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IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Brian J. Rautio Mahmoud El Sabbagh James C. Rautio L.C. Smith College of Engineering and Computer Science Syracuse University Syracuse NY USA Sonnet Software North Syracuse NY USA

A broadband methodology for measurement of uniaxial dielectric anisotropy is described. Previous work is improved with reduced measurement error, enhanced automation, and additional material testing. Additionally, per... 详细信息

关键词： Permittivity Temperature measurement Permittivity measurement Semiconductor device measurement Materials Pollution measurement

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An Efficient Hardware Architecture for Activation Function in Deep Learning Processor

An Efficient Hardware Architecture for Activation Function i...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Lin Li Shengbing Zhang Juan Wu School of Computer Science and Engineering Northwestern Polytechnical University Xi'an China Xi'an Vocational and Technical College School of Animation Software and Education Xi'an China

ISBN: (纸本)9781538649923

In order to explore the efficient design and implementation of activation function in deep learning processor, this paper presents an efficient five-stage pipelined hardware architecture for activation function based on the piecewise linear interpolation, and a novel neuron data-LUT address mapping algorithm. Compared with the previous designs based on serial calculation, the proposed hardware architecture can achieve at least 3 times of acceleration. Four commonly used activation functions are designed based on the proposed hardware architecture, which is implemented on the XC6VLX240T of Xilinx. The LeNet-5 and AlexNet are selected as benchmarks to test the inference accuracy of different activation functions with different piecewise numbers on the MNIST and CIFAR-10 test sets in the deep learning processor prototype system. The experiment results show that the proposed hardware architecture can effectively accomplish the relevant calculation of activation functions in the deep learning processor and the accuracy loss is negligible. The proposed hardware architecture is adaptable for numerous activation functions, which can be widely used in the design of other deep learning processors.

关键词： Neurons Hardware Machine learning Biological neural networks Interpolation Table lookup

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A Self-adaption Quantum Genetic Algorithm Used in the Design of Command and ControlStructure

A Self-adaption Quantum Genetic Algorithm Used in the Design...

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2017 3rd International Conference on Computational Systems and Communications(ICCSC 2017)

作者： SUN Peng WU Jun-sheng ZHANG Jie-yong LIAO Meng-chen School of computer science Northwestern Polytechnical University College of Information and Navigation Air Force Engineering University School of software and microelectronics Northwestern Polytechnical University

The paper mainly solved the problem of the design of command and control structure. First, the key elements in command and control structure are defined and we introduced the concept of work load of decision makers to describe the problem mathematically. Next, a mathematic model aimed at minimizing the root mean square of decision makers' work load is developed. Finally, we combine the quantum genetic algorithm with self-adaption strategy and get the self-adaption quantum genetic algorithm. Major characteristic of this algorithm is adjusting the quantum rotation gate, generating the crossover probability and the mutation probability in a self-adaption way. Experimental results show that the self-adaption quantum genetic algorithm has a feature of evolving fast and searching precise, and it can cluster the platforms well to accomplish the design of command and control structure.

关键词： Work load Root mean square Quantum genetic algorithm Self-adaption

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Crowd express: A probabilistic framework for on-time crowdsourced package deliveries

arXiv

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arXiv 2018年

作者： Chen, Chao Yang, Sen Liu, Weichen Wang, Yasha Guo, Bin Zhang, Daqing Ministry of Education and also with the College of Computer Science Chongqing University Chongqing400044 China Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing100871 China School of Computer Science Northwestern Polytechnical University Xi'an710072 China

Speed and cost of logistics are two major concerns to on-line shoppers, but they generally conflict with each other in nature. To alleviate the contradiction, we propose to exploit existing taxis that are transporting passengers on the street to relay packages collaboratively, which can simultaneously lower the cost and accelerate the speed. Specifically, we propose a probabilistic framework containing two phases called CrowdExpress for the on-time package express deliveries. In the first phase, we mine the historical taxi GPS trajectory data offline to build the package transport network. In the second phase, we develop an online adaptive taxi scheduling algorithm to find the path with the maximum arriving-on-time probability "on-the-fly" upon realtime requests, and direct the package routing accordingly. Finally, we evaluate the system using the real-world taxi data generated by over 19,000 taxis in a month in the city of New York, US. Results show that around 9,500 packages can be delivered successfully on time per day with the success rate over 94%, moreover, the average computation time is within 25 milliseconds. Copyright © 2018, The Authors. All rights reserved.

关键词： Taxicabs

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An evolutionary algorithm for magic squares

An evolutionary algorithm for magic squares

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Congress on Evolutionary Computation

作者： Tao Xie Lishan Kang College of Computer Science National University of Defense Technology Changsha China National Key Laboratory of Software Engineering Wuhan University of China Wuhan China

ISBN: (纸本)0780378040

Magic square construction is a complex and hard permutation problem of recreational combinatorics with a long history. Not only does the complexity consist in that the number of magic squares increases rapidly with the order of magic square, but also in that the percentage of magic squares in the possible permutation of the first n/sup 2/ natural numbers decreases with the order. Based on the two-phase construction conjecture, we propose an improved evolutionary algorithm for magic square construction. Mutation operators are specially designed so that the mutation domain can be located and the mutation probabilities adjusted adaptively, which include the number pair permutations, the row permutations and column permutations. In addition, some heuristics-based local permutations, like the row/column local rectification and the local diagonal rectification, are used to complement the stochastic mechanism. Computational results show that, the two-phase construction conjecture is computationally effective, and the improved evolutionary algorithm is highly efficient for magic square construction.

关键词： Evolutionary computation Genetic mutations Combinatorial mathematics History Educational institutions computer science Stochastic processes software engineering Rivers Humans

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Can Forensic Detectors Identify GAN Generated Images?

