• Title/Summary/Keyword: Euclidean distance analysis

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Measure of the Associations of Accupoints and Pathologies Documented in the Classical Acupuncture Literature (고의서에 나타난 경혈과 병증의 연관성 측정 및 시각화 - 침구자생경 분석 예를 중심으로 -)

  • Oh, Junho
    • Korean Journal of Acupuncture
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    • v.33 no.1
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    • pp.18-32
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    • 2016
  • Objectives : This study aims to analyze the co-occurrence of pathological symptoms and corresponding acupoints as documented by the comprehensive acupuncture and moxibustion records in the classical texts of Far East traditional medicine as an aid to a more efficient understanding of the tacit treatment principles of ancient physicians. Methods : The Classic of Nourishing Life with Acupuncture and Moxibustion(Zhenjiu Zisheng Jing; hereinafter ZZJ) was selected as the primary reference book for the analysis. The pathology-acupoint co-occurrence analysis was performed by applying 4 values of vector space measures(weighted Euclidean distance, Euclidean distance, $Cram\acute{e}r^{\prime}s$ V and Canberra distance), which measure the distance between the observed and expected co-occurrence counts, and 3 values of probabilistic measures(association strength, Fisher's exact test and Jaccard similarity), which measure the probability of observed co-occurrences. Results : The treatment records contained in ZZJ were preprocessed, which yielded 4162 pathology-acupoint sets. Co-occurrence was performed applying 7 different analysis variables, followed by a prediction simulation. The prediction simulation results revealed the Weighted Euclidean distance had the highest prediction rate with 24.32%, followed by Canberra distance(23.14%) and association strength(21.29%). Conclusions : The weighted Euclidean distance among the vector space measures and the association strength among the probabilistic measures were verified to be the most efficient analysis methods in analyzing the correlation between acupoints and pathologies found in the classical medical texts.

Clustering-based Monitoring and Fault detection in Hot Strip Roughing Mill (군집기반 열간조압연설비 상태모니터링과 진단)

  • SEO, MYUNG-KYO;YUN, WON YOUNG
    • Journal of Korean Society for Quality Management
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    • v.45 no.1
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    • pp.25-38
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    • 2017
  • Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

Operation Modes Classification of Chemical Processes for History Data-Based Fault Diagnosis Methods (데이터 기반 이상진단법을 위한 화학공정의 조업모드 판별)

  • Lee, Chang Jun;Ko, Jae Wook;Lee, Gibaek
    • Korean Chemical Engineering Research
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    • v.46 no.2
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    • pp.383-388
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    • 2008
  • The safe and efficient operation of the chemical processes has become one of the primary concerns of chemical companies, and a variety of fault diagnosis methods have been developed to diagnose faults when abnormal situations arise. Recently, many research efforts have focused on fault diagnosis methods based on quantitative history data-based methods such as statistical models. However, when the history data-based models trained with the data obtained on an operation mode are applied to another operating condition, the models can make continuous wrong diagnosis, and have limits to be applied to real chemical processes with various operation modes. In order to classify operation modes of chemical processes, this study considers three multivariate models of Euclidean distance, FDA (Fisher's Discriminant Analysis), and PCA (principal component analysis), and integrates them with process dynamics to lead dynamic Euclidean distance, dynamic FDA, and dynamic PCA. A case study of the TE (Tennessee Eastman) process having six operation modes illustrates the conclusion that dynamic PCA model shows the best classification performance.

Weight Vector Analysis to Portfolio Performance with Diversification Constraints (비중 상한 제약조건에 따른 포트폴리오 성과에 대한 투자 비중 분석)

  • Park, Kyungchan;Kim, Hongseon;Kim, Seongmoon
    • Korean Management Science Review
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    • v.33 no.4
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    • pp.51-64
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    • 2016
  • The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

수치변화탐지의 새로운 접근 - 기하거리분석법 -

  • Jeong, Seong-Hak
    • 한국지형공간정보학회:학술대회논문집
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    • 1993.10a
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    • pp.141-145
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    • 1993
  • A new digital change detection algorithm, Euclidean Distance Analysis, was developed in an attempt to utilize the multi-band information in a selected band-comination, as an alternative to the conventional single-band analysis methods. To evaluate the relative performance of this new method, image differencing was applied. The better performance in change detection between the two algorithms investigated was provided by the Euclidean distance analysis. The new technique of Euclidean distance analysis holds promise for change detection, since it summarizes the multiple-band information on the cover-type changes and reduces the data dimensionality. It is suggested to further evaluate this new method, quantitatively, in the different environments. The use of different accuracy indices was also examined in the determining the optimal threshold level for each change image. As the standard measure for classification accuracy, the Kappa coefficient of agreement was used for evaluation.

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Spatial Implications of Euclidean Distance on the Service Use in Oriental Medicine Hospital (공간적 거리와 한방병원 서비스의 이용 간의 관계에 관한 연구)

  • Lee, Kwang-Soo;Lee, Jung-Soo;Hong, Sang-Jin;Chun, Bong-Jae
    • The Korean Journal of Health Service Management
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    • v.4 no.2
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    • pp.23-31
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    • 2010
  • This study analyzed whether the patients' visits to oriental medicine hospitals were influenced by the Euclidean distance from patients' residence to oriental medicine hospitals. Patient who visited two oriental medicine hospitals in a metropolitan area were selected for study sample. The number of patient from each Dong (which is the smallest administrative district) to two hospitals was calculated based on claims data in 2008. ArcGIS was used to calculate the distance. Distance variable was not statistically significant in regression analysis after controlling the difference of socio-economic status of people in each Dong. It seems that distance factor did not play an important role in deciding whether to use the services of oriental medicine hospitals in a metropolitan area.

