army Engineering University of Pla Institute of Communications Engineering Nanjing China University of Nebraska-Lincoln Department of Electrical and Computer Engineering Lincoln United States

ISBN: (纸本)9798350351255

With the rise of the Internet of Everything, machine-type wireless video applications like intelligent surveillance are increasingly becoming mainstream network services. However, the massive transmission of video streams heavily burdens wireless networks. Existing methods typically establish a correlation between the transmitted content and the quality of experience or service, making it challenging to balance trade-offs among decision quality, bandwidth utilization, and latency requirements. To address this issue fundamentally, this paper proposes a novel perspective by designing wireless video transmission strategies from the angle of decision quality, where only the content that impacts the decision outcomes is transmitted. The highlight of this paper is designing a lightweight yet efficient binary classifier that predicts whether the current content will change decision outcomes based on content discrepancies, measured only through pixel-level differences and macroblock-level similarity. Furthermore, these discrepancies can be used to distinguish the background, thereby further saving bandwidth by reusing the background information. Additionally, a fine-tuning module is incorporated to flexibly update the classifier model, ensuring adaptability across various scenarios. Extensive results demonstrate that the proposed strategy achieves over 81% redundant bandwidth savings while maintaining decision quality and catering to strict latency requirements on computation-constrained devices. © 2024 IEEE.

关键词： Television transmission

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Normalized cut segmentation algorithm combined with fractional differential

Normalized cut segmentation algorithm combined with fraction...

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Huang, Ying Xie, Mei Li, Weisheng Zhou, Lifang School of Electronic Engineering University of Electronic Science and Technology of China Chengdu 610054 China Chongqing Key Lab of Computer Network and Communication Technology Chongqing 400065 China Institute of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Software Chongqing University of Posts and Telecommunications Chongqing 400065 China

ISBN: (纸本)9781612841816

Fractional differential is used to adjust the affinity matrix of the image and to extract more useful edge and texture information. A graph is constructed for the original image with edge and texture information calculated with fractional differential, and the Laplacian matrix is obtained and the eigenvector corresponding to the second eigenvalue is classified to get the final segmentation results. Experimental results show that the proposed method can extract more fine details, preserve more useful information and get more accurate results. © 2011 IEEE.

关键词： Eigenvalues and eigenfunctions

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LAVS: A LIGHTWEIGHT AUDIO-VISUAL SALIENCY PREDICTION MODEL

LAVS: A LIGHTWEIGHT AUDIO-VISUAL SALIENCY PREDICTION MODEL

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Zhu, Dandan Zhao, Defang Min, Xiongkuo Han, Tian Zhou, Qiangqiang Yu, Shaobo Chen, Yongqing Zhai, Guangtao Yang, Xiaokang MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China School of Software Engineering Tongji University China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Department of Computer Science Stevens Institute of Technology United States School of Software Jiangxi Normal University China Information Technology Services East China Normal University China College of Information and Communication Hainan University China

ISBN: (纸本)9781665438643

Audio information is essential for guiding human attention and visual perception, which has been verified by many comprehensive psychological studies. However, the audio modality has been rather neglected in modeling visual attention, most of the current visual attention models heavily depend on visual information. Additionally, current existing high-performing visual attention models rely on deeper convolution neural networks (CNNs), benefiting from their extraordinary feature learning ability but incurring high computational cost. To this end, we propose a novel lightweight audio-visual saliency (LAVS) model to efficiently address the problem of fixation prediction in videos. To the best of our knowledge, our proposed model constitutes the first attempt to exploit a lightweight network and combines the visual and audio cues to perform saliency estimation in videos. Specifically, our proposed model consists of four modules, which are spatial-temporal visual saliency estimation module, audio features extraction module, source sound localization module, and audio-visual saliency fusion module. Extensive experiments across datasets validate the effectiveness and real-time performance of the proposed LAVS model, which outperforms the other state-of-the-art methods. © 2021 IEEE

关键词： Behavioral research

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A load-balanced data aggregation scheduling for duty-cycled wireless sensor networks

A load-balanced data aggregation scheduling for duty-cycled ...

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2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012

作者： Chen, Zhengyu Yang, Geng Chen, Lei Xu, Jian Wang, Haiyong Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts AndTelecommunications Nanjing 210046 China College of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing 210046 China School of Information Technology Jinling Institute of Technology Nanjing 211169 China

ISBN: (纸本)9781467345095

To bridge the gap between limited energy supplies of the sensor nodes and the system lifetime, duty-cycle Wireless Sensor networks (WSNs) with data aggregation are studied in this paper. We proposed a load-balanced and latency-efficient data aggregation scheduling for duty-cycled WSNs. A shortest path tree (SPT) is used as the routing structure for data aggregation scheduling. In SPT, parent-children assignments are well-designed to assign nodes from level h+1 to the parents at level h such that every parent has a balanced load, while reducing the sleep latency which is a period of time for a sender to wait for its parent to be active. Finally, through the simulation and comparisons, we prove the effectiveness of our approach. © 2012 IEEE.

