• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1281-1282
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• 2011

아웃라이어란 데이터 셋에서 다른 객체들과 비교해 상대적으로 이질적인 객체를 의미한다. 본 논문에서는 HITS 기반 아웃라이어 검출 방법의 매개변수 변화에 따른 성능 변화를 분석하고, 매개변수 설정을 위한 가이드라인을 제안한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.455-458
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• 2003

The variety of document ranking algorithms have developed to provide efficient mining results for user's query on the web environment. The typical ranking algorithms are the Vector-Space Model based on the text, PsgeRank and HITS algorithms based on the hyperlink structures and other several improvement algorithms. All these are for the user's convenience and preference. However, these algorithms are usually developed on then Horizontal and non-hierarchial web environments and are not suitable for the hierarchial web environments such as enterprise and defense networks. Thus, we must consider the special environment factors in order to improve the ranking algorithms. In this paper, we analyze the several typical algorithms used by hyperlink structures on the web environment. We, then suggest a configuration of the hierarchical web environment and also give the relations between agents of the web mining system. Next, we propose an improved ranking algorithm suitable to this kind of special environments. The proposed algorithm is considered both the hyperlink structures of the documents and the location of the user of the hierarchical web.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.185-196
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Simple tension and AE tests were conducted against the 3 kind of welding test specimens. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multivariate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• Journal of the Korea Safety Management & Science
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• v.10 no.4
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• pp.127-134
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Monotonic simple tension and AE tests were conducted against the 3 kinds of welded specimen. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multi-variate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.67-73
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• 2020

The clustering algorithm is the grouping of similar objects. In radar system, it is mainly used to group adjacent hits using the CFAR algorithm results. However it is difficult to separate adjacent targets by a general clustering method. In this paper, we describe how to separate adjacent targets using double clustering method. First, we execute a range direction clustering. And we find the inflection point and separate it. Next, we execute a doppler direction clustering using range clustering results. This method makes the computation time less change even if the target increases by range-doppler clustering respectively.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.487-503
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• 2016

Urban-to-rural migration for farming has recently emerged as a new way to vitalize rural economies in a fast-aging rural Korea. In this paper, we analyze the 2013 data of returning farmers with statistical network methods. We identify urban to rural migration hubs with centrality measures and find migration trends based on regional clusters with similar features via statistical network models. We also fit a latent distance model to investigate the role of distance in migration.

• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.385-392
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• 2005

We developed an algorithm to efficiently detect streaks in survey images and made a performance test with YSTAR-NEOPAT images obtained by the 0.5m telescope stationed in South Africa. Fast moving objects whose apparent speeds exceed 10 arcsec/min are the main target of our algorithm; these include artificial satellites, space debris, and very fast Near-Earth Objects. Our algorithm, based on the outline shape of elongated sources employs a step of image subtraction in order to reduce the confusion caused by dense distribution of faint stars. It takes less than a second to find and characterize streaks present in normal astronomical images of 2K format. Comparison with visual inspection proves the efficiency and completeness of our automated detection algorithm. When applied to about 7,000 time-series images from YSTAR telescope, nearly 700 incidents of streaks are detected. Fast moving objects are identified by the presence of matching streaks in adjoining frames. Nearly all of confirmed fast moving objects turn out to be artificial satellites or space debris. Majority of streaks are however meteors and cosmic ray hits, whose identity is often difficult to classify.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.753-758
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• 2017

The ray-shooting problem is to find the first intersection point on the surface of given geometric objects where a ray moving along a straight line hits. Since rays are usually given in the form of queries, this problem is typically solved as follows. First, a data structure for a collection of objects is constructed as preprocessing. Then, the answer for each query ray is quickly computed using the data structure. In this paper, we consider the ray-shooting problem about the set of vertical line segments on the x-axis. We present a new data structure called a convex layer tree for n vertical line segments given by input. This is a tree structure consisting of layers of convex hulls of vertical line segments. It can be constructed in O(n log n) time and O(n) space and is easy to implement. We also present an algorithm to solve each query in O(log n) time using this data structure.

• Journal of Ocean Engineering and Technology
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• v.32 no.3
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• pp.158-165
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• 2018

Generally, container ships contain cargo holds with cell guides that serve to increase the container loading and unloading efficiency, minimize the space loss, and fix containers during the voyage. This paper describes a new quality management system for the cell guides of container ships (the so-called Trim Cell Guide system). The main functions of this system are the trimming of the point cloud obtained using a 3D scanner and an inspection simulation for cell guide quality. In other words, the raw point cloud of cell guides after construction is measured using a 3D scanner. Here, the raw point cloud contains a lot of noise and unnecessary information. Using the GUI interface supported by the system, the raw point cloud can be trimmed. The trimmed point cloud is used in a simulation for cell guide quality inspection. The RANSAC (Random Sample Consensus) algorithm is used for the transverse section representation of a cell guide at a certain height and applied for the calculation of the intervals between the cell guides and container. When the container hits the cell guides during the inspection simulation, the container is rotated horizontally and checked again for a possible collision. It focuses on a system that can be simulated with the same inspection process as in a shipyard. For a practicality review, we compared the precision data gained from an inspection simulation with the measured data. As a result, it was confirmed that these values were within approximately ${\pm}2mm$.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.9-16
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• 2022

Today, with the advent of the 4th industrial revolution, IoT (Internet of Things) systems are advancing rapidly. For this reason, a various application with high-performance and large-capacity are emerging. Therefore, there is a need for low-power and high-performance memory for computing systems with these applications. In this paper, we propose an effective structure for the L1 cache memory, which consumes the most energy in the computing system. The proposed cache system is largely composed of two parts, the L1 main cache and the buffer cache. The main cache is 2 banks, and each bank consists of a 2-way set association. When the L1 cache hits, the data is copied into buffer cache according to the proposed algorithm. According to simulation, the proposed L1 cache system improved the performance of energy delay products by about 65% compared to the existing 4-way set associative cache memory.