• Tuberculosis and Respiratory Diseases
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• v.46 no.2
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• pp.204-214
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• 1999

Background: Resting pulmonary function tests(PFTs) are routinely used in the evaluation of pulmonary impairment/disability. But the significance of the cardiopulmonary exercise test(CPX) in the evaluation of pulmonary impairment is controvertible. Many experts believe that dyspnea, though a necessary part of the assessment, is not a reliable predictor of impairment. Nevertheless, oxygen requirements of an organism at rest are different from at activity or exercising, and a clear relationship between resting PFTs and exercise tolerance has not been established in patients with chronic pulmonary disease. As well, the relationship between resting PFTs and dyspnea is complex. To investigate the relationship of dyspnea, resting PFTs, and CPX, we evaluated the patients of stabilized chronic pulmonary disease with clinical dyspnea rating(baseline dyspnea index, BDI), resting PFTs, and CPX. Method: The 50 patients were divided into two groups: non-severe and severe group on basis of results of resting PFTs(by criteria of ATS), CPX(by criteria of ATS or Ortega), and dyspnea rating(by focal score of BDI). Groups were compared with respect to pulmonary function, indices of CPX, and dyspnea rating. Results: 1. According to the criteria of pulmonary impairment with resting PFTs, $VO_2$max, and focal score of BDI were significantly low in the severe group(p<0.01). According to the criteria of $VO_2$max(ml/kg/min) and $VO_2$max(%), the parameters of resting PFTs, except $FEV_1$ were not significantly different between non-severe and severe(p>0.05). According to focal score($FEV_1$(%), FVC(%), MW(%), $FEV_1/FVC$, and $VO_2$max were significantly lower in the severe group(p<0.01). However, in the more severe dyspneic group(focal score<5), only $VO_2$max(ml/kg/min) and $VO_2$max(%) were low(p<0.01). $FEV_1$(%) was correlated with $VO_2$max(%)(r=0.52;p<0.01), but not predictive of exercise performance. The focal score had the correlation with max WR(%) (r=0.55;p<0.01). Sensitivity and specificity analysis were utilized to compare the different criteria used to evaluate the severity of pulmonary impairment, revealed that the classification would be different according to the criteria used. And focal score for dyspnea showed similar sensitivity and specificity. Conclusion : According to these result, resting PFTs were not superior to rating of dyspnea in prediction of exercise performance in patients with chronic pulmonary diseases and less correlative with focal score for dyspnea than $VO_2$max and max WR. Therefore, if not contraindicated, CPX would be considered to evaluate the severity of pulmonary impairment in patients with chronic pulmonary diseases, including with severe resting PFTs. Current criteria used to evaluate the severity of impairment were insufficient in considering the degree of dyspnea, so new criteria, including the severity of dyspnea, may be necessary.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• The Korean Journal of Archival Studies
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• no.22
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• pp.157-199
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• 2009

The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.

• Journal of Gastric Cancer
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• v.6 no.1
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• pp.36-42
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• 2006

