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2019 International Conference on networking and network Applications, NaNA 2019

作者： Tong, Wei Dong, Xuewen Zheng, Jiawei Shaanxi Key Laboratory of Network and System Security Xidian University Xi'an China School of Cyber Engineering Xidian University Xi'an China School of Computer Science and Technology Xidian University Xi'an China

ISBN: (纸本)9781728126296

Blockchain is becoming increasingly popular, while the performance problems have confused its implementation, especially the limited size of the distributed network. In this paper, we propose Trust-PBFT, a combination of PeerTrust P2P trust calculation model and PBFT consensus algorithm. We first introduce PeerTrust to evaluate the trustworthy of the nodes that qualify as participants of PBFT, which replaces the original that all nodes participate in so that the size of the distributed network can be expanded arbitrarily. Besides, in order to simplify the structure of block storage, particularly the storage of the feedbacks of transaction used to calculate trust value of nodes, we design a tri-chain architecture to store accounts, transactions and feedbacks in three blockchains, respectively. Moreover, due to the introduction of PeerTrust, a weak benefit is to improve the fault tolerance performance efficiently. Finally, we design simulation experiments to evaluate the fault tolerance performance and scalability of Trust-PBFT. © 2019 IEEE.

关键词： Blockchain

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Dynamics and Resonance Fluorescence from a Superconducting Artificial Atom Doubly Driven by Quantized and Classical Fields

arXiv

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arXiv 2024年

作者： Ruan, Xinhui Wang, Jia-Heng He, Dong Song, Pengtao Li, Shengyong Zhao, Qianchuan Kuang, L.M. Tsai, Jaw-Shen Zou, Chang-Ling Zhang, Jing Zheng, Dongning Astafiev, O.V. Liu, Yu-Xi Peng, Zhihui Department of Automation Tsinghua University Beijing100084 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center of Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Integrated Circuits Tsinghua University Beijing100084 China Institute of Physics Chinese Academy of Sciences Beijing100190 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100190 China Center for Quantum Computing RIKEN Saitama351-0198 Japan Graduate School of Science Tokyo University of Science 1-3 Kagurazaka Shinjuku Tokyo162-0825 Japan CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei Anhui230026 China Hefei National Laboratory Hefei230088 China School of Automation Science and Engineering Xi'an Jiaotong University Xi’an710049 China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi’an710049 China Skolkovo Institute of Science and Technology Nobel str. 3 Moscow143026 Russia Moscow Institute of Physics and Technology Institutskiy Pereulok 9 Dolgoprudny141701 Russia Royal Holloway University of London Surrey EghamTW20 0EX United Kingdom

We report an experimental demonstration of resonance fluorescence in a two-level superconducting artificial atom under two driving fields coupled to a detuned cavity. One of the fields is classical and the other is varied from quantum (vacuum fluctuations) to classical one by controlling the photon number inside the cavity. The device consists of a transmon qubit strongly coupled to a one-dimensional transmission line and a coplanar waveguide resonator. We observe a sideband anti-crossing and asymmetry in the emission spectra of the system through a one-dimensional transmission line, which is fundamentally different from the weak coupling case. By changing the photon number inside the cavity, the emission spectrum of our doubly driven system approaches to the case when the atom is driven by two classical bichromatic fields. We also measure the dynamical evolution of the system through the transmission line and study the properties of the first-order correlation function, Rabi oscillations and energy relaxation in the system. The study of resonance fluorescence from an atom driven by two fields promotes understanding decoherence in superconducting quantum circuits and may find applications in superconducting quantum computing and quantum networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Electric lines

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Android Malicious Code Detection Based on Secondary Pruning Optimization 12

Android Malicious Code Detection Based on Secondary Pruning ...

引用

12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Yu, Qing Ma, Kuolang Wang, Zuohua Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin China Tianjin Times Shengshi Technology Co. Ltd. No. 216 Hongqi Road Nankai District Tianjin300000 China

ISBN: (纸本)9781728148526

In this paper, we propose a detection algorithm for Android malicious code based on integrated multi-feature. By decompiling and processing APK files, the multi-class behavior features of Android application are extracted, and the classification is achieved through an integrated learning framework based on quadratic pruning optimization. The prototype system automatically detects the malicious code of the Android platform and analyzes the validity of the algorithm through experimental verification. © 2019 IEEE.

