• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.17-18
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• 2007

데이터베이스 튜닝은 일반적으로 데이터베이스 어플리케이션을 "좀 더 빠르게" 실행하게 하는 일련의 활동을 뜻한다[1]. 데이터베이스 관리자가 튜닝에 필요한 주먹구구식 룰(Rule of thumb)들을 모두 파악 하고 상황에 맞추어 적용하는 것은 비싼 비용과 오랜 시간을 요구한다. 그렇게 때문에 서로 다른 어플 리케이션들이 맞물려 있는 복잡한 서비스는 필수적으로 자동화된 데이터베이스 성능 관리와 튜닝을 필 요로 한다. 본 논문에서는 이를 해결하기 위하여 지식 도매인(Knowledge Domain)을 기초로 한 자동화 된 데이터베이스 튜닝 원칙(Tuning Principle)을 제시하는 시스템을 제안한다. 각각의 데이터베이스 튜닝 이론들은 지식 도매인의 지식으로 활용되며, 성능에 영향을 미치는 요소들을 개체(Object)와 콘셉트 (Concept)로 구성하고 추론 시스템을 통해 튜닝 원칙을 추론하여 쉽고 빠르게 현재 상황에 맞는 튜닝 방법론을 적용시킬 수 있다. 자동화된 데이터베이스 튜닝에 대해 여러 분야에 걸쳐 학문적인 연구가 이루어지고 있다. 그 예로써 Microsoft의 AutoAdmin Project[2], Oracle의 SQL 튜닝 아키텍처[3], COLT[4], DBA Companion[5], SQUASH[6] 등을 들 수 있다. 이러한 최적화 기법들을 각각의 기능적인 방법론에 따라 다시 분류하면 크게 Design Tuning, Logical Structure Tuning, Sentence Tuning, SQL Tuning, Server Tuning, System/Network Tuning으로 나누어 볼 수 있다. 이 중 SQL Tuning 등은 수치적으로 결정되어 이미 존재하는 정보를 이용하기 때문에 구조화된 모델로 표현하기 쉽고 사용자의 다양한 요구에 의해 변화하는 조건들을 수용하기 쉽기 때문에 이에 중점을 두고 성능 문제를 해결하는 데 초점을 맞추었다. 데이터베이스 시스템의 일련의 처리 과정에 따라 DBMS를 구성하는 개체들과 속성, 그리고 연관 관계들이 모델링된다. 데이터베이스 시스템은 Application / Query / DBMS Level의 3개 레벨에 따라 구조화되며, 본 논문에서는 개체, 속성, 연관 관계 및 데이터베이스 튜닝에 사용되는 Rule of thumb들을 분석하여 튜닝 원칙을 포함한 지식의 형태로 변환하였다. 튜닝 원칙은 데이터베이스 시스템에서 발생하는 문제를 해결할 수 있게 하는 일종의 황금률로써 지식 도매인의 바탕이 되는 사실(Fact)과 룰(Rule) 로써 표현된다. Fact는 모델링된 시스템을 지식 도매인의 하나의 지식 개체로 표현하는 방식이고, Rule 은 Fact에 기반을 두어 튜닝 원칙을 지식의 형태로 표현한 것이다. Rule은 다시 시스템 모델링을 통해 사전에 정의되는 Rule와 튜닝 원칙을 추론하기 위해 사용되는 Rule의 두 가지 타업으로 나뉘며, 대부분의 Rule은 입력되는 값에 따라 다른 솔루션을 취하게 하는 분기의 역할을 수행한다. 사용자는 제한적으로 자동 생성된 Fact와 Rule을 통해 튜닝 원칙을 추론하여 데이터베이스 시스템에 적용할 수 있으며, 요구나 필요에 따라 GUI를 통해 상황에 맞는 Fact와 Rule을 수동으로 추가할 수도 었다. 지식 도매인에서 튜닝 원칙을 추론하기 위해 JAVA 기반의 추론 엔진인 JESS가 사용된다. JESS는 스크립트 언어를 사용하는 전문가 시스템[7]으로 선언적 룰(Declarative Rule)을 이용하여 지식을 표현 하고 추론을 수행하는 추론 엔진의 한 종류이다. JESS의 지식 표현 방식은 튜닝 원칙을 쉽게 표현하고 수용할 수 있는 구조를 가지고 있으며 작은 크기와 빠른 추론 성능을 가지기 때문에 실시간으로 처리 되는 어플리케이션 튜닝에 적합하다. 지식 기반 모률의 가장 큰 역할은 주어진 데이터베이스 시스템의 모델을 통하여 필요한 새로운 지식을 생성하고 저장하는 것이다. 이를 위하여 Fact와 Rule은 지식 표현 의 기본 단위인 트리플(Triple)의 형태로 표현된다, 트리플은 Subject, Property, Object의 3가지 요소로 구성되며, 대부분의 Fact와 Rule들은 트리플의 기본 형태 또는 트리플의 조합으로 이루어진 C Condition과 Action의 두 부분의 결합으로 구성된다. 이와 같이 데이터베이스 시스템 모델의 개체들과 속성, 그리고 연관 관계들을 표현함으로써 지식들이 추론 엔진의 Fact와 Rule로 기능할 수 있다. 본 시스템에서는 이를 구현 및 실험하기 위하여 웹 기반 서버-클라이언트 시스템을 가정하였다. 서버는 Process Controller, Parser, Rule Database, JESS Reasoning Engine으로 구성 되 어 있으며, 클라이 언트는 Rule Manager Interface와 Result Viewer로 구성되어 었다. 실험을 통해 얻어지는 튜닝 원칙 적용 전후의 실행 시간 측정 등 데이터베이스 시스템 성능 척도를 비교함으로써 시스템의 효용을 판단하였으며, 실험 결과 적용 전에 비하여 튜닝 원칙을 적용한 경우 최대 1초 미만의 전처리에 따른 부하 시간 추가와 최소 약 1.5배에서 최대 약 3배까지의 처리 시간 개선을 확인하였다. 