7 populations of rare endemic Berchemia berchemiaefolia were analysed using multivariate analysis for 9 characteristics of leaf morphology. The aim of this study was to examine geographic variation to support a genetic resource conservation plan of B. berchemiaefolia in Korea. In the morphological characters, nine characters of leaf were 10.25 cm (blade length), 4.10 cm (maximum width), 2.52 (blade length/maximum width), 3.22 cm (upper 1/3 width), 3.42 cm (lower 1/3 width), 0.95 (upper 1/3 width/lower 1/3 width), 1.24 cm (petiole length), 8.91 (blade length/petiole length), 8.16ea (vein number), respectively. Nested anova showed that were statistically significant differences among populations as well as among individuals within populations in all 9 quantitative characters. In 7 of 9 characters, variance components among individuals within populations were higher than those among populations. Cluster analysis using complete linkage method showed two groups (Chungbuk and Gyeongbuk districts) to Euclidean distance 1.2. Among principal components, primary 3 principal components appeared to be major variables because of the loading contribution of 87.3%. The first contribution was blade length, blade length/maximum width and blade length/petiole length; the second one was maximum width, upper 1/3 width and lower 1/3 width; the third one was petiole length, respectively.
We have examined the correlation between the physicochemical and microbiological environment variables for the different layers of oak forest soil in Mt. Gyeryong, Korea. The result shows that there is a high correlation in the environment variables between the soil parameters of the fermented (F) layer and humus (H) layer. In particular, the pH level in the F layer shows a high correlation with C and N, while the various organic acids of the H layer turns out to be closely correlated with soil bacteria density. As we evaluated phylogenetic characteristics of bacterial populations by DGGE analysis with DNA extracted. Total of 175 bands including 43 bands from litter (L) layer, 42 bands from F layer, 43 bands from H layer and 47 bands from rhizosphere (A) layer were selected as the major DGGE band of oak forest soil. Based on the 16S rRNA gene sequences, 175 DGGE bands were classified into 32 orders in 7 phylum. The heat map was analyzed in order to compare the quantity of the base sequences of each order and based on the clustering of the different layers of oak forest soil, the result confirms that the F layer and H layer belong to a different cluster from that of L layer and A layer. Furthermore, it also showed that approximately 50% of the total microbial population in different layers is ${\alpha}$-proteobacteria, which indicates that they belong to the dominant system group. In particular, Rhizobiales, Burkholderiales and Actinobacteriales were observed in all the seasons and layers of oak forest soil, which confirms that they are the indigenous soil bacterial community in oak forest soil.
Thirty-six plots (each size 100m2) have been set up and surveyed to investigate the plant community structure and the ecological density of Pinus densiflora for. eracta(Chunyang-type) community in Seobyeok-ri, Chungyang-myeon, bonghwa-gun, Kyeongsangbuk-do. Four communities, Community I (large DBH class), Community II (large DBH class), Community III (middle DBH class), Community IV(small DBH class), were classified into by mean DBH and mean height. Pinus densiflora for. eracta dominate in canopy layer, Fraxinus sieboldiana and Quercus mongolica dominate in understory layer, Rhododendron Schlippenbachii and R. mucronulatum dominate in shrub layer. It turned out that thefour communiteis had low species diversity(0.4320~0.9487; unit: 400$m^2$) and high similarity. By the result of ecological density analysis. the mean basal area was proportionated to mean DBH (cm) size. By the result of simple regression analysis between mean DBH(cm), mean distance(m), and the number of individual were as follow: Ecological distance(m) = 0.0934$\times$ DBH(cm) +0.6117, Number of individual=242.47$\times$ DBH(cm)$^{-1.009}$, Ecological distance=9.643$\times$No. of individua $l^{-0.7016}$. In addition to four communities were suitable to the growth of Tricholoma matsutake because average species were about 30~50 years old, litter layer was 0.5~2.5cm and the ratio of coverage shrub was 20% .
