Semantic Access Path Generation in Web Information Management (웹 정보의 관리에 있어서 의미적 접근경로의 형성에 관한 연구)
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- Journal of the Korea Society of Computer and Information
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- v.8 no.2
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- pp.51-56
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- 2003
The structuring of Web information supports a strong user side viewpoint that a user wants his/her own needs on snooping a specific Web site. Not only the depth first algorithm or the breadth-first algorithm, but also the Web information is abstracted to a hierarchical structure. A prototype system is suggested in order to visualize and to represent a semantic significance. As a motivating example, the Web test site is suggested and analyzed with respect to several keywords. As a future research, the Web site model should be extended to the whole WWW and an accurate assessment function needs to be devised by which several suggested models should be evaluated.
In this study, elementary school students of both urban and rural areas as its subjects were asked to draw 'A beautiful landscape' by employing the perspective representation technique, i. e., the Perception Map, and to write down the elements comprising 'A beautiful landscape' in the questionnaire sheets. By doing so, an attempt was made 1) to analyze whether there are differences in perceiving 'A beautiful landscape' according to the differences of the environment in which they were brought up ; and, if there are differences. 2) to identify them ; and based on that , 3) to present basic data for evaluation on landscape, on its preference analysis and for Park Planning. The summary of this study is as follows ; 1) The main elements, elementary school students think, comprising 'A beautiful landscape' are 25 ones such as Sky(7), Sea(2), Water(2), Topography(5), Plants(5), Animals(3), School(1), Rural village(1). The natural elements showing a difference are ; Water fall in urban areas and School landscape in rural areas ; the artificial elements are ; City groups(Structures, Facilities, Necessities, Transportation means and Space) in urban areas and School groups in rural areas. Especially, in case of rural area children, they regard 'Trees' as an essential element to be 'A beautiful landscape' comparing to those in urban areas. 2) According to the analysis result on the correlation between the elements comprising a beautiful rural landscape and a beautiful ruban landscape, the correlation between boys and girls is high, showing the same trend with any difference. In comparison of urban areas with rural areas, there is no difference between natural elements, but in artificial elements(7 groups without family) the correlation is quite low, showing that all comprising elements are not the same between rural schools and cities, between schools within the same areas, and between schools of different areas. 3) In identifying the names of elements comprising 'A beautiful landscape', Back-Du Mountain and Sorak Mountain are shown the highest frequency in the category of mountains. In the names of trees and flowers, the elementary school children are thought to consider the kinds of trees and flowers they can see always at hand, i. e., those in their school ground where they spend most of their day time. 4) In the analysis of the numbers of comprising elements according to the responses in the questionnaire sheets and in the Perception Map, 'less than 10' is the most frequently counted number of comprising elements by individual students regardless of rural and urban differences. When the total frequency is divided by the number of students, the mean score is 6-7 without any differences between rural and urban areas, implying that there are no differences in the expression ability between urban and rural schools. 5) According to the result of classyfying and analysizing the landscape appeared on the Perception Map by similar elements and by similar scenes, 'A beautiful landscape' thought by elementary school children is defined not as a standardized form but as 11 types such as the landscape of fields, the landscape of a sea, the landscape of a rural village, a type where elements are assembled, the landscape of cities, the landscape of a school, the landscape coming out of a imagination, and other landscape. Both rural and urban children all consider the landscape of mountains and field and the landscape where several elements are assembled as a commonly beautiful one. Among the landscapes showing rural and urban differences, it can be analyzed that urban children regard the landscapes of cities, imagination, and waterfalls as something characteristic, while rural children regard the landscape of schools and rural villages as something characteristic.
With stabilization of the recent multi-GNSS infrastructure, and as multi-GNSS has been proven to be effective in improving the accuracy of the positioning performance in various industrial sectors. In this study, in view that SF(Single frequency) GNSS receivers are widely used due to the low costs, evaluate effectiveness of SF Real Time Point Positioning(SF-RT-PP) based on four multi-GNSS surveying methods with RTCM-SSR correction streams in static and kinematic modes, and also derive response challenges. Results of applying SSR correction streams, CNES presented good results compared to other SSR streams in 2D coordinate. Looking at the results of the SF-RT-PP surveying using SF signals from multi-GNSS, were able to identify the common cause of large deviations in the altitude components, as well as confirm the importance of signal bias correction according to combinations of different types of satellite signals and ionospheric delay compensation algorithm using undifferenced and uncombined observations. In addition, confirmed that the improvement of the infrastructure of Multi-GNSS allows SF-RT-SPP surveying with only one of the four GNSS satellites. In particular, in the case of code-based SF-RT-SPP measurements using SF signals from GPS satellites only, the difference in the application effect between broadcast ephemeris and SSR correction for satellite orbits/clocks was small, but in the case of ionospheric delay compensation, the use of SBAS correction information provided more than twice the accuracy compared to result of the Klobuchar model. With GPS and GLONASS, both the BDS and GALILEO constellations will be fully deployed in the end of 2020, and the greater benefits from the multi-GNSS integration can be expected. Specially, If RT-ionospheric correction services reflecting regional characteristics and SSR correction information reflecting atmospheric characteristics are carried out in real-time, expected that the utilization of SF-RT-PPP survey technology by multi-GNSS and various demands will be created in various industrial sectors.
The study on Musan twelve peaks of Yongho garden in Jinju, Gyeongnam was anticipated to provide data and implication for reproducing similar spaces and modern changes in terms of design factor since it is the prototype of traditional mount for overcoming monotonous geographical features and intriguing changes and interests. The study analyzed and interpreted the symbolism of twelve peaks, principles of space composition and function and effect of visual construction that were pursued by the builder in terms of landscape view, which results are as following. The center of Yongho garden, Yonghoji(龍虎池) is a typical man-made pond for a supportive feng shui feature. It is a supporting equipment to complete the state of feng shui, and the result of strengthening the completion through the connection with the dragon-related name of the place. The shape of Musan twelve peaks looks like an oval form of Geumseongsan(金星山), 2~3.5m in height and 6~12m in diameter. Peaks are estimated as 1.5~3.7m(2.4m in average) in height,
With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70