• Journal of Plant Biotechnology
• /
• 제3권3호
• /
• pp.145-149
• /
• 2001

This study was conducted to analyze the morphological characteristics such as flower color, flower type, flower diameter and flower stalk, and the main annual production yield, and genetic similarity of twenty four Gerbera species growing in Korea. Most of flower colors were pink. The numerical order of flower color was pink, orange, red, double-colored, and milk-white. Majority of flower types were sin81e or semidouble flowers. A few species were double flowers. flower diameters were from 7 ㎝ to 12 ㎝, showed significant differences compared to other characteristics. Flower stalks were ranged from 55 ㎝ to 65 ㎝. Only one species was the shortest as 55 ㎝. The others were similar size as about 65 ㎝. Main annual production yields were between 190 and 400 blossoms. Fifty seven reproducible polymorphic bands from eighty primers were used for analyses of genetic similarity. The genetic similarity of 24 collected Gerberas was largely classified into five groups. The average similarity coefficient was 0.72 ranged from 0.50 to 0.90. The highest similarity coefficient was shown between 'Sardana' with red/white flower color and double flower type, and 'Tamara' with orange flower color and double flower type as 0.90.

• Journal of Crop Science and Biotechnology
• /
• 제11권1호
• /
• pp.39-44
• /
• 2008

Korean cultivated bramble, which is known as Bokbunja-ddal-gi is regarded to be originated from Korea native Rubus coreanus. However, little scientific evidence and significant morphological differences between Korean cultivated bramble(KCB) and R. coreanus throw doubt on the ancestry of KCB. This study was carried out to obtain phylogenetic information on KCB by comparing its nuclear genomic background with those of R. coreanus, black(R. occidentalis) and red(R. idaeus) raspberry, blackberry(R. lanciniatus) and R. crataegifolius. A total of 99 random amplified polymorphic DNA(RAPD) markers were generated and used for phylogenetic analysis of 76 Rubus accessions. Accessions of each species were grouped into each distinct subclade by the RAPD markers at a similarity coefficient of about 0.59. The KCB subclade formed a clade with R. occidentalis and R. crataegifolius subclades at a similarity coefficient of 0.47. The R. coreanus subclade formed a clade with R. idaeus, R. lanciniatus and R. crataegifolius subclades at a similar similarity coefficient. Only one KCB accession from Hoengsung was included in R. coreanus subclade. The accession shows leaf and flower characteristics different from the rest of the KCB accessions. The phylogenetic relationship inferred from the RAPD markers suggests that the nuclear genomic background of KCB accessions which show morphological similarity to black raspberry is more closely related to black raspberry than to R. coreanus. This brings about the need for close scientific evaluations on the ancestry of KCB at both morphological and molecular levels.

• 한국지능시스템학회논문지
• /
• 제22권3호
• /
• pp.287-293
• /
• 2012

본 논문에서는 영상의 다차원 명암도 증감에 기반을 둔 유사도 측정에 의한 효율적인 영상정합 방법을 제안하였다. 여기서 다차원 명암도는 영상의 4방향을 고려한 유사성 판정으로 영상이 가지는 속성을 더욱 더 많이 반영하기 위함이고, 명암도 증감은 인접 픽셀간의 밝기변화를 고려함으로써 좀 더 포괄적으로 유사성을 측정하기 위함이다. 또한 측정된 4방향 각각의 명암도 증감에 대한 정규상호상관계수를 구하고, 그 각각에 바탕을 둔 전체 정규상호상관계수, 각 방향의 상관계수에 대한 산술평균과 단순 곱 및 최대값으로 정규화된 상관계수의 산술평균과 단순 곱으로 정의된 유사도 계수로 각각 정합을 측정하였다. 제안된 방법을 22개의 243*243 픽셀 얼굴영상과 9개의 500*500 픽셀 인물영상을 대상으로 각각 실험한 결과, 영상의 속성을 잘 반영한 우수한 정합성능이 있음을 확인하였다. 특히 각 방향의 상관계수에 대한 산술평균 유사도가 가장 우수한 신뢰성을 가지는 정합척도임을 알 수 있었다.

• 원예과학기술지
• /
• 제18권2호
• /
• pp.103-106
• /
• 2000

RAPD 방법을 이용하여 국내자생 자란과 일본자생 자란의 유전적 다형성을 연구하였다. PCR 결과 156개의 재현성을 보이는 band를 얻었으며 그 중 58개가 다형성을 보였고 98개는 단일성을 나타냈다. 유연관계 분석 결과 자란은 세가지의 그룹으로 분류되었다. 첫 번째 그룹은 국내 A(자생일반종), B(목포산 자생 반엽종), C(자생 반엽종) 그리고 일본품종 D와 E(일본자생 일반종)가 속한다. 국내 무늬종 B와 C의 유사도 0.806, 일본품종 D와 E는 0.778로 매우 높게 나타났다. 두 번째 그룹은 일본품종 G(일본자생 왜성종)만이 분류되었다. 그리고 세 번째 그룹은 일본자생 무늬종인 F와 H(일본자생 무늬종)가 포함되었다.