关键词： Android (operating system)

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XTQA: Span-Level Explanations for Textbook Question Answering

arXiv

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arXiv 2020年

作者： Ma, Jie Chai, Qi Liu, Jun Yin, Qingyu Wang, Pinghui Zheng, Qinghua Ministry of Education of Key Lab for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering The School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Xi’an710049 China Amazon United States

Textbook Question Answering (TQA) is the task of correctly answering diagram or non-diagram questions given large multi-modal contexts consisting of abundant essays and diagrams. In real-world scenarios, an explainable TQA system plays a key role in deepening humans’ understanding of learned knowledge. However, there is no work to investigate how to provide explanations currently. To address this issue, we devise a novel architecture towards span-level eXplanations for TQA (XTQA). In this paper, spans are the combinations of sentences within a paragraph. The key idea is to consider the entire textual context of a lesson as candidate evidence, and then use our proposed coarse-to-fine grained Explanation Extracting (EE) algorithm to narrow down the evidence scope and extract the span-level explanations with varying lengths for answering different questions. The EE algorithm can also be integrated into other TQA methods to make them explainable and improve the TQA performance. Experimental results show that XTQA obtains the best overall explanation result (mIoU) of 52.38% on the first 300 questions of CK12-QA test splits, demonstrating the explainability of our method (non-diagram: 150 and diagram: 150). The results also show that XTQA achieves the best TQA performance of 36.46% and 36.95% on the aforementioned splits respectively. We have released our code in https://***/dr-majie/*** Codes 68T07 Copyright © 2020, The Authors. All rights reserved.

关键词： Textbooks

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Trading Based Service-Oriented Spectrum-Aware RAN-Slicing Under Spectrum Sharing

Trading Based Service-Oriented Spectrum-Aware RAN-Slicing Un...

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IEEE Conference on Wireless Communications and networking

作者： Kajia Jiao Xuanheng Li Miao Pan Fan Jiang Ming Li School of Information and Communication Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Houston Houston TX USA Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and Telecommunications Xian Shaanxi China

ISBN: (数字)9781728131061

ISBN: (纸本)9781728131078

The fast development on emerging services makes our telecommunications networks witness two key problems. One is the flexibility to fulfill the diverse service requests and the other is the shortage on spectrum. network slicing and spectrum sharing have been regarded as two prominent solutions, which, however, are barely jointly studied. When taking the shared spectrum into account, its unique feature of heterogeneity and uncertainty will bring new challenges for the slicing. In this paper, we propose a service-oriented spectrum-aware RAN-slicing trading (SSRT) scheme with a comprehensive consideration on both aspects. For the SSRT scheme, we jointly slice three kinds of resources, namely, time, spectrum (including both licensed one and shared one), and network facilities, according to the diverse traffic requests, which are classified into delay-tolerant (DT) ones and delay-sensitive (DS) ones, as well as the willing payments from different service providers (SPs). To achieve both inter-slice and intra-slice isolation, we construct a three-dimensional (3D) conflict graph and formulate the SSRT scheme into a mixed-integer nonlinear programming (MINLP) problem with a cross-layer spectrum-aware resource allocation and a hybrid transmission mode (including both single-hop and multi-hop). Since finding all the maximum independent sets (MIS) for the 3D conflict graph is an NP-hard problem, we further develop an iterative heuristic algorithm for the MIS determination.

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Traffic Off-Loading over Uncertain Shared Spectrums with End-to-End Session Guarantee

Traffic Off-Loading over Uncertain Shared Spectrums with End...

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IEEE Conference on Vehicular technology (VTC)

作者： Ruyi Xiao Xuanheng Li Miao Pan Nan Zhao Fan Jiang Xianbin Wang School of Information and Communication Engineering Dalian University of Technology Dalian China University of Houston Houston TX USA Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and Telecommunications Xian Shaanxi China University of Western Ontario London ON Canada

ISBN: (数字)9781728194844

ISBN: (纸本)9781728194851

As a promising solution of spectrum shortage, spectrum sharing has received tremendous interests recently. However, under different sharing policies of different licensees, the shared spectrum is heterogeneous both temporally and spatially, and is usually uncertain due to the unpredictable activities of incumbent users. In this paper, considering the spectrum uncertainty, we propose a spectrum sharing based delay-tolerant traffic off-loading (SDTO) scheme. To capture the available heterogeneous shared bands, we adopt a mesh cognitive radio network and employ the multi-hop transmission mode. To statistically guarantee the end-to-end (E2E) session request under the uncertain spectrum supply, we formulate the SDTO scheme into a stochastic optimization problem, which is transformed into a mixed integer nonlinear programming (MINLP) problem. Then, a coarse-fine search based iterative heuristic algorithm is proposed to solve the MINLP problem. Simulation results demonstrate that the proposed SDTO scheme can well schedule the network resource with an E2E session guarantee.

关键词： Vehicular and wireless technologies Uncertainty Simulation Heuristic algorithms Search problems Iterative algorithms Optimization

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Sentiment Analysis of Web Text Based on Deep Learning with a Attention Mechanism

Sentiment Analysis of Web Text Based on Deep Learning with a...

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International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Qing Yu Hui Zhao Kaiwen Jiang Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin China

The sentiment analysis of online commentary is a hot research topic in the field of network information mining. Traditional text sentiment analysis methods are mainly based on emotional dictionaries or machine learning. However, it relies on the structure of the sentiment dictionary and the artificial design and extraction features, which limits the generalization ability. In contrast, the deep learning model has a stronger ability to express complex mapping functions from data to emotional semantics. This paper proposes a model combining Bidirectional Gated Recurrent Unit(BGRU) neural network and Convolutional Neural network(CNN), and introduces attention mechanism for text sentiment analysis. The experimental results show that compared with the traditional method, the method effectively improves the accuracy of text sentiment classification.

