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International Conference on Mobile Ad-hoc and Sensor networks, MSN

作者： Xinjing Yuan Lingjun Pu Ruilin Yun Jingdong Xu Institute of Systems and Networks College of Computer Science Nankai University Tianjin China State Key Laboratory of Integrated Services Networks (Xidian University) Xi’an China Tianjin Key Laboratory of Network and Data Security Technology Tianjin China

ISBN: (数字)9781728199160

ISBN: (纸本)9781728192369

360° UHD videos have absorbed great attention in recent years. However, as they are of significant size and usually watched from a close range, they require extremely high bandwidth for a good immersive experience, which poses a great challenge on the current single-source adaptive streaming strategies. Realizing the great potentials of tile-based video streaming and pervasive edge services, we advocate a tile-based multi-source adaptive streaming strategy for 360° UHD videos over edge networks. In order to reap its benefits, we consider a comprehensive model which captures the key components of tile-based multi-source adaptive streaming. Then we formulate a joint bitrate selection and request scheduling problem, aiming at maximizing the system utility (i.e., user QoE minus service overhead) while satisfying the service integrity and latency constraints. To solve the formulated non-linear integer programming problem efficiently, we decouple the control variables and resort to matroid theory to design an optimal master-slave algorithm. In addition, we improve our proposed algorithm with a deep learning-based bitrate selection algorithm, which can achieve a rationalization result in a short running time. Extensive datadriven simulations validate the superior performance of our proposed algorithm.

关键词： Integer programming Deep learning Adaptation models Adaptive systems Bit rate Master-slave Videos

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Field Test of Twin-Field Quantum key Distribution through Sending-or-Not-Sending over 428 km

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Physical Review Letters 2021年第25期126卷 250502-250502页

作者： Hui Liu Cong Jiang Hao-Tao Zhu Mi Zou Zong-Wen Yu Xiao-Long Hu Hai Xu Shizhao Ma Zhiyong Han Jiu-Peng Chen Yunqi Dai Shi-Biao Tang Weijun Zhang Hao Li Lixing You Zhen Wang Yong Hua Hongkun Hu Hongbo Zhang Fei Zhou Qiang Zhang Xiang-Bin Wang Teng-Yun Chen Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology ofChina Hefei Anhui 230026 People’s Republic of China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 People’s Republic of China Jinan Institute of Quantum Technology Jinan Shandong 250101 People’s Republic of China State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing 100084 People’s Republic of China Data Communication Science and Technology Research Institute Beijing 100191 People’s Republic of China QuantumCTek Corporation Limited Hefei Anhui 230088 People’s Republic of China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 People’s Republic of China Chongqing Optoelectronics Research Institute Chongqing 400060 People’s Republic of China

Quantum key distribution endows people with information-theoretical security in communications. Twin-field quantum key distribution (TF-QKD) has attracted considerable attention because of its outstanding key rates over long distances. Recently, several demonstrations of TF-QKD have been realized. Nevertheless, those experiments are implemented in the laboratory, and therefore a critical question remains about whether the TF-QKD is feasible in real-world circumstances. Here, by adopting the sending-or-not-sending twin-field QKD (SNS-TF-QKD) with the method of actively odd parity pairing (AOPP), we demonstrate a field-test QKD over 428 km of deployed commercial fiber and two users are physically separated by about 300 km in a straight line. To this end, we explicitly measure the relevant properties of the deployed fiber and develop a carefully designed system with high stability. The secure key rate we achieved breaks the absolute key rate limit of repeaterless QKD. The result provides a new distance record for the field test of both TF-QKD and all types of fiber-based QKD systems. Our work bridges the gap of QKD between laboratory demonstrations and practical applications and paves the way for an intercity QKD network with measurement-device-independent security.

关键词： Optical quantum information processing Quantum cryptography Quantum optics

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Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning

Weakly Supervised Fine-Grained Image Classification via Guas...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhihui Wang Shijie Wang Shuhui Yang Haojie Li Jianjun Li Zezhou Li International School of Information Science & Engineering Dalian University of Technology China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province China School of Computer Science and Technology Hangzhou Dianzi University China Shanghai Pinlan Data Technology