Can Forensic Detectors Identify GAN Generated Images?

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Haodong Li Han Chen Bin Li Shunquan Tan Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728102436;9789881476852

Generative adversarial network (GAN) has shown its powerful capability in generating photorealistic images. Although the generated images can fool human eyes, it is not clear whether they can evade the detection of forensic detectors, which aim to identify the originality and authenticity of images. In this paper, we investigate how forensic detectors perform in differentiating between GAN generated images and real images. We consider two kinds of approaches, one is intrusive and the other is non-intrusive, based on whether the GAN architecture is needed for performing detection. We have conducted extensive experiments on a celebrity face image dataset to evaluate the effectiveness of different approaches. The results and analyses show that the intrusive approach can detect GAN generated images but with a relatively high false alarm rate. The non-intrusive approach with features extracted from a VGG network is very effective for detecting GAN generated images when the training data is sufficient, but it still faces challenge when the training data and testing data are mismatched.

关键词： Gallium nitride Face Detectors Training Training data Generators Histograms

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CNN channel pruning via gradient integration and knowledge distillation

CNN channel pruning via gradient integration and knowledge d...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Suyun Lian Yang Zhao Jiajian Cai Jihong Pei The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

With the advancement of artificial intelligence technology, intelligent applications have permeated all aspects of human life, including automatic driving, intelligent security, and face recognition. Convolutional neural networks (CNNs) are essential models for AI, but their complexity increases with more available data. The complex models are unsuitable for edge devices like wearables and smartphones due to high memory and computational requirements. In this paper, the compact model is achieved by pruning some redundant output channels. To effectively measure the validity of the output channels, this paper proposes a channel pruning algorithm based on gradient integration, which combines the gradient of the channel with the model output and the channel’s values. This pruning could destroy model accuracy, so knowledge distillation is introduced during fine-tuning to leverage the original model’s reasoning ability. Experiments show that our approach improves accuracy by 0.51% while reducing parameters by 30.1% and FLOPs by 26% in the VGG16 model.

关键词： Training Accuracy Computational modeling Signal processing algorithms Signal processing Cognition Convolutional neural networks Security Wearable devices Smart phones

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VFDS: Very fast database sampling system

VFDS: Very fast database sampling system

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IEEE International Conference on Information Reuse and Integration (IRI)

作者： Teodora Sandra Buda Thomas Cerqueus John Murphy Morten Kristiansen Lero Performance Engineering Laboratory Computer Science and Informatics University College Dublin Ireland IBM Software Group IBM Collaboration Solutions Dublin Ireland

In a wide range of application areas (e.g. data mining, approximate query evaluation, histogram construction), database sampling has proved to be a powerful technique. It is generally used when the computational cost of processing large amounts of information is extremely high, and a faster response with a lower level of accuracy for the results is preferred. Previous sampling techniques achieve this balance, however, an evaluation of the cost of the database sampling process should be considered. We argue that the performance of current relational database sampling techniques that maintain the data integrity of the sample database is low and a faster strategy needs to be devised. In this paper we propose a very fast sampling method that maintains the referential integrity of the sample database intact. The sampling method targets the production environment of a system under development, that generally consists of large amounts of data computationally costly to analyze. We evaluate our method in comparison with previous database sampling approaches and show that our method produces a sample database at least 300 times faster and with a maximum trade off of 0.5% in terms of sample size error.

关键词： Diamonds Relational databases Testing Production Educational institutions computer science

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Multi-Stage Transfer Learning Evolutionary Algorithm for Dynamic Multiobjective Optimization

Multi-Stage Transfer Learning Evolutionary Algorithm for Dyn...

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Congress on Evolutionary Computation

作者： Qianhui Wang Qingling Zhu Junkai Ji College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen PR China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Recently, the application of transfer learning within dynamic multiobjective evolutionary algorithms (DMOEAs) has shown significant potential to solve dynamic multiobjective optimization problems (DMOPs). This approach utilizes the transfer learning technique which reuses information from previous environments to accelerate the search process in the new environment. However, the risk of negative transfer can lead to an erroneous search direction and inefficient use of computational resources. To address this issue, this paper proposes a novel multistage transfer learning DMOEA, named MSTL. The algorithm is designed to enhance the convergence and diversity of the population through the combination of the pre-transfer learning stage and the transfer learning and validation stage when environmental changes occur. In the pre-transfer learning stage, a suitable target domain, source domain, and validation classifier sample sets are generated guided by historical information. In the transfer learning and validation stage, the TrAdaboost technique to transfer knowledge from the target to the source domain, with the results verified by two validation classifiers to mitigate negative transfer. Experimental results demonstrate that our proposed algorithm outperforms four competing algorithms in terms of diversity and convergence on a widely recognized benchmark suite.

关键词： Accuracy Heuristic algorithms Transfer learning Sociology Evolutionary computation Benchmark testing Classification algorithms

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Research on the least square source localization algorithm

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Journal of Computational Information Systems 2013年第11期9卷 4363-4370页

作者： Zhang, Mingsheng Xie, Shengdong Oxbridge College Kunming University of Science and Technology Kunming 650106 China Computer and Software Institute Nanjing University of Information Science and Technology Nanjing 210044 China School of Information Science and Engineering Southeast University Nanjing 210096 China

Localization algorithm based on the linear least square principle has the advantages of small amount of calculations, and attracts many researchers. In this paper, some algorithms based on linear least square estimation for single target localization are researched. We analyze the essence of these algorithms, give the specific estimation process and summarize the advantages and drawbacks of them. Finally, we point out the direction of such algorithms for further research. © 2013 by Binary Information Press.

关键词： Information systems

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