• Korean Journal of Plant Resources
• /
• v.24 no.6
• /
• pp.675-687
• /
• 2011

Mulberries have importance in the sericulture industry as food for Bombyx mori, silkworm reared for its silk. Korean Morus alba have many cultivars and, for the protection of these cultivars and for utilization in plant-breeding programs, genetic information and the diversity among cultivars are essential. This study with 14 mulberry genotypes was undertaken using RAPD and ISSR fingerprinting to discover the genetic divergences between cultivars. Polymorphism rate among the cultivars produced by RAPD primer was found to be 64.48% and 66.29% relative to ISSR primer. The genetic relationships among the cultivars were identified using a dendrogram constructed with the UPGMA clustering method. Nei's method was used to calculate the genetic dissimilarity coefficients between each pair of genotypes, and the highest dissimilarity coefficient of 0.246 was exhibited between Suwon and Hwanggum cultivars. To determine the efficiency of each primer, a polymorphic index was calculated, and the robustness of the dendrogram was checked using cophenetic correlation coefficient. The results of this study can be utilized for the improvement of mulberry varieties in plant-breeding programs.

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.263-270
• /
• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of Korean Society of Forest Science
• /
• v.109 no.4
• /
• pp.421-428
• /
• 2020

Tamarind (Tamarindus indica L.) is one of the multipurpose tree species distributed in the tropical and sub-tropical climates. It is an important fruit yielding tree that supports the livelihood and has high social and cultural values for rural communities. The vegetative, reproductive, qualitative, and quantitative traits of tamarind vary widely. Characterization of phenotypic and genetic structure is essential for the selection of suitable accessions for sustainable cultivation and conservation. This study aimedto examine the genetic relationship among the collected accessions of sweet, red, and sour tamarind by using Random Amplified Polymorphic DNA (RAPD) primers. Nine accessions were collected from germplasm gene banks and subjected to marker analysis. Fifteen highly polymorphic primers generated a total of 169 fragments, out of which 138 bands were polymorphic. The polymorphic information content of RAPD markers varied from 0.10 to 0.44, and the Jaccard's similarity coefficient values ranged from 0.37 to 0.70. The genetic clustering showed a sizable genetic variation in the tamarind accessions at the molecular level. The molecular and biochemical variations in the selected accessions are very important for developing varieties with high sugar, anthocyanin, and acidity traits in the ongoing tamarind improvement program.

• Journal of the Korean Society of Radiology
• /
• v.85 no.2
• /
• pp.381-393
• /
• 2024

Purpose Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ² distance measure and Ward's method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

• Journal of Radiation Industry
• /
• v.6 no.1
• /
• pp.23-29
• /
• 2012

In this study, we investigated the genetic variation in the general of monocot model plant (rice) in response to various ionizing irradiations including gamma-ray, ion beam and cosmic-ray. The non-irradiated and three irradiated (200 Gy of gamma-ray and 40 Gy of ion beam and cosmic-ray) plants were analyzed by AFLP technique using capillary electrophoresis with ABI3130xl genetic analyzer. The 29 primer combinations tested produced polymorphism results showing a total of 2,238 bands with fragments sizes ranged from 30 bp to 600 bp. The number of polymorphism generated by each primer combinations was varied significantly, ranging from 2 (M-CAC/E-ACG) to 158 (M-CAT/E-AGG) with an average of 77 bands. Polymorphic peaks were detected as 1,269 with an average of 44 per primer combinations. By UPGMA (Unweighted Pair Group Method using Arithmetic clustering) analysis method, the clusters were divided into non-irradiated sample and three irradiated samples at a similarity coefficient of 0.41 and three irradiation samples was subdivided into cosmic-ray and two irradiation samples (200 Gy of gamma-ray and 40 Gy of ion beam) at similarity coefficient of 0.48. Similarity coefficient values ranged from 0.41 to 0.55.

• The Plant Pathology Journal
• /
• v.23 no.2
• /
• pp.45-50
• /
• 2007

Genetic diversity among selected isolates of Macrophomina phaseolina, a causal agent of charcoal rot (stalk rot) disease in sorghum was studied using PCR-RAPD markers. A set of ten isolates, from ten different rabi sorghum genotypes representing two traditional sorghum growing situations viz., Dharwad- a transitional high rainfall region and Bijapur- a semi-arid low rainfall region in South India. From a set of 40 random primers tested, amplicon profiles of 15 were reproducible. A total of 149 amplicon levels, with an average of 9.9 bands per primer, were available for analysis, of which 148 were polymorphic (99.3%). It was possible to discriminate all the isolates with any of the 15 primers employed. UPGMA clustering of data indicated that the isolates shared varied levels of genetic similarity within a range of 0.14 to 0.72 similarity coefficient index and it was suggestive that grouping of isolates was not related to sampling location in anyway. A high level of genetic heterogeneity of 0.28 was recorded among the isolates.