Cross-Generational Differences of /o/ and /u/ in Informal Text Reading (편지글 읽기에 나타난 한국어 모음 /오/-/우/의 세대간 차이)

  • Han, Jeong-Im;Kang, Hyunsook;Kim, Joo-Yeon
    • Phonetics and Speech Sciences
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    • v.5 no.4
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    • pp.201-207
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    • 2013
  • This study is a follow-up study of Han and Kang (2013) and Kang and Han (2013) which examined cross-generational changes in the Korean vowels /o/ and /u/ using acoustic analyses of the vowel formants of these two vowels, their Euclidean distances and the overlap fraction values generated in SOAM 2D (Wassink, 2006). Their results showed an on-going approximation of /o/ and /u/, more evident in female speakers and non-initial vowels. However, these studies employed non-words in a frame sentence. To see the extent to which these two vowels are merged in real words in spontaneous speech, we conducted an acoustic analysis of the formants of /o/ and /u/ produced by two age groups of female speakers while reading a letter sample. The results demonstrate that 1) the younger speakers employed mostly F2 but not F1 differences in the production of /o/ and /u/; 2) the Euclidean distance of these two vowels was shorter in non-initial than initial position, but there was no difference in Euclidean distance between the two age groups (20's vs. 40-50's); 3) overall, /o/ and /u/ were more overlapped in non-initial than initial position, but in non-initial position, younger speakers showed more congested distribution of the vowels than in older speakers.

Face Image Retrieval by Using Eigenface Projection Distance (고유영상 투영거리를 이용한 얼굴영상 검색)

  • Lim, Kil-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.5
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    • pp.43-51
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    • 2009
  • In this paper, we propose an efficient method of face retrieval by using PCA(principal component analysis) based features. The coarse-to-fine strategy is adopted to sort the retrieval results in the lower dimensional eigenface space and to rearrange candidates at high ranks in higher dimensional eigenface space. To evaluate similarity between a query face image and class reference image, we utilize the PD (projection distance), MQDF(modified quadratic distance function) and MED(minimum Euclidean distance). The experimental results show that the proposed method which rearrange the retrieval results incrementally by using projection distance is efficient for face image retrieval.

MANAGEMENT DECISION-MAKING FOR SUGARCANE FERTILIZER MIX PROBLEMS THROUGH GOAL PROGRAMMING

  • Sharma, Dinesh K.;Ghosh, Debasis;Alade, Julius A.
    • Journal of applied mathematics & informatics
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    • v.13 no.1_2
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    • pp.323-334
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    • 2003
  • This paper presents a goal-programming (GP) model for management decision-making for sugarcane fertilizer mix problems. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses Euclidean distance function to measure distances of all possible solutions from the ideal solution. The optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the problem. The optimum solution corresponds to the appropriate priority structure of the problem in the decision-making context. furthermore, the results obtained from sensitivity analysis on the cost of combination of fertilizers confirm the priority structure.

Euclidean Genetic Distances of Four Manila Clam (Ruditapes philippinarum) Populations analyzed by PCR Research

  • Yoon, Jong-Man
    • Development and Reproduction
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    • v.21 no.3
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    • pp.269-274
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    • 2017
  • The PCR analysis was performed on DNA samples extracted from a total of 20 individuals using six oligonucleotides primers. The author accomplished clustering analyses to reveal the Euclidean genetic distances among four clam populations from Gochang, Seocheon, Taean and Anmyeon of the Korean peninsula. The oligonucleotides primer OPA-08 generated 5 unique loci to each population, approximately 550 bp and 600 bp, respectively, in the MCS population. Especially, the primer OPA-20 generated 15 unique loci to each population, which were identifying each population, approximately 400 bp, 750 bp and 800 bp, in the MCT population. Individuals from MCG clam population ($0.637{\pm}0.227$) exhibited higher band-sharing values than did individuals from MCG clam population ($0.402{\pm}0.115$) (P<0.05). The dendrogram obtained by the six oligonucleotides primers indicates four genetic clusters: cluster 1 (MCG 01, 02, 04 and 05), cluster 2 (MCS 06, 07, 08, 09 and 10), cluster 3 (MCT 11, 12, 13, 14 and 15) and cluster 4 (MCA 16, 17, 18, 19, 20 and MCG 03). Among the twenty clam individuals, the shortest genetic distance that displayed significant molecular differences was between individuals 14 and 15 from the MCT population (genetic distance = 0.094), while the longest genetic distance among the twenty individuals that displayed significant molecular differences was between individuals MCG no. 01 and MCG no. 02 (genetic distance = 0.687). Comparatively, individuals of MCS clam population were fairly closely related to that of MCT clam population, as shown in the hierarchical dendrogram of Euclidean genetic distances.