• Journal of the Korea Institute of Information Security & Cryptology
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• v.7 no.3
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• pp.79-94
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• 1997

OMG (Object Management Group) published a security service specification, called CORBA (Common Object Request Broker Architecture) security reference model because the integration of security and object-oriented techniques was critical for successful deployment of distributed object systems. The CORBA security reference model treats access control as an implementation independent semantic concept but has incomplete semantics of the access control function. Because of such imcompleteness it is difficult for the system administrator and the CORBA security implementor to have the same understanding for the meaning of access control in the CORBA security. We propose a formal model for access control the CORBA security using the formal description language, which is called Z language based on typed set theory. The proposed model provides concrete semantics of the access control function to both the system administrator and the implementor.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.75-83
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• 2015

In mobile ad-hoc networks (MANETs), nodes are mobile in nature. Collaboration between mobile nodes is more significant in MANETs, which have as their greatest challenges vulnerabilities to various security attacks and an inability to operate securely while preserving its resources and performing secure routing among nodes. Therefore, it is essential to develop an effective secure routing protocol to protect the nodes from anonymous behaviors. Currently, game theory is a tool that analyzes, formulates and solves selfishness issues. It is seldom applied to detect malicious behavior in networks. It deals, instead, with the strategic and rational behavior of each node. In our study,we used the dynamic Bayesian signaling game to analyze the strategy profile for regular and malicious nodes. This game also revealed the best actions of individual strategies for each node. Perfect Bayesian equilibrium (PBE) provides a prominent solution for signaling games to solve incomplete information by combining strategies and payoff of players that constitute equilibrium. Using PBE strategies of nodes are private information of regular and malicious nodes. Regular nodes should be cooperative during routing and update their payoff, while malicious nodes take sophisticated risks by evaluating their risk of being identified to decide when to decline. This approach minimizes the utility of malicious nodes and it motivates better cooperation between nodes by using the reputation system. Regular nodes monitor continuously to evaluate their neighbors using belief updating systems of the Bayes rule.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.6
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• pp.683-690
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• 2015

In Rough set, attribute missing values have several problems such as reduct and core estimation. Further, they do not give some discernable pattern for decision tree construction. Now, there are several methods such as substitutions of typical attribute values, assignment of every possible value, event covering, C4.5 and special LEMS algorithm. However, they are mainly substitutions into frequently appearing values or common attribute ones. Thus, decision rules with high information loss are derived in case that important attribute values are missing in pattern matching. In particular, there is difficult to implement cross validation of the decision rules. In this paper we suggest new method for substituting the missing attribute values into high information gain by using entropy variation among given attributes, and thereby completing the information table. The suggested method is validated by conducting the same rough set analysis on the incomplete information system using the software ROSE.

• The Research Journal of the Costume Culture
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• v.24 no.6
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• pp.803-816
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• 2016

The purposes of this study were to investigate the influences of channel assessments on the usage of multi-channels by product types, and the differences in the usage of multi-channels among product types in buying decision making process for fashion products. Data were collected from 510 consumers in their 20s to 50s with purchasing experiences through multi-channel distribution system and living in Seoul and Kyunggi province; 491 were analyzed after deleting incomplete questionnaires. Factor analysis, multiple regression analysis and one-way ANOVA were used for statistical analysis by using SPSS 18.0. The results were as follows: 5 factors were extracted for channel assessment: utility, accuracy, risk, price benefit and sharing information. Price benefits, utility and sharing information for online channel tended to influence positively on the usage of online channel and online+offline channels. Accuracy and low perceived risk of offline influenced positively on offline and on+offline channel usages. The usage levels of on-line and off-line channels for cosmetics were significantly lower than the usage levels for clothes and accessories on information search, evaluation of alternatives, and purchase stages. Significant differences were also found in the usage levels of multi-channels (on+off-line) on information search and evaluation of alternatives stages. The usage levels of the multi-channels for clothes were the highest followed by those of accessories and cosmetics in order.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.670-679
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• 2015

