• Title/Summary/Keyword: 생성규칙변환

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Medical Image Encryption based on C-MLCA and 1D CAT (C-MLCA와 1차원 CAT를 이용한 의료 영상 암호화)

  • Jeong, Hyun-Soo;Cho, Sung-Jin;Kim, Seok-Tae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.2
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    • pp.439-446
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    • 2019
  • In this paper, we propose a encryption method using C-MLCA and 1D CAT to secure medical image for efficiently. First, we generate a state transition matrix using a Wolfram rule and create a sequence of maximum length. By operating the complemented vector, it converts an existing sequence to a more complex sequence. Then, we multiply the two sequences by rows and columns to generate C-MLCA basis images of the original image size and go through a XOR operation. Finally, we will get the encrypted image to operate the 1D CAT basis function created by setting the gateway values and the image which is calculated by transform coefficients. By comparing the encrypted image with the original image, we evaluate to analyze the histogram and PSNR. Also, by analyzing NPCR and key space, we confirmed that the proposed encryption method has a high level of stability and security.

Automatic Construction of SHACL Schemas for RDF Knowledge Graphs Generated by Direct Mappings

  • Choi, Ji-Woong
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.10
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    • pp.23-34
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    • 2020
  • In this paper, we proposes a method to automatically construct SHACL schemas for RDF knowledge graphs(KGs) generated by Direct Mapping(DM). DM and SHACL are all W3C recommendations. DM consists of rules to transform the data in an RDB into an RDF graph. SHACL is a language to describe and validate the structure of RDF graphs. The proposed method automatically translates the integrity constraints as well as the structure information in an RDB schema into SHACL. Thus, our SHACL schemas are able to check integrity instead of RDBMSs. This is a consideration to assure database consistency even when RDBs are served as virtual RDF KGs. We tested our results on 24 DM test cases, published by W3C. It was shown that they are effective in describing and validating RDF KGs.

Effective Studying Methods during a School Vacation: A Data Mining Approach (데이타 마이닝을 사용한 방학 중 학습방법과 학업성취도의 관계 분석)

  • Kim, Hea-Suk;Moon, Yang-Sae;Kim, Jin-Ho;Loh, Woong-Kee
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.40-51
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    • 2007
  • To improve academic achievement, the most students not only participate in regular classes but also take various extra programs such as private lessons, private institutes, and educational TV programs. In this paper, we propose a data mining approach to identify which studying methods or usual life patterns during a school vacation affect changes in the academic achievement. First, we derive various studying methods and life patterns that are thought to be affecting changes in the academic achievement during a school vacation. Second, we propose the method of transforming and analyzing data to apply them to decision trees and association rules, which are representative data mining techniques. Third, we construct decision trees and find association rules from the real survey data of middle school students. We have discovered four representative results from the decision trees. First, for students in the higher rank, there is a tendency that private institutes give a positive effect on the academic achievement. Second, for the most students, the Internet teaming sites nay give a negative effect on the achievement. Third, private lessons that have thought to be making a large impact to the achievement, however, do not make a positive effect on the achievement. Fourth, taking several studying methods in parallel nay give a negative effect on the achievement. In association rules, however, we cannot find any meaningful relationships between academic achievement and usual life patterns during a school vacation. We believe that our approach will be very helpful for teachers and parents to give a good direction both in preparing a studying plan and in selecting studying methods during a school vacation.

A Topographical Classifier Development Support System Cooperating with Data Mining Tool WEKA from Airborne LiDAR Data (항공 라이다 데이터로부터 데이터마이닝 도구 WEKA를 이용한 지형 분류기 제작 지원 시스템)

  • Lee, Sung-Gyu;Lee, Ho-Jun;Sung, Chul-Woong;Park, Chang-Hoo;Cho, Woo-Sug;Kim, Yoo-Sung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.133-142
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    • 2010
  • To monitor composition and change of the national land, intelligent topographical classifier which enables accurate classification of land-cover types from airborne LiDAR data is highly required. We developed a topographical classifier development support system cooperating with da1a mining tool WEKA to help users to construct accurate topographical classification systems. The topographical classifier development support system has the following functions; superposing LiDAR data upon corresponding aerial images, dividing LiDAR data into tiles for efficient processing, 3D visualization of partial LiDAR data, feature from tiles, automatic WEKA input generation, and automatic C++ program generation from the classification rule set. In addition, with dam mining tool WEKA, we can choose highly distinguishable features by attribute selection function and choose the best classification model as the result topographical classifier. Therefore, users can easily develop intelligent topographical classifier which is well fitted to the developing objectives by using the topographical classifier development support system.

Experimental Design of S box and G function strong with attacks in SEED-type cipher (SEED 형식 암호에서 공격에 강한 S 박스와 G 함수의 실험적 설계)

  • 박창수;송홍복;조경연
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.1
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    • pp.123-136
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    • 2004
  • In this paper, complexity and regularity of polynomial multiplication over $GF({2^n})$ are defined by using Hamming weight of rows and columns of the matrix ever GF(2) which represents polynomial multiplication. It is shown experimentally that in order to construct the block cipher robust against differential cryptanalysis, polynomial multiplication of substitution layer and the permutation layer should have high complexity and high regularity. With result of the experiment, a way of constituting S box and G function is suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with a nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over $GF({2^8})$ which has neither a fixed pout, whose input and output are the same except 0 and 1, nor an opposite fixed number, whose output is one`s complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes linear transform with 4 S-box outputs using the matrix of 4${\times}$4 over $GF({2^8})$. The components in the matrix of linear transformation have high complexity and high regularity. Furthermore, G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, and there can be no weak input where a fixed point an opposite fixed point, and output can be two`s complement of input. The primitive polynomials of nonlinear function affine transform and linear transformation are different each other. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.