Purpose: The $p21^{Waf1/Cip1}$ protein Inhibits the cell cycle by Inhibiting the phosphorylation at the $G1{\rightarrow}S$ check point, and the $p27^{kip1}$ protein similarly performs the suppressor function by controlling the p27-mediated G1 arrest. In this study, we analysed the clinical status and survival rates in correlations with p21 and p27 expression patterns in gastric cancer. Materials and Methods: Between 1993 and 1997, 192 patients who underwent surgeries in Catholic Medical Center were analysed retrospectively in this study. Immunohistochemical staining was performed and if the nuclei of the tumor cells were stained, we assumed those as positive results. Statistical analysis was based on clinicopathological findings and differences in survival rates. Results: The expression rate of p27 was 28.1% and 15.6% in p21 each. The ratio of T1-2(80.0%) was significantly high in p21 (+), but the ratio of T3-4 (50.6%) was slightly high in p21 (-). There was no statistical significance regarding other factors. The results in p27 was not much different from expression rate of p21 in T-stage. In addition, p27 expression in diffuse type (91.3%) was higher than in intestinal type (62.7%) by Lauren's classification (P<0.05). Also, there was no statistical significance in other factors. In the correlation of p21 and p27, p27 was positive when p21 was positive (53.5%). Conversely, p27 was negative when p21 was negative (76.5%, p<0.05). In the p21 and p27 combination test, there was higher rate of T1-2 (87.5%) in p21 (+)/p27 (+), and higher rate of T3-4 (58.1%) in p21 (-)/p27 (-) (P<0.05). Results showed higher rate of intestinal type (100%) in p21 (+)/p27 (+), and diffuse type (87.0%) was dominant in p21 (-)/p27 (-) (P<0.05) by Lauren's classification. Moreover, there was no statistical significance in the 5-year survival rate in the expression of p21 and p27, and the 5-year survival rate was highest in the case of p21 (+)/p27 (+) without statistical significance. Conclusion: In our study, $p21^{Waf1/Cip1}\;and\;p27^{kip1}$ expressed similar patterns. The expression of $p21^{Waf1/Cip1}\;and\;p27^{kip1}$ affected the degree of invasiveness of the tumor, and. Combined examination result revealed the correlation of $p21^{Waf1/Cip1}\;and\;p27^{kip1}$ with Lauren's classification and depth of invasion of the tumor. However, we assumed that little difference between the survival rates depending on expression of $p21^{Waf1/Cip1}\;and\;p27^{kip1}$ has limited their value as predictable prognostic indicators.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Radiation Oncology Journal
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• v.13 no.4
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• pp.349-357
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• 1995

Purpose : To analyze survival rate and late rectal and bladder complication for patients with stage I and II carcinoma of uterine cervix treated by radiation alone or combined with chemotherapy Materials and Methods : Between November 1984 and December 1993, 127 patients with stage I and II carcinoma of uterine cervix treated by radiation alone or combined therapy of radiation and chemotherapy. Retrospective analysis for survival rate was carried out on eligible 107 patients and review for complication was possible in 91 patients. The median follow-up was 47 months (range 3-118) and the median age of patiens was 56 years (range 31-76). 26 patients were stage IB by FIGO classification, 40 were stage IIA and 41 were stage IIB. 86 cases were treated by radiation alone and 21 were treated by radiation and chemotherapy. 101 patients were treated with intracavitary radiation therapy (ICRT), of these, 80 were received low dose rate (LDR) ICRT and 21 were received high dose rate (HDR) ICRT. Of the patients who received LDR ICRT, 63 were treated by 1 intracavitary insertion and 17 were underwent 2 insertions And we evaluated the external radiation dose and midline shield. Results : Actuarial survival rate at 5 years was $92{\%}$ for stage IB, $75{\%}$ for stage IIA, $53{\%}$ for stage IIB and $69{\%}$ in all patients Grade 1 rectal complications were developed in 20 cases ($22{\%}$), grade 2 were in 22 cases ($24{\%}$). 22 cases ($24{\%}$) of grade 1 urinary complications and 17 cases ($19{\%}$) of grade 2 urinary complications were observed But no patient had severe complications that needed surgical management or admission care. Maximum bladder dose for the group of patients with urinary complications was higher than that for the patients without urinary complications (7608 cGy v 6960cGy. p<0.01) Maximum rectal dose for the group of patients with rectal complications was higher than that for the patients without rectal complications (7041cGy v 6269cGy, p<0.01). While there was no significant difference for survival rate or bladder complication incidence as a function of dose to whole pelvis, Grade 2 rectal complication incidence was significantly lower for the patients receiving less than 4500cGy ($6.3{\%}$ v $25.5{\%}$, p<0.05). There was no significant differance between HDR ICRT group and LDR ICRT group for survival rate according to stage, on the other hand complication incidence was higher in the HDR group than LDR group, This was maybe due to different prescription doses between HDR group and LDR group. Midline shield neither improved survival rate nor decreased complication rate. The number of insertion in LDR ICRT group did not affect on survival and compication rate. Conclusion : In stage I and II carcinoma of uterine cervix there was no significant differance for 5 year survival rate by radiation therapy technique. Rectal complication incidence was as a function of dose to whole pelvis and there were positive correlations of maximum dose of rectum and bladder and each complication incidence. So we recommand whole pelvis dose less than 4500cGy and maximum dose of rectum and bladder as low as possible.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.4
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• pp.10-20
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• 2014