This study was carried out to investigate soil properties, ordination, and vegetation of a forest wetland in Jangdo, Sinan-Gun. Peculiar species such as Epilobium pyrricholophum and Lycopus ramosissim us were found in the forest wetland of Jangdo, and Hosta yingeri and Carpinus turczaninovii for coreana that are an endemic species of Korea were also found. The vascular plants of 40 families 62 genera 57 species 9 varieties 1 form, total 67 taxa were accounted for. The communities were classified as Salix koreensis-Isachne globosa community, Isachne globosa community, and Miscathus sinensis var purpurascens community. Soil organic matter, total nitrogen, available phosphorous concentrations, and cation exchange capacity each ranged from 20.6 to 72.4%, 0.74 to 2.13%, 33.3 to 114.6 ppm, and 25.5 to 94.3 me/100g, respectively. Soil pH ranged from 5.10 to 5.42. Soil texture was clay loam. Results of the correlation between Jangdo forest community and environmental factor are as follows; Soil pH was the most effective factor for plant community distribution. The Salix koreensis-Isachne globosa community was found where it had the highest soil organic matter, nitrogen, and exchangeable Na, Ca, Mg concentration, ana CEC among the three communities. Miscathus sinensis var. purpurascens community was found where it had the lowest soil organic matter, nitrogen, and exchangeable Na, Ca, Mg concentration, and CEC among the three plant communities.
In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.
The main objective of this study was to analyse polycyclic aromatic hydrocarbons in surface sediments obtained from near Nakdong estuary, and to estimate ecological risks of PAHs using PAHs concentrations. The main constituents of sediments were $SiO_2$, $Al_2O_3$, CaO, $Fe_2O_3$, and ignition loss of sediments ranged from 2.97% and 8.39%. Total concentrations of PAHs ranged from $128.4ng\;g^{-1}$ and $507.4ng\;g^{-1}$, and the major PAHs were 2 ring and 4 ring aromatic hydrocarbons. Each concentrations of PAHs are all below effect range low, which indicated that each PAHs in 8 studying sites show low ecological risk. From M-ERM-Q analyses, M-ERM-Q values of 8 studying sites are below 0.1 indicating low ecological risk. From source apportionment analyses, PAHs come from grass, wood, charcoal combustion for N-1 and N-7, petroleum combustion for N-5 and N-6, petroleum pollution for N-2, N-3, N-4, N-8.
Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.
The authors developed 28 needs assessment tools for integrated assessment centered on needs, which is the core element in care management for the elderly in home. Also, the authors collected the assessment data of 676 elderly persons in home from 120 centers under the Korea Association of Senior Welfare Centers by using the needs assessment tools, and finally developed needs extraction algorithm through decision tree analysis in data mining to identify their actual needs and provide social welfare service suitable for such needs. The needs extraction algorithm for 28 needs of the elderly in home are summarized in
. The Need No. 8 "Having need of help in going out" of the decision-making model, for example, was divided into 80.3% of asking for help and 11.4% not asking for help with Appeal No. 23 as a major variable. The need increased by 87.9% when the elderly appealed for help to go out and they had a caregiver but decreased by 47.4% when they had no caregiver. When the elderly asked for help in going out, they had a caregiver, and they needed complete help in cleaning, their need of help in going out was shown as 94.2%. However, seen from their answer that they needed complete help in bathing of ADL even if they did not ask for help in going out, it was found that the need of help in going out sharply increased from 11.4% to 80.0%. On the other hand, when they needed partial help or self-supported in bathing, the potential for them to be classified as asking for help in going out was shown to be low as 7.7%. In the said decision-making model, the number of cases for parent node and child node was designated as 50 and 25, respectively, with level 5 of the maximum tree depth as stopping rule. By this, it was shown that their decision-making was found to be effective as 182.13% for the need "Having need of help in going out". The algorithm presented in this study can be useful as systematic and scientific fundamental data in assessment of needs of the elderly in home.
