• Title/Summary/Keyword: pattern similarity

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Analysis of Image Similarity Index of Woven Fabrics and Virtual Fabrics - Application of Textile Design CAD System and Shuttle Loom - (직물과 가상소재의 화상 유사성 분석 연구 - 수직기 및 텍스타일 CAD시스템 활용 -)

  • Yoon, Jung-Won;Kim, Jong-Jun
    • Fashion & Textile Research Journal
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    • v.15 no.6
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    • pp.1010-1017
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    • 2013
  • Current global textiles and fashion industries have gradually shifted focus to high value-added, high sensibility, and multi-functional products based on new human-friendliness and sustainable growth technologies. Textile design CAD systems have been developed in conjunction with computer hardware and software sector advances. This study compares the patterns or images of actual woven fabrics and virtual fabrics prepared with a textile design CAD system. In this study, several weave structures (such as fancy yarn weave and patterns) were prepared with a shuttle loom. The woven textile images were taken using a CCD camera. The same weave structure data and yarn data were fed into a textile design CAD system in order to simulate fabric images as similarly as possible. Similarity Index analysis methods allowed for an analysis of the index between the actual fabric specimen and the simulated image of the corresponding fabric. The results showed that repeated small pattern weaves provide superior similarity index values than those of a fancy yarn weave that indicate some irregularities due to fancy yarn attributes. A Complex Wavelet Structural Similarity(CW-SSIM) index resulted in a better index than other methods such as Multi-Scale(MS) SSIM, and Feature Similarity(FS) SSIM, across fabric specimen images. A correlation analysis of the similarity index based on an image analysis and a similarity evaluation by panel members was also implemented.

A Study of Similarity Measures on Multidimensional Data Sequences Using Semantic Information (의미 정보를 이용한 다차원 데이터 시퀀스의 유사성 척도 연구)

  • Lee, Seok-Lyong;Lee, Ju-Hong;Chun, Seok-Ju
    • The KIPS Transactions:PartD
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    • v.10D no.2
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    • pp.283-292
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    • 2003
  • One-dimensional time-series data have been studied in various database applications such as data mining and data warehousing. However, in the current complex business environment, multidimensional data sequences (MDS') become increasingly important in addition to one-dimensional time-series data. For example, a video stream can be modeled as an MDS in the multidimensional space with respect to color and texture attributes. In this paper, we propose the effective similarity measures on which the similar pattern retrieval is based. An MDS is partitioned into segments, each of which is represented by various geometric and semantic features. The similarity measures are defined on the basis of these segments. Using the measures, irrelevant segments are pruned from a database with respect to a given query. Both data sequences and query sequences are partitioned into segments, and the query processing is based upon the comparison of the features between data and query segments, instead of scanning all data elements of entire sequences.

Molecular Typing of Acinetobacter Baumannii Strains by Randomly Amplified Polymorphic DNA (RAPD) Analysis (Randomly Amplified Polymorphic DNA (RAPD) 분석에 의한 Acinetobacter Baumannii 균주의 유전형 분류)

  • Oh, Jae-Young;Cho, Jae-Wee;Park, Jong-Chun;Lee, Je-Chul
    • The Journal of the Korean Society for Microbiology
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    • v.35 no.2
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    • pp.129-139
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    • 2000
  • Acinetobacter baumannii strains are emerging pathogens of the nosocomial infection with an increasing frequency in recent years. The therapeutic difficulty due to the wide spread of multiple resistant strains was major problem in A. baumannii infection. It seems likely that high frequency of A. baumannii infection will be increasing epidemiological importance in the future. However, the current limited understanding of the epidemiology of A. baumannii infections is caused by lack of a rapid and practical method for the molecular characterization of A. baumannii strains. This study was undertaken to determine molecular types and genetic similarity among A. baumannii strains isolated from four hospitals by RAPD analysis. Eighty-five strains, including 40 from Chunnam University Hospital, 27 from Dankook University Hospital, 15 from Yonsei University Hospital, and 3 from Seonam University Hospital, were classified into three molecular types. Molecular type II was the most common pattern and included 72 strains. All strains from Dankook University Hospital and 40 strains from Chunnam University Hospital belonged to molecular type I or II. A. baumannii strains form Yonsei University Hospital were very distant similarity values. The range of genetic similarity values among 85 strains of A. baumannii was 0.26 to 1.00. Although phenotypes including biotype and antimicrobial resistance pattern of A. baumannii strains were same or very similar to each other, their RAPD patterns were quite different. Typing with phenotypes was found to be less reliable than molecular typing by RAPD analysis. These results suggest that RAPD analysis provides rapid and simple typing method of A. baumannii strains for epidemiological studies. This work is the first epidemiological report of A. baumannii infections in Korea and it is hoped that results of this work may contribute to a better understanding of the clinical importance and epidemiology of A. baumannii strains.