With a rapid development of internet, many users these days refer to various recommender sites when buying items, movies, music and more. However, there are malicious users (Sybil) who raise or lower item ratings intentionally in these recommender sites. And as a result, a recommender system (RS) may recommend incomplete or inaccurate results to normal users. We suggest a recommender algorithm to separate ratings generated by users into normal ratings and outlier ratings, and to minimize the effects of malicious users. Specifically, our algorithm first ensures a stable RS against three kinds of attack models (Random attack, Average attack, and Bandwagon attack) which are the main recent security issues in RS. To prove the performance of the method of suggestion, we conducted performance analysis on real world data that we crawled. The performance analysis demonstrated that the suggested method performs well regardless of Sybil size and type when compared to existing algorithms.

• Smart Structures and Systems
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• v.3 no.3
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• pp.245-261
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• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.1
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• pp.34-40
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• 2012

We have developed a highly sensitive inspection technique based on an electron beam inspection for detecting the contact failure of a poly-Si plugged layer. It was difficult to distinguish the contact failure from normal landing plugs with high impedance. Normally, the thermal annealing method has been used to decrease the impedance of poly-Si plugs and this method increases the difference of charged characteristics and voltage contrast. However, the additional process made the loss of time and broke down the device characteristics. Here, the interval scanning method without thermal annealing was effectively applied to enhance the difference of surface voltage between well-contacted poly-Si plugs and incomplete contact plugs. It is extremely useful to detect the contact failures of non-annealed plug contacts with high impedance.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Toxicological Research
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• v.29 no.4
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• pp.221-227
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• 2013

Embryonic stem (ES) cells have potential for use in evaluation of developmental toxicity because they are generated in large numbers and differentiate into three germ layers following formation of embryoid bodies (EBs). In earlier study, embryonic stem cell test (EST) was established for assessment of the embryotoxic potential of compounds. Using EBs indicating the onset of differentiation of mouse ES cells, many toxicologists have refined the developmental toxicity of a variety of compounds. However, due to some limitation of the EST method resulting from species-specific differences between humans and mouse, it is an incomplete approach. In this regard, we examined the effects of several developmental toxic chemicals on formation of EBs using human ES cells. Although human ES cells are fastidious in culture and differentiation, we concluded that the relevancy of our experimental method is more accurate than that of EST using mouse ES cells. These types of studies could extend our understanding of how human ES cells could be used for monitoring developmental toxicity and its relevance in relation to its differentiation progress. In addition, this concept will be used as a model system for screening for developmental toxicity of various chemicals. This article might update new information about the usage of embryonic stem cells in the context of their possible ability in the toxicological fields.

• Progress in Medical Physics
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• v.25 no.4
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• pp.271-280
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• 2014

Recently, digital breast tomosynthesis (DBT) has been investigated to overcome the limitation of conventional mammography for overlapping anatomical structures and high patient dose with cone-beam computed tomography (CBCT). However incomplete sampling due to limited angle leads to interference on the neighboring slices. Many studies have investigated to reduce artifacts such as interference. Moreover, appropriate filters for tomosynthesis have been researched to solve artifacts resulted from incomplete sampling. The primary purpose of this study is finding appropriate filter scheme with FBP reconstruction for DBT system to reduce artifacts. In this study, we investigated characteristics of various filter schemes with simulation and prototype digital breast tomosynthesis under same acquisition parameters and conditions. We evaluated artifacts and noise with profiles and COV (coefficinet of variation) to study characteristic of filter. As a result, the noise with parameter 0.25 of Spectral filter reduced by 10% in comparison to that with only Ramp-lak filter. Because unbalance of information reduced with decreasing B of Slice thickness filter, artifacts caused by incomplete sampling reduced. In conclusion, we confirmed basic characteristics of filter operations and improvement of image quality by appropriate filter scheme. The results of this study can be utilized as base in research and development of DBT system by providing information that is about noise and artifacts depend on various filter schemes.