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intelligent computing and Wireless Optical Communications (ICWOC), International Conference on

作者： Yunyun Gao Qiang Zhang Lasheng Zhao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

As a representation of speech information, acoustic word embedding can enable query-by-example keyword search with low-resource speech data. An acoustic word embedding model with Transformer encoder and multivariate joint loss is presented in this article. First of all, on the basis of BLSTM, the model can extract richer information by adding a Transformer encoder, which improves representation ability of the embedding vector. Then, the contrast loss is improved according to the multiple negative samples, and combined with the hinge loss with distance characteristics, the model generates a more compact vector representation and improves the identification of features. Finally, considering the unbalanced characteristics of samples, the anti-focal loss is introduced to form a multivariate joint loss together with the above two losses, so as to make the model performance better. The model has achieved certain results in word recognition tasks and has certain competitiveness compared with other acoustic word models.

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A novel robust digital image watermarking using LPM and HVS

A novel robust digital image watermarking using LPM and HVS

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The 2013 3rd International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2013)

作者： Qiang Zhang Mingli Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of EducationDalian University

ISBN: (纸本)9780819495587

To resist on general attacks, such as compression, noising and geometric distortion attacks is a common requirement for digital image watermarking or data hiding techniques comparing with rotation, scaling and translation(RST) attacks which are considered to be more challenging. Based on invariant centroid and LPM which is also used to analyze the angle of rotation and ratio of scaling influence after attacks of watermarked image combining with chaotic system and a novel adaptive coefficient α, this paper presents a robust and invisible digital image watermarking technology. The experiment results show that this method has high invisibility and robust, especially withstand RST attacks.

关键词： watermarking LPM α mix-chaotic system invariant centroid

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On the lower bounds of DNA word sets for DNA computing

On the lower bounds of DNA word sets for DNA computing

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Bin Wang Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

DNA computing is a new research field, which has been paid attention to by more and more experts with the DNA computing bringing the flying development of mathematics, computer science and other subjects. Because the DNA coding could decrease the emergence of false negative and false positive, it affects the reliability and the accuracy of DNA computing. In the DNA coding, DNA word sets could provide the best and effective DNA sequences which are used in DNA computing to improve the reliability and accuracy of biochemical reaction. However, there are no entire and exact values which satisfy combinational constraints, which induce many problems in DNA coding. For this reason, in this paper, we use the dynamic genetic algorithm to improve lower bounds of DNA word sets which satisfy combinational constraints. By comparing our experimental results with previous researchful work, the results improve the lower bounds and further shorten the value range of DNA word sets.

关键词： DNA computing Sequences Biology computing Biological information theory Computer science Mathematics Genetic algorithms design methodology Thermodynamics Computer science education

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IABC: An iteratively automatic machine learning boosted hand-eye calibration method for laser displacement sensor

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Chinese Journal of Aeronautics 2023年第8期36卷 422-453页

作者： Helin LI Bin LIN Tianyi SUI Liang XU Chen ZHANG Shuai YAN Yang WANG Xinquan HAO Deyu LOU School of Mechanical Engineering Ministry of EducationTianjin UniversityTianjin 300350China International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University Shaoxing 312000China Science and Technology of Advanced Functional Composite Laboratory Aerospace Research Institute of Materials and Processing TechnologyBeijing 100076China Key Laboratory of Advanced Ceramics and Machining Technology of Ministry of Education Tianjin UniversityTianjin 300072China

An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s *** improve the measurement accuracy of the OMM system,a novel Iteratively Automatic machine learning Boosted hand-eye Calibration(IABC)method is *** the hand-eye relationship and LDS measurement errors can be calibrated in one calibration process without any hardware changes via ***,a new objective function is derived,containing analytical parameters of the handeye relationship and LDS ***,a hybrid calibration model composed of two kernels is proposed to solve the objective *** kernel is the analytical kernel designed for solving analytical *** kernel is the automatic machine learning(AutoML)kernel designed to model LDS *** two kernels are connected with stepwise iterations to find the best calibration *** with traditional methods,hand-eye experiments show that IABC reduces the calibration RMSE by about 50%.Verification experiments show that IABC reduces the measurement deviations by about 25%-50%and RMSEs within 40%.Even when the training data are obviously less than the test data,IABC performs *** demonstrate that IABC is more accurate than traditional hand-eye methods.

关键词： Hand-Eye Calibration Laser Displacement Sensor Machine learning Measurement errors On-Machine Measurement

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Palmprint recognition based on CNN and local coding features 6

Palmprint recognition based on CNN and local coding features

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6th International Conference on Computer Science and Network Technology, ICCSNT 2017

作者： Yang, Aoqi Zhang, Jianxin Sun, Qiule Zhang, Qiang Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China Faculty of Electronic Information and Electric Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781538604922

The convolutional neural network(CNN) has received an excellent performance in the recent tasks of image retrieval and image classification. Besides, some local coding methods have been focused on because of their outstanding local description. In this paper, we present a novel method for palmprint recognition, which combines CNN and local coding techniques. We conduct feature extraction on palmprint images using the pre-trained networks and obtain the local convolutional features. Then three different local coding methods are adopted to code the features from CNN, including Bag of Visual Word(BoVW), Locality-constrained Linear Coding(LLC) and Vector of Locally Aggregated Descriptors (VLAD). The features extracted from CNN have better representation. Meanwhile, the local coding makes local features more important. Hence the combination of them can get the anticipated better results. The proposed method is extensively evaluated on the PolyU palmprint database and PolyU multispectral palmprint database, illuminating the remarkable performance on palmprint recognition. © 2017 IEEE.