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Comparison of Ginsenoside Contents and Pattern Similarity Between Root Parts of New Cultivars in Panax ginseng C.A. Meyer (인삼 신품종의 뿌리부위별 진세노사이드 함량 및 패턴비교)

  • Ahn, In-Ok;Lee, Sung-Sik;Lee, Jang-Ho;Lee, Mi-Ja;Jo, Byung-Gu
    • Journal of Ginseng Research
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    • v.32 no.1
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    • pp.15-18
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    • 2008
  • This study was carried out to evaluate the basic information on ginsenoside contents and pattern similarity in five cultivars of Panax ginseng C.A. Meyer. Among five cultivars the unit content and total content of ginsenosides were the highest in Gopoong cultivar as 18.9 mg/g and 596 mg/root, respectively. The unit content and total content of ginsenosides decreased in the order of Yunpoong, Gumpoong, Seonpoong and Chunpoong cultivar. Ginsenoside pattern similarity between tap root and lateral root was high as 0.95 but that between tap root and fine root was low as 0.72. Correlation of ginsenoside contents between tap root and lateral root exhibited the highest value as 0.843 and decreased in the order of main root, fine root, and rhizome. And the correlation value between unit content and total content of ginsenoside was very high as 0.933.

Discrimination of Plant Transient by Using the Fuzzy Pattern Recognition (퍼지 패턴인식법을 이용한 발전소 과도상태 판별)

  • Kim Jong-Seog;Lee Dong-ju
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.1
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    • pp.37-43
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    • 2005
  • Plant pipe has a fatigue life which is induced by repeated stress come from the variation of temperature and pressure. To avoid the fatigue crack of plant pipe which is produced by long term repeated stress, plant operator has to limit the mont of operating transient. This paper introduced the study result about discrimination methodology of plant transient by using the fuzzy pattern recognition. As result of applying the fuzzy pattern recognition to actual plant operation data, it is confirmed that fuzzy pattern recognition methodology can be useful for the comparison of similarity for the transients of similar output but has different time pattern.

Normal and Malicious Application Pattern Analysis using System Call Event on Android Mobile Devices for Similarity Extraction (안드로이드 모바일 정상 및 악성 앱 시스템 콜 이벤트 패턴 분석을 통한 유사도 추출 기법)

  • Ham, You Joung;Lee, Hyung-Woo
    • Journal of Internet Computing and Services
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    • v.14 no.6
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    • pp.125-139
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    • 2013
  • Distribution of malicious applications developed by attackers is increasing along with general normal applications due to the openness of the Android-based open market. Mechanism that allows more accurate ways to distinguish normal apps and malicious apps for common mobile devices should be developed in order to reduce the damage caused by the rampant malicious applications. This paper analysed the normal event pattern from the most highly used game apps in the Android open market to analyse the event pattern from normal apps and malicious apps of mobile devices that are based on the Android platform, and analysed the malicious event pattern from the malicious apps and the disguising malicious apps in the form of a game app among 1260 malware samples distributed by Android MalGenome Project. As described, experiment that extracts normal app and malicious app events was performed using Strace, the Linux-based system call extraction tool, targeting normal apps and malicious apps on Android-based mobile devices. Relevance analysis for each event set was performed on collected events that occurred when normal apps and malicious apps were running. This paper successfully extracted event similarity through this process of analyzing the event occurrence characteristics, pattern and distribution on each set of normal apps and malicious apps, and lastly suggested a mechanism that determines whether any given app is malicious.