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Edge-cloud cooperation driven surface roughness classification method for selective laser melting

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Advanced Engineering Informatics 2025年 66卷

作者： Ma, Shuaiyin Huang, Yuming Liu, Yang Yan, Zhiqiang Lv, Jingxiang Cai, Wei School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi'an710121 China Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'an710121 China Shaanxi Union Research Centre of University and Enterprise for 5G+ Industrial Internet Communication Terminal Technology Xi'an University of Posts and Telecommunications Xi'an710121 China Department of Management and Engineering Linköping University LinköpingSE-581 83 Sweden Industrial Engineering and Management University of Oulu Oulu90570 Finland Key Laboratory of Road Construction Technology and Equipment of MOE Chang'an University Xi'an710064 China College of Engineering and Technology Southwest University Chongqing400715 China

Additive manufacturing (AM) technology is extensively utilized in aerospace and industrial manufacturing. However, parts built using AM are susceptible to spheroidization, porosity, cracks, and poor surface quality, making it difficult to establish an actionable product quality degree. Hence, developing a reasonable method to equate product quality with a new degree and further analyzing the product quality based on these standards has proven effective for enhancing part quality in AM. To achieve this goal, this paper proposes a surface roughness classification method that utilizes surface roughness analysis and sample enhancement. This method leverages edge cloud cooperation to efficiently analyze and integrate data from different sensors, enabling real-time monitoring and adjustment of the manufacturing process. Subsequently, the quality degree analysis system was developed utilizing matter-element extension cloud model. Furthermore, a bidirectional-gated recurrent unit (Bi-GRU) based model for quality classification and recognition has been established, with Wasserstein generative adversarial network (WGAN) employed for sample enhancement to address the issue of imbalanced column classification and to enhance the accuracy of both classification and recognition. Finally, the results obtained from this case study demonstrate through comparative experiments that the proposed method for classifying surface roughness can accurately identify 98% of prepared samples. © 2025 The Authors

关键词： Inspection

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Investigating Bi-level optimization for learning and vision from a unified perspective: A survey and beyond

arXiv

引用

arXiv 2021年

作者： Liu, Risheng Gao, Jiaxin Zhang, Jin Meng, Deyu Lin, Zhouchen DUT-RU International School of Information Science & Engineering Dalian University of Technology Key Laboratory for Ubiquitous Network Service Software of Liaoning Province Dalian116024 China Department of Mathematics Southern University of Science and Technology National Center for Applied Mathematics Shenzhen China School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an Shaanxi China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Cooperative Medianet Innovation Center Shanghai Jiao Tong University Shanghai200240 China

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchical structure, involving two levels of optimization tasks, where one task is nested inside the other. In machine learning and computer vision fields, despite the different motivations and mechanisms, a lot of complex problems, such as hyper-parameter optimization, multi-task and meta learning, neural architecture search, adversarial learning and deep reinforcement learning, actually all contain a series of closely related subproblms. In this paper, we first uniformly express these complex learning and vision problems from the perspective of BLO. Then we construct a best-response-based single-level reformulation and establish a unified algorithmic framework to understand and formulate mainstream gradient-based BLO methodologies, covering aspects ranging from fundamental automatic differentiation schemes to various accelerations, simplifications, extensions and their convergence and complexity properties. Last but not least, we discuss the potentials of our unified BLO framework for designing new algorithms and point out some promising directions for future research. © 2021, CC BY.

关键词： Deep learning

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Using Reduced Graphene Oxide to Generate Q-Switched Pulses in Er-Doped Fiber Laser

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Chinese Physics Letters 2018年第11期35卷 32-34页

作者： Lu Li Rui-Dong Lv Si-Cong Liu Zhen-Dong Chen Jiang Wang Yong-Gang Wang Wei Ren School of Science Xi＇an University of Posts and TelecommunicationsXi＇an 710121 School of Physics and information Technology Shaanxi Normal UniversityXi＇an 710119 Shaanxi Key Laboratory of Information Communication Network and Security Xi＇an University of Posts and TelecommunicationsXi＇an 710121

Using the reduced graphene oxide（rGO） as a saturable absorber（SA） in an Er-doped fiber（EDF） laser cavity,we obtain the Q-switching operation. The rGO SA is prepared by depositing the GO on fluorine mica（FM） using the thermal reduction method. The modulation depth of rGO/FM is measured to be 3.2%. By incorporating the rGO/FM film into the EDF laser cavity, we obtain stable Q-switched pulses. The shortest pulse duration is3.53 μs, and the maximum single pulse energy is 48.19 nJ. The long-term stability of working is well *** experimental results show that the rGO possesses potential photonics applications.

关键词： EDF GO Using Reduced Graphene Oxide to Generate Q-Switched Pulses in Er-Doped Fiber Laser SA

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