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Passivity of Reaction–Diffusion Genetic Regulatory Networks with Time-Varying Delays

Neural Processing Letters 2017年第3期47卷 1115-1132页

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

This article investigates the passivity of reaction–diffusion genetic regulatory networks (GRNs) with time-varying delays and uncertainty terms under Dirichlet, Neumann, and Robin boundary conditions. We provide delay-dependent stability criteria by constructing appropriate Lyapunov–Krasovskii functions and linear matrix inequalities, and offer conditions sufficient to ensure the passivity of GRNs. We conducted a comparative analysis of GRNs under these three conditions. Numerical examples of the proposed approaches are provided to illustrate its effectiveness, and represent the three-dimensional figures of the trajectories of the concentrations of mRNA and the proteins of GRNs under Dirichlet boundary conditions.

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Optimal Tracking Performance of Networked Control Systems Under DoS and Its Applications

Optimal Tracking Performance of Networked Control Systems Un...

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2024 China Automation Congress, CAC 2024

作者： Ren, Xinyu Li, Bo Zhao, Feng Chen, Xiangyong Zhang, Xianhe Jiang, Xiaowei School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Finance Anhui University of Finance and Economics Bengbu China Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi China School of Automation and Electrical Engineering Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

ISBN: (纸本)9798350368604

This paper investigates the optimal tracking performance (OTP) of multiple-input multiple-output (MIMO) discrete networked control systems (NCSs) under the influence of Denial of Service (DoS) attack, channel noise, and bandwidth constraints. The channel noise is assumed to be additive Gaussian white noise (AWGN). Due to the randomness of DoS attack, a Bernoulli distribution is used for DoS modeling. Utilizing frequency domain analysis methods, coprime factorization, all-pass decomposition, and Youla parameterization, an explicit expression for the optimal tracking performance (OTP) of the system under the two-degree-of-freedom (TDOF) controller is derived. The analysis indicates that non-minimum phase (NMP) zeros, unstable poles (UPs), DoS attack, and network constraints affect the OTP of NCSs. Finally, the theoretical results are validated through simulations of MIMO NCS and vehicle control system. © 2024 IEEE.

关键词： White noise

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9th International Conference on intelligent computing, ICIC 2013

作者： Wang, Bing Ji, Zhiwei Advanced Research Institute of Intelligent Sensing Network Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China School of Electronics and Information Engineering Tongji University Shanghai 201804 China

ISBN: (纸本)9783642394812

The development of novel high-throughput experimental techniques makes it possible to comprehensively analyze biological data in health and disease. However, a large amount of data generated results in dramatic data-analytic challenges in discovery of 'signature' molecules, which are specific to different biological conditions (e.g. normal vs. disease, treated vs. untreated). Current statistical methods are effective only in the case their hypothesis can be matched. In this paper, we apply an ensemble statistical method to infer significant molecules. In our approach, four well-done and well-understanding statistical techniques had been used for the analysis to the experimental data, and then the results will be collected into an ensemble framework to find the high confident "significant" molecules which can distinguish the different experimental conditions. We evaluate the performance of our approach on a test dataset which deposited on GEO database with an access number of GSE45114. © 2013 Springer-Verlag.

关键词： Molecules

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Desired clustering of genetic regulatory networks with mixed delays

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Advances in Difference Equations 2018年第1期2018卷 1-14页

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

In this study, we propose two techniques for clustering genetic regulatory networks with mixed delays. Laws for identifying coupling parameters are designed, and the Lyapunov theorem and Lipschitz condition are employed to achieve the desired stability and to identify the coupling parameters. Using our proposed methods, the value of a cluster or the sum of clusters can approach the expected values. Numerical examples verify the feasibility and effectiveness of this method.