Vegetation Classification from Time Series NOAA/AVHRR Data

  • Yasuoka, Yoshifumi;Nakagawa, Ai;Kokubu, Keiko;Pahari, Krishna;Sugita, Mikio;Tamura, Masayuki
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.429-432
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    • 1999
  • Vegetation cover classification is examined based on a time series NOAA/AVHRR data. Time series data analysis methods including Fourier transform, Auto-Regressive (AR) model and temporal signature similarity matching are developed to extract phenological features of vegetation from a time series NDVI data from NOAA/AVHRR and to classify vegetation types. In the Fourier transform method, typical three spectral components expressing the phenological features of vegetation are selected for classification, and also in the AR model method AR coefficients are selected. In the temporal signature similarity matching method a new index evaluating the similarity of temporal pattern of the NDVI is introduced for classification.

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Quantitative Measure of the Changes of Migration Patterns Using Cosine Similarity (코사인 유사도를 이용한 이주패턴 변화의 정량적 측정)

  • Han, Yicheol
    • Journal of Korean Society of Rural Planning
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    • v.23 no.2
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    • pp.67-74
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    • 2017
  • Migration is defined as the movement of people between residential places, and represents interactions between regions. Changes in migration involve changes in both the number of migrants toward/from regions and migration patterns across regions. However, most migration studies have focused only on the change in migrants, while no empirical study captures changes in migration patterns. In this paper, I present a function using the cosine similarity to measure changes in migration patterns, and apply it to 2001-2016 migration data of Korea. The results show that the migration patterns of Korea shifted in 2007, resulting in two distinct clusters. Local areas experienced various migration pattern changes despite few changes in the number of migrants.

Performance Analysis of the Time-series Pattern Index File for Content-based Music Genre Retrieval (내용기반 음악장르 검색에서 시계열 패턴 인덱스 화일의 성능 분석)

  • Kim, Young-In;Kim, Seon-Jong
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.5
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    • pp.18-27
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    • 2006
  • Rapid increase of the amount of music data demands for a new method that allows efficient similarity retrieval of music genre using audio features in music databases. To build this similarity retrieval, an indexing techniques that support audio features as a time-series pattern and data mining technologies are needed. In this paper, we address the development of a system that retrieves similar genre music based on the indexing techniques. We first propose the structure of content-based music genre retrieval system based on the time-series pattern index file and data mining technologies. In addition, we implement the time-series pattern index file using audio features and present performance analysis of the time-series pattern index file for similar genre retrieval. The experiments are performed on real data to verify the performance of the proposed method.

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Improving The Performance of Triple Generation Based on Distant Supervision By Using Semantic Similarity (의미 유사도를 활용한 Distant Supervision 기반의 트리플 생성 성능 향상)

  • Yoon, Hee-Geun;Choi, Su Jeong;Park, Seong-Bae
    • Journal of KIISE
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    • v.43 no.6
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    • pp.653-661
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    • 2016
  • The existing pattern-based triple generation systems based on distant supervision could be flawed by assumption of distant supervision. For resolving flaw from an excessive assumption, statistics information has been commonly used for measuring confidence of patterns in previous studies. In this study, we proposed a more accurate confidence measure based on semantic similarity between patterns and properties. Unsupervised learning method, word embedding and WordNet-based similarity measures were adopted for learning meaning of words and measuring semantic similarity. For resolving language discordance between patterns and properties, we adopted CCA for aligning bilingual word embedding models and a translation-based approach for a WordNet-based measure. The results of our experiments indicated that the accuracy of triples that are filtered by the semantic similarity-based confidence measure was 16% higher than that of the statistics-based approach. These results suggested that semantic similarity-based confidence measure is more effective than statistics-based approach for generating high quality triples.