• 한국균학회지
• /
• 제26권1호통권84호
• /
• pp.1-7
• /
• 1998

동충하초 균주의 종간 또는 종내의 근연관계를 구명하고자 단백질 분석을 실시한 결과 25개 공시 균주는 85%의 유사도범위에서 세개의 그룹으로 분류되었다. C. militaris 종내의 유사도는 $0.787{\sim}1.000$ 범위로 나타났으며 C. kyushuensis는 $0.958{\sim}1.000$으로 상당히 높은 유사성을 보였다. C. pruinosa역시 종내의 유사성이 $0.993{\sim}1.000$의 높은 수준을 보였다. C. militaris종내에서는 형태적으로 다른 C. militaris균주와는 달리 다소 매생한 형태의 자낭각을 형성한 C210균주와 C298균주가 단백질분석에서도 약 91%의 상동성을 보이며 clustering되었다. 또한 유충을 기주로 자실체를 형성하는 균주들(C108, C225-1, C228)에 있어서도 약 89%의 높은 상동성을 보이며 clustering되었다. C. militaris그룹과 가장 가까운 근연관계를 보인 그룹은 박각시 나방의 유충을 기주로하는 C. kyushuensis와 인시목의 번데기를 기주로 자실체를 형성하는 C. pruinosa로 C. militaris그룹과는 약 87%의 상동성을 보였으며 C. pruinosa와 C. kyushuensis간에는 88%의 상동성을 보였다. 인시목의 번데기를 기주로 자실체를 형성하며 평판배지상에서 분생포자를 형성하는 C. bifusispora는 불완전 균인 Paecilomyces tenuipes와 89%의 상동성을 보였으며 풍뎅이 성충만을 특이적으로 침입하는 C. scarabaeicola는 이 두종과 약 82%의 상동성을 보였다 C. militaris로 동정한 C118의 경우는 단백질 분석에서도 밴드양상이 C. militaris그룹과는 상당히 다른 양상을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권8호
• /
• pp.2587-2605
• /
• 2022

In order to efficiently detect community structure in complex networks, community detection algorithms can be designed from the perspective of node similarity. However, the appropriate parameters should be chosen to achieve community division, furthermore, these existing algorithms based on the similarity of common neighbors have low discrimination between node pairs. To solve the above problems, a noval community detection algorithm using closeness similarity based on common neighbor node clustering entropy is proposed, shorted as CSCDA. Firstly, to improve detection accuracy, common neighbors and clustering coefficient are combined in the form of entropy, then a new closeness similarity measure is proposed. Through the designed similarity measure, the closeness similar node set of each node can be further accurately identified. Secondly, to reduce the randomness of the community detection result, based on the closeness similar node set, the node leadership is used to determine the most closeness similar first-order neighbor node for merging to create the initial communities. Thirdly, for the difficult problem of parameter selection in existing algorithms, the merging of two levels is used to iteratively detect the final communities with the idea of modularity optimization. Finally, experiments show that the normalized mutual information values are increased by an average of 8.06% and 5.94% on two scales of synthetic networks and real-world networks with real communities, and modularity is increased by an average of 0.80% on the real-world networks without real communities.

• Asia pacific journal of information systems
• /
• 제18권1호
• /
• pp.79-96
• /
• 2008

