치과용 니켈-티타늄 합금의 갈바닉 부식

최창혁,최기열,이중배 大韓齒科器材學會 2004 대한치과재료학회지 Vol.31 No.1

The purpose of this study was to evaluate the galvanic corrosion behavior of NT by coupling with other dental alloys in artificial saliva. The variation of galvanic current and common potential (mixed potential) were monitored as a function of time, and interpreted in terms of the electrochemical properties of each alloy. The effects of adding some constituents such as acid or chloride to the ordinary composition of artificial saliva were also estimated. For most cases of coupling, the significant current was observed only at early stage for several seconds or several minutes, then gradually diminished. The current value was affected by the excessive amount of acid or chloride added to artificial saliva, depending on their aggressiveness on each alloy ; the current was increased in the couples with HG, LG, VT, and decreased in the couples with AM and G2. The results were more complicated in the couples with AP and TC, where some mixed reaction occurred. The common potential was always between two corrosion potentials of alloys involved in the couple, and did not exceed the breakdown potential of alloy acted as anode except the case of coupling with AM in acid-containing artificial saliva. The coupling with AM was found to be the most susceptible to galvanic corrosion.

침입탐지에서 지지율 기반 클러스터링을 이용한 정상행위 패턴 생성

오상현,장중혁 대구대학교 정보통신연구소 2010 情報通信硏究 Vol.7 No.1

For effectively detecting the intrusion through computers, many algorithms have been actively proposed so far, and recently the works related to anomaly detection, which is extended from misuse detection techniques by reducing their drawbacks, have attracted considerable attention since the anomaly detection technique can identify unknown intrusion methods. In this paper, a new clustering algorithm is proposed in order to extract patterns from the normal user activities. For the purpose, the anomalous user behaviors should be analyzed in various angles, and be classified by many different types of measures. 컴퓨터를 통한 침입을 효과적으로 탐지하기 위해서 많은 기법들이 제안되어 왔으며, 근래에는 오용 탐지 기법을 개선하기 위해서 비정상행위 탐지 기법에 관련된 연구들이 활발히 진행중이다. 본 논문에서는 침입탐지에서 정상행위 패턴을 생성하기 위해 지지율에 기반한 새로운 클러스터링 알고리즘을 제시한다. 이를 위해서 정상적인 사용에 대한 행위를 다양한 각도에서 분석될 수 있도록 여러 판정요소로 분류하고 각 판정요소에 대해서 제시된 알고리즘을 이용하여 정상행위 패턴을 생성한다.

estWin: Online data stream mining of recent frequent itemsets by sliding window method

Chang, Joong Hyuk,Lee, Won Suk Sage Publications 2005 JOURNAL OF INFORMATION SCIENCE Vol.31 No.2

<P> <B>Knowledge embedded in a data stream is likely to be changed as time goes by. Identifying the recent change of the knowledge quickly can provide valuable information for the analysis of the data stream. However, most mining algorithms over a data stream are not able to extract the recent change of knowledge in a data stream adaptively. This is because the obsolete information of old data elements which may be no longer useful or possibly invalid at present is regarded as being as important as that of recent data elements. This paper proposes a sliding window method that finds recently frequent itemsets over a transactional online data stream adaptively. The size of a sliding window defines the desired life-time of information in a newly generated transaction. Consequently, only recently generated transactions in the range of the window are considered to find the recently frequent itemsets of a data stream.</B> </P>

English Paper Presentation 6: Radiology/Procedures/Education/Administration/Q.I : OE6-1 ; Development & Clinical Application of Tele-ultrasonography Using A Smartphone Based Real-time Ultrasound Image Transmission

( Chang Sun Kim ),( Bo Seung Kang ),( Jin Hyuk Lee ),( Hyuk Joong Choi ) 대한응급의학회 2014 대한응급의학회 학술대회초록집 Vol.2014 No.2

We aim to introduce our findings of tele-ultrasonography using a smartphone-based real-time ultrasound image transmission system. The ultrasonography machine in our emergency department (ED) was equipped with the real-time image transmission system (E-Cube 15, Alpinion medical system, Seoul, Korea). From June 2014, using this system, on-site ultrasound performer could seek a remote experts` mentoring and these practices were recorded in predesigned registry, which included patients` information, type and speed of mobile network, type of diseases, initial diagnosis of on-site performer, the diagnosis after tele-mentoring, the problems encountered during the practice and etc. The subjective quality assessment for the images on the smartphone was graded by tele-mentoring experts using the five-Likert scale. There were 21 cases which were tele-consulted using this system between June and July 2014; Of these, ten cases (47.6%) were suspected acute appendicitis and four (19%) were suspected acute coronary syndrome. The LTE network was used in 14 connections and the remaining seven were connected via WiFi. The average connection speed was 67.6 (SD: 25.8) Mbps. Users complained of a little delay time, but they stated it did not significantly affect the tele-mentoring. All of the subjective image quality assessments were moderate to very good (mean: 4.2, SD: 0.6). Most initial diagnoses of on-site performers (19 cases) were not changed after tele-mentoring, but the on-site performer stated that they could have increased confidence in their diagnosis after tele-mentoring. The diagnoses after tele-mentoring compared to the final diagnoses of each case which were confirmed by pathology, clinical follow up and the results of other experts-performed ultrasonography were identical. Although the number of cases enrolled was quite small, there were no significant problems during the tele-mentoring using the smartphone-based tele-ultrasonography system, and this system was usually used as the assistant device for obtaining experts` help in diagnosing equivocal cases.