Classification of Multi-temporal SAR Data by Using Data Transform Based Features and Multiple Classifiers (자료변환 기반 특징과 다중 분류자를 이용한 다중시기 SAR자료의 분류)

  • Yoo, Hee Young;Park, No-Wook;Hong, Sukyoung;Lee, Kyungdo;Kim, Yeseul
    • Korean Journal of Remote Sensing
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    • v.31 no.3
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    • pp.205-214
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    • 2015
  • In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

Web Information Extraction and Multidimensional Analysis Using XML (XML을 이용한 웹 정보 추출 및 다차원 분석)

  • Park, Byung-Kwon
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.567-578
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    • 2008
  • For analyzing a huge amount of web pages available in the Internet, we need to extract the encoded information in web pages. In this paper, we propose a method to extract and convert web information from web pages into XML documents for multidimensional analysis. For extracting information from web pages, we propose two languages: one for describing web information extraction rules based on the object-oriented model, and another for describing regular expressions of HTML tag patterns to search for target information. For multidimensional analysis on XML documents, we propose a method for constructing an XML warehouse and various XML cubes from it like the way we do for relational data. Finally, we show the validness of our method through the application to US patent web pages.

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A Study on Proportion-Generating System Based on Dom Hans van der Laan′s Proportion Theory (돔 한스 반 데어 란의 비례론에 기초한 비례생성 시스템에 관한 연구)

  • Choo Seung Yeon
    • Journal of the Korean housing association
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    • v.15 no.5
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    • pp.69-76
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    • 2004
  • 비트루비우스(Vitruvius)에서 벤츄리(Venturi)에 이르기까지 많은 건축사가(建榮史家) 또는 건축가(建築家)들이 건축원리에 대한 각자의 규범적 태도를 글로써 밝혀왔다. 이러한 규범적 내용 중 비례이론은 서양건축에 있어 건축미(建築美) 비밀로 간주되어, 조화로운 건축물이 꼭 갖추어야 할 덕목중의 하나로 인식되었다. 현대건축에서 비교적 근대 비례시스템이라 불릴 수 있는 것으로 르 꼬르뷔지에의 모될로르와 반 데어 란의 플라스틱 넘버를 들 수 있다. 모될로르는 현재까지 아주 제한된 성공밖에 거두지 못했는데, 이는 피보나치 수열에 기초한 수치들이 커졌을 때 단위의 배수관계가 거의 형성되지 않는다는 사실에 기인한다. 반면에 플라스틱 넘버는 모될로르의 결점들을 보완할 수 있는 매력적인 수열을 가지고 있다. 이에 본 연구는 반 데어 란의 비례시스템 분석을 통하여 유도된 수열규칙이 건축디자인과 관련되어 직접적으로 적용되어 질 수 있는 CAAD시스템을 제안한다. 본 시스템의 초점은 반 데어 란의 비례이론이 어떻게 컴퓨터 언어로 변환 및 CAAD시스템에 적용되어, 실질적인 건축 실무행위에 있어 컴퓨터가 디자인 도우미로서 역할을 수행할 수 있겠는가하는 것이다. 연구의 결과, 사용자는 이러한 시스템을 사용함으로써 반 데어 란의 비례시스템을 자신의 디자인에 손쉽게 적용할 수 있으며, 이는 복잡한 치수관계로 구성된 비례시스템의 건축실무 활용으로 발전되어질 수 있을 것으로 사료된다.

A Morph Analyzer For MATES/CK (중한 기계 번역 시스템을 위한 형태소 분석기)

  • Kang, Won-Seok;Kim, Ji-Hyoun;Song, Young-Mi;Song, Hee-Jung;Huang, Jin-Xia;Chae, Young-Soog;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 2000.10d
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    • pp.331-336
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    • 2000
  • MATES/CK는 기계번역 시스템에서 전통적으로 사용하고 있는 세 단계(분석/변환/생성)에 의해서 중한 번역을 수행하는 시스템이다. MATES/CK는 시스템 성능을 높이기 위해 패턴 기반과 통계적 정보를 이용한다. 태거(Tagger)는 중국어 단어 분리를 최장일치법으로 수행하기 때문에 일부 단어에 대해 오류를 범하게 되고 품사(POS : Part Of Speech) 태깅 시 확률적 정보만 이용하여 특정 단어가 다 품사인 경우 그 단어에 대해 특정 품사만 태깅되는 문제점이 발생한다. 또한 중국어 및 외국어 인명 및 지명에 대한 미등록들에 대해서도 올바른 결과를 도출하지 못한다. 사전에 있어서 텍스트 기반으로 존재하여 이를 관리하기에 힘이 든다. 본 논문에서는 단어 분리 오류 및 품사 태깅 오류를 해결하기 위해 중국어 태깅 제약 규칙을 적용하는 방법을 제시하고 중국어 및 외국어 인명/지명에 대한 미등록어 처리방법을 제시한다. 또한 중국어 사전 관리에 대해 알아본다.

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Korean Sentence Symbol Preprocess System for the Improvement of Speech Synthesis Quality (음성 합성 시스템의 품질 향상을 위한 한국어 문장 기호 전처리 시스템)

  • Lee, Ho-Joon
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.2
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    • pp.149-156
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    • 2015
  • In this paper, we propose a Korean sentence symbol preprocessor for a SSML (speech synthesis markup language) supported speech synthesis system in order to improve the quality of the synthesized result. After the analysis of Korean Wikipedia documents, we propose 8 categories for the meaning of sentence symbols and 11 regular expression for the classification of each category. After the development of a Korean sentence symbol preprocess system we archived 56% of precision and 71.45% of recall ratio for 63,000 sentences.