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Speech Emotion Recognition Based on Image Enhancement

Speech Emotion Recognition Based on Image Enhancement

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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Dongyan Wang Jing Dong Dongsheng Zhou Xiaopeng Wei Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (数字)9781728123486

ISBN: (纸本)9781728123493

The performance of an emotion recognition system is determined by the quality of emotional features. In this paper, we propose a feature optimization algorithm based on image enhancement and present a convolutional recurrent model to realize emotional recognition of natural speech. For three-dimensional (3-D) log-Mel spectrum and 3-D spectrogram features, the fast gamma transformation with an adaptive threshold is adopted for feature enhancement to make full use of the dynamic characteristics of non-stationary speech signals. Meanwhile, the model combining Convolutional Neural Network (CNN) with the rectangular kernels and Long Short-Term Memory (LSTM) is used to complete speech emotion recognition tasks. Experiments are carried out on two public emotional datasets, and results demonstrate the good generalization ability and recognition performance of our proposed model.

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keyword mask pre-training model for the review of standard declaration

Keyword mask pre-training model for the review of standard d...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Chuang Feng Chao Che Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

The review of standard declaration of import and export commodities refers to the evaluation of whether the declaration information of the commodities filled in by enterprises conforms to the customs filling standards according to the standardized declaration catalogue The manual review method cannot meet the actual work needs. Therefore, using text classification algorithm to conduct this task is necessary. The classification method based on the pre-training model would rely on the keywords. However, for the review of standard declaration task, excessive reliance on keywords will reduce the classification effect because of ignoring the overall information of the text. keyword mask pre-training model is proposed. In the fine-tuning stage, the model designs a keyword masking strategy and a keyword blinding strategy. The keyword masking strategy regularizes the BERT model with a mask mechanism, that is, the keywords are reconstructed with other text information except keywords, so that the model focuses on non-keywords information; keyword blinding strategy makes the model unable to distinguish the categories of text information without contextual text information, which can eliminate the influence of keywords on model decision-making. The experimental results on the real customs declaration data set showing that the method in this thesis exceeds the baseline method in terms of precision and true negative rate.

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A Protein Embedding Model for Drug Molecular Screening

A Protein Embedding Model for Drug Molecular Screening

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International Conference on Big Data and Smart computing (BIGCOMP)

作者： Chao Che Min Zhu Yongjun Zhu Qiang Zhang Dongsheng Zhou Bin Wang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China Department of Library and Information Science Sungkyunkwan University Seoul Republic of Korea

ISBN: (数字)9781728160344

ISBN: (纸本)9781728160351

Application of machine learning method in new drug development can greatly shorten the process of experimental discovery and reduce the risk of clinical failure. However, the feature extraction of proteins sequence is very difficult due to the large dimension. To this end, we propose a Protein Embedding Model(PEM) for drug molecular screening to predict the interaction between proteins and small molecules. Specifically, PEM first classifies 20 kinds of amino acids into 6 categories to reduce the dimension and learns the representation of protein borrowing the idea of word embedding. Then the model uses multiple imputation to fill the physical and chemical properties of small molecule compounds. Finally, the model uses LightGBM model to predict the affinity value Ki between proteins and small molecules. Experiments show that the model can effectively extract the features of proteins and small molecules and outperforms other traditional methods on the data provided by a drug discovery and development company.

关键词： Amino acids Feature extraction Drugs Protein sequence Chemicals Compounds

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Comparison of wavelet, contourlet and dual-tree complex wavelet for palmprint recognition

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ICIC Express Letters, Part B: Applications 2012年第8期6卷 2005-2010页

作者： Wei, Xiaopeng Liu, Jianyang Zhang, Jianxin Zhang, Qiang Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Economic Technological Development Zone No. 10 Xuefu Ave Dalian 116622 China

Many multi-resolution analysis methods have been proposed for palmprint recognition due to the fact that there are three types of lines in human palm. In this pa- per, we make a systematic comparison of discrete wavelet transform (DWT), contourlet transform (CT) and dual-tree complex wavelet transform (DT-CWT) for palmprint recognition to find a better palmprint multi-resolution representation. In each method, the detail palmprint images or subbands are divided into several non-overlapping blocks, and the energy of each block is computed as recognition feature. The three methods are tested on the public PolyU Palmprint Database with various resolution levels and block numbers. Experiment results show that the best equal error rates achieved by DWT, CT and DT-CWT are 2.46%, 1.61% and 1.50%, respectively, which are mainly obtained by using smaller size non-overlapping blocks. The directional information can significantly improve the recognition accuracy, and the shift invariance property makes little contribution to the improvement of the recognition performance because the palmprint images for feature extraction have been preprocessed and normalized. © 2012 ICIC International.

