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Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network with latent variables Research Articles

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9,   Pages 1234-1246 doi: 10.1631/FITEE.2000426

Abstract:

It is necessary to construct an adaptive model to cope with process non-stationaries. In this study, a novel quality-related locally weighted soft sensing method is designed for non-stationary processes based on a Bayesian network with . Specifically, a is proposed where quality-oriented are extracted and further applied to a double-layer similarity measurement algorithm. The proposed soft sensing method tries to find a general approach for non-stationary processes via quality-related information where the concepts of local similarities and window confidence are explained in detail. The performance of the developed method is demonstrated by application to a numerical example and a debutanizer column. It is shown that the proposed method outperforms competitive methods in terms of the accuracy of predicting key quality variables.

Keywords： 软测量；有监督贝叶斯网络；隐变量；局部加权建模；质量预测    

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A novel confidence estimation method for heterogeneous implicit feedback Article

Jing WANG, Lan-fen LIN, Heng ZHANG, Jia-qi TU, Peng-hua YU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1817-1827 doi: 10.1631/FITEE.1601468

Abstract: Implicit feedback, which indirectly reflects opinion through user behaviors, has gained increasing attention in rec-ommender system communities due to its accessibility and richness in real-world applications. A major way of exploiting implicit feedback is to treat the data as an indication of positive and negative preferences associated with vastly varying confidence levels. Such algorithms assume that the numerical value of implicit feedback, such as time of watching, indicates confidence, rather than degree of preference, and a larger value indicates a higher confidence, although this works only when just one type of implicit feedback is available. However, in real-world applications, there are usually various types of implicit feedback, which can be referred to as heterogeneous implicit feedback. Existing methods cannot efficiently infer confidence levels from heterogeneous implicit feedback. In this paper, we propose a novel confidence estimation approach to infer the confidence level of user prefer-ence based on heterogeneous implicit feedback. Then we apply the inferred confidence to both point-wise and pair-wise matrix factorization models, and propose a more generic strategy to select effective training samples for pair-wise methods. Experiments on real-world e-commerce datasets from Tmall.com show that our methods outperform the state-of-the-art approaches, consid-ering several commonly used ranking-oriented evaluation criteria.

Keywords： Recommender systems     Heterogeneous implicit feedback     Confidence     Collaborative filtering     E-commerce    

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Tandem hiddenMarkovmodels using deep belief networks for offline handwriting recognition Article

Partha Pratim ROY, Guoqiang ZHONG, Mohamed CHERIET

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 978-988 doi: 10.1631/FITEE.1600996

Abstract: Unconstrained offline handwriting recognition is a challenging task in the areas of document analysis and pattern recognition. In recent years, to sufficiently exploit the supervisory information hidden in document images, much effort has been made to integrate multi-layer perceptrons (MLPs) in either a hybrid or a tandem fashion into hidden Markov models (HMMs). However, due to the weak learnability of MLPs, the learnt features are not necessarily optimal for subsequent recognition tasks. In this paper, we propose a deep architecture-based tandem approach for unconstrained offline handwriting recognition. In the proposed model, deep belief networks are adopted to learn the compact representations of sequential data, while HMMs are applied for (sub-)word recognition. We evaluate the proposed model on two publicly available datasets, i.e., RIMES and IFN/ENIT, which are based on Latin and Arabic languages respectively, and one dataset collected by ourselves called Devanagari (an Indian script). Extensive experiments show the advantage of the proposed model, especially over the MLP-HMMs tandem approaches.

Keywords： Handwriting recognition     Hidden Markov models     Deep learning     Deep belief networks     Tandem approach    

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Explicit–Implicit Co-Simulation Techniques for Dynamic Responses of a Passenger Car on Arbitrary Road Surfaces Article

Hongzhou Hu, Zhihua Zhong

Engineering 2019, Volume 5, Issue 6,   Pages 1171-1178 doi: 10.1016/j.eng.2019.09.003

Abstract:

To study the durability of a passenger car, this work investigates numerical simulation techniques. The investigations are based on an explicit–implicit approach in which substructure techniques are used to reduce the simulation time, allowing full vehicle dynamic analyses to be performed on a timescale that is difficult or impossible with the conventional finite element model (FEM). The model used here includes all necessary nonlinearities in order to maintain accuracy. All key components of the car structure are modeled with deformable materials. Tire–road interactions are modeled in the explicit package with contact-impact interfaces with arbitrary frictional and geometric properties. Key parameters of the responses of the car driven on six different kinds of test road surfaces are examined and compared with experimental values. It can be concluded that the explicit–implicit co-simulation techniques used here are efficient and accurate enough for engineering purposes. This paper also discusses the limitations of the proposed method and outlines possible improvements for future work.