关键词： Scheduling

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Human Attention Based Movie Summarization: Dataset and Baseline Model

Human Attention Based Movie Summarization: Dataset and Basel...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Zhao, Defang Zhu, Dandan Min, Xiongkuo Yue, Jiaomin Zhang, Kaiwei Zhou, Qiangqiang Zhai, Guangtao Yang, Xiaokang CloudWalk Technology Shanghai China School of Computer Science and Technology Donghua University Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China School of Software Jiangxi Normal University Nanchang China Ai Institute Shanghai Jiao Tong University MOE Key Lab of Artificial Intelligence Shanghai China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

The movie summarization model can automatically edit a condensed and succinct version of the movie by selecting the keyframes. Previous works mainly resort to hand-crafted heuristics and most of them are unsupervised. Supervised movie summarization is a new research field and, there is currently no publicly suitable dataset available. Moreover, existing works only focus on the movies themselves while neglecting the audiences, who have the most say in which part of the movie is more attractive. To deal with the aforementioned limitations, we establish a human attention based movie summarization dataset Movie50. Specifically, we explore the human attention variations when watching videos and have the following findings: (1) The attention of humans is concentrated when watching keyframes. (2) The attention of humans is distracted when watching non-keyframes. Inspired by these findings, we collect the eye fixations of 20 participants when watching 50 movies and propose a novel human attention based annotation pipeline. In addition, we introduce A/V-MSNet, an audiovisual neural network that takes advantage of spatio-temporal visual and auditory information to better model human attention as well as exploit more plentiful information. Extensive experiments demonstrate the superiority of the proposed method. © 2022 IEEE.

关键词： Motion pictures

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Learning interpretable deep state space model for probabilistic time series forecasting

arXiv

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arXiv 2021年

作者： Li, Longyuan Yan, Junchi Yang, Xiaokang Jin, Yaohui State Key Lab of Advanced Optical Communication System and Network MoE Key Lab of Artificial Intelligence AI Institute Department of Computer Science and Engineering Shanghai Jiao Tong University China

Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We propose a deep state space model for probabilistic time series forecasting whereby the non-linear emission model and transition model are parameterized by networks and the dependency is modeled by recurrent neural nets. We take the automatic relevance determination (ARD) view and devise a network to exploit the exogenous variables in addition to time series. In particular, our ARD network can incorporate the uncertainty of the exogenous variables and eventually helps identify useful exogenous variables and suppress those irrelevant for forecasting. The distribution of multi-step ahead forecasts are approximated by Monte Carlo simulation. We show in experiments that our model produces accurate and sharp probabilistic forecasts. The estimated uncertainty of our forecasting also realistically increases over time, in a spontaneous manner. © 2021, CC BY.

关键词： State space methods

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Secure beamformer design for cognitive satellite terrestrial networks 4

Secure beamformer design for cognitive satellite terrestrial...

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4th IEEE International Conference on computer and communications, ICCC 2018

作者： Yin, Chunyan Lin, Zhi Tao, Xiangshuai Ouyang, Jian Lin, Min Panagopoulos, Athanasios D. Ministry of Education Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing China College of Communications Engineering Army Engineering University of PLA Nanjing China Nanjing Institute of Telecommunication Technology Nanjing China School of Electrical and Computer Engineering National Technical University of Athens Zografou15780 Greece

ISBN: (纸本)9781538683392

This paper proposes a beamforming (BF) scheme based on multi-objective optimization (MOO) for a cognitive satellite-terrestrial network (CSTN), where the eavesdroppers (Eves) attempt to intercept the private message conveyed to an intended user. By considering that the maximization of achievable secrecy rate (ASR) and the minimization of transmit power can not be achieved simultanesouly, we adopt artificial noise (AN) and apply the weighted Tchebycheff approach to formulate a multi-object optimization problem. Then, by introducing several auxiliary variables, applying semidefinite programming (SDP) and means of Taylor approximation, the original nonconvex MOO problem is transformed into a convex one with a series of linear constraints, and the BF weight vector and AN vector can be obtained. Finally, simulation results are given to illustrate the tradeoff between the conflicting objectives and the superiority of the proposed algorithm in comparison with the commonly used schemes. © 2018 IEEE.

关键词： Beamforming

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