• Title/Summary/Keyword: Similarity determination

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Analysis on Triangle Determination and Congruence (삼각형의 결정과 합동의 분석)

  • Kim, Su-Hyun;Choi, Yoon-Sang
    • Journal of the Korean School Mathematics Society
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    • v.10 no.3
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    • pp.341-351
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    • 2007
  • The primary purpose of this treatise is to suggest the solutions as follows for the errors concerning the triangle determination and congruence in every Korean mathematics textbook for 7th graders: showing that SsA, along with SSS, SAS, ASA, should also be included as the condition for triangle determination, congruence and similarity; proving that contrary to what has been believed, minimality applies only to congruence and similarity but not to determination; examining related Euclidean propositions; discussing the confusion about the characteristics of determination and congruence; and considering the negative effects of giving definite figures in construction education. The secondary purpose is to analyze the significance of triangle determinant that is not dealt with in either Euclid's Elements or the text books in the U.S. or Japan, and suggest a way to effectively deal with triangle determination and congruence in education.

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Image Positioning for Spa Destinations: Focusing on the Top 10 Spa Destinations in Korea (온천관광지 이미지 포지셔닝: 국내 10대 온천을 중심으로)

  • Yang, Lee-Na;Kim, Si-Joong
    • The Journal of Industrial Distribution & Business
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    • v.9 no.2
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    • pp.39-45
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    • 2018
  • Purpose - The purpose of this study is to examine the image similarity and attribute recognition of the top 10 rated spa destinations (Chungnam Deoksan, Chungnam Dogo, Busan Dongrae, Daejeon Yuseong, Chungnam Asan, Gyeongbuk Bomun, Chungbuk Suanbo, Gyeongnam Jangyu, Chungnam Onyang, & Gyeongbol Bugok) in Korea based on the visits to these spa places by the customers. Research design, data, and methodology - The survey of this study was conducted on the visitors to the top 10 spa destinations in Korea from April 8 ~ April 21, 2017, and a total of 300 questionnaires were distributed. Of them, effective questionnaires used in the final study were a total of 241. In this study, empirical analysis was made through frequency analysis, factor analysis, and multidimensional scaling ALSCAL(spinning symmetry for image similarity and rectangle for attributes recognition) by using the Statistics Package SPSS 24.0. Results - According to the analysis result of spa destination image similarity, the stress level was 0.16453 and the level of the stress was good. Moreover, the coefficient of determination (RSQ) was, which had a description of each aspect of the spa destination, 0.79908. According to the results of attribute recognition, the stress value of 0.11805 represents a degree of conformity, and the coefficient of determination(RSQ) appeared at 0.98665. Therefore, the results of this analysis are that the similarities between spa destinations and the attribute recognition of the spa destinations is a suitable model that is properly expressed in two dimensions. Conclusions - First, according to the analysis result of image similarity, Deoksan & Dogo spa revealed similar images, as well as the Dongrae and Yuseong spa, while on the contrary Asan, Bomun, Suanbo spa has different images from the rest. Second, according to the results of attribute recognition, Asan and Onyang spa has competitiveness in terms of accessibility to spa destination; Yuseong, Dongrae, Jangyu spa in terms of spa facilities, spa tourism conditions, and service & shopping conditions. while spa water quality and spa costs showed low attribute reflection for all 10 spas. Therefore, the spa visitors cannot recognize the differentiation of spa water quality and spa costs.

AWGN Removal Algorithm using Similarity Determination of Block Matching (블록 매칭의 유사도 판별을 이용한 AWGN 제거 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.11
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    • pp.1424-1430
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    • 2020
  • In this paper, we propose an algorithm to remove AWGN by considering the characteristics of noise present in the image. The proposed algorithm uses block matching to calculate the output, and calculates an estimate by determining the similarity between the center mask and the matching mask. The output of the filter is calculated by adding or subtracting the estimated value and the input pixel value, and weighting is given according to the standard deviation of the center mask and the noise constant to obtain the final output. In order to evaluate the proposed algorithm, the simulation was performed in comparison with the existing methods, and analyzed through the enlarged image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves important characteristics of the image, and shows the performance of removing noise efficiently.