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

Existing weakly supervised fine-grained image recognition (WFGIR) methods usually pick out the discriminative regions from the high-level feature maps directly. We discover that due to the operation of stacking local receptive filed, Convolutional Neural network causes the discriminative region diffusion in high-level feature maps, which leads to inaccurate discriminative region localization. In this paper, we propose an end-to-end Discriminative Feature-oriented Gaussian Mixture Model (DF-GMM), to address the problem of discriminative region diffusion and find better fine-grained details. Specifically, DF-GMM consists of 1) a low-rank representation mechanism (LRM), which learns a set of low-rank discriminative bases by Gaussian Mixture Model (GMM) to accurately select discriminative details and filter more irrelevant information in high-level semantic feature maps, 2) a low-rank representation reorganization mechanism (LR2M) which resumes the space information of low-rank discriminative bases to reconstruct the low-rank feature maps. By recovering the low-rank discriminative bases into the same embedding space of highlevel feature maps, LR2M alleviates the discriminative region diffusion problem in high-level feature map and discriminative regions can be located more precisely on the new low-rank feature maps. Extensive experiments verify that DF-GMM yields the best performance under the same settings with the most competitive approaches, in CUBBird, Stanford-Cars datasets, and FGVC Aircraft.

关键词： Gaussian mixture model Correlation Feature extraction Kernel Image recognition Semantics

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Generating High-quality Movie Tags from Social Reviews: A Learning-driven Approach

Generating High-quality Movie Tags from Social Reviews: A Le...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Zhenxiao Luo Guopin Tang Chen Wang Yipeng Zhou Xi Zheng Jessie Hui Wang Gang Liu Di Wu School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Faculty of Science and Engineering Macquarie University Sydney Australia Institute for Network Sciences and Cyberspace Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781665417631

As a kind of keywords to describe video contents, tags are extremely beneficial for viewers to locate videos when they search the site. Additionally, tags also help video platform operators to better organize and recommend videos to platform users. Previous approaches are mainly based on manually tagging or tag propagation via video content analysis, which is time-consuming and resource-consuming. Especially, given the high volume of fresh movies generated per year, it is difficult to accurately tag all the movies manually. Moreover, video content analysis is also not easy considering typical features (e.g., long duration, complicated scenarios) of commercial movies. In this paper, we propose an automatic tagging algorithm called TagRec that exploits crowdsourced user reviews to generate accurate movie tags. We observe that user reviews contain rich information about movies (e.g., quality, actors) which can be learned to generate high-quality movie tags. Inspired by the above observation, we choose to transform the movie video tagging problem into a tag recommendation problem, in which tags are recommended to different movies by extracting knowledge from crowdsourced movie reviews. We take latent topics, tag co-occurrence probability and tag semantics into account, and formulate the problem as a recommendation optimization problem. We evaluate the performance of our pro-posed TagRec algorithm with a large-scale real-world dataset. Extensive experiments demonstrate that TagRec achieves 7.1 % and 9.6% improvement compared with other state-of-the-art methods in terms of Hit Ratio and Normalized Discounted Cumulative Gain respectively.

关键词： Social computing Filtering Semantics Transforms Tagging Motion pictures Optimization

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Intelligence’s Dilemma: AI Algorithms May Cause Anti-Intelligence 1

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4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018

作者： Zhang, Yuhong Nauman, Umer Network and Data Security Key Laboratory of Sichuan University of Electronic Science and Technology of China Chengdu610054 China Information Science and Engineering College Henan University of Technology Zhengzhou450001 China

ISBN: (数字)9789811379833

ISBN: (纸本)9789811379826

As the intelligent age continues and technology gets more advanced, algorithms offer some of the solutions for our better work and life. However, research suggests that the proliferation and abuse of intelligent algorithms may lead us to a decline in cognitive performance. In this paper, we first discuss the role of intelligent algorithms in terms of highlighting the value of data. Next, we analyse the non-neutrality of these data-driven algorithms. Further, we analyze the intrinsic discrimination of AI algorithm based on prejudice psychology. Next, we argue that overusing AI algorithms and strengthening the dependency on them will lead to lower our cognitive level in terms of slow thinking. Thus, the conclusion is that, in the intelligent age, the more intelligent algorithms we use, the lower our cognitive level will be. This is the dilemma of intelligence. Finally, we offer some possible principles that may apply to alleviate the above disadvantageous scenarios. © 2019, Springer Nature Singapore Pte Ltd.

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Correction: A scale-adaptive estimation for mixed geographically and temporally weighted regression models

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Journal of Geographical Systems 2025年第2期27卷 337-337页

作者： Hong, Zhimin Wang, Zhiwen Wang, Huhu Wang, Ruoxuan Department of Mathematics School of Science Inner Mongolia University of Technology Hohhot China Statistics Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling Hohhot China Institute for Infectious Disease and Endemic Disease Control Inner Mongolia Autonomous Region Center for Disease Control and Prevention Hohhot China

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Robust twin-field quantum key distribution through sending-or-not-sending

arXiv

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arXiv 2021年

作者： Jiang, Cong Yu, Zong-Wen Hu, Xiao-Long Wang, Xiang-Bin Jinan Institute of Quantum Technology Shandong Jinan250101 China State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Data Communication Science and Technology Research Institute Beijing100191 China School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangzhou510275 China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China Shenzhen Institute for Quantum Science and Engineering Physics Department Southern University of Science and Technology Shenzhen518055 China Frontier Science Center for Quantum Information Beijing China