Keywords： Durability study     Dynamic responses     Passenger car     Explicit–implicit co-simulation     Contact-impact     Friction     Substructures    

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The Mathematic Model of Medium-sized Agro-ecological Engineering

Bian Yousheng,Liu Laifu,Xu Rumei

Strategic Study of CAE 2001, Volume 3, Issue 11,   Pages 39-44

Abstract:

Mathematic model of agricultural eco-engineering is to represent the knowledge of system*s present situation, function and structure. Based on study and analysis, a mathematic model of medium-sized agro-ecological engineering—Liuminying ecological agro-systemisis established. This system consists of eight branch rooms. The state variables and the control variables for each branch room are given and the mathematical models for the branch rooms are also built. The mathematical model has been applied to guiding the pratical production in Luiminying Villnge and satisfactory results are achieved.

Keywords： mathematic model     agro-ecological engineering     state variables     control variables    

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Cross-lingual implicit discourse relation recognitionwith co-training None

Yao-jie LU, Mu XU, Chang-xing WU, De-yi XIONG, Hong-ji WANG, Jin-song SU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 5,   Pages 651-661 doi: 10.1631/FITEE.1601865

Abstract: A lack of labeled corpora obstructs the research progress on implicit discourse relation recognition (DRR) for Chinese, while there are some available discourse corpora in other languages, such as English. In this paper, we propose a cross-lingual implicit DRR framework that exploits an available English corpus for the Chinese DRR task. We use machine translation to generate Chinese instances from a labeled English discourse corpus. In this way, each instance has two independent views: Chinese and English views. Then we train two classifiers in Chinese and English in a co-training way, which exploits unlabeled Chinese data to implement better implicit DRR for Chinese. Experimental results demonstrate the effectiveness of our method.

Keywords： Cross-lingual     Implicit discourse relation recognition     Co-training    

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Knowledge-Based Variable Structure Decoupling Control of a Nonlinear Multivariable System

Tu Chengyuan,Zeng Yanjun

Strategic Study of CAE 2001, Volume 3, Issue 10,   Pages 48-52

Abstract:

A knowledge-based variable-structure decoupling is developed, and be utilized to control a nonlinear multivariable system, so as to avoid the model-establishing process, especially avoid large amount of complex matrix operations required for the conventional decoupling control. Some modules in the knowledge base of this kind of control are described, and the main points of the related algorithms are introduced. Strategies described in this paper have been successively utilized to the set-point temperature control of a 3 × 3 strong coupled system —a three winding heater type standard temperature source, and an effect that the temperature stability as well as temperature homogeneity all better than 1℃ has been attained, which is impossible for the conventional control method.

Keywords： nonlinear multivariable system     decoupling control     knowledge based variable structure decoupling    

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An algorithm for identifying symmetric variables based on the order eigenvalue matrix Article

Xiao-hua LI, Ji-zhong SHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1644-1653 doi: 10.1631/FITEE.1601052

Abstract: To simplify the process for identifying 12 types of symmetric variables in Boolean functions, we propose a new symmetry detection algorithm based on minterm expansion or the truth table. First, the order eigenvalue matrix based on a truth table is defined according to the symmetry definition of a logic variable. By analyzing the constraint conditions of the order eigenvalue matrix for 12 types of symmetric variables, an algorithm is proposed for identifying symmetric variables of the Boolean function. This algorithm can be applied to identify the symmetric variables of Boolean functions with or without don’t-care terms. The proposed method avoids the restriction by the number of logic variables of the graphical method, spectral coefficient methods, and AND-XOR expansion coefficient methods, and solves the problem of completeness in the fast compu-tation method. The algorithm has been implemented in C language and tested on MCNC91 benchmarks. The application results show that, compared with the traditional methods, the new algorithm is an optimal detection method in terms of the applicability of the number of logic variables, the Boolean function including don’t-care terms, detection type, and complexity of the identification process.

Keywords： Boolean function     Symmetric variable     Boolean logic algebra system     Order eigenvalue matrix     Truth table    

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MIMO-GPC Stability Analysis Based on Frequency Domain

Sun Qinglin,Chen Zengqiang,Yuan Zhuzhi

Strategic Study of CAE 2004, Volume 6, Issue 10,   Pages 39-44

Abstract:

A MIMO-GPC stability theorem based on frequency domain is presented in the paper. The closed-loop feedback structure of MIMO-GPC is proposed. Nyquist array methodology is used to analyze the stability of MIMO-GPC. The parameters of MIMO-GPC can be determined by stability criterion.