본 논문에서 제안하는 시스템은 튜닝 원칙을 자동으로 생성하고 지식 형태로 변형시킴으로써 새로운 튜닝 원칙을 파생하여 제공하고, 성능에 영향을 미치는 요소와 함께 직접 Fact과 Rule을 추가함으로써 커스터마이정된 튜닝을 수행할 수 있게 하는 장점을 가진다. 추후 쿼리 자체의 튜닝 및 인텍스 최적화 등의 프로세스 자동화와 Rule을 효율적으로 정의하고 추가하는 방법 그리고 시스템 모델링을 효과적으로 구성하는 방법에 대한 연구를 통해 본 연구를 더욱 개선시킬 수 있을 것이다.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.361-365
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• 2007

자연재난은 발생원인에 따라 바람, 강우, 적설, 파고등으로 구분할 수 있다. 이러한 재난원인은 자연현상의 일부로 발생하였으나, 경제가 발전함에 따라 과거에 비해 재해에 안전한 사회를 요구하게 되어 재해저감을 위한 투자와 방재정책 개발의 필요성이 증대되고 있다. 기존에는 자연재난을 저감시키기 위하여 연최대치 강우를 통계 분석하고 강우-유출관계를 이용하여 장래에 발생할 홍수량을 예측하여 자연재난을 저감할 수 있도록 설계하는 것이 일반적인 재난저감계획 수립으로 간주되었다. 그러나, 재해예방을 위해서는 과거에 발생한 재난의 지역적 특성을 분석하여 재난발생 위험과 피해규모를 파악함으로써 재난계획 수립의 기초자료로 활용할 필요성이 있다. 이러한 자연재난에 대한 대책수립은 국가차원에서 필요하며 이를 위해서는 지역별 안전도 평가의 필요성이 증가하게 된다. 그러나 이러한 연구를 수행하기 위해서는 방대한 자료를 바탕으로 풍수해 발생특성을 분석하는 연구와 지자체 또는 지역별 재난피해저감 능력을 수치적으로 나타낼 필요성이 있다. 따라서, 공학적인 면뿐만 아니라 행정적인 면을 동시에 고려하는 학제간 연구가 필요하다. 본 연구에서는 우리나라에서 주로 발생하는 풍수해에 의한 자연재난 특성을 파악하고 재난발생 확률을 고려한 재난피해규모와 재난피해 저감능력을 비교하여 전국 234개 지자체별 지역 및 시설물별 안전도를 평가하고자 한다. 과거 10년간 재해연보에 수록된 지자체별 피해현황을 지자체별 특성을 고려하여 분석, 지자체별 연평균 피해규모를 소방방재청의 지역별 안전도 지침서에 의거, 10등급으로 분석하였다. 또한, 지자체별로 투자우선순위 및 방재예산편성의 효율성 극대화를 위해 지자체별 시설물별 피해현황을 분석하는 기법을 개발하여 지자체별 시설물별 안전도 진단지표를 설정하였다. 분석된 결과는 지자체별 시설물별 재해저감을 위한 풍수해저감 종합계획 재난보험제도 도입등의 기초자료로 적용될 수 있다.로 나타났다. 이는 두 흐름에 의해 와(vortex)가 크게 형성되어 하상의 세굴에 영향을 미치기 때문으로 판단되었다.보다 본질부가 차지하는 면적이 월등히 적고 제1차 및 제2차섬유가 차지하는 면적이 많았다. 따라서 고섬유함량인 대마의 품종개량에 있어서는 가능한 한 본질부가 차지하는 면적은 축소시키고 제1차 및 제2차섬유가 차지하는 면적은 증대시켜야 할 것으로 본다.우리 나라 수도의 작기는 앞으로 당기는 것이 좋다고 고찰된다. 6. 우리 나라의 현행 수도작기로 본 기온 및 일조조건은 수도의 분얼전기에 대해서는 호조건하에 놓여 있으나, 분얼후기인 7월 중ㆍ하순 경의 일조부족과 고온다습조건은 병해, 특히 도열병의 유발원인이 되고 있다. 7. 우리 나라의 현행수도작기로 본 전국각지의 수도의 출수기는 모두 일조시간이 적은 부적당한 시기에 처해 있다. 8. 출수후 40일간의 평균기온에 의한 적산온도 88$0^{\circ}C$의 출현기일은 수원에서 8월 23일이었고, 년간편차를 고려한 안전출수기일은 8월 19일로서 적산온도면에서는 관행 출수기일은 약간 늦다고 보았다. 9. 등열기의 평균기온에 의한 적산온도는 현행 수도작기로서는 최종한계시기에 놓여 있으며, 평균기온의 년간편차와 우리 나라의 최저기온이 낮은 점을 고려할 때, 현행출수기는 다소 늦은 것으로 보았다. 10. 생육단계별의 수도체내의 질소함량은 영양생장기의 질소함량이 과다하였으며, 출수 이후에 영양조락을 여하히 방지하느냐가 문제된다고 보았다. 11. 수리불안전답 및 천수답이 차지하는 전답면적의 비율은 차차 감소되고 있는데, 이와 전체 10a당 수량의 증가율과의 상관계수를 산출하였는데, 수리불안전답과의 상관계수 (4)는 +0.525였으며, 천수답과는 r=+0.832, 그리고 수리불안전답과 천수답을 합계한 것과의 상관계수 (r)는 +0.841로서 후2자와는 고도의 정(+) 상관을 보여 천수답이 차지하는 면적비율이 작

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Korean Journal of Ecology and Environment
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• v.38 no.3 s.113
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• pp.361-371