The sending-or-not-sending (SNS) protocol is one of the most major variants of the twin-field (TF) quantum key distribution (QKD) protocol and has been realized in a 511 km field fiber, the farthest field experiment to date. In practice, however, all decoy-state methods have unavoidable source errors, and the source errors may be non-random, which compromises the security condition of the existing TF-QKD protocols. In this study, we present a general approach for efficiently calculating the SNS protocol’s secure key rate with source errors, by establishing the equivalent protocols through virtual attenuation and tagged model. This makes the first result for TF-QKD in practice where source intensity cannot be controlled exactly. Our method can be combined with the two-way classical communication method such as active odd-parity pairing to further improve the key rate. The numerical results show that if the intensity error is within a few percent, the key rate and secure distance only decrease marginally. The key rate of the recent SNS experiment in the 511 km field fiber is still positive using our method presented here, even if there is ±9.5% intensity fluctuation. This shows that the SNS protocol is robust against source errors. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum cryptography

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Composable security for practical quantum key distribution with two way classical communication

arXiv

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arXiv 2021年

作者： Jiang, Cong Hu, Xiao-Long Yu, Zong-Wen Wang, Xiang-Bin State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Jinan Institute of Quantum Technology JinanShandong250101 China School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangzhou510275 China Data Communication Science and Technology Research Institute Beijing100191 China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China Shenzhen Institute for Quantum Science and Engineering Physics Department Southern University of Science and Technology Shenzhen518055 China Frontier Science Center for Quantum Information Beijing China

We present methods to strictly calculate the finite-key effects in quantum key distribution (QKD) with error rejection through two-way classical communication (TWCC) for the sending-or-not-sending twin-field protocol. Unlike the normal QKD without TWCC, here the probability of tagging or untagging for each two-bit random group is not independent. We rigorously solve this problem by imagining a virtual set of bits where every bit is independent and identical. We show the relationship between the outcome starting from this imagined set containing independent and identical bits and the outcome starting with the real set of non-independent bits. With explicit formulas, we show that simply applying Chernoff bound in the calculation gives correct key rate, but the failure probability changes a little bit. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum cryptography

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Signal Feature Analysis of Contact Force at the Tip of a Flexible Ureteroscope*

Signal Feature Analysis of Contact Force at the Tip of a Fle...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Deng Yinan Yang Tangwen Dai Shaotao Guoli Song Institute of Information Science and the Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing China School of Electrical Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

This paper presents a signal analysis approach to identify the contact objects at the tip of a flexible ureteroscope. First, a miniature triaxial fiber optic sensor based on Fiber Bragg Grating(FBG) is devised to measure the interactive force signals at the ureteroscope tip. Due to the multidimensional properties of these force signals, the principal components analysis(PCA) method is introduced to reduce dimensions. The signal features are then extracted from the representative principal component signals using the wavelet transform(WT) method. Experimental results show that the contact objects at the tip of a ureteroscope are readily discriminated from the measured force signals with the proposed *** Relevance-This work commits to analyze the contact force signals at the tip of a flexible ureteroscope for the purpose of contact objects identification.

关键词： Force Feature extraction Robot sensing systems Force measurement Wavelet transforms Time-frequency analysis

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Optimal algorithm for profiling dynamic arrays with finite values 22

Optimal algorithm for profiling dynamic arrays with finite v...

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22nd International Conference on Extending database technology, EDBT 2019

作者： Yang, Dingcheng Yu, Wenjian Deng, Junhui Liu, Shenghua BNRist Dept. Computer Science and Tech. Tsinghua Univ. Beijing China CAS Key Lab. Network Data Science and Tech. Inst. Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783893180813

How can one quickly answer the most and top popular objects at any time, given a large log stream in a system of billions of users? It is equivalent to find the mode and top-frequent elements in a dynamic array corresponding to the log stream. However, most existing work either restrain the dynamic array within a sliding window, or do not take advantages of only one element can be added or removed in a log stream. Therefore, we propose a profiling algorithm, named S-Profile, which is of O(1) time complexity for every updating of the dynamic array, and optimal in terms of computational complexity. With the profiling results, answering the queries on the statistics of dynamic array becomes trivial and fast. With the experiments of various settings of dynamic arrays, our accurate S-Profile algorithm outperforms the existing methods, showing at least 2X speedup to the heap based approach and 13X speedup to the balanced tree based approach. © 2019 Copyright held by the owner/author(s).

关键词： Trees (mathematics)

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