• Korean Management Science Review
• /
• v.32 no.4
• /
• pp.81-96
• /
• 2015

This paper models knowledge diffusion on an inter-organizational network. Based on literatures related to knowledge diffusion, the model considers critical factors that affect diffusion behavior including nodal property, relational property, and environmental property. We examine the relationships among network structure, knowledge search, and diffusion performance. Through a massive simulation runs based on the agent-based model, we find that the average path length of a network decreases a firm's cumulative knowledge stock, whereas the clustering coefficient of a firm has no significant relationship with the firm's knowledge. We also find that there is an interaction effect of network structure and the range of knowledge search on knowledge diffusion. Specifically, in a network of a larger average path length (APL) the marginal effect of search conduct is significantly greater than in that of a smaller APL.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06e
• /
• pp.369-372
• /
• 1998

본 논문은 어휘독립(Vocabulary-Independent) 환경에서 별도의 훈련과정 없이 인식대상 어휘를 추가 및 변경할 수 있는 가변어휘(Variable Vocabulary) 음성인식에 관한 연구를 다룬다. 가변어휘 인식은 처음에 대용량 음성 데이터베이스(DB)로 음소모델을 훈련하고 인식대상 어휘가 결정되면 발음사전에 의거하여 음소모델을 연결함으로써 별도의 훈련과정 없이 인식대상 어휘를 변경 및 추가할 수 있다. 문맥 종속형(Context-Dependent) 음소 모델인 triphone을 사용하여 인식실험을 하였고, 인식성능의 비교를 위해 어휘종속 모델을 별도로 구성하여 인식실험을 하였다. Unseen triphone 문제와 훈련 DB의 부족으로 인한 모델 파라메터의 신뢰성 저하를 방지하기 위해 state-tying 방법 중 음성학적 지식에 기반을 둔 tree-based clustering(TBC) 기법[1]을 도입하였다. Mel Frequency Cepstrum Coefficient(MFCC)와 대수에너지에 기반을 둔 3 가지 음성특징 벡터를 사용하여 인식 실험을 병행하였고, 연속 확률분포를 가지는 Hidden Markov Model(HMM) 기반의 고립단어 인식시스템을 구현하였다. 인식 실험에는 22 개 부서명 DB[3]를 사용하였다. 실험결과 어휘독립 환경에서 최고 98.4%의 인식률이 얻어졌으며, 어휘종속 환경에서의 인식률 99.7%에 근접한 성능을 보였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10d
• /
• pp.135-139
• /
• 2006

Today's social networking services have tens of millions of users, and are growing fast. Their sheer size poses a significant challenge in capturing and analyzing their topological characteristics. Snowball sampling is a popular method to crawl and sample network topologies, but requires a high sampling ratio for accurate estimation of certain metrics. In this work, we evaluate how close topological characteristics of snowball sampled networks are to the complete network. Instead of using a synthetically generated topology, we use the complete topology of Cyworld ilchon network. The goal of this work is to determine sampling ratios for accurate estimation of key topological characteristics, such as the degree distribution, the degree correlation, the assortativity, and the clustering coefficient.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.10d
• /
• pp.331-333
• /
• 2002

협력적 여과 방법은 사용자의 평가 데이터를 이용하므로, 항상 초기 평가 문제(First-Rating Problem)와 희박성 문제(Sparsity Problem)가 발생한다. 최근 이러한 문제를 해결하기 위해 많은 연구가 진행되고 있는 데, 본 논문에서는 연관 규칙을 이용하여 이러한 문제를 해결하고자 한다. 사용자의 평가 데이터를 이용하여 아이템간의 연관성을 산출하고, 연관성이 높은 아이템끼리 군집한다. 사용자와 군집간에 피어슨 상관 계수(Pearson Correlation Coefficient)를 이용하여 가중치를 구하고, 이것으로 선호도를 예측한다. 이러한 방법을 기존의 협력적 여과 방법과 함께 속성에 의한 군집 방식과 비교 평가하였다. 또한, 효율적인 군집을 위한 Split Cluster Method를 제안하고, 기존의 트리 방식의 군집과 비교 평가하였다.