• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1183-1186
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• 2014

Our research is different form traditional to have some large LED screen grouping together to constitute multi-vision technique. In this paper, we purpose a method of using k-path diffusion method to build connect between the devices and find an optimal data transmission path. In second half of this paper, through practical application, we using this technique transmitting data successfully and achieving a simple Multi-vision effect. This technique possess smart devices and Wifi P2P's features, these features improve system's dynamic and decentralized processing ability make our technique has high scalability.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.882-895
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• 2020

The amount of malware increases exponentially every day and poses a threat to networks and operating systems. Most new malware is a variant of existing malware. It is difficult to deal with numerous malware variants since they bypass the existing signature-based malware detection method. Thus, research on automated methods of detecting and processing variant malware has been continuously conducted. This report proposes a method of extracting feature data from files and detecting malware using machine learning. Feature data were extracted from 7,000 malware and 3,000 benign files using static and dynamic malware analysis tools. A malware classification model was constructed using multiple DNN, XGBoost, and RandomForest layers and the performance was analyzed. The proposed method achieved up to 96.3% accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.295-297
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• 2007

교통 관련 검지기 시스템에 의해 수집된 교통량, 점유율, 속도와 같은 교통 정보 데이터는 품질평가, 오류판단, 결측보정의 자료처리를 거치게 되며 이러한 전처리 후 다양한 목적에 의해 연구자들에게 활용된다. 신속하고 정확한 자료처리와 보다 편리하고 효과적인 웹 UI 의 제공은 매우 중요하다. 본 논문에서는 품질평가, 오류판단, 결측보정에 해당하는 세 단계의 자료처리 알고리즘을 개발하고 사용자에게 자료처리의 과정을 제공하는 웹 UI 시스템을 구현한다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.7-14
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• 2005

An OLAP(On-Line Analytical Processing) system is the decision support tool with which a user can analyze the information interactively in the various aspects. However, the traditional existing construction of an OLAP system has the inefficiency Problem of increasing the processing time and cost caused by the use of complex MDX(Multidimensional Expressions) queries. In an attempt to solve this problem, a new concept of data structuring technique, where a unit column whose elements are all 1 is added to the fact table, was suggested. With the data structuring technique, we can reduce the processing time and cost in OLAP systems.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.223-224
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• 2021

Recently, k-farthest neighbor (kFN) queries have not as much attention as k-nearest neighbor (kNN) queries. Therefore, this study considers moving k-farthest neighbor (MkFN) queries for spatial network databases. Given a positive integer k, a moving query point q, and a set of data points P, MkFN queries can constantly retrieve k data points that are farthest from the query point q. The challenge with processing MkFN queries in spatial networks is to avoid unnecessary or superfluous distance calculations between the query and associated data points. This study proposes a batch processing algorithm, called MOFA, to enable efficient processing of MkFN queries in spatial networks. MOFA aims to avoid dispensable distance computations based on the clustering of both query and data points. Moreover, a time complexity analysis is presented to clarify the effect of the clustering method on the query processing time. Extensive experiments using real-world roadmaps demonstrated the efficiency and scalability of the MOFA when compared with a conventional solution.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.93-96
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• 2006

본 논문에서는 OGC 의 공간 정보 인코딩 표준 명세인 GML 을 기반으로 공간 데이터 웨어하우스를 구축하는 스키마를 제안한다. GML 기반의 스키마는 비공간 정보뿐만 아니라 공간 정보에 대한 정의가 가능하다. 그리고 XML 스키마를 이용하여 전체 큐브 스키마, 차원 스키마 및 사실테이블에 대한 스키마 정의의 예를 보인다. 따라서 제안 기법은 GML 을 이용하여 이질적인 시스템간의 데이터 통합이 용이하고, 비공간 정보뿐만 아니라 공간 정보의 활용이 가능하다. 그리고 공간 데이터 웨어하우스의 개념계층 관계에 대한 표현이 용이하고 구조에 대한 이해가 쉽다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.265-271
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• 2015

This study proposes an algorithm for recognizing apple trees in images and detecting apples to measure the number of apples on the trees. The proposed algorithm explores whether there are apple trees or not based on the number of image block-unit edges, and then it detects apple areas. In order to extract colors appropriate for apple areas, the CIE $L^*a^*b^*$ color space is used. In order to extract apple characteristics strong against illumination changes, modified census transform (MCT) is used. Then, using the AdaBoost learning algorithm, characteristics data on the apples are learned and generated. With the generated data, the detection of apple areas is made. The proposed algorithm has a higher detection rate than existing pixel-based image processing algorithms and minimizes false detection.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1190-1193
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• 2012

본 논문에서는 공간 데이터를 기반으로 한 도시 정보를 알고리즘을 통해서 시각화하고 시각화된 데이터를 지도와 사상(Mapping)하여 볼 수 있게 할 뿐만 아니라 공간적 정보를 기반으로 의사 결정을 하는 경우 활용할 수 있는 문서를 사용자의 간단한 조작으로 프로그래밍 방식에 의해 작성해주는 시스템을 제안한다. 본 시스템을 통해서 공간적 정보를 시각화를 한다면 지역의 공간적 정보를 쉽게 파악할 수 있을 것이다. 또한 분석된 정보를 기반으로 제공되고 있는 문서 자동화를 활용한다면 공간적 정보의 문서화에 필요한 많은 시간과 비용을 절감할 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.457-458
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• 2007

Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer poor performance of learning. To archive good clustering performance, we develop a hybrid neural network model. It is the combination of Multi-Layer Perceptron (MLP) and Adaptive Resonance Theory 2 (ART2). It inherits two distinct advantages of stability and plasticity from ART2. Meanwhile, by combining the merits of MLP, it improves the performance for clustering. Experiment results show that our model can be used for clustering with promising performance.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.125-134
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• 2009

A biological data acquisition based on web has emerged as a powerful tool for allowing scientists to interactively view entries form different databases, and to navigate from one database to another molecular-biology database links. In this paper, the biological conceptual model is constructed hybrid biological data model to represent interesting entities in the data sources to applying navigation rule property for each biological data source based on four biological data integrating layers to control biological data. When some user's requests for application service are occurred, we can get the data from database and data source via web service. In this paper, we propose a query processing model and execution structure based on integrating data layers that can search information on biological data sources.