This study is to establish a management method for conservation through comparison and analysis on vegetation structures of Pinus densiflora forest around Beopjusa area for past 17-year. The spatial range of the study was $3.6km^2$ from maintenance office to Beopjusa area. The analysis results of the actual vegetation showed that the ratio of vegetation were composed of 64.7% of Pinus densiflora forest, 3.2% of mixed forest of P. densiflora and deciduous broadleaf trees and 5.9% of deciduous broadleaf tree community out of overall area, 360ha. The type of P. densiflora forest were categorized into four communities; community having high potential of succession, community having low potential of it, the community being in the process of succession and community being in the process of natural selection. The succession tendency was in order of the community having low potential of succession(P. densiflora forest), having high potential of it(P. densiflora forest which is deciduous broadleaf trees are dominating in sub-canopy layer), being in the process of succession(P. densiflora-Prunus sargentii and P. densiflora-Quercus serrata community) and being in the process of natural selection(Q. serrata-P. densiflora and Q. aliena-P. densiflora community). In terms of vegetation management, P. densiflora forest having high potential of succession was needed to remove deciduous broadleaf trees in the sub-canopy layer and the community being in the process of succession was required to be pruning the branch in the canopy layer. Lastly, the community being in the process of natural selection was suggested to let it be in succession, since it is hard to be in the status of P. densiflora Forest.
Kim, Hyun-Ji;Jeong, Hye-Ran;Ku, Ja-Jung;Choi, Kyung;Park, Kwang-Woo;Cho, Do-Soon
Korean Journal of Environmental Biology
/
v.30
no.2
/
pp.90-97
/
2012
Environmental characteristics and vegetation of the natural habitats of Eranthis byunsanensis B.Y. Sun were investigated in order to provide the basic data for conservation, restoration, and utilization of this Korean endemic plant. This study was conducted in Anyang, Byeonsan, Geoje, Gyeongju, Jeju, Ulsan and Yeosu. E. byunsanensis was distributed around the altitudes of 84~585 m with a slope degree of $10{\sim}20^{\circ}$, and mostly formed discontinuous populations in north-east part of valleys. Soil analysis showed the mean organic matter of 9.6% and a slightly acidic pH (mean pH of 4.9). The mean gravimetric water content was 16.5%. Correlation coefficients between environmental factors and community characteristics suggested that there was a positive correlation between slope degree and soil water content, between slope degree and soil pH, between soil organic matter and importance value, and between species richness or evenness and species diversity. The vascular plants from 59 quadrats of 7 habitats were identified into 144 taxa. A few species were dominants and similarly distributed in Byeonsan, Jeju, Ulsan and Yeosu. The highest species diversity was found in Geoje (1.43), while Anyang showed the lowest (0.87). Species evenness of Gyeongju and Jeju was bigger than 0.8, but that of Geoje was the lowest (0.59). Dominant species of woody plants in and around the 59 plots were represented by high frequency of Acer pictum subsp. mono, Carpinus cordata, Lindera obtusiloba, and Carpinus laxiflora. The results of this study can provide useful data for conservation and restoration of natural habitats of Korean endemic Eranthis byunsanensis and for the development and growth of this species for ornamental purposes.
본 웹사이트에 게시된 이메일 주소가 전자우편 수집 프로그램이나
그 밖의 기술적 장치를 이용하여 무단으로 수집되는 것을 거부하며,
이를 위반시 정보통신망법에 의해 형사 처벌됨을 유념하시기 바랍니다.
[게시일 2004년 10월 1일]
이용약관
제 1 장 총칙
제 1 조 (목적)
이 이용약관은 KoreaScience 홈페이지(이하 “당 사이트”)에서 제공하는 인터넷 서비스(이하 '서비스')의 가입조건 및 이용에 관한 제반 사항과 기타 필요한 사항을 구체적으로 규정함을 목적으로 합니다.
제 2 조 (용어의 정의)
① "이용자"라 함은 당 사이트에 접속하여 이 약관에 따라 당 사이트가 제공하는 서비스를 받는 회원 및 비회원을
말합니다.
② "회원"이라 함은 서비스를 이용하기 위하여 당 사이트에 개인정보를 제공하여 아이디(ID)와 비밀번호를 부여
받은 자를 말합니다.
③ "회원 아이디(ID)"라 함은 회원의 식별 및 서비스 이용을 위하여 자신이 선정한 문자 및 숫자의 조합을
말합니다.
④ "비밀번호(패스워드)"라 함은 회원이 자신의 비밀보호를 위하여 선정한 문자 및 숫자의 조합을 말합니다.
