제주 정의읍성 벽면식생에 근거한 벽면식재용 식물 선정에 관한 기초연구 (A Basic Study on the Selection of Plants for the Walls of Fortresses in the Case of the Jeongyi Town Wall in Jeju)
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- 한국조경학회지