A Study on the Case-Based Reasoning Setup Planning: Focused on the Similarity Index (CBR을 이용한 Setup Planning에서의 Similarity Index 결정에 관한 연구)

  • Han, Man-Chul;Park, Sun-Joo;Ha, Sung-Do
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.9 s.186
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    • pp.119-126
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    • 2006
  • This paper addresses the methodology development far the automated machining setup planning system using case-based reasoning(CBR). The case-based reasoning is used to develop a setup planning system. which consists of part input and representation module, case retrieval module, and case adaptation module. We present new approaches in the part input and representation module and the case retrieval module focusing on the similarity index determination. An illustrative example is included to demonstrate the proposed method.

Application of Euclidean Distance Similarity for Smartphone-Based Moving Context Determination (스마트폰 기반의 이동상황 판별을 위한 유클리디안 거리유사도의 응용)

  • Jang, Young-Wan;Kim, Byeong Man;Jang, Sung Bong;Shin, Yoon Sik
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.4
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    • pp.53-63
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    • 2014
  • Moving context determination is an important issue to be resolved in a mobile computing environment. This paper presents a method for recognizing and classifying a mobile user's moving context by Euclidean distance similarity. In the proposed method, basic data are gathered using Global Positioning System (GPS) and accelerometer sensors, and by using the data, the system decides which moving situation the user is in. The decided situation is one of the four categories: stop, walking, run, and moved by a car. In order to evaluate the effectiveness and feasibility of the proposed scheme, we have implemented applications using several variations of Euclidean distance similarity on the Android system, and measured the accuracies. Experimental results show that the proposed system achieves more than 90% accuracy.

Similarity Measurement of 3D Shapes Using Ray Distances (Ray distance를 이용한 3차원 형상의 유사성 판단)

  • 황태진;정지훈;오헌영;이건우
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.1
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    • pp.159-166
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    • 2004
  • Custom-tailored products are meant by the products having various sizes and shapes to meet the customer's different tastes or needs. Thus fabrication of custom-tailored products inherently involves inefficiency. To minimize this inefficiency, a new paradigm is proposed in this work. In this paradigm, different parts are grouped together according to their sizes and shapes. Then, representative shape of each group is derived and it will be used as the work-piece from which the parts in the group are machined. Once a new product is ordered, the optimal work-piece is selected through making similarity comparisons of new product and each representative shape. Then an effective NC tool-path is generated to machine only the different portions between the work-piece and the ordered product. The efficient machining conditions are also derived from this shape difference. By machining only the different portions between the work-piece and the ordered product, it saves time. Similarity comparison starts with the determination of the closest pose between two shapes in consideration. The closest pose is derived by comparing the ray distances while one shape is virtually rotated with respect to the other. Shape similarity value and overall similarity value calculated from ray distances are used for grouping. A prototype system based on the proposed methodology has been implemented and applied to the grouping and machining of the shoe lasts of various shapes and sizes.

Similarity Measurement of 3D Shapes Using Ray Distances (Ray distance를 이용한 3차원 형상의 유사성 판단)

  • 정지훈;황태진;오헌영;이건우
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.70-73
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    • 2003
  • Custom-tailored products are meant by the products having various sizes and shapes to meet the customer's different tastes or needs. Thus fabrication of custom-tailored products inherently involves inefficiency. To minimize this inefficiency, a new paradigm is proposed in this work. In this paradigm. different paris are grouped together according to their sizes and shapes. Then, representative shape of each group is derived and it will be used as the work-piece from which the parts in the group are machined. Once a new product is ordered, the optimal work-piece is selected through making similarity comparisons of new product and each representative shape. Then an effective NC tool-path is generated to machine only the different portions between the work-piece and the ordered product. The efficient machining conditions are also derived from this shape difference. By machining only the different portions between the work-piece and the ordered product, it saves time. Similarity comparison starts with the determination of the closest pose between two shapes in consideration. The closest pose is derived by comparing the ray distances while one shape is virtually rotated with respect to the other. Shape similarity value and overall similarity value calculated from ray distances are used for grouping. A prototype system based on the proposed methodology has been implemented and applied to the grouping and machining of the shoe lasts of various shapes and sizes.