Finding Interesting Sequential Patterns in Sequence Data Streams via a Time-Interval Weighting Approach

CHANG, Joong Hyuk,PARK, Nam Hun 'Institute of Electronics, Information and Communi 2013 IEICE transactions on information and systems Vol.96e.d No.8

발생 간격 기반 가중치 부여 기법을 활용한 데이터 스트림에서 가중치 순차패턴 탐색

장중혁(Joong Hyuk Chang) 한국지능정보시스템학회 2010 지능정보연구 Vol.16 No.3

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledgeembedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

웹 클릭 스트림에서 고유용 과거 정보 탐색

장중혁(Chang, Joong-Hyuk) 한국산학기술학회 2016 한국산학기술학회논문지 Vol.17 No.4

개인용 컴퓨터 및 각종 모바일 기기의 이용 증가로 인해 많은 분야에서 다양한 형태의 웹기반 서비스들이 널리 활용 되고 있다. 이에 따라 해당 분야에서 개인 맞춤형 서비스를 지원하기 위한 사용자 이용 로그 분석 등에 대한 연구가 활발히 진행되고 있으며, 특히 사용자 로그 데이터를 구성하는 구성요소의 중요성 차별화에 기반한 분석 기법들이 활발히 연구되었 다. 본 논문에서는 웹 클릭 스트림에서 유용하게 적용될 수 있는 고유용 과거 정보 탐색 기법을 제시한다. 해당 기법을 통해 기존의 웹 클릭 스트림 분석 기법에서는 쉽게 탐색하지 못했던 정보인 타겟 마케팅 등에 유용하게 활용될 수 있는 중요 정보 를 쉽게 탐색할 수 있다. 본 논문의 연구 결과는 IoT 환경 및 생물정보 분석 등과 같이 데이터 스트림 형태로 정보를 발생시키 는 다양한 컴퓨터 응용 분야에도 활용될 수 있을 것이다. Web-based services are used widely in many computer application fields due to the increasing use of PCs and mobile devices. Accordingly, topics on the analysis of access logs generated in the application fields have been researched actively to support personalized services in the field, and analyzing techniques based on the weight differentiation of information in access logs have been proposed. This paper outlines an analysis technique for web-click streams, which is useful for finding high utility old item sets in web-click streams, whose data elements are generated at a rapid rate. Using the technique, interesting information can be found, which is difficult to find in conventional techniques for analyzing web-click streams and is used effectively in target marketing. The proposed technique can be adapted widely to analyzing the data generated in a range of computing application fields, such as IoT environments, bio-informatics, etc., which generated data as a form of data streams.

순차패턴 마이닝에서 발생 간격 기반 가중치 부여 기법

장중혁 ( Joong-hyuk Chang ),신무종 ( Mu-jong Shin ) 한국정보처리학회 2010 한국정보처리학회 학술대회논문집 Vol.17 No.1

순차패턴 마이닝에서 관심도가 큰 순차패턴을 얻기 위해서 구성요소의 단순 발생 순서뿐만 아니라 구성요소의 가중치를 추가로 고려할 수 있다. 본 논문에서는 순차패턴 마이닝에서 가중치 순차패턴을 탐색하기 위한 가중치 계산 기법으로 발생 간격에 기반한 순차패턴 가중치 부여 기법을 제안한다. 발생 간격 기반 가중치는 사전에 정의된 별도의 가중치 정보를 필요로 하지 않으며 순차정보를 구성하는 구성요소들의 발생 간격으로부터 구해진다. 즉, 순차패턴의 가중치를 구하는데 있어서 구성요소의 발생 순서와 더불어 이들의 발생 간격을 고려하며, 따라서 보다 관심도가 크고 유용한 순차패턴을 얻도록 지원한다.

