• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.221-230
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• 2011

Digital comic images are one of popular contents on the Internet. Usually, they are scanned from comic books by digital scanners. Without post-processing, they may have different sizes, skews and margins other than contents at the boundary. To normalize the size of their contents without the skews and margins is an important step in comic image analysis and application such as content-based comic image retrieval system. In this paper, we propose a method to detect a box frame in comic images by extracting of line segments using the gradient Radon transform. The box frame in comic images is the maximum rectangle which consists of contents without margins. We use the detected box frame to normalize the size of comic images and to make them no skew. In addition, the proposed method is implemented by OpenCL to speed up the detection of the line segments. Experimental results show that our proposed method effectively detects the box frame in comic images.

• Convergence Security Journal
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• v.8 no.4
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• pp.105-113
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• 2008

Mobile computing environment is known to be quite difficult to provide user with a stable Quality of Service (QoS) due to vehicle mobility nature. In order to protect the inherent characteristics of wireless network such as low bandwidth and high transmission delay along with the vehicle's mobility, many works are conducted to apply caching and prefetching methods. This paper presents a novel prefetching technique which is based on owner's profile. It is the scheme with the vehicle velocity, the visit frequency and resident time of specific region for vehicle owner's past given period, and the user profile which has owner's personal inclination about a certain place. The proposed scheme shown relatively superior performance in terms of the utilization ratio of prefetched information and the failure ratio of information retrieval than the previous methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.9-16
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• 2005

For designing the database more efficiently, normailzation can be enforced to minimize the degree of unnecessary data redundancy and contribute to enhance data integrity. However, deep normalization tends to provoke multiple way of schema join, which could then induces response time degradation. To mitigate this sort of side effect that the normalization could brought, a number of field studies we observed adopted the idea of denormalization. To measure whether denormalization contributes to response time improvement, we in this paper developed two different data models about customer service system, one with perfect normalization and the other with denormalization, and evaluated their query response time behaviors. Performance results show that normalization case consistently outperforms denormalization case in terms of response time. This study show that the idea of denormalization, quite rarely contributes to that sort of improvement due ironically to the unnecessary data redundancy.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.262-267
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• 2006

Inhibitory effects of fungal metabolites isolated from foodstuffs on growth of human cancer cell lines were evaluated. Isolated strains were divided into four classes based on color (aerial, reverse), shape, and growth speed. Fungal metabolites extracted with ethyl acetate were investigated for their growth inhibition on six kinds of human cancer cells by MTT assay. Ethyl acetate extract showed high growth inhibition against all cancer cells tested, with D4 exhibiting the strongest growth inhibition effects against Kato III, AGS, Hepa1c1c7, and MDA-MB-231 cancer cells. These results suggest ethyl acetate extract from fungal metabolites as effective natural cancer therapeutic material.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.137-141
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• 2005

Optimal path search algorithm should consider traffic flows of the roads as well as the distance between a departure and destination, The existing path search algorithms, however, usually don't apply the continuously changed traffic flows. In this paper, we propose a new optimal path search algorithm. the algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road networks into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and $A^*$ algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• The KIPS Transactions:PartA
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• v.18A no.2
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• pp.75-80
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• 2011

Recently, many cleaning robots have been made with various algorithms for efficient cleaning. One of them is a DmaxCoverage algorithm which efficiently clean for the situation when the robot has a time limit. This algorithm uses Rectangle Tiling method for finding the biggest rectangle that doesn't have any obstacle. When the robot uses grid map, Rectangle Tiling method can find the optimal value. Rectangle Tiling method is to find all of the rectangles in the grid map. But when the grid map is big, it has a problem that spends a lot of times because of the large numbers of rectangles. In this paper, we propose Four Direction Rectangle Scanning(FDRS) method that has similar accuracy but faster than Rectangle Tiling method. FDRS method is not to find all of the rectangle, but to search the obstacle's all directions. We will show the FDRS method's performance by comparing of FDRS and Rectangle Tiling methods.

• Journal of the Korean Institute of Gas
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• v.3 no.1
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• pp.41-47
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• 1999

Recently, HAZOP has been used as one of the most effective way of qualitative risk assessment for plant industries. However, this technique requires much man labor to be successfully performed. This fact enables the adequate HAZOP worksheet program to help speeding up the procedure and managing the data of analysis. Based on the experience of HAZOP carrying out, the authors focused the purpose of this study on developing a useful and comfortable HAZOP worksheet program. The unique characteristics of developed program are the menu window expressed in common steps of HAZOP, versatile edit functions, and search menu for investigating the scenario data. The tendency analysis for existing HAZOP results was performed to validate the usefulness of the developed program.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.89-104
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• 2011

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In order to extract these entities automatically from scientific documents at once, we developed a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer and terminology extractor.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.855-864
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• 2001

With the increasing importance and complexity of EC (Electronic Commerce) across the Internet, the need and expectation for intelligent software agents to support both consumers and suppliers through the whole process of EC are growing rapidly. To realize the intelligent EC. a multiagent based EC system. which includes foundational technologies such as the establishment of standard product ontology the definition of message and negotiation protocol and brockering, is required. In this paper we propose an intelligent EC System named ICOMA(Intelligent electronic CO mmerce system based on Multi-Agent) as an open infrastructure of multiagent-based EC. Concretely we have proposed. designed and implemented an architecture of multiagent-based EC system including 6-types of agents message protocol for inter-agent negotiation, personalized produst retrieval and filtering., We have confirmed the effectiveness of the system through experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.285-290
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• 2010

인터넷이 대중화됨에 따라 누구나 쉽게 자신의 의견을 온라인상에 표현할 수 있게 되었다. 그 결과 생각이나 느낌을 나타내는 의견 데이터들의 양이 급속도로 방대해졌으며, 이러한 데이터들을 이용한 여러 응용 사례들의 등장으로, 효율적인 검색 및 자동 분류 기술이 요구되고 있다. 이런 기술적 흐름에 맞추어 의견 데이터 분류에 관한 여러 연구들이 이루어져 왔다. 이러한 의견 분류에 대한 연구들을 살펴보면, 분류를 위해 자질(Feature)로서 사용한 단일어(Single word)가 아닌 2개 이상의 N-gram 단어, 어휘 구문 패턴 및 통사 구문 패턴 등을 사용한다. 특히, 패턴은 단일어나 N-gram 단어에 비해 유연하고, 언어학적으로 풍부한 정보를 표현할 수 있기 때문에 이를 주요 연구 주제로 사용되었다. 그럼에도 불구하고, 이러한 연구들은 주로 영어에 대한 연구들이었으며, 한국어에 패턴을 적용하여 주관성을 갖는 문장을 분류하거나, 극성을 분류하는 연구들은 아직 미비하다. 한국어의 특색으로 한국어는 용언의 활용이 발달되어 있어, 어미의 변화가 다양하며, 그 변화에 따라 의미가 미묘하게 변화한다. 그러나 기존 한국어에 대한 의견 분류 연구들은 단어의 핵심 의미만을 파악하기 위해 어미 부분을 제거하고 어간만을 취해서 처리하여 어미에 대한 의미변화를 고려하지 못하므로 분류 정확도가 영어권에 연구 결과에 비해 떨어진다. 그래서 본 연구는 영어에 적용된 패턴을 이용한 기존 방법들을 정리하고, 그 방법들 중에서 극성을 지닌 문장성분 패턴을 한국어에 적용하였다. 그리고 어미의 변화에 대한 패턴을 추출하여 이 변화가 의견 분류의 성능에 미치는 영향을 분석하였다.