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• 2005

The objective of study was to diagnose integrative ecological health of Daejeon Stream, one of the tributaries of Guem River, during May 2004 ${\sim}$ April 2005. The research approach was primarily based on a Qualitative Habitat Evaluation Index (QHEI) and the Index of Biological Integrity (IBI) using fish assemblage. These outcomes were compared with conventional chemical dataset. For the experiment, four sampling sites were chosen from Daejeon Stream and long-term water quality data during 1995 ${\sim}$ 2004 (obtained from the Ministry of Environment) were analyzed in the spatial and temporal aspects. For the biological health assessment, we developed a stream health assessment model (SHA model) far regional applications. We found that current water quality conditions, based on the COD, BOD, TN and TP, were enhanced by 1.6 ${\sim}$ 5.3 fold over the period of 1995 ${\sim}$ 2004 and that the parameters showed a typical longitudinal decline from the upstream to downstream reach. The differences of water quality between the two reaches were more than 4.4 times, indicating a large spatial variations within the stream. The health conditions, based on the SHA model, averaged 23 and varied from 20 to 26 depending on the sampling stations. Values of the QHEI varied from 39 (Poor condition) to 124 (Cood condition)and values of QHEI in the reach of S2 ${\sim}$ S4 had significantly lower than in the headwater site (S1). Also, biological stream health, based on the criteria of US EPA (1993), was judged as 'Poor condition', in the S4 where TN, TP, BOD and COD were highest. In the meantime, maximum value of SHA (26) was found in the upstream reach (S1) where the water quality and QHEI were best. We also found that compositions of sensitive species showed a linear function with water quality conditions and this pattern was evident in the tolerant species. Thus, the biological stream health, based on the SHA model, matched well water chemistry. Overall outcomes suggest that the biological health impact was a function of chemical degradation and physical habitat quality in the stream.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.42-50
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• 2021