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A Tolerant Rough Set Approach for Handwritten Numeral Character Classification

  • Kim, Daijin;Kim, Chul-Hyun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.288-295
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    • 1998
  • This paper proposes a new data classification method based on the tolerant rough set that extends the existing equivalent rough set. Similarity measure between two data is described by a distance function of all constituent attributes and they are defined to be tolerant when their similarity measure exceeds a similarity threshold value. The determination of optimal similarity theshold value is very important for the accurate classification. So, we determine it optimally by using the genetic algorithm (GA), where the goal of evolution is to balance two requirements such that (1) some tolerant objects are required to be included in the same class as many as possible. After finding the optimal similarity threshold value, a tolerant set of each object is obtained and the data set is grounded into the lower and upper approximation set depending on the coincidence of their classes. We propose a two-stage classification method that all data are classified by using the lower approxi ation at the first stage and then the non-classified data at the first stage are classified again by using the rough membership functions obtained from the upper approximation set. We apply the proposed classification method to the handwritten numeral character classification. problem and compare its classification performance and learning time with those of the feed forward neural network's back propagation algorithm.

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Vertical composition and character analysis of saprophytic bacteria isolated from the mudflat of Nakdong river estuary (낙동강 하구 간석지에서 분리된 세균의 층별 종조성 및 특성에 관하여)

  • Hong, Soon-Woo;Kim, Sang-Jong;Rhie, Youn;Choi, Sung-Chan
    • Korean Journal of Microbiology
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    • v.23 no.2
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    • pp.157-165
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    • 1985
  • Bacterial identification was performed with morphological, physiological and biochemical tests to the isolates from the mudflat of 30cm depth sampled in Nakdong river estuary in March and June, 1985. Flavobacterium and Cnterobacteriaceae were regarded as dominants. Pseudomonas, Bacillus, Micrococcus, Vibrio, Aerococcus, Aerononas, Acinetobacter and Staphylococcus were founded in various depth. Vertical composition of bacterial genera in March was more diversiform than that of June. Character analysis was carried out with the calculation of similarity index (S). At a level of 85% similarity, the isolates were clustered into 5 groups and ungrouped 2 strains. Classifying groups of bacterial strains with determination schemes and groups from similarity index were in good agreement.

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Determination of Object Similarity Closure Using Shared Neighborhood Connectivity

  • Radhakrishnan, Palanikumar;Arokiasamy, Clementking
    • Journal of the Korea Convergence Society
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    • v.5 no.3
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    • pp.41-44
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    • 2014
  • Sequential object analysis are playing vital role in real time application in computer vision and object detections.Measuring the similarity in two images are very important issue any authentication activities with how best to compare two independent images. Identification of similarities of two or more sequential images is also the important in respect to moving of neighborhoods pixels. In our study we introduce the morphological and shared near neighborhoods concept which produces a sufficient results of comparing the two images with objects. Considering the each pixel compare with 8-connectivity pixels of second image. For consider the pixels we expect the noise removed images are to be considered, so we apply the morphological transformations such as opening, closing with erosion and dilations. RGB of pixel values are compared for the two sequential images if it is similar we include the pixels in the resultant image otherwise ignore the pixels. All un-similar pixels are identified and ignored which produces the similarity of two independent images. The results are produced from the images with objects and gray levels. It produces the expected results from our process.