• Journal of the Korean Society of Food Culture
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• v.17 no.1
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• pp.16-29
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• 2002

This study had two major purposes: 1) to establish a quantitative measure of the overall restaurant attractiveness for each of the selected restaurants. 2) to examine the implications of the findings from the above concerning the operating initiatives necessary to improve the restaurant attractiveness. A multi attribute model was employed to obtain a numerical index of the attractiveness for each of the three fast food restaurants. It was found that certain of the attributes selected were clearly established as determinant variables(p<0.05). The research plotted the location of Attributes on a graph where the axes are the salience and importance scores to indicate approximate positions in four cells. Finally, the implications of these findings concering marketing and develpment initiatives to improve the perceptual attractiveness of the three fast food restaurant1.s are discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.111-126
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• 2002

This paper presents an interactive decision procedure to aggregate each group member's preferences when each group member articulates his or her preference information incompletely. An index, an indicative for the preference strength between alternatives, is derived to aid each decision maker to articulate preference information about alternatives. We develop a mathematical programming model that can establish dominance relations when the preference information about values of alternatives, attribute weights, and group member's importance weights are provided incompletely. Also, the preference relation between alternatives is to be considered in the model. Based on the preference strength measure and mathematical model, we develop an interactive group decision support procedure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1597-1605
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• 2015

Password authenticated key exchange (PAKE) is a protocol that a client stores its password to a server, authenticates itself using its password and shares a session key with the server. In multi-server PAKE, a client splits its password and stores them to several servers separately. Unless all the servers are compromised, client's password will not be disclosed in the multi-server setting. In attribute-based encryption (ABE), a sender encrypts a message M using a set of attributes and then a receiver decrypts it using the same set of attributes. In this paper, we introduce multi-server PAKE protocol that utilizes a set of attributes of ABE as a client's password. In the protocol, the client and servers do not need to create additional public/private key pairs because the password is used as a set of public keys. Also, the client and the servers exchange only one round-trip message per server. The protocol is secure against dictionary attacks. We prove our system is secure in a proposed threat model. Finally we show feasibility through evaluating the execution time of the protocol.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.319-332
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• 2008

Data cube, which is multi-dimensional data model, have been successfully applied in many cases of multi-dimensional data analysis, and is still being researched to be applied in data stream analysis. Data stream is being generated in real-time, incessant, immense, and volatile manner. The distribution characteristics of data arc changing rapidly due to those characteristics, so the primary rule of handling data stream is to check once and dispose it. For those characteristics, users are more interested in high support attribute values observed rather than the entire attribute values over data streams. This paper propose dynamic data cube for applying data cube to data stream environment. Dynamic data cube specify user's interested area by the support ratio of attribute value, and dynamically manage the attribute values by grouping each other. By doing this it reduce the memory usage and process time. And it can efficiently shows or emphasize user's interested area by increasing the granularity for attributes that have higher support. We perform experiments to verify how efficiently dynamic data cube works in limited memory usage.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.492-499
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• 2009

This research was conducted in order to know how influential the acknowledgment of factors such as the quality of educational contents and the conducting of off-line lectures is in terms of effective learning for leaners. Based on the satisfaction-importance model of the multi-attribute attitude model, this study would like to clarify the degree to which the quality of on-line contents of on-line education and the simultaneous conducting of off-line lectures influences one's learning attitude. On-line contents satisfaction will evaluated through the three categories: audio lectures, video lecture and WEI lectures, which make up the quality of on-line contents. We would also like to do a survey on the transformation of learning attitudes when on-line and off-line lectures were conducted simultaneously.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.373-377
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• 2009

This research was conducted in order to know how influential the acknowledgment of factors such as the quality of educational contents and the conducting of off-line lectures is in terms of effective learning for leaners. Based on the satisfaction-importance model of the multi-attribute attitude model, this study would like to clarify the degree to which the quality of on-line contents of on-line education and the simultaneous conducting of off-line lectures influences one's learning attitude. On-line contents satisfaction will evaluated through the three categories: audio lectures, video lecture and WBI lectures, which make up the quality of on-line contents. We would also like to do a survey on the transformation of learning attitudes when on-line and off-line lectures were conducted simultaneously.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.32-39
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• 2020

In the large-scale infrastructure of cloud environment, illegal access rights are frequently caused by sharing applications and devices, so in order to actively respond to such attacks, a strengthened access control system is required to prepare for each situation. We proposed an entity attribute-based access control(EABAC) model based on security level and relation concept. This model has enhanced access control characteristics that give integrity and confidentiality to subjects and objects, and can provide different services to the same role. It has flexibility in authority management by assigning roles and rights to contexts, which are relations and context related to services. In addition, we have shown application cases of this model in multi service environment such as university.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.249-273
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• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• Proceedings of the Technology Innovation Conference
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• 1999.06a
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• pp.245-265
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• 1999

MAUT and AHP are widely used for quantification of subjective judgements in various fields of decision making. This study focuses on the introduction and application of MAUT/AHP method which is a hybrid of MAUT and AHP techniques in R&D project priority setting. This hybrid model can clarify each factors' contribution using MAUT method and can reduce the number of pairwise comparisons of AHP method. This study applies AMUT/AHP method to the evaluation of R&D projects in a Government - funded research institute. To evaluate R&D projects, six evaluation factors are derived. SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement ) out of many MAUT methods are used to design the utility function ad AHP is used to allocate the weights among evaluation factors. The major findings of this study can be summarized as follows. First, the SMART/AHP and the DVM/AHP have the same results with the SMART and the DVM, and they are different results with AHP. It is very hard to decide which one is better. Second, MAUT/AHP's strength is analyzed. MAUT reflects utility values of evaluators to alternatives and AHP results objective and consistent weights of factors through pariwise comparisons. Third, its possible application fields are proposed. It is applicable to subjective decision making problems with high complexity and inter-independent factors.