Along with the rapid growth of the food service industry, food safety requirements and hygiene are increasing in importance in restaurants and hotels. Accordingly, there is a need for quick and practical monitoring techniques to determine hygiene status in the field. In this study, we investigated 5 domestic 5-star hotels specifically, personal hygiene (hands of workers), cooking utensils (knife, cutting board, food storage container, slicing machine blade, ice-maker scoop) and other facilities (refrigerator handle, sink). In addition, we examined the hygiene management status of customer contact points (tongs for buffet, etc.) to derive the correlation between the ATP values as a, a verification method. As a result of our five-hotel survey, we found that cooking utensils and personal hygiene were relatively sanitary compared to other inspection items (cookware 92.2%, personal hygiene 91.4%, facilities and equipment 76.19%, customer contact items 88.6%). According to our ATP-based mothod, kitchen utensils (51 ± 45 RLU/25㎠) were relatively clean compared to other with facilities and equipment (167 ± 123 RLU/25㎠). In the present study, we also evaluated the usefulness of the ATP bioluminescence method for monitoring surface hygiene at hotel restaurants. After correlation analysis of surveillance of hygienic status points and ATP assay, most results showed negative and high correlation (-0.64--0.89). Our ATP assay (92 ± 67 RLU/25㎠) of each item after cleaning showed signigicantly reduced results compared to the ATP assay (1020 ± 1254 RLU/25㎠) for normal status, thereby indicating its suitability as a tool to verify the validity of cleaning. By our results, ATP bioluminescence could be used as an effective tool for visual numerical evaluation of invisible contaminants.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.137-155
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• 1999

Recently, Televiewer(Borehole Acoustic Scanner(Televiewer)) has come to be widely used specially for the general engineering construction design. The Televiewer tool using a focussed acoustic beam is to detect the amplitude and traveltime of each reflected acoustic signal at the wall, resulting in the amplitude- and traveltime image respectively. Fractures can be well detected, because they easily scatter the acoustic energy due to the highly narrow beam. In addition, the drilling work will rough the borehole wall so that the acoustic energy can be scattered simply due to the roughness of the wall. Thus, the amplitude level can be directed associated with the elastic properties(impedance) and the hardness of the rock as well. Meanwhile, the traveltime image provides an information about the borehole shape and can be converted to a high precision 3D caliper log(max. 288 arms). In this paper, based on the high resolution of Televiewer images, general evaluation methods are illustrated to derive very reliable rock parameters.