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An efficient quantum circuits optimizing scheme compared with QISKit

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arXiv 2018年

作者： Zhang, Xin Xiang, Hong Xiang, Tao Fu, Li Sang, Jun School of Big Data and Software Engineering Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education School of Computer Science Chongqing University

Recently, the development of quantum chips has made great progress-the number of qubits is increasing and the fidelity is getting higher. However, qubits of these chips are not always fully connected, which sets additional barriers for implementing quantum algorithms and pro-gramming quantum programs. In this paper, we introduce a general circuit optimizing scheme, which can efficiently adjust and optimize quantum circuits according to arbitrary given qubits' layout by adding additional quantum gates, exchanging qubits and merging single-qubit gates. Compared with the optimizing algorithm of IBM's QISKit, the quantum gates consumed by our scheme is 74.7%, and the execution time is only 12.9% on average. Copyright © 2018, The Authors. All rights reserved.

关键词： Timing circuits

Peter H. Rose - Father of Ion Implantation: The Early Years

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Peter H. Rose - Father of Ion Implantation: The Early Years

International Conference on Ion Implantation Technology (IIT)

作者： Andrew Wittkower Geoffrey Ryding ESAT/STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In 1996, President Clinton presented Peter Rose with the National Medal of Technology and Innovation. This paper describes his innovations in ion implantation technology which led to the award presented twenty years l... 详细信息

ISBN: (纸本)9781538668306

关键词： Ion implantation Ion sources Business Technological innovation Acceleration Particle beams

Max-min fairness user scheduling and power allocation in full-duplex OFDMA systems

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arXiv 2018年

作者： Zhang, Xiaozhou Chang, Tsung-Hui Liu, Ya-Feng Shen, Chao Zhu, Gang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In a full-duplex (FD) multi-user network, the system performance is not only limited by the self-interference but also by the co-channel interference due to the simultaneous uplink and downlink transmissions. Joint design of the uplink/downlink transmission direction of users and the power allocation is crucial for achieving high system performance in the FD multi-user network. In this paper, we investigate the joint uplink/downlink transmission direction assignment (TDA), user paring (UP) and power allocation problem for maximizing the system max-min fairness (MMF) rate in a FD multi-user orthogonal frequency division multiple access (OFDMA) system. The problem is formulated with a two-time-scale structure where the TDA and the UP variables are for optimizing a long-term MMF rate while the power allocation is for optimizing an instantaneous MMF rate during each channel coherence interval. We show that the studied joint MMF rate maximization problem is NP-hard in general. To obtain high-quality suboptimal solutions, we propose efficient methods based on simple relaxation and greedy rounding techniques. Simulation results are presented to show that the proposed algorithms are effective and achieve higher MMF rates than the existing heuristic methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Optimization

Comparison of UAV-based multispectral sensors for detection of Solenopsis invicta Nests

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IOP Conference Series: Earth and Environmental Science 2020年第1期569卷

作者： Yuejun Song Feng Chen Kaitao Liao Jiangxi Institute of Soil and Water Conservation Nanchang 330029 China Jiangxi Key Laboratory of Soil Erosion and Prevention Nanchang 330029 China College of Computer and Information Engineering Xiamen University of Technology Xiamen 361024 China Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen 361024 China Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University Xiamen 361005 China

The invasive red imported fire ant (Solenopsis invicta Buren) (Hymenoptera: Formicidae) has been continuing to expand its range in China, resulting in adverse ecological impacts to where it has invaded. As such, the reliable detection of Solenopsis invicta Buren nests is needed to effectively manage the species. In this paper, the spectral features of the Solenopsis invicta Buren nests were demonstrated using spectra samples obtained by ASD FieldSpec 4 during field surveys in Shanggao County, Jiangxi Province. Furthermore, channel reflectance estimations for three unmanned aerial vehicle (UAV)-based multispectral sensors were simulated correspondingly. Based on the channel reflectance from individual sensors, the detection of the Solenopsis invicta Buren nests was investigated. Generally, between-class differences in reflectance were relatively significant in both Green channel and Red channel, which suggests the importance of these two channels for the detection of Solenopsis invicta Buren nest. Minor between-sensor differences observed in both Green channel and Red channel suggest that detection results obtained from UAV-based multispectral observations could be comparable among the three sensors, considering only the spectral features. There are significant differences in reflectance between the soil of Solenopsis invicta Buren nests and ordinary soil over the longwave region of near infrared (NIR). It suggests the spectral measurement over the longwave region of NIR could be more useful in distinguishing the soil of Solenopsis invicta Buren nests from ordinary soil. Nevertheless, the multispectral sensors provided with channels covering visible and the shortwave region of NIR, possibly do not meet requirements completely for application. An effective method for detecting Solenopsis invicta Buren nests using UAV-based multispectral sensors is currently being evaluated.

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Semi-supervised dictionary learning with label propagation for image classification

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Computational visual Media 2017年第1期3卷 83-94页

作者： Lin Chen Meng Yang College of Computer Science and Software Engineering Shenzhen UniversityShenzhenChina School of Data and Computer Science Sun Yat-sen UniversityGuangzhouChina Key Laboratory of Machine Intelligence and Advanced Computing(Sun Yat-sen University) Ministry of EducationChina

Sparse coding and supervised dictionary learning have rapidly developed in recent years,and achieved impressive performance in image classification. However, there is usually a limited number of labeled training samples and a huge amount of unlabeled data in practical image classification,which degrades the discrimination of the learned dictionary. How to effectively utilize unlabeled training data and explore the information hidden in unlabeled data has drawn much attention of researchers. In this paper, we propose a novel discriminative semisupervised dictionary learning method using label propagation(SSD-LP). Specifically, we utilize a label propagation algorithm based on class-specific reconstruction errors to accurately estimate the identities of unlabeled training samples, and develop an algorithm for optimizing the discriminative dictionary and discriminative coding vectors *** experiments on face recognition, digit recognition, and texture classification demonstrate the effectiveness of the proposed method.

