• Proceedings of the Korea Information Processing Society Conference
• /
• 2001.10b
• /
• pp.1403-1406
• /
• 2001

인터넷은 처음에는 단순히 오프라인에서 유통되는 실물 상품의 흐름을 중개해주는 역할을 해왔으나 인터넷을 통한 실물상품의 중개는 아날로그 상태의 상품들이 인터넷이라는 거간꾼의 중개작용을 통한 전자상거래 형태로 정착되었다. 이러한 실물 상품 유통의 중개자였던 인터넷은 실물 상품들이 디지털화 됨으로써 컨텐츠들의 유통을 위한 통로이면서 동시에 그 자체로서 메시지가 되어버린 하나의 매체로 전환하게 되었다. 그러나, 인터넷을 통해 디지털 컨텐츠들이 쉽고 간편하게 원본과 똑같은 품질로 복제할 수 있을 뿐만 아니라 상상을 초월하는 빠른 속도로 이동이 가능하여 사용자들이 불법으로 얼마든지 이용할 수 있다는 것이다. 현재 국내, 국외에서 이러한 문제를 해결하기 위해 제안한 기술 디지털 컨텐츠들을 보호하고 관리할 수 있도록 하는 DRM(Digital Rights Management)이라는 시스템이 계속적으로 개발되고 있다[1]. 디지털 컨텐츠를 보호하고 저작권을 관리하는 시스템인 DRM 에는 크게 세 가지의 기본 시스템(Publisher, Customer, DRM Server System)이 있다. 본 논문에서는 컨텐츠를 등록하고 저작권자가 그 컨텐츠를 관리하는 DRM Publisher System을 키 알고리즘을 이용하여 설계한다.

• Journal of Platform Technology
• /
• v.10 no.3
• /
• pp.51-59
• /
• 2022

Machine learning, which has recently innovatively developed, has become an important technology that can solve various optimization problems. In this paper, we introduce the latest research papers that solve the problem of channel sharing in heterogeneous networks using machine learning, analyze the characteristics of mainstream approaches, and present a guide to future research directions. Existing studies have generally adopted Q-learning since it supports fast learning both on online and offline environment. On the contrary, conventional studies have either not considered various coexistence scenarios or lacked consideration for the location of machine learning controllers that can have a significant impact on network performance. One of the powerful ways to overcome these disadvantages is to selectively use a machine learning algorithm according to changes in network environment based on the logical network architecture for machine learning proposed by ITU.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.1
• /
• pp.85-92
• /
• 2015

As computer game maps get more elaborate, path-finding by using $A^*$ algorithm in grid-based game maps becomes bottlenecks of the overall game performance. It is because the search space becomes large as the number of nodes increases with detailed representation in cells. In this paper we propose an efficient pathfinding method in which the computer game maps in a regular grid is converted into the polygon-based representation of the list of vertices and then the visibility information about vertices of polygons can be utilized. The conversion to the polygon-based map does not give any effect to the real-time query process because it is preprocessed offline. The number of visited nodes during search can be reduced dramatically by designing heuristics using visibility information of vertices that make the accuracy of the estimation enhanced. Through simulations, we show that the proposed methods reduce the search space and the search time effectively while maintaining the advantages of the grid-based method.

• KEPCO Journal on Electric Power and Energy
• /
• v.5 no.4
• /
• pp.275-286
• /
• 2019

This paper presents real-time Direct Current (DC) network analysis applications for operation of DC distribution system or DC microgrid. These applications are installed on central Energy Management System (EMS) and provide solutions of DC network operation. To analysis DC distribution network, this paper proposes composition and sequence of applications. Algorithm of applications is presented in this paper. Demonstration tests are performed on DC distribution site in Gochang Power Testing Center of Korea Electric Power Corporation (KEPCO). To verify the performance, developed DC applications installed on EMS. Scenarios for demonstration test of voltage control are presented. Finally, measured data, application output data and simulation data (by PSCAD/EMTDC) are compared and analyze accuracy of applications.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.9
• /
• pp.5446-5451
• /
• 2014

Because there are some mistakes by hand in processing electronic maps using a navigation terminal, this paper proposes an automatic offline recognition for traffic signs, which are considered ingredient navigation information. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which have been used widely in the field of 2D face recognition as computer vision and pattern recognition applications, was used to recognize traffic signs. First, using PCA, a high-dimensional 2D image data was projected to a low-dimensional feature vector. The LDA maximized the between scatter matrix and minimized the within scatter matrix using the low-dimensional feature vector obtained from PCA. The extracted traffic signs under a real-world road environment were recognized successfully with a 92.3% recognition rate using the 40 feature vectors created by the proposed algorithm.

• The KIPS Transactions:PartD
• /
• v.14D no.3 s.113
• /
• pp.347-354
• /
• 2007

It is not easy for the customers to search the valuable information on the goods among countless items available in the Internet. In order to save time and efforts in searching the goods the customers want, it is very important for a recommender system to have a capability to predict accurately customers' preferences. In this paper we present a refined neighbor selection algorithm for clustering based collaborative filtering in recommender systems. The algorithm exploits a graph approach and searches more efficiently for set of influential customers with respect to a given customer; it searches with concepts of weighted similarity and ranked clustering. The experimental results show that the recommender systems using the proposed method find the proper neighbors and give a good prediction quality.

• Journal of IKEEE
• /
• v.2 no.1 s.2
• /
• pp.150-159
• /
• 1998

This paper described the recognition of the Off-line handwritten Hangul based on neural network using a feature extraction method. Features of Hangul can be extracted by a $5{\times}5$ window method which is the modified $3{\times}3$ mask method. These features are coded to binary patterns in order to use neural network's inputs efficiently. Hangul character is recognized by the consonant, the vertical vowel, and the horizontal vowel, separately. In order to verify the recognition rate, three different coding methods were used for neural networks. Three methods were the fixed-code method, the learned-code I method, and the learned-code II method. The result was shown that the learned-code II method was the best among three methods. The result of the learned-code II method was shown 100% recognition rate for the vertical vowel, 100% for the horizontal vowel, and 98.33% for the learned consonants and 93.75% for the new consonants.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.5
• /
• pp.985-993
• /
• 2001

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.

• Journal of KIISE
• /
• v.43 no.9
• /
• pp.1026-1033
• /
• 2016

Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.2961-2967
• /
• 2014

Nowadays, a private protection act has come into effect which demands for the protection of personal image information obtained by the CCTV. According to this act, the object out of interest has to be mosaicked such that it can not be identified before the image is sent to the investigation office. Meanwhile, the demand for digital videos obtained by CCTV is also increasing for digital forensic. Therefore, due to the two conflicting demands, the demand for a solution which can automatically mask an object in the CCTV video is increasing and related IT industry is expected to grow. The core technology in developing a target masking solution is the object tracking technique. In this paper, we propose an object tracking technique which suits for the application of CCTV video object masking as a postprocess. The proposed method simultaneously uses the motion and the color information to produce a stable tracking result. Furthermore, the proposed method is based on the centroid shifting method, which is a fast color based tracking method, and thus the overall tracking becomes fast.