• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.947-953
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• 2011

These days, a consistent and fatal attack attribute toward a database has proportionally evolved in the similar development form to that of security policy. Because of access control-based defensive techniques regarding information created in closed networks and attacks on a limited access pathway, cases of infringement of many systems and databases based on accumulated and learned attack patterns from the past are increasing. Therefore, the paper aims to separate attack information by its types based on a virtual infringement pattern system loaded with dualistic VM in order to ensure stability to limited certification and authority to access, to propose a system that blocks infringement through the intensive management of infringement pattern concerning attack networks, and to improve the mechanism for implementing a test that defends the final database, the optimal defensive techniques, and the security policies, through research.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.774-779
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• 2012

Brain-computer interface based on motor imagery is a system that transforms a subject's intention into a control signal by classifying EEG signals obtained from the imagination of movement of a subject's limbs. For the new paradigm, we do not know which positions are activated or not. A simple approach is to use as many channels as possible. The problem is that using many channels causes other problems. When applying a common spatial pattern (CSP), which is an EEG extraction method, many channels cause an overfit problem, in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest a binary particle swarm optimization with channel impact factor in order to select channels close to the most important channels as channel selection method. This paper examines whether or not channel impact factor can improve accuracy by Support Vector Machine(SVM).

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.179-192
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• 2007

This paper addresses an approach that recommends investment types for stock investors by discovering useful rules from past changing patterns of stock prices in databases. First, we define a new rule model for recommending stock investment types. For a frequent pattern of stock prices, if its subsequent stock prices are matched to a condition of an investor, the model recommends a corresponding investment type for this stock. The frequent pattern is regarded as a rule head, and the subsequent part a rule body. We observed that the conditions on rule bodies are quite different depending on dispositions of investors while rule heads are independent of characteristics of investors in most cases. With this observation, we propose a new method that discovers and stores only the rule heads rather than the whole rules in a rule discovery process. This allows investors to define various conditions on rule bodies flexibly, and also improves the performance of a rule discovery process by reducing the number of rules. For efficient discovery and matching of rules, we propose methods for discovering frequent patterns, constructing a frequent pattern base, and indexing them. We also suggest a method that finds the rules matched to a query issued by an investor from a frequent pattern base, and a method that recommends an investment type using the rules. Finally, we verify the superiority of our approach via various experiments using real-life stock data.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.353-360
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• 2004

Ontology defines the terms used in a specific domain and the relationships between them and represents them as hierarchical taxonomy. The present paper proposes a semi-automatic domain-specific ontology construction method based on terminology Processing. For this purpose, it presents an algorithm to extract terminology according to the noun/suffix pattern of terminology in domain texts and find their hierarchical structure. The experiment was carried out using pharmacy-related documents. As singleton terminology with noun/suffix were identified, the average accuracy was 92.57%. In case of multi-word terminology, the average accuracy was 66.64%. The constructed ontology forms natural semantic clusters with based on suffices and semantic information, so can be utilized in approaches to specific knowledge such as information look-up or as the base of inference to improve searching abilities.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.303-312
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• 2010

VHF Omnidirectional Radio range(VOR) is used as an aircraft navigational aid. The VOR is a short-range air navigation system providing aircraft with its bearing relative to the ground station. The accuracy of a VOR must be checked in accordance with the current ICAO, FAA and domestic regulations. The primary purpose of performing VOR station ground checks is to minimize the need for expensive flight checks by determining the amount and direction of any course bearing inaccuracies being transmitted. In this paper we present current and advanced way of monitoring of VOR system. We verify this way by field test of the monitoring and it is a high performance way to achieve an improvement in accuracy and an effect compared to present monitoring system.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.63-73
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• 2009

Architecture base mechanism centers to construct software system. There is construction of successful software system how firmly define software. Reason that architecture base software is important is used and expresses early design decision item of system and is because reusability is possible by means of communication between comprehension person concerned. Analyzed special quality of pattern and importance of architecture and general requirement and portability and consider ISO/IEC 9126 and ISO/IEC 14598 and propose system and Metrik in this research. Also, do defect particulars and efficiency test that test according to examination formality of architecture base software and analyzed result.

• Journal of KIISE
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• v.45 no.2
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• pp.99-105
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• 2018

One of the spatial statistical analysis, hotspot analysis is one of easy method of see spatial patterns. It is based on the concept that "Adjacent ones are more relevant than those that are far away". However, in hotspot analysis is spatial adjacency must be considered, Therefore, distributed processing is not easy. In this paper, we proposed a distributed algorithm design for hotspot spatial analysis. Its performance was compared to standalone system and Hadoop, Spark based processing. As a result, it is compare to standalone system, Performance improvement rate of Hadoop at 625.89% and Spark at 870.14%. Furthermore, performance improvement rate is high at Spark processing than Hadoop at as more large data set.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.73-86
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• 2014

The traditional markets representing the lives of ordinary people have been pivotal in retail markets for a long time, but they suffer from deterioration due to the downturns of competitiveness caused by the inactive confrontation with changes of life styles and the large retailers' marketing territories. Recently the efforts to vitalize the traditional markets are widely developed, and this research will cover the necessity of such activation through the use of market competitiveness and cultural properties which have the social and cultural functionalities. By analyzing the case of Namhang market in Busan, this study suggests the specific activation measures in the aspects of hardware, software, human ware, and a joint venture.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.81-91
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• 2011

Hacking tools are evolving along the growth of on-line game industry. Those tools allow users with no programming knowledge to hack the game, which causes a lot of problems in on-line game services. Specifically, FPS games based on peer-to-peer networks are vulnerable to hacks. This paper analyzes cheating patterns by the case of Point Blank in Indonesia and prioritize countermeasures, which helps game companies handle hacks efficiently.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.29-45
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• 2015

Systematic theory, concepts, and methodology for the biological evolution have been developed while patterns and principles of the evolution have been actively studied in the past 200 years. Furthermore, they are applied to various fields such as evolutionary economics, evolutionary psychology, evolutionary linguistics, making significant progress in research. In addition, existing studies have applied main biological evolutionary models to artifacts although such methods do not fit to them. These models are also limited to generalize evolutionary patterns of artifacts because they are designed in terms of a subjective point of view of experts who know well about the artifacts. Unlike biological organisms, because artifacts are likely to reflect the imagination of the human will, it is known that the theory of biological evolution cannot be directly applied to artifacts. In this paper, beyond the individual's subjective, the aim of our research is to present evolutionary patterns of a given artifact based on peeping the idea of the public. For this, we propose a text mining approach that presents a systematic framework that can find out the evolutionary patterns of a given artifact and then visualize effectively. In particular, based on our proposal, we focus mainly on a case study of mobile phone that has emerged as an icon of innovation in recent years. We collect and analyze review posts on mobile phone available in the domestic market over the past decade, and discuss the detailed results about evolutionary patterns of the mobile phone. Moreover, this kind of task is a tedious work over a long period of time because a small number of experts carry out an extensive literature survey and summarize a huge number of materials to finally draw a diagram of evolutionary patterns of the mobile phone. However, in this work, to minimize the human efforts, we present a semi-automatic mining algorithm, and through this research we can understand how human creativity and imagination are implemented. In addition, it is a big help to predict the future trend of mobile phone in business and industries.