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A Knowledge-Based Image Segmentation System and Its Hardware Support System
Jing, Shen Xuan,Ji, Qian Qing 대한전자공학회 1992 HICEC:Harbin International Conference on Electroni Vol.1 No.1
A major problem in machine vision is the segmentation of images. In this paper, we present a new approach to solve the image segmentation problem that is based on the design of a knowledge-based image segmentation system(KBISS). The KBISS is an expert system which is based on production system, and according to two type knowledge, i.e region analysis rules and line analysis rules, performs the image segmentation. In general, a knowledge-based system realized on the conventional computer is low efficient. For this reason, we developed a KBISS hardware support system which is an electro-optical hybrid system. The experiment results show the KBISS and its hardware support system is valid and reasonable.
Shen, Xing-Rong,Feng, Rui,Chai, Jing,Cheng, Jing,Wang, De-Bin Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.22
Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.
Shen, Xing-Rong,Chai, Jing,Feng, Rui,Liu, Tong-Zhu,Tong, Gui-Xian,Cheng, Jing,Li, Kai-Chun,Xie, Shao-Yu,Shi, Yong,Wang, De-Bin Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.24
The big gap between efficacy of population level prevention and expectations due to heterogeneity and complexity of cancer etiologic factors calls for selective yet personalized interventions based on effective risk assessment. This paper documents our research protocol aimed at refining and validating a two-stage and web-based cancer risk assessment tool, from a tentative one in use by an ongoing project, capable of identifying individuals at elevated risk for one or more types of the 80% leading cancers in rural China with adequate sensitivity and specificity and featuring low cost, easy application and cultural and technical sensitivity for farmers and village doctors. The protocol adopted a modified population-based case control design using 72, 000 non-patients as controls, 2, 200 cancer patients as cases, and another 600 patients as cases for external validation. Factors taken into account comprised 8 domains including diet and nutrition, risk behaviors, family history, precancerous diseases, related medical procedures, exposure to environment hazards, mood and feelings, physical activities and anthropologic and biologic factors. Modeling stresses explored various methodologies like empirical analysis, logistic regression, neuro-network analysis, decision theory and both internal and external validation using concordance statistics, predictive values, etc..
Fractional order viscoelasticity in characterization for atrial tissue
Jing Jin Shen,Cheng Gang Li,Hongtao Wu,Masoud Kalantari 한국유변학회 2013 Korea-Australia rheology journal Vol.25 No.2
Atrial tissue due to its solid-like and fluid-like constituents shows highly viscoelastic properties. Up to now, the distribution pattern of muscle fiber in heart is not well established, and it is hard to establish the constitutive model for atrial tissue completely based on the microstructure level. Consider the equivalence between the fractional viscoelasticity and the fractal spring-dashpot model, a generalized fractional order Maxwell model is proposed to model the porcine atrial tissue in the phenomenological sense. This model has a simple expression and intuitively physical meanings. The constitutive parameters in the model are estimated in the complex domain by a genetic algorithm. Final results illustrate the proposed model gets a well agreement with the experimental data.
Fractional order viscoelasticity in characterization for atrial tissue
Shen, Jing Jin,Li, Cheng Gang,Wu, Hong Tao,Kalantari, Masoud 한국유변학회 2013 Korea-Australia rheology journal Vol.25 No.2
Atrial tissue due to its solid-like and fluid-like constituents shows highly viscoelastic properties. Up to now, the distribution pattern of muscle fiber in heart is not well established, and it is hard to establish the constitutive model for atrial tissue completely based on the microstructure level. Consider the equivalence between the fractional viscoelasticity and the fractal spring-dashpot model, a generalized fractional order Maxwell model is proposed to model the porcine atrial tissue in the phenomenological sense. This model has a simple expression and intuitively physical meanings. The constitutive parameters in the model are estimated in the complex domain by a genetic algorithm. Final results illustrate the proposed model gets a well agreement with the experimental data.
( Jing Shen Ou ),( Yi Cheng Cao ) 한국미생물 · 생명공학회 2014 Journal of microbiology and biotechnology Vol.24 No.9
In this study, the yeast Pichia pastoris was genetically modified to assemble minicellulosomes on its cell surface by the heterologous expression of a truncated scaffoldin CipA from Clostridium acetobutylicum. Fluorescence microscopy and western blot analysis confirmed that CipA was targeted to the yeast cell surface and that NtEGD, the Nasutitermes takasagoensis endoglucanase that was fused with dockerin, interacted with CipA on the yeast cell surface, suggesting that the cohesin and dockerin domains and cellulose-binding module of C. acetobutylicum were functional in the yeasts. The enzymatic activities of the cellulases in the minicellulosomes that were displayed on the yeast cell surfaces increased dramatically following interaction with the cohesin-dockerin domains. Additionally, the hydrolysis efficiencies of NtEGD for carboxymethyl cellulose, microcrystal cellulose, and filter paper increased up to 1.4-fold, 2.0-fold, and 3.2-fold, respectively. To the best of our knowledge, this is the first report describing the expression of C. acetobutylicum minicellulosomes in yeast and the incorporation of animal cellulases into cellulosomes. This strategy of heterologous cellulase incorporation lends novel insight into the process of cellulosome assembly. Potentially, the surface display of cellulosomes, such as that reported in this study, may be utilized in the engineering of S. cerevisiae for ethanol production from cellulose and additional future applications.
Jing Shen,Jilin Zhang,Jian Wan,Li Zhou,Ming Jiang 보안공학연구지원센터 2014 International Journal of Database Theory and Appli Vol.7 No.6
Stencils are finite-difference algorithms for solving large-scale and high-dimension partial differential equations. Due to the data dependences among the iterative statements in Stencils, traditional Stencil computations are be executed serially, rather than in parallel. It’s challenging to design an effective and scalable Stencil parallelized method. To address the issue of 3D data space computing, we present a serial execution model based on multi-layers symmetric Stencil method and time skewing techniques. Within this model, the iteration space is divided to multiple tiles based on time skewing, where the executive process is ordered by the sequence of tiles, and the nodes in each individual tile can be swept repeatedly to improve the data locality. In addition, we propose a novel 3D iterative space alternate tiling Stencil parallel method, which subdivides the iteration space along high dimension, and changes the execution sequence of tiles to reduce the data dependency and communication cost, where the partial order of tiles is still guaranteed. Experimental results demonstrate our proposed alternative tiling parallel method achieves better parallel efficiency and scalability compared with the domain-decomposition methods.