关键词： Discrete wavelet transforms

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Ultrafine-grained LaB_(6)–ZrB_(2) composite ceramics with superior mechanical and thermionic emission properties prepared by highpressure sintering

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Journal of advanced Ceramics 2024年第12期13卷 2021-2029页

作者： Xiaogang Guo An Liu Lingjuan Hao Hang Zhou Shuai Chen Pan Ying Bing Liu Baozhong Li Yufei Gao Zhisheng Zhao Ling Kong Mengdong Ma Xinyu Yang Dongli Yu Center for High Pressure Science(CHiPS) State Key Laboratory of Metastable Materials Science and TechnologyYanshan UniversityQinhuangdao 066004China State Key Laboratory of Crane Technology Yanshan UniversityQinhuangdao 066004China Handan key Laboratory of Intelligent Awareness and Application Handan UniversityHandan 056001China National Key Laboratory of Advanced Casting Technologies MIIT Key Laboratory of Advanced Metallic and Intermetallic Materials TechnologyEngineering Research Center of Materials Behavior and DesignMinistry of EducationNanjing University of Science and TechnologyNanjing 210094China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China School of Materials Science and Engineering Hefei University of TechnologyHefei 230009China

In this study,ultrafine-grained LaB_(6)–ZrB_(2)composite ceramics were successfully synthesized by sintering a mixture of self-produced LaB_(6)nanopowder and commercial ZrB_(2)nanopowder under high *** with their coarse-grained counterparts,ultrafine-grained ceramics exhibit improved mechanical ***,the ultrafinegrained LaB_(6)–ZrB_(2)composite ceramic sintered at 4 GPa and 1673 K,with an average grain size of 286 nm,shows optimal mechanical performance characterized by a Vickers hardness of 25.6 GPa,a fracture toughness of 4.1 MPa·m^(1/2),and an elastic modulus of 338 ***,the ultrafine-grained LaB_(6)–ZrB_(2)composite ceramics displayed strong thermal emission,reaching a maximum current density of 27.5 A∙cm^(−2)at 1773 *** structural and functional advantages of ultrafine-grained LaB_(6)–ZrB_(2)composite ceramics render them suitable for potential use in thermionic emission cathodes.

关键词： LaB_(6)-ZrB_(2) ultrafine-grained high pressure mechanical properties thermal field emission

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A molecular device: A DNA molecular lock driven by the nicking enzymes

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Computational and structural biotechnology journal 2020年 18卷 2107-2116页

作者： Xiaokang Zhang Qiang Zhang Yuan Liu Bin Wang Shihua Zhou Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian 116622 China. School of Computer Science and Technology Dalian University of Technology Dalian 116024 China.

As people are placing more and more importance on information security, how to realize the protection of information has become a hotspot of current research. As a security device, DNA molecular locks have great potential to realize information protection at the molecular level. However, building a highly secure molecular lock is still a serious challenge. Therefore, taking advantage of the DNA strand displacement and enzyme control technology, we constructed a molecular lock with a self-destructive mechanism. This molecular lock is mainly composed of logic circuits and takes nicking enzymes as inputs. To build this molecular lock, we first constructed a series of cascade circuits, including a YES-YES cascade circuit and a YES-AND cascade circuit. Then, an Inhibit logic gate was constructed to explore the inhibitory properties between different combinations of two nicking enzymes. Finally, using the characteristics of mutual inhibition between several enzymes, a DNA molecular lock driven by three nicking enzymes was constructed. In this molecular device, only the correct sequence of nicking enzymes can be input to ensure the normal operation of the molecular lock. Once the wrong password is entered, the device will be destroyed and cannot be recovered, which effectively prevents intruders from cracking the lock through exhaustive methods. The molecular lock has the function of simulating an electronic keyboard, which can realize the protection of information at the molecular level, and provides a new implementation method for building more advanced and complex molecular devices.

关键词： DNA Information Security Molecular Lock Nicking Enzyme

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