Keywords： MIMO-GPC     frequency domain analysis     stability criterion    

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Vectorial Eigenmode Analysis of Optical Waveguides Based on the Variable Transformed Series Expansion Method

Xiao Jinbiao,Sun Xiaohan,Zhang Mingde,Ding Dong

Strategic Study of CAE 2001, Volume 3, Issue 11,   Pages 49-53

Abstract:

Vectorial eigenmodes supported by the buried rectangular and rib optical waveguides are obtained using variable transformed series expansion method. The infinite x-y plane is mapped into a unit square by an elegant tangent-type variable transformation. Consequently, the boundary truncation is not necessary, and the nonphysical reflection is eliminated. As a result, the calculation accuracy is promoted. In addition, small matrix derived from this method promotes the computational efficiency. Comparatively agreeing with those previously published, the results can be used to optimize the photonic devices.

Keywords： variable transformed series expansion method     optical waveguides     vectorial eigenmode analysis    

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Automatic discovery of stateful variables in network protocol software based on replay analysis Research Article

Jianxin HUANG, Bo YU, Runhao LIU, Jinshu SU

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 3,   Pages 403-416 doi: 10.1631/FITEE.2200275

Abstract: is usually characterized by complicated functions and a vast state space. In this type of program, a massive number of that are used to represent the evolution of the states and store some information about the sessions are prone to potential flaws caused by violations of protocol specification requirements and program logic. Discovering such variables is significant in discovering and exploiting vulnerabilities in protocol software, and still needs massive manual verifications. In this paper, we propose a novel method that could automatically discover the use of in . The core idea is that a stateful variable features information of the communication entities and the software states, so it will exist in the form of a global or static variable during program execution. Based on recording and replaying a protocol program's execution, varieties of variables in the life cycle can be tracked with the technique of dynamic instrument. We draw up some rules from multiple dimensions by taking full advantage of the existing vulnerability knowledge to determine whether the data stored in critical memory areas have stateful characteristics. We also implement a prototype system that can discover automatically and then perform it on nine programs in ProFuzzBench and two complex real-world software programs. With the help of available open-source code, the evaluation results show that the average true positive rate (TPR) can reach 82% and the average precision can be approximately up to 96%.

Keywords： Stateful variables     Network protocol software     Program analysis technology     Network security    

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Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China Article

Yurui Fan,Guohe Huang,Yin Zhang,Yongping Li

Engineering 2018, Volume 4, Issue 5,   Pages 617-626 doi: 10.1016/j.eng.2018.06.006

Abstract:

This study develops a multivariate eco-hydrological risk-assessment framework based on the multivariate copula method in order to evaluate the occurrence of extreme eco-hydrological events for the Xiangxi River within the Three Gorges Reservoir (TGR) area in China. Parameter uncertainties in marginal distributions and dependence structure are quantified by a Markov chain Monte Carlo (MCMC) algorithm. Uncertainties in the joint return periods are evaluated based on the posterior distributions. The probabilistic features of bivariate and multivariate hydrological risk are also characterized. The results show that the obtained predictive intervals bracketed the observations well, especially for flood duration. The uncertainty for the joint return period in "AND" case increases with an increase in the return period for univariate flood variables. Furthermore, a low design discharge and high service time may lead to high bivariate hydrological risk with great uncertainty.

Keywords： Flood risk     Copula     Multivariate flood frequency analysis     Distribution     Markov chain Monte Carlo    

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TPE-H2MWD: an exact thumbnail preserving encryption scheme with hidden Markov model and weighted diffusion Research Article

Xiuli CHAI, Xiuhui CHEN, Yakun MA, Fang ZUO, Zhihua GAN, Yushu ZHANG,chaixiuli@henu.edu.cn,2923105987@qq.com,1060734169@qq.com,zuofang@henu.edu.cn,gzh@henu.edu.cn,yushu@nuaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8,   Pages 1169-1180 doi: 10.1631/FITEE.2200498

Abstract: With the substantial increase in image transmission, the demand for image security is increasing. Noise-like images can be obtained by conventional encryption schemes, and although the security of the images can be guaranteed, the noise-like images cannot be directly previewed and retrieved. Based on the rank-then-encipher method, some researchers have designed a three-pixel exact thumbnail preserving encryption (TPE2) scheme, which can be applied to balance the security and availability of images, but this scheme has low encryption efficiency. In this paper, we introduce an efficient exact thumbnail preserving encryption scheme. First, blocking and bit-plane decomposition operations are performed on the plaintext image. The zigzag scrambling model is used to change the bit positions in the lower four bit planes. Subsequently, an operation is devised to permute the higher four bit planes, which is an extended application of the . Finally, according to the difference in bit weights in each bit plane, a bit-level rule is established to generate an encrypted image and still maintain the same sum of pixels within the block. Simulation results show that the proposed scheme improves the encryption efficiency and can guarantee the availability of images while protecting their privacy.