关键词： semi-supervised learning dictionary learning label propagation image classification

Partial-order Algorithm of Model Checking in µ-Predicate Ambient Logic

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Journal of Computers (Taiwan) 2018年第5期29卷 142-159页

作者： Jiang, Hua Lin, Rong-De Zou, Fu-Min Li, Ling-Xiang Key Lab of Granular Computing Minnan Normal University ZhangZhou China School of Mathematical Science Huaqiao university QuanZhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fuzhou Fujian350008 China School of Electronics and Information Engineering Hunan University of Science and Engineering Yongzhou425199 China

This paper introduces a kind of partial-order algorithm of model-checking in finite-control mobile ambients against μ-predicate ambient logic(Ambient logic based on first-order μ-calculus). Based on Tarski's fixpoint theorem, nested predicate equations and Block Dependency Graph, a group of partial ordering relation between inter-mediate results in the process of model checking is given, and thus a kind of local model-checking algorithm is proposed. To our knowledge, this is the first algorithm which exponent of time complexity is d/2+2, the exponent of space complexity is d/2 (d is the alternate nesting depth of fixpoint operator in the formula) and this is the third model-checking algorithm for predicate ambient logic with recursion. This paper's contributions are: (1) getting a group of partial ordering relation between intermediate results in the computing process of model checking for µ-calculus first-order predicate ambient logic based on Tarski's fixpoint theorem;(2) using the partial ordering relation to design an algorithm for model checking in mobile ambients;(3) analyzing the complexity of the algorithm. © 2018 Computer Society of the Republic of China. All rights reserved.

关键词： Model checking

WISERNet: Wider Separate-then-reunion Network for Steganalysis of Color Images

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arXiv 2018年

作者： Zeng, Jishen Tan, Shunquan Liu, Guangqing Li, Bin Huang, Jiwu Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518052 China

Until recently, deep steganalyzers in spatial domain have been all designed for gray-scale images. In this paper, we propose WISERNet (the wider separate-then-reunion network) for steganalysis of color images. We provide theoretical rationale to claim that the summation in normal convolution is one sort of "linear collusion attack" which reserves strong correlated patterns while impairs uncorrelated noises. Therefore in the bottom convolutional layer which aims at suppressing correlated image contents, we adopt separate channel-wise convolution without summation instead. Conversely, in the upper convolutional layers we believe that the summation in normal convolution is beneficial. Therefore we adopt united normal convolution in those layers and make them remarkably wider to reinforce the effect of "linear collusion attack". As a result, our proposed wide-and-shallow, separate-then-reunion network structure is specifically suitable for color image steganalysis. We have conducted extensive experiments on color image datasets generated from BOSSBase raw images and another large-scale dataset which contains 100,000 raw images, with di_erent demosaicking algorithms and downsampling algorithms. The experimental results show that our proposed network outperforms other state-of-the-art color image steganalytic models either hand-crafted or learned using deep networks in the literature by a clear margin. Specifically, it is noted that the detection performance gain is achieved with less than half the complexity compared to the most advanced deeplearning steganalyzer as far as we know, which is scarce in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Steganography

Lightweight Pyramid Networks for Image Deraining

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arXiv 2018年

作者： Fu, Xueyang Liang, Borong Huang, Yue Ding, Xinghao Paisley, John Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University Xiamen361005 China Department of Electrical Engineering & Data Science Institute Columbia University New YorkNY10027 United States

Existing deep convolutional neural networks have found major success in image deraining, but at the expense of an enormous number of parameters. This limits their potential application, for example in mobile devices. In this paper, we propose a lightweight pyramid of networks (LPNet) for single image deraining. Instead of designing a complex network structures, we use domain-specific knowledge to simplify the learning process. Specifically, we find that by introducing the mature Gaussian-Laplacian image pyramid decomposition technology to the neural network, the learning problem at each pyramid level is greatly simplified and can be handled by a relatively shallow network with few parameters. We adopt recursive and residual network structures to build the proposed LPNet, which has less than 8K parameters while still achieving state-of-the-art performance on rain removal. We also discuss the potential value of LPNet for other low- and high-level vision tasks. Copyright © 2018, The Authors. All rights reserved.

关键词： Complex networks

Reliable Shortest Path Guidance in Stochastic Road Networks Using Convolution-Based Path Finding Algorithm 18

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Reliable Shortest Path Guidance in Stochastic Road Networks ...

18th COTA International Conference of Transportation Professionals: Intelligence, Connectivity, and Mobility, CICTP 2018

作者： Chen, Peng Tong, Rui Lu, Guangquan Wang, Yunpeng Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang Univ. Xue Yuan Rd. No. 37 Hai Dian District Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Xue Yuan Rd. No. 37 Hai Dian District Beijing100191 China

ISBN: (数字)9780784481523

ISBN: (纸本)9780784481523

Most existing research on routing guidance only pays attention to the average value of path travel time, which fails to consider travel time variability (TTV) and travel time reliability preferences by different travelers. In this study, a convolution-based modified genetic algorithm (CMGA) is proposed to find the reliable shortest path in stochastic road networks. By accounting for traveler risk tolerance, the algorithm enables the provision of personalized routing guidance for individual travelers. To support online applications in a large-scale network, reasonable heuristic constraints are imposed to help reduce the computational workload and accelerate the convergence speed of the search process. Numerical case studies based on a grid network with random offsets are provided, and the results help verify that the algorithm has the potential to solve reliable shortest path searching problems in a large-scale network with desirable efficiency. © 2018 American Society of Civil Engineers.

关键词： Convolution