This study was carried out for the purpose of analysis correlations between street furniture design elements and preference of street furniture. This research analyzed the various street furniture set on Ilsan new town street, which are rest, hygiene, light, information, sale, traffic, and landscape. This study has processed by analysing street furniture literature investigation and consideration of theory. First, for analysed effect of street furniture element, has been appear as element 'relaxation facilities', 'information facilities', landscape facilities' mainly effect on street. Specially, 'rest', 'landscape', 'information' in order had a major influence on scenery. Each kind of 'chair elements' in rest facilities, 'sign board' in information facilities, 'sculpture', 'fountain' in 'landscape facilities' has analyzed as the main elements in the landscape affinity property affecting factor. Second, the results of analyzed landscape elements (shape, colour, texture, scale) affect to the affinity of street furniture. chair which are included in rest facilities affect "texture", "form", "scale", "color" in the order of preference of the molding design elements that influence landscape. Particularly, showed statistically significant on 'colour' element affecting the landscape preference than the other three elements. It means as the chair element which is rest facilities mainly affect on preferences, rather than texture, form, scale, colour. Monument in the landscape associated with a preference 'colour', 'shape', 'texture' 'scale' and appears to be in order of impact so we could get the consequence like chair and rest facilities show different aspects of the respectively. It means, visual element which are colour and shape significantly impact on landscape preferences. Third, information facilities such as signboard formative elements of landscape design preferences and correlation with negative showed that the correlation. That mean if the sign board is very negative influence on landscape preferences and the correlations of the design formative elements appear in order of 'scale', 'colour', 'texture'. It also means that the 'scale' namely the size of advertising material and colour are adversely affected in terms of landscape. As these results, when design street furniture as the street scenery, facilities according to the kind of the shape element and need to focus on relative shape element according to the kind of facilities difference. Finally, so far as to clarify the street furniture, mainly 'function' and 'system' classification shows undesirable in outdoor scape. Thus, performed studies in relationship with landscape, classify 'kind of facilities' is more desirable than 'system'.

• Journal of Wetlands Research
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• v.14 no.1
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• pp.59-73
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• 2012

The importance of rice paddy wetland has been raised since the 10th Ramsar Convention in 2010. However, there is shortage of study on the evaluation of rice paddy wetland and also of the study on the effect of organic agriculture on the vegetation characteristics. Accordingly, this study examined the vegetation characteristics of organic rice paddy for the basic resources of evaluating value of rice paddy wetland. 6 places of organic rice paddy and conventional rice paddy were chosen as research targets. It analyzed the function of 'Floral Diversity and Wildlife Habitat' among the revised RAM, an existing wetland evaluation system. As to the factor affecting the analysis result, simple land-use result was proved to determine the evaluation. As a result of vegetation investigation total 176 taxa, 53 families, 146 generics, 148 species, 26 varieties and 1 forma. When the difference of appearance of life form between organic area and conventional area was examined, organic paddy had higher appearance of life form in Therophyte and Megaphanerophyte. For the distribution of Naturalized plants, organic rice paddy had lower naturalized rate and urbanization index than conventional rice paddy. As to the Pearson correlation analysis between growing condition and vegetation characteristics, variety of rice paddy vegetation showed it was not heavily influenced by the land use. However, the organic rice paddy area had more variety in vegetation than conventional rice paddy. There was about 1% correlation with types of Cyperaceae, which means that the classification group of Cyperaceae can be utilized in evaluating rice paddy wetland later on. It is determined that the wetland evaluation has been widely influenced by soil environment, water environment and surrounding natural and artificial landscape as well as vegetation characteristics. Accordingly, further research seems to be required with minute investigation to an extensive area.