Keywords： Hidden Markov model     Weighted diffusion     Balance between usability and privacy     Image encryption    

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Variable-separating-based Space Decomposition Algorithm of Production Scheduling

Gao Yongchao,Li Qiqiang,Ding Ran,Guo Qingqiang

Strategic Study of CAE 2006, Volume 8, Issue 9,   Pages 61-64

Abstract:

Most static production scheduling problems are formulated in MILP ( mixed integer linear programming) or MINLP(mixed integer non-linear programming) . It is difficult to find solutions of scheduling because of its large scale and combinatorial characters. According to the features of MIP (mixed integer programming), integral variables and continuous variables are separated and the searching space is decomposed naturally into many continuous subspaces of less scale. Taking a typical batch production scheduling as a case, the analysis shows that variable-separating strategy decreases the scale of continuous searching problem greatly and makes it easy to solve, which can improve the speed and efficiency of optimization.

Keywords： production scheduling     space decomposition     sub-definite method    

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Multi-band Synchronization Model for Speech Recognition Under Noisy Condition

Sun Wei,Wu Zhenyang

Strategic Study of CAE 2006, Volume 8, Issue 3,   Pages 31-34

Abstract:

Based on perception characteristic of human ear, this paper proposes synchronization multi-band maximum likelihood linear regression algorithm for robust speech recognition under noisy condition. The algorithm utilizes maximum likelihood as estimation criteria to compensate the effects of noisy condition with multi-band synchronization model and noise corruption assumption. The tests show that the proposed algorithm improves the performance of recognition system effectively.

Keywords： hidden Markov model     maximum likelihood     multi-band synchronization model     speech recognition    

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Title Author Date Type Operation

Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network with latent variables

Journal Article

A novel confidence estimation method for heterogeneous implicit feedback

Jing WANG, Lan-fen LIN, Heng ZHANG, Jia-qi TU, Peng-hua YU

Journal Article

Tandem hiddenMarkovmodels using deep belief networks for offline handwriting recognition

Partha Pratim ROY, Guoqiang ZHONG, Mohamed CHERIET

Journal Article

Explicit–Implicit Co-Simulation Techniques for Dynamic Responses of a Passenger Car on Arbitrary Road Surfaces

Hongzhou Hu, Zhihua Zhong

Journal Article

The Mathematic Model of Medium-sized Agro-ecological Engineering

Bian Yousheng,Liu Laifu,Xu Rumei

Journal Article

Cross-lingual implicit discourse relation recognitionwith co-training

Yao-jie LU, Mu XU, Chang-xing WU, De-yi XIONG, Hong-ji WANG, Jin-song SU

Journal Article

Knowledge-Based Variable Structure Decoupling Control of a Nonlinear Multivariable System

Tu Chengyuan,Zeng Yanjun

Journal Article

An algorithm for identifying symmetric variables based on the order eigenvalue matrix

Xiao-hua LI, Ji-zhong SHEN

Journal Article

MIMO-GPC Stability Analysis Based on Frequency Domain

Sun Qinglin,Chen Zengqiang,Yuan Zhuzhi

Journal Article

Vectorial Eigenmode Analysis of Optical Waveguides Based on the Variable Transformed Series Expansion Method

Xiao Jinbiao,Sun Xiaohan,Zhang Mingde,Ding Dong

Journal Article

Automatic discovery of stateful variables in network protocol software based on replay analysis

Jianxin HUANG, Bo YU, Runhao LIU, Jinshu SU

Journal Article

Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China

Yurui Fan,Guohe Huang,Yin Zhang,Yongping Li

Journal Article

TPE-H2MWD: an exact thumbnail preserving encryption scheme with hidden Markov model and weighted diffusion

Xiuli CHAI, Xiuhui CHEN, Yakun MA, Fang ZUO, Zhihua GAN, Yushu ZHANG,chaixiuli@henu.edu.cn,2923105987@qq.com,1060734169@qq.com,zuofang@henu.edu.cn,gzh@henu.edu.cn,yushu@nuaa.edu.cn

Journal Article

Variable-separating-based Space Decomposition Algorithm of Production Scheduling

Gao Yongchao,Li Qiqiang,Ding Ran,Guo Qingqiang

Journal Article

Multi-band Synchronization Model for Speech Recognition Under Noisy Condition

Sun Wei,Wu Zhenyang

Journal Article