웹 클릭 스트림의 효율적 분석을 위한 시간 간격 제한을 활용한 관심 순차패턴 탐색

장중혁(Joong-Hyuk Chang) 한국산업정보학회 2011 한국산업정보학회논문지 Vol.16 No.2

웹 관련 기술의 발달 및 스마트폰과 같은 지능형 모바일 서비스 기기의 사용 증가로 인해 오늘날 많은 분야에서 다양한 웹기반 서비스들이 널리 활용되고 있다. 이러한 환정에서 개인화 및 지능화된 웹 서비스를 제공하기 위한 연구들이 활발히 진행되고 있으며, 웹 서비스 이용 기록으로부터 생성되는 웹 클릭 스트림에 대한 분석 기술은 관련 기술 중 핵심 기술의 하나이다. 본 논문에서는 순차정보 형태로 발생되는 웹 클릭 스트림에 대한 효율적 분석을 위해서 데이터 스트림 처리에 대한 기본적인 요구사항을 만족하면서 정제된 결과를 얻기 위한 순차패턴 마이닝 방법을 제시한다. 이를 위해서 먼저 순차패턴에 포함되는 단위항목들의 단순 발생 순서뿐만 아니라 발생 시간 정보를 추가로 활용하는 시간 간격 제한 관심 순차패턴을 정의하고, 이어서 웹 클릭 스트림과 같은 데이터 스트림에서 이를 효율적으로 탐색하기 위한 마이닝 방법을 제안한다. 해당 연구 결과는 웹 클릭 스트림뿐만 아니라 전자상거래, 생물정보학 및 USN 환경 등과 같이 데이터 스트림 형태로 정보를 발생시키는 여러 컴퓨터 용용 분야에서 유용하게 활용될 수 있을 것이다. Due to the development of web technologies and the increasing use of smart devices such as smart phone, in recent various web services are widely used in many application fields. In this environment, the topic of supporting personalized and intelligent web services have been actively researched, and an analysis technique on a web-click stream generated from web usage logs is one of the essential techniques related to the topic. In this paper, for efficient analyzing a web-click stream of sequences, a sequential pattern mining technique is proposed, which satisfies the basic requirements for data stream processing and finds a refined mining result. For this purpose, a concept of interesting sequential patterns with a time-interval constraint is defined, which uses not on1y the order of items in a sequential pattern but also their generation times. In addition, A mining method to find the interesting sequential patterns efficiently over a data stream such as a web-click stream is proposed. The proposed method can be effectively used to various computing application fields such as E-commerce, bio-informatics, and USN environments, which generate data as a form of data streams.

데이터 스트림 마이닝에서 정보 중요성 차별화를 위한 퍼지 윈도우 기법

장중혁(Chang, Joong-Hyuk) 한국산학기술학회 2011 한국산학기술학회논문지 Vol.12 No.9

구성요소가 지속적으로 생성되고 시간 흐름에 따라 변화되기도 하는 데이터 스트림의 특성을 고려하여 데이 터 스트림 구성요소의 중요성을 발생 시간에 따라 차별화하기 위한 기법들이 활발히 제안되어 왔다. 기존의 방법들은 최근에 발생된 정보에 집중된 분석 결과를 제공하는데 효과적이나 보다 유연하게 다양한 형태로 정보 중요성을 차별 화하는데 한계가 있다. 퍼지 개념에 기반한 정보 중요성 차별화는 이러한 한계를 보완하는 좋은 대안이 될 수 있다. 퍼지 개념은 기존의 뚜렷한 경계를 갖는 접근법의 문제점을 극복하고 실세계의 요구에 보다 부합되는 결과를 제공할 수 있는 방법으로 여러 데이터 마이닝 분야에서 널리 적용되어 왔다. 본 논문에서는 퍼지 개념을 적용하여 데이터 스 트림 마이닝에서 정보 중요성 차별화에 효율적으로 활용될 수 있는 퍼지 윈도우 기법을 제안한다. 퍼지 캘린더를 포 함한 기본적인 퍼지 개념에 대해서 먼저 기술하고, 다음으로 데이터 스트림 마이닝에서 퍼지 윈도우 기법을 적용한 가중치 패턴 탐색에 대한 세부 내용을 기술한다. Considering the characteristics of a data stream whose data elements are continuously generated and may change over time, there have been many techniques to differentiate the importance of data elements in a data stream by their generation time. The conventional techniques are efficient to get an analysis result focusing on the recent information in a data stream, but they have a limitation to differentiate the importance of information in various ways more flexible. An information differentiation technique based on the term of a fuzzy set can be an alternative way to compensate the limitation. A term of a fuzzy set has been widely used in various data mining fields, which can overcome the sharp boundary problem and give an analysis result reflecting the requirements in real world applications more. In this paper, a fuzzy window mechanism is proposed, which is adapting a term of a fuzzy set and is efficiently used to differentiate the importance of information in mining data streams. Basic concepts including fuzzy calendars are described first, and subsequently details on data stream mining of weighted patterns using a fuzzy window technique are described.