• 한국의류학회지
• /
• 제32권5호
• /
• pp.846-858
• /
• 2008

This study was designed to propose a method to draft bodice block pattern from 3D body scan data. Subjects were ten elderly women in their 60's, who wear basic size(B: 94cm, W: 82cm) garment. Scanning was done using 3D whole body scanner(WB4, Cyberware). Measurements for 3D data and cross section were attained using Auto CAD, by which a upper bodice pattern for elderly women was drawn on the basis of short measured method. The results are as following: As for most items, no significant differences were shown between measurements from Martin's anthropometry and those from 3D scan data, suggesting measurement from 3D scan data could be used to draft a pattern. The drafting equations acquired were as follows; width of pattern=B/2+5.5, width of waist=W/2+3.5cm, dart amount=8cm. Dart distributions were 23%(B.P.) : 20%(front armpit) : 17%(side seam) : 18%(back armpit) : 15%(back protruded point) : 7% (center back line). Through wearing test using 5-point Likert scale, resultant pattern was evaluated as appropriate for elderly women's pattern to get over 4 point. As a result, it might be said that 3D scanning application is effective for elderly women in that it doesn't take time so much as Martin's anthropometry and that their body shape vary compared with those of young women.

• Ocean and Polar Research
• /
• 제44권4호
• /
• pp.287-296
• /
• 2022

High-frequency (HF) radar measures sea surface currents from the radio waves transmitted and received by antenna on land. Since the data quality of HF radar measurements sensitively depend on the radio wave environment around antenna, Antenna Pattern Measurements (APM) plays an important role in evaluating the accuracy of measured surface currents. In this study, APM was performed by selecting the times when the background noise level around antenna was high and low, and radial data were generated by applying the ideal pattern and measured pattern. The measured antenna pattern for each case was verified with the current velocity data collected by drifters. The radial velocity to which the ideal pattern was applied was not affected by the background noise level around antenna. However, the radial velocity obtained with APM in the period of high background noise was significantly lower in quality than the radial velocity in a low noise environment. It is recomended that APM be carried out in consideration of the radio wave environment around antenna, and that the applied result be compared and verified with the current velocity measurements by drifters. If it is difficult to re-measure APM, we suggest using radial velocity in generating total vector with the ideal pattern through comparative verification, rather than poorly measured patterns, for better data quality.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2013년도 춘계학술대회
• /
• pp.213-216
• /
• 2013

인터넷의 발달과 유무선 네트워크 인프라 기술의 발전으로 빅테이터 및 개인정보보의 활용이 많아지고 있다. 하지만 개인정보보호법의 시행에도 불구하고, 개인정보 유출로 인한 침해사고가 발생하고 있다. 개인정보 유출은 개인의 사생활피해와 금융피해로 연관된다. 따라서 개인정보의 탐색 및 검출과정에서 개인정보의 패턴을 분석하여 추출하는 연구와 불필요한 개인정보의 완전삭제에 관한 연구가 필요하다. 본 연구에서는 개인정보보호에 대한 패턴추출 연구와 완전삭제 방법을 연구하여 개인정보의 패턴추출 및 완전삭제 실험을 하였다.

• 한국전자통신학회논문지
• /
• 제9권10호
• /
• pp.1071-1078
• /
• 2014

최근 빅데이터(Big Data)를 이용한 정보 제공 서비스가 확대되고 빅데이터 처리 기술 역시 IT 업체의 중요한 이슈로 학문적인 연구가 활발히 진행되고 있는 실정이다. 이에 본 논문에서는 R 프로그래밍을 기반으로 용접의 빅데이터 분석 및 추출을 통하여 용접사의 숙련된 패턴을 분석하고 분석된 결과를 비 숙련공에게 제공함으로써 용접 품질 및 용접 시간 단축 등의 용접 작업에 적용되는 비용을 절감하고자 한다. 용접은 숙련공이 되기 위하여 오랜 시간을 투자해야 하는 문제점이 있다. 이러한 단점을 해결하고자 숙련공들의 용접 패턴 분석을 위하여 다량의 패턴 변수에 R의 연관 규칙 알고리즘과 회귀분석 방식을 적용한다. 상위 N개의 규칙을 분석한 후 분석된 규칙의 변수에 따른 숙련자의 패턴을 분석한다. 본 논문에서는 분석된 용접 패턴 분석을 통해 실험 결과를 분석하여 전력소비량과 와이어 소모 길이에 대한 패턴 구조를 확인하였다.