제 3 조 (이용약관의 효력 및 변경)
① 이 약관은 당 사이트에 게시하거나 기타의 방법으로 회원에게 공지함으로써 효력이 발생합니다.
② 당 사이트는 이 약관을 개정할 경우에 적용일자 및 개정사유를 명시하여 현행 약관과 함께 당 사이트의
초기화면에 그 적용일자 7일 이전부터 적용일자 전일까지 공지합니다. 다만, 회원에게 불리하게 약관내용을
변경하는 경우에는 최소한 30일 이상의 사전 유예기간을 두고 공지합니다. 이 경우 당 사이트는 개정 전
내용과 개정 후 내용을 명확하게 비교하여 이용자가 알기 쉽도록 표시합니다.
제 4 조(약관 외 준칙)
① 이 약관은 당 사이트가 제공하는 서비스에 관한 이용안내와 함께 적용됩니다.
② 이 약관에 명시되지 아니한 사항은 관계법령의 규정이 적용됩니다.
제 2 장 이용계약의 체결
제 5 조 (이용계약의 성립 등)
① 이용계약은 이용고객이 당 사이트가 정한 약관에 「동의합니다」를 선택하고, 당 사이트가 정한
온라인신청양식을 작성하여 서비스 이용을 신청한 후, 당 사이트가 이를 승낙함으로써 성립합니다.
② 제1항의 승낙은 당 사이트가 제공하는 과학기술정보검색, 맞춤정보, 서지정보 등 다른 서비스의 이용승낙을
포함합니다.
제 6 조 (회원가입)
서비스를 이용하고자 하는 고객은 당 사이트에서 정한 회원가입양식에 개인정보를 기재하여 가입을 하여야 합니다.
제 7 조 (개인정보의 보호 및 사용)
당 사이트는 관계법령이 정하는 바에 따라 회원 등록정보를 포함한 회원의 개인정보를 보호하기 위해 노력합니다. 회원 개인정보의 보호 및 사용에 대해서는 관련법령 및 당 사이트의 개인정보 보호정책이 적용됩니다.
제 8 조 (이용 신청의 승낙과 제한)
① 당 사이트는 제6조의 규정에 의한 이용신청고객에 대하여 서비스 이용을 승낙합니다.
② 당 사이트는 아래사항에 해당하는 경우에 대해서 승낙하지 아니 합니다.
- 이용계약 신청서의 내용을 허위로 기재한 경우
- 기타 규정한 제반사항을 위반하며 신청하는 경우
제 9 조 (회원 ID 부여 및 변경 등)
① 당 사이트는 이용고객에 대하여 약관에 정하는 바에 따라 자신이 선정한 회원 ID를 부여합니다.
② 회원 ID는 원칙적으로 변경이 불가하며 부득이한 사유로 인하여 변경 하고자 하는 경우에는 해당 ID를
해지하고 재가입해야 합니다.
③ 기타 회원 개인정보 관리 및 변경 등에 관한 사항은 서비스별 안내에 정하는 바에 의합니다.
제 3 장 계약 당사자의 의무
제 10 조 (KISTI의 의무)
① 당 사이트는 이용고객이 희망한 서비스 제공 개시일에 특별한 사정이 없는 한 서비스를 이용할 수 있도록
하여야 합니다.
② 당 사이트는 개인정보 보호를 위해 보안시스템을 구축하며 개인정보 보호정책을 공시하고 준수합니다.
③ 당 사이트는 회원으로부터 제기되는 의견이나 불만이 정당하다고 객관적으로 인정될 경우에는 적절한 절차를
거쳐 즉시 처리하여야 합니다. 다만, 즉시 처리가 곤란한 경우는 회원에게 그 사유와 처리일정을 통보하여야
합니다.
제 11 조 (회원의 의무)
① 이용자는 회원가입 신청 또는 회원정보 변경 시 실명으로 모든 사항을 사실에 근거하여 작성하여야 하며,
허위 또는 타인의 정보를 등록할 경우 일체의 권리를 주장할 수 없습니다.
