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Study on Spring Cocoon Crops with the Leaf Produced in the Mulberry Field close to the Totacco Field (개량 Mulching 담배밭 부근뽕잎이 춘잠작에 미치는 영향에 관한 연구)

  • 이상풍;김정배;김계명;박광준
    • Journal of Sericultural and Entomological Science
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    • v.16 no.1
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    • pp.67-75
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    • 1974
  • The studies are to know how much cocoon crops is damaged by the stained leaf with nicotine produced from the tobacco field cultivated in mulching system in spring season and by residual nicotine in autumn season. Furthermore, the new knowledges are to make both industries keep up with their development. In spring season mulberry Held is located higher on the West-North of tobacco held below 20 degrees of slope and with 36 per cent of East-South wind and 18 per cent of South wind blowing from tobacco fold to the mulberry fold. In addition, silkworm larvae are fed with the mulberry leaf produced in the different plots placing by the different distances, l0m, 25m, 50m, 80m, and loom far from the tobacco Held as a control and it is also considered that narcotic larvae including the dead larvae are not observed. On the other hand, it is noted that better leaf quality and abundant growth of mulberry tree is produced from the mulberry fold closer to the tobacco field and with a low slope. 1) Maximum weight of larval body at the 5th stage is damaged by the stained leaf with the nicotine up to 25m far from the tobacco held. 2) The larvae fed with the mulberry leaf in mulberry Held up to 25m far from the tobacco fold produce small number of the fresh cocoons per 1 liter. 3) Low single cocoon weight and low cocoon shell weight are produced by the poison damaged larvae fed with the mulberry. leaf up to 25m far from the tobacco field and weight of cocoon shell is damaged higher than the single cocoon weight. It is resulted in low percentage of cocoon shell. 4) Cocoon yield including the double cocoon from 10,000 larvae is decreased by the larvae fed with the stained leaf in the mulberry fold up to 25m far from the tobacco fold and 19 per cent of cocoon yield is decreased with 2.4kg of cocoon yield in l0m plot and with 2.5kg of cocoon yield in 25m plot at the first season and at the 2nd season with 1.8kg o( cocoon yield in l0m plot and with 11.5kg of cocoon yield in 25m plot, 11 per cent and 9 per cent of cocoon yield including double cocoon from 10,000 larvae is decreased, as compared with the control, respectively. With these results, it is observed that nicotine damage is occurred to the silkworm larvae if the larvae are fed with the leaf in the mulberry Held within 25m-50m far from the tobacco field.

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Strategy for Store Management Using SOM Based on RFM (RFM 기반 SOM을 이용한 매장관리 전략 도출)

  • Jeong, Yoon Jeong;Choi, Il Young;Kim, Jae Kyeong;Choi, Ju Choel
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.93-112
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    • 2015
  • Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

The Clinical Features of Endobronchial Tuberculosis - A Retrospective Study on 201 Patients for 6 years (기관지결핵의 임상상-201예에 대한 후향적 고찰)

  • Lee, Jae Young;Kim, Chung Mi;Moon, Doo Seop;Lee, Chang Wha;Lee, Kyung Sang;Yang, Suck Chul;Yoon, Ho Joo;Shin, Dong Ho;Park, Sung Soo;Lee, Jung Hee
    • Tuberculosis and Respiratory Diseases
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    • v.43 no.5
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    • pp.671-682
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    • 1996
  • Background : Endobronchial tuberculosis is definded as tuberculous infection of the tracheobronchial tree with microbiological and histopathological evidence. Endobronchial tuberculosis has clinical significance due to its sequela of cicatrical stenosis which causes atelectasis, dyspnea and secondary pneumonia and may mimic bronchial asthma and pulmanary malignancy. Method : The authors carried out, retrospectively, a clinical study on 201 patients confirmed with endobronchial tuberculosis who visited the Department of Pulmonary Medicine at Hangyang University Hospital from January 1990 10 April 1996. The following results were obtained. Results: 1) Total 201 parients(l9.5%) were confirmed as endobronchial tuberculosis among 1031 patients who had been undergone flexible bronchofiberscopic examination. The number of male patients were 55 and that of female patients were 146. and the male to female ratio was 1 : 2.7. 2) The age distribution were as follows: there were 61(30.3%) cases in the third decade, 40 cases(19.9%) in the fourth decade, 27 cases(13.4%) in the sixth decade, 21 cases(10.4%) in the fifth decade, 19 cases(9.5%) in the age group between 15 and 19 years, 19 cases(9.5%) in the seventh decade, and 14 cases(7.0%) over 70 years, in decreasing order. 3) The most common symptom, in 192 cases, was cough 74.5%, followed by sputum 55.2%, dyspnea 28.6%, chest discomfort 19.8%, fever 17.2%, hemoptysis 11.5%, in decreasing order, and localized wheezing was heard in 15.6%. 4) In chest X-ray of 189 cases, consolidation was the most frequent finding in 67.7%, followed by collapse 43.9%. cavitary lesion 11.6%, pleural effusion 7.4%, in decreasing order, and there was no abnormal findings in 3.2%. 5) In the 76 pulmanary function tests, a normal pattern was found in 44.7%, restrictive pattern in 39.5 %, obstructive pattern in 11.8%, and combined pattern in 3.9%. 6) Among total 201 patients, bronchoscopy showed caseous pseudomembrane in 70 cases(34.8%), mucosal erythema and edema in 54 cases(26.9%), hyperplastic lesion in 52 cases(25.9%), fibrous s.enosis in 22 cases(10.9%), and erosion or ulcer in 3 cases(1.5%). 7) In total 201 cases, bronchial washing AFB stain was positive in 103 cases(51.2%), bronchial washing culture for tuberculous bacilli in 55 cases(27.4%). In the 99 bronchoscopic biopsies, AFB slain positive in 36.4%. granuloma without AFB stain positive in 13.1%, chronic inflammation only in 36.4%. and non diagnostic biopsy finding in 14.1%. Conclusions : Young female patients, whose cough resistant to genenal antitussive agents, should be evaluated for endobronchial tuberculosis, even with clear chest roentgenogram and negative sputum AFB stain. Furthermore, we would like to emphasize that the bronchoscopic approach is a substantially useful means of making a differential diagnosis of atelectasis in older patients of cancer age. At this time we have to make a standard endoscopic classification of endobronchial tuberculosis, and well designed prospective studies are required to elucidate the effect of combination therapy using antituberculous chemotherapy with steroids on bronchial stenosis in patients with endobronchial tuberculosis.

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Suggestion of Urban Regeneration Type Recommendation System Based on Local Characteristics Using Text Mining (텍스트 마이닝을 활용한 지역 특성 기반 도시재생 유형 추천 시스템 제안)

  • Kim, Ikjun;Lee, Junho;Kim, Hyomin;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.149-169
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    • 2020
  • "The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."