• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1136-1146
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• 2005

Fingerprint classification is useful in an automated fingerprint identification system (AFIS) to reduce the matching time by categorizing fingerprints. Based on Henry system that classifies fingerprints into S classes, various techniques such as neural networks and support vector machines (SVMs) have been widely used to classify fingerprints. Especially, SVMs of high classification performance have been actively investigated. Since the SVM is binary classifier, we propose a novel classifier-combination model, multiple decision templates (MuDTs), to classily fingerprints. The method extracts several clusters of different characteristics from samples of a class and constructs a suitable combination model to overcome the restriction of the single model, which may be subject to the ambiguous images. With the experimental results of the proposed on the FingerCodes extracted from NIST Database4 for the five-class and four-class problems, we have achieved a classification accuracy of $90.4\%\;and\;94.9\%\;with\;1.8\%$ rejection, respectively.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.603-615
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• 2005

As recent business environments are changed and become complex, a more efficient and effective business process management are needed. This paper proposes a new approach to the automatic execution of business processes using Event-Condition-Action (ECA) rules that can be automatically triggered by an active database. First of all, we propose the concept of blocks that can classify process flows into several patterns. A block is a minimal unit that can specify the behaviors represented in a process model. An algorithm is developed to detect blocks from a process definition network and transform it into a hierarchical tree model. The behaviors in each block type are modeled using ACTA formalism. This provides a theoretical basis from which ECA rules are identified. The proposed ECA rule-based approach shows that it is possible to execute the workflow using the active capability of database without users' intervention.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.141-150
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• 2004

The method of reusing the environmental data which is previously modelled in modeling and simulation is very important. So, we need an environmental data representation and interchange mechanism which satisfies the requirements of sharing. The SEDRIS STF(SEDRIS Transmittal Format) provides environmental data users and producers with a clearly defined interchange specification. In this paper, We design and implement an automatic converter which converts commercial data(Maya) format to standard interchange format and vice verse without losing semantic of information content using SEDRIS standard interchange format.

• Applied Chemistry for Engineering
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• v.5 no.6
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• pp.1016-1023
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• 1994

In process of manufacturing acrylonitrile azeotrope of acetonitrile-water was come into being as by-product. For the purpose of recovering acetonitrile through solvent extraction process benzene, toluene, o-xylene, ethylacetate and monochlorobenzene as solvents were selected in order to separate acetonitrile from azeotrope of acetonitrile-water. In this study liquid-liquid equilibrium data were determined and consistency of the experimental data was investigated. The tie line and plait point for solvent(1)-water(2)-acetonitrile(3) system were determined at $25^{\circ}C$. The parameters in the NRTL, UNIQUAC and modified UNIQUAC model were predicted, distribution coefficient and selectivity of each solvent were determined respectively.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.239-249
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• 2006

Interoperability has been deemphasized from the hospital information system in general, because it is operated independently of other hospital information systems. This study proposes a future-oriented hospital information system through the design and actualization of the HL7 clinical document architecture. A clinical document is generated using the hospital information system by analysis and designing the clinical document architecture, after we defined the item regulations and the templates for the release form and radiation interpretation form. The schema is analyzed based on the HL7 reference information model, and HL7 interface engine ver.2.4 was used as the transmission protocol. This study has the following significance. First, an expansion and redefining process conducted, founded on the HL7 clinical document architecture and reference information model, to apply international standards to Korean contexts. Second, we propose a next-generation web based hospital information system that is based on the clinical document architecture. In conclusion, the study of the clinical document architecture will include an electronic health record (EHR) and a clinical data repository (CDR), and also make possible medical information-sharing among various healthcare institutions.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.35-45
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• 2007

This paper proposes a classification model for systematical management of resources in educational repositories. A classification scheme should be provided to systematically store and manage, precisely retrieve, and maximize the usability of the resources. However, there is little research result on the classification scheme and classification model for educational repository resources. It causes several issues such as inefficient management of educational resources, incorrect retrieval, and low usability. However, there are different characteristics between the educational resource information and information of the previous fields. Therefore, a novel research on the classification scheme and classification model for the resources in educational repositories is required. To achieve the goal for efficient and easy use of the educational resources, we should manage consistently the resources according to the classification scheme accepting several views. This paper proposes a classification model to systematically manage and increase the usability of the educational resources. In other words, the proposed classification model can manages dynamically the classification scheme for the resources in educational repositories according to various views. To achieve the objectives, we first define a proper classification scheme for the implementation resources based on the classification scheme in relevant scientific technology fields. Especially, we define a novel classification model to dynamically manage the defined classification scheme. The proposed classification scheme and classification model enable more precise and systematic management of implementation resources and also increase the ease of usability.

• Microbiology and Biotechnology Letters
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• v.20 no.5
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• pp.597-606
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• 1992

Effects of dilution rate, inlet glucose and ammonium chloride concentrations on ,he performance of continuous culture of Alcaligenes eutrQPhus for poly-p-hydroxybutyrate (PHB) production were investigated. When inlet substrate concentrations were maintained constant (inlet glucose concentration = 20 g/l, inlet ammonium chloride concentration = 2 g/l), growth rate of residual biomass and PHB production rate showed its maximum at $0.1h^{-1}$ and $0.06h^{-1}$, respectively, and washout at $0.13h^{-1}$. PHB content decreased from 50% to 25% by increasing dilution rate, while specific PHB production rate increased continuously. Cell mass and PHB concentration gave its maximum values at inlet ammonium chloride concentration of 2 g/l and thereafter decreased, which showed the existence of substrate inhibition by ammonium. When inlet glucose concentration was 30 g/l, cell mass reached its maximum value, while PHB concentration increased continuously. The parameters of kinetic model were evaluated by the graphical and parameter estimation methods. The computer simulation results for the effects of dilution rate, inlet glucose and ammonium chloride concentrations fitted the experimental data very well.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.299-308
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• 2004

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance probability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a Protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated for the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as teaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.