② 당 사이트가 관계법령 및 개인정보 보호정책에 의거하여 그 책임을 지는 경우를 제외하고 회원에게 부여된
ID의 비밀번호 관리소홀, 부정사용에 의하여 발생하는 모든 결과에 대한 책임은 회원에게 있습니다.
③ 회원은 당 사이트 및 제 3자의 지적 재산권을 침해해서는 안 됩니다.
제 4 장 서비스의 이용
제 12 조 (서비스 이용 시간)
① 서비스 이용은 당 사이트의 업무상 또는 기술상 특별한 지장이 없는 한 연중무휴, 1일 24시간 운영을
원칙으로 합니다. 단, 당 사이트는 시스템 정기점검, 증설 및 교체를 위해 당 사이트가 정한 날이나 시간에
서비스를 일시 중단할 수 있으며, 예정되어 있는 작업으로 인한 서비스 일시중단은 당 사이트 홈페이지를
통해 사전에 공지합니다.
② 당 사이트는 서비스를 특정범위로 분할하여 각 범위별로 이용가능시간을 별도로 지정할 수 있습니다. 다만
이 경우 그 내용을 공지합니다.
제 13 조 (홈페이지 저작권)
① NDSL에서 제공하는 모든 저작물의 저작권은 원저작자에게 있으며, KISTI는 복제/배포/전송권을 확보하고
있습니다.
② NDSL에서 제공하는 콘텐츠를 상업적 및 기타 영리목적으로 복제/배포/전송할 경우 사전에 KISTI의 허락을
받아야 합니다.
③ NDSL에서 제공하는 콘텐츠를 보도, 비평, 교육, 연구 등을 위하여 정당한 범위 안에서 공정한 관행에
합치되게 인용할 수 있습니다.
④ NDSL에서 제공하는 콘텐츠를 무단 복제, 전송, 배포 기타 저작권법에 위반되는 방법으로 이용할 경우
저작권법 제136조에 따라 5년 이하의 징역 또는 5천만 원 이하의 벌금에 처해질 수 있습니다.
제 14 조 (유료서비스)
① 당 사이트 및 협력기관이 정한 유료서비스(원문복사 등)는 별도로 정해진 바에 따르며, 변경사항은 시행 전에
당 사이트 홈페이지를 통하여 회원에게 공지합니다.
② 유료서비스를 이용하려는 회원은 정해진 요금체계에 따라 요금을 납부해야 합니다.
제 5 장 계약 해지 및 이용 제한
제 15 조 (계약 해지)
회원이 이용계약을 해지하고자 하는 때에는 [가입해지] 메뉴를 이용해 직접 해지해야 합니다.
제 16 조 (서비스 이용제한)
① 당 사이트는 회원이 서비스 이용내용에 있어서 본 약관 제 11조 내용을 위반하거나, 다음 각 호에 해당하는
경우 서비스 이용을 제한할 수 있습니다.
- 2년 이상 서비스를 이용한 적이 없는 경우
- 기타 정상적인 서비스 운영에 방해가 될 경우
② 상기 이용제한 규정에 따라 서비스를 이용하는 회원에게 서비스 이용에 대하여 별도 공지 없이 서비스 이용의
일시정지, 이용계약 해지 할 수 있습니다.
제 17 조 (전자우편주소 수집 금지)
회원은 전자우편주소 추출기 등을 이용하여 전자우편주소를 수집 또는 제3자에게 제공할 수 없습니다.
제 6 장 손해배상 및 기타사항
제 18 조 (손해배상)
당 사이트는 무료로 제공되는 서비스와 관련하여 회원에게 어떠한 손해가 발생하더라도 당 사이트가 고의 또는 과실로 인한 손해발생을 제외하고는 이에 대하여 책임을 부담하지 아니합니다.
제 19 조 (관할 법원)
서비스 이용으로 발생한 분쟁에 대해 소송이 제기되는 경우 민사 소송법상의 관할 법원에 제기합니다.
[부 칙]
1. (시행일) 이 약관은 2016년 9월 5일부터 적용되며, 종전 약관은 본 약관으로 대체되며, 개정된 약관의 적용일 이전 가입자도 개정된 약관의 적용을 받습니다.