• 한국의류산업학회지
• /
• 제17권3호
• /
• pp.447-461
• /
• 2015

The purpose of this study is to develop a torso pattern that is highly representative for the proper body shape of women in their thirties. Size data of the women with age of 30 through 39 from the database of Size Korea 2004 were used for the study. In order to develop a master pattern which will be used as the benchmark for grading of research group, 4 existing torso block drafting methods were compared based on the data gathered and the block with the highest evaluation score was utilized as a reference point. For the analysis, data was divided into four types, only the data of 138 subjects which were evaluated at least by four or more experts as valid were used for the study. The major results can be summarized as follow. The women of bust girth of 91cm and height of 160cm which was turned out to be representative type of research group were used as standard measurement for the purpose of reflecting not only curve length of the 3D analysis measurement but also the difference between front and back thickness to the pattern. Dart locations were set based on front and back torso ease, shoulder area revisions, front sagging length 1.5cm and cross section crevice length analysis. According to the experts' appearance evaluation of the pattern was found to be better than the control pattern which was regarded as the best among 4 patterns created based on existing torso block drafting methods.

• Smart Structures and Systems
• /
• 제8권1호
• /
• pp.69-92
• /
• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• 정보처리학회논문지D
• /
• 제18D권2호
• /
• pp.81-88
• /
• 2011

시퀀스(sequence) 데이터가 주어졌을 때 그 중에서 빈번(frequent)한 순차 패턴을 찾는 순차 패턴 마이닝(sequential pattern mining)은 여러 어플리케이션(application)에 사용되는 중요한 데이터마이닝 문제이다. 순차 패턴 마이닝은 웹 접속 패턴, 고객 구매 패턴, 특정 질병의 DNA 시퀀스를 찾는 등 광범위한 분야에서 사용된다. 본 논문에서는 맵리듀스(MapReduce) 프레임웍 상에서 맵리듀스 함수 호출을 최적화하는 순차 패턴 마이닝 알고리즘을 개발하였다. 이 알고리즘은 여러 대의 기계에 데이터들을 분산시켜 병렬적으로 빈번한 순차 패턴을 찾는다. 실험적으로 다양한 데이터를 이용하여 파라미터 값을 변화시켜가며 제안된 알고리즘의 성능을 종합적으로 확인하였다. 그리고 실험 결과를 통해 제안된 알고리즘은 기계 수에 대해 선형적인 속도 개선을 보인다는 것을 확인하였다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
• /
• pp.627-630
• /
• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 한국정보시스템학회지:정보시스템연구
• /
• 제27권3호
• /
• pp.123-140
• /
• 2018

Purpose The purpose of this study is to explore the optimal trading frequency which is useful for stock price prediction by using deep learning for charting image data. We also want to identify the appropriate time for accurate forecasting of stock price when performing pattern analysis. Design/methodology/approach In order to find the optimal trading frequency patterns and forecast timings, this study is performed as follows. First, stock price data is collected using OpenAPI provided by Daishin Securities, and candle chart images are created by data frequency and forecasting time. Second, the patterns are generated by the charting images and the learning is performed using the CNN. Finally, we find the optimal trading frequency patterns and forecasting timings. Findings According to the experiment results, this study confirmed that when the 10 minute frequency data is judged to be a decline pattern at previous 1 tick, the accuracy of predicting the market frequency pattern at which the market decreasing is 76%, which is determined by the optimal frequency pattern. In addition, we confirmed that forecasting of the sales frequency pattern at previous 1 tick shows higher accuracy than previous 2 tick and 3 tick.

• 한국의류학회지
• /
• 제29권9_10호
• /
• pp.1359-1368
• /
• 2005

When we develop the tight-fit 2D pattern from the 3D scan data, segmentation of the 3D scan data into several parts is necessary to make a curved surface into a flat plane. In this study, Garland's method of triangle simplification was adopted to reduce the number of data point without distorting the original shape. The Runge-Kutta method was applied to make triangular patch from the 3D surface in a 2D plane. We also explored the detailed arrangement method of small 2D patches to make a tight-fit pattern for a male body. As results, minimum triangle numbers in the simplification process and efficient arrangement methods of many pieces were suggested for the optimal 2D pattern development. Among four arrangement methods, a block method is faster and easier when dealing with the triangle patches of male's upper body. Anchoring neighboring vertices of blocks to make 2D pattern was observed to be a reasonable arrangement method to get even distribution of stress in a 2D plane.