On a perturbed MAP risk model under a threshold dividend strategy

Jianhua Cheng,Dehui Wang 한국통계학회 2013 Journal of the Korean Statistical Society Vol.42 No.4

In this paper, we consider a perturbed risk model where the claims arrive according toa Markovian arrival process (MAP) under a threshold dividend strategy. We derive theintegro-differential equations for the Gerber–Shiu expected discounted penalty functionand the moments of total dividend payments until ruin, obtain the analytical solutionsto these equations, and give numerical examples to illustrate our main results. We alsoget a matrix renewal equation for the Gerber–Shiu function, and present some asymptoticformulas for the Gerber–Shiu function when the claim size distributions are heavy-tailed.

A New Spatio-temporal Event Model based on Multi-tuple for Cyber-Physical Systems

Jianhua Wang,Lianglun Cheng,Jun Liu 보안공학연구지원센터 2013 International Journal of Control and Automation Vol.6 No.6

A Quick Tables Look-up Optimization Algorithm for CAVLC Decoding

Jianhua Wang,Lianglun Cheng,Jun Liu,Tao Wang 보안공학연구지원센터(IJSIP) 2014 International Journal of Signal Processing, Image Vol.7 No.3

An elastoplastic bounding surface model for the cyclic undrained behaviour of saturated soft clays

Cheng, Xinglei,Wang, Jianhua Techno-Press 2016 Geomechanics & engineering Vol.11 No.3

A total stress-based bounding surface model is developed to predict the undrained behaviour of saturated soft clays under cyclic loads based on the anisotropic hardening modulus field and bounding-surface theories. A new hardening rule is developed based on a new interpolation function of the hardening modulus that has simple mathematic expression and fewer model parameters. The evolution of hardening modulus field is described in the deviatoric stress space. It is assumed that the stress reverse points are the mapping centre points and the mapping centre moves with the variation of loading and unloading paths to describe the cyclic stress-strain hysteresis curve. In addition, by introducing a model parameter that reflects the accumulation rate and level of shear strain to the interpolation function, the cyclic shakedown and failure behaviour of soil elements with different combinations of initial and cyclic stresses can be captured. The methods to determine the model parameters using cyclic triaxial compression tests are also studied. Finally, the cyclic triaxial extension and torsional shear tests are performed. By comparing the predictions with the test results, the model can be used to describe undrained cyclic stress-strain responses of elements with different stress states for the tested clays.

A Regular Expression Matching Algorithm Based on High-Efficient Finite Automaton

Jianhua Wang,Lianglun Cheng,Jun Liu 한국정보과학회 2014 Journal of Computing Science and Engineering Vol.8 No.2

Aiming to solve the problems of high memory access and big storage space and long matching time in the regular expression matching of extended finite automaton (XFA), a new regular expression matching algorithm based on high-efficient finite automaton is presented in this paper. The basic idea of the new algorithm is that some extra judging instruments are added at the starting state in order to reduce any unnecessary transition paths as well as to eliminate any unnecessary state transitions. Consequently, the problems of high memory access consumption and big storage space and long matching time during the regular expression matching process of XFA can be efficiently improved. The simulation results convey that our proposed scheme can lower approximately 40% memory access, save about 45% storage space consumption, and reduce about 12% matching time during the same regular expression matching process compared with XFA, but without degrading the matching quality.

An Efficient Complex Event Processing Algorithm based on Multipattern Sharing for Massive Manufacturing Event Streams

( Jianhua Wang ),( Yubin Lan ),( Shilei Lu ),( Lianglun Cheng ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.3

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

A Quick Tables Look-up Algorithm based on Hash Query for CAVLC Decoding

Jianhua Wang,Lianglun Cheng,Jun Liu 보안공학연구지원센터(IJSIP) 2013 International Journal of Signal Processing, Image Vol.6 No.5

Electrospinning versus microfluidic spinning of functional fibers for biomedical applications

Cheng, Jie,Jun, Yesl,Qin, Jianhua,Lee, Sang-Hoon Elsevier 2017 Biomaterials Vol.114 No.-

<P><B>Abstract</B></P> <P>Micro- or nanofiber-based materials have extensive applications in biomedical fields due to their capability to mimic many aspects of physiological microenvironment <I>in vivo</I>. Fabricating micro- or nanofibers using biocompatible and biodegradable materials is becoming of great interest in the area of biomaterials and tissue engineering. Among the various technologies, electrospinning and microfluidic spinning are the two promising approaches to produce fibers at micro- and nano-scale. Choosing an appropriate spinning method is critical important for a specific application. Although some review papers on each spinning method have been published, a review comparing these two methods has not been reported yet. In this review, we present an overview of the two spinning methods including the spinning principle, their unique features and materials selections. Several applications of fibers spun by both methods, especially in tissue engineering, organ function regeneration and drug delivery are introduced. The current challenges, future directions and potential applications of these approaches are discussed as well.</P>

A Fast CU Size Decision Optimal Algorithm Based on Neighborhood Prediction for HEVC

Jianhua Wang,Haozhan Wang,Fujian Xu,Jun Liu,Lianglun Cheng 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.4

High efficiency video coding (HEVC) employs quadtree coding tree unit (CTU) structure to improve its coding efficiency, but at the same time, it also requires a very high computational complexity due to its exhaustive search processes for an optimal coding unit (CU) partition. With the aim of solving the problem, a fast CU sizedecision optimal algorithm based on neighborhood prediction is presented for HEVC in this paper. The contribution of this paper lies in the fact that we successfully use the partition information of neighborhood CUs in different depth to quickly determine the optimal partition mode for the current CU by neighborhood prediction technology, which can save much computational complexity for HEVC with negligible RDrate(ratedistortion rate) performance loss. Specifically, in our scheme, we use the partition information of left, up, and leftup CUs to quickly predict the optimal partition mode for the current CU by neighborhood prediction technology, as a result, our proposed algorithm can effectively solve the problem above by reducing manyunnecessary prediction and partition operations for HEVC. The simulation results show that our proposed fast CU size decision algorithm based on neighborhood prediction in this paper can reduce about 19.0% coding time, and only increase 0.102% BDrate (Bjontegaard delta rate) compared with the standard reference softwareof HM16.1, thus improving the coding performance of HEVC.

An Efficient Complex Event Processing Algorithm based on NFA_HTS for Massive RFID Event Stream

Jianhua Wang,Jun Liu,Jun Liu,Lianglun Cheng 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.2

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.