• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.71-79
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• 2009

Currently much research is being done on host based intrusion detection using system calls which is a portion of kernel based data. Sequence based and frequency based preprocessing methods are mostly used in research for intrusion detection using system calls. Due to the large amount of data and system call types, it requires a significant amount of preprocessing time. Therefore, it is difficult to implement real-time intrusion detection systems. Despite this disadvantage, the frequency based method which requires a relatively small amount of preprocessing time is usually used. This paper proposes an effective method for detecting denial of service attacks using the frequency based method. Principal Component Analysis(PCA) will be used to select the principle system calls and a bayesian network will be composed and the bayesian classifier will be used for the classification.

• Journal of Korean Society for Quality Management
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• v.26 no.2
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• pp.27-38
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• 1998

Consider a life testing experiment in which multiple two-component shared parallel systems are put on test, and the test is terminated at a specified number of system failures. The bivariate data obtained from such a system-level life testing can be classified into three classes: 1) the case of failed two components with known failure times, 2) the case of censored two components, and 3) the case of one censored component and the other failed component of which the failure time might be known or unknown. Under this censoring scheme and the assumption of Freund's bivariate exponential life distribution, the maximum likelihood estimators are obtained. Results of comparative studies based on Monte Carlo simulation are presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.142-147
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• 2011

In this paper, we make a RT component as a configuration element of cooperation robot of 7 degree of freedom manipulator using RTM which was adapted international standardization among the robot middleware technology. We implemented the one system by connecting the RT component of elements of a robot organize to each other based on middleware network and tested an operation of implemented system using the 7 degree of freedom manipulator which was real made.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.126-128
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• 2004

As e-mail is becoming increasingly important in every day life activity, mail users spend more and more time organizing and classifying the e-mails they receive into folder. Many existing recommendation systems or text classification are mostly focused on recommending the products for the commercial purposes or web documents. So this study aims to apply these application to e-mail more necessary to users. This paper suggests a dynamic recommendation agent system based on Rule Filtering Component recommending the relevant category to enable users directly to manage the optimum classification when a new e-mail is received as the effective method for E-Mail Management. Moreover we try to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, we prove to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. We designed main modules by rule filtering component for enhanced scalability and reusability of our system.

• Journal of Digital Contents Society
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• v.3 no.2
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• pp.177-185
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• 2002

E-Business part is activated to base on contents for supports various constomer's desire. That is, techniqueses for efficient business transaction processing are studied and Web-Based component technology such as EJB is applied. Thus, this research designed Wokeflow for efficient E-Business contents supervision and processing that apply Web-Based EJB component technology. Accordingly, 1 used web server component model EJB for handling of various contents. Components of function module can improve system development efficiency of reusability, maintenance etc.. to process various contents.

• Proceedings of the CALSEC Conference
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• 1999.07b
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• pp.607-614
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• 1999

In this paper, we demonstrate the implementation case using component based development tool under development process for application developments. The tool suggested provides the programming environment for the development of distributed manufacturing applications primarily. The development tool is classified into visual component, logic component, data component, knowledge component, neural net component, and service component which is a core component for the support component edit and execution. We applied the tool to the domain of the design and routing plan to retrieve existing similar design models in database, initiate a model, generate a process plan, and store the new model in the database automatically. Utilizing the tool, it integrates a geometric modeler, engineering/manufacturing database, and knowledge sources over the Internet.

• Journal of Information Technology Services
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• v.1 no.1
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• pp.141-148
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• 2002

As an optimun alternatives for the solution of recent software crisis, we have to develop component technologies so as to develop and propagate business components for various domains to industries. For the sake of development of business components, a conceptual architecture which defines a model for component assembly should be prescribed first, and a systematic specification method based on this model be defined, so we can build a system environments for making specifications and development of each component by the consistent scheme. In this study, we propose a domain architecture model for implementing the pUblic component bank as a project supported by the ministry of information and communication, discuss the conceptual model of specification for developing components of storing component bank, specification steps, specification approach for application of business domains and the development results of them.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• ETRI Journal
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• v.26 no.2
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• pp.167-180
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• 2004

As component-based development (CBD) rapidly spread throughout the software industry, a comprehensive methodology is needed to apply it more systematically. For this purpose, a new CBD methodology named Magic & Robust Methodology Integrated III (MaRMI-III) has been developed. The purpose of this paper is to present MaRMI-III by its constituent processes and claim that it can be used to support system developers conduct CBD in a consistent manner. First, we review the CBD approach to system development and the role of CBD methodology, and then we explain the several characteristics of MaRMI-III which are considered necessary to the CBD environment. Next, we explain a process model of MaRMI-III which separates the development process from the project management process and prescribes well-ordered activities and tasks that the developer should conduct. Each phase forming the Process Model is explained in terms of its objectives and main constituent activities. Some techniques and workproducts related to each phase are also explained. Finally, to examine the usefulness of MaRMI-III, an analytical comparison with other CBD methodologies and the results of a questionnaire survey are described.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.