关键词： Palmprint recognition

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CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing

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Protein & Cell 2012年第2期3卷 148-152页

作者： Guoguang Zhao Dechao Bu Changning Liu Jing Li Jian Yang Zhiyong Liu Yi Zhao Runsheng Chen Bioinformatics Research Group Key Laboratory of Intelligent Information ProcessingAdvanced Computing Research LaboratoryInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Bioinformatics Laboratory and National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China State Key Laboratory for Molecular Virology and Genetic Engineering National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 100176China Graduate School of the Chinese Academy of Sciences Beijing 100190China

Estimating taxonomic content constitutes a key problem in metagenomic sequencing data ***,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available ***,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data *** show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin *** comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat *** can be run on one multiprocessor node or a *** is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following ***,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.

关键词： CloudLCA metagenome analysis cloud computing

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Half adder and half subtractor logic gates based on nicking enzymes

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Molecular Systems design and Engineering 2019年第6期4卷 1103-1113页

作者： Zhao, Yunbin Liu, Yuan Zheng, Xuedong Wang, Bin Lv, Hui Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China School of Computer Science and Technology Dalian University of Technology Dalian 116024 China College of Computer Science Shenyang Aerospace University Shenyang 110136 China

The excellent specificity and predictability of DNA pairing and its natural ability to interact with other biomolecules make DNA an ideal material for building molecular logic devices (MLDs). However, there are still many challenges in the process of building such devices, including their complex structures, potentially harsh reaction conditions, long reaction times and so on. Thus, the parallel nature of DNA and other biomolecules needs to be developed before MLDs based on DNA can be exploited to a greater extent. In order to solve this problem, herein, we carefully selected two enzymes, *** and ***, that were both persistent and compatible, and used them to build a nicking enzyme platform. Based on this enzyme platform, we constructed a novel XOR logic gate with flexible internal signaling. Furthermore, AND and INHIBIT logic gates were also modified to use the same enzymes as the XOR logic gate as their inputs. As a result, the algorithm process of half adder and half subtractor was realized by this work. This study provides a new approach for typical DNA-based arithmetic operations and promotes the development of advanced MLDs. © 2019 The Royal Society of Chemistry.

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Robust stability of interactional genetic regulatory networks with reaction-diffusion terms

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Advances in Difference Equations 2017年第1期2017卷 1-20页

作者： Zou, Chengye Wei, Xiaopeng Zhang, Qiang Zhou, Changjun Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

We have analyzed the stability of interactional genetic regulatory networks with reaction-diffusion terms under Dirichlet boundary conditions in this article. Corresponding to interaction between unstable genetic regulatory networks and stable genetic regulatory networks, the model is given, and a stability criterion is proposed through construction of appropriate Lyapunov-Krasovskii functions and linear matrix inequalities (LMI). By means of a numerical simulation, we have proved the effectiveness and correctness of the theorem, and we analyzed the factors that influence the stability for interactional genetic regulatory networks. © 2017, The Author(s).

关键词： Dirichlet boundary interactional genetic regulatory networks linear matrix inequalities reaction-diffusion

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Phasor Domain Transmission Line Fault Locating with Three Phase Distributed Parameter Modeling

Phasor Domain Transmission Line Fault Locating with Three Ph...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Liu, Yu Tan, Zhenyu Xie, Jiahao Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology School of Electronic Science & Applied Physics Hefei University of Technology Hefei Anhui China

ISBN: (纸本)9781538677032

Accurate fault locating reduces power outage time and operational costs. In this paper, a novel phasor domain transmission line fault locating algorithm is proposed. Best implementation requires GPS synchronized measurements at both terminals of the line. First, the model of the transmission line with fault is constructed using three phase distributed parameter modeling with neutral conductors and grounding representation. The model is without the assumption that the transmission line is geometrically balanced. Next, the state estimation algorithm is utilized to solve the model of the transmission line with fault, where the fault location is included as a state. Numerical experiments demonstrate that the method has higher accuracy than traditional fault locating methods, independent of fault types, locations and impedances.

关键词： Three Phase Distributed Parameter Modeling State Estimation (SE) Fault Locating

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Dual-axial self-attention network for text classification

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Science China(Information Sciences) 2021年第12期64卷 80-90页

作者： Xiaochuan ZHANG Xipeng QIU Jianmin PANG Fudong LIU Xingwei LI State Key Laboratory of Mathematical Engineering and Advanced Computing Shanghai Key Laboratory of Intelligent Information Processing Fudan University School of Computer Science Fudan University

Text classification is an important task in natural language processing and numerous studies aim to improve the accuracy and efficiency of text classification models. In this study, we propose an effective and efficient text classification model which is based on self-attention solely. The recently proposed multidimensional self-attention significantly improved the performance of self-attention. However, existing models suffer from two major limitations:(1) the previous multi-dimensional self-attention models are quite timeconsuming;(2) the dependencies of elements along the feature axis are not taken into account. To overcome these problems, in this paper, a much more computational efficient multi-dimensional self-attention model is proposed, and two parallel self-attention modules, called dual-axial self-attention, are applied to capture rich dependencies along the feature axis as well as the text axis. A text classification model is then *** experimental results on eight representative datasets show that the proposed text classification model can obtain state-of-the-art results and the proposed self-attention outperforms conventional self-attention models.

关键词： text classification dual-axial self-attention feature-axial dependency

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