One of the roles of the Semantic Web services is to execute dynamic intra-organizational services including the integration and interoperation of business processes. Since different organizations design their processes differently, the retrieval of similar semantic business processes is necessary in order to support inter-organizational collaborations. Most approaches for finding services that have certain features and support certain business processes have relied on some type of logical reasoning and exact matching. This paper presents our approach of using imprecise matching for expanding results from an exact matching engine to query the OWL(Web Ontology Language) MIT Process Handbook. MIT Process Handbook is an electronic repository of best-practice business processes. The Handbook is intended to help people: (1) redesigning organizational processes, (2) inventing new processes, and (3) sharing ideas about organizational practices. In order to use the MIT Process Handbook for process retrieval experiments, we had to export it into an OWL-based format. We model the Process Handbook meta-model in OWL and export the processes in the Handbook as instances of the meta-model. Next, we need to find a sizable number of queries and their corresponding correct answers in the Process Handbook. Many previous studies devised artificial dataset composed of randomly generated numbers without real meaning and used subjective ratings for correct answers and similarity values between processes. To generate a semantic-preserving test data set, we create 20 variants for each target process that are syntactically different but semantically equivalent using mutation operators. These variants represent the correct answers of the target process. We devise diverse similarity algorithms based on values of process attributes and structures of business processes. We use simple similarity algorithms for text retrieval such as TF-IDF and Levenshtein edit distance to devise our approaches, and utilize tree edit distance measure because semantic processes are appeared to have a graph structure. Also, we design similarity algorithms considering similarity of process structure such as part process, goal, and exception. Since we can identify relationships between semantic process and its subcomponents, this information can be utilized for calculating similarities between processes. Dice's coefficient and Jaccard similarity measures are utilized to calculate portion of overlaps between processes in diverse ways. We perform retrieval experiments to compare the performance of the devised similarity algorithms. We measure the retrieval performance in terms of precision, recall and F measure? the harmonic mean of precision and recall. The tree edit distance shows the poorest performance in terms of all measures. TF-IDF and the method incorporating TF-IDF measure and Levenshtein edit distance show better performances than other devised methods. These two measures are focused on similarity between name and descriptions of process. In addition, we calculate rank correlation coefficient, Kendall's tau b, between the number of process mutations and ranking of similarity values among the mutation sets. In this experiment, similarity measures based on process structure, such as Dice's, Jaccard, and derivatives of these measures, show greater coefficient than measures based on values of process attributes. However, the Lev-TFIDF-JaccardAll measure considering process structure and attributes' values together shows reasonably better performances in these two experiments. For retrieving semantic process, we can think that it's better to consider diverse aspects of process similarity such as process structure and values of process attributes. We generate semantic process data and its dataset for retrieval experiment from MIT Process Handbook repository. We suggest imprecise query algorithms that expand retrieval results from exact matching engine such as SPARQL, and compare the retrieval performances of the similarity algorithms. For the limitations and future work, we need to perform experiments with other dataset from other domain. And, since there are many similarity values from diverse measures, we may find better ways to identify relevant processes by applying these values simultaneously.

• 한국전자통신학회논문지
• /
• 제13권3호
• /
• pp.579-586
• /
• 2018

빅데이터에 대한 관심이 증가하면서 데이터로부터 의미 있는 정보의 추출 및 예측은 중요한 연구분야가 되고 있다. 본 연구에서는 신약개발과정에서 필요한 후보약물의 약리적인 활성을 분석하기 위한 데이터를 획득하고 이를 기반으로 의미 있는 예측 분석을 하고자 한다. 신약개발과정에서 대사반응 된 신약후보물질의 약리적인 활성 연구는 신약개발 성공률을 높이기 위해 필요한 단계이다. 본 연구에서, 약용 후보물질의 체내 효소 반응 유무를 예측하기 위해, 유사도 모델들을 적용 분석하였다. 유사도 모델의 군집별 특성을 반영하여 13개의 모델을 선택하여 효소 반응 예측을 수행하였다. 이들 모델들을 민감도와 AUC를 기반으로 비교 평가하였다. 평가 모델들 중, 효소 사이의 반응성을 예측하는데 있어서 Simpson coefficient 모델이 가장 좋은 성능을 보였다. 분석된 유사도 모델 전체를 웹 서비스로 구축하였다. 제안된 모델은 반응정보의 추가에 동적으로 대응 할 수 있으며 신약개발시간 단축 및 비용 절감에 기여할 것으로 여겨진다.

• 산경연구논집
• /
• 제9권2호
• /
• pp.39-45
• /
• 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.

• 경영정보학연구
• /
• 제9권1호
• /
• pp.85-103
• /
• 2007

본 연구의 목적은 좀 더 정확한 고객 선호도 예측을 위한 협업 필터링 알고리즘의 예측 성능을 평가하기 위한 것이다. 고객 선호도 예측의 정확도를 비교하기 위하여 이웃 기반의 협업 필터링 알고리즘과 대응평균 알고리즘에 의한 고객 선호도 예측의 MAE를 비교하였다. 예측 알고리즘의 정확성을 분석하기 위하여 MovieLens 1 Million dataset을 이용하여 실험을 하였다. 각 예측 알고리즘에 사용된 유사도 가중치는 일반적으로 이용되는 피어슨 상관계수와 벡터 유사도를 이용하였으며 분석결과 대응평균 알고리즘의 예측 정확도가 이웃 기반의 협업 필터링 알고리즘의 예측 정확도 보다 우수한 것으로 나타났다. 두 알고리즘에 사용된 유사도 가중치인 피어슨 상관계수와 벡터 유사도는 두 고객이 특정 상품에 대하여 공통으로 평가한 선호도 평가치를 이용하여 계산된다. 이때 공통으로 평가한 선호도 평가치의 개수가 적으면 계산된 유사도 가중치가 과대 평가된다. 과대 평가된 유사도 가중치를 보정하여 고객 선호도 예측의 정확도를 높이기 위하여 기존의 연구에서 고려한 공통 평가 영화의 개수 보다 확대된 범위를 적용하였으며 각 예측 방법에 따라 서로 다른 개선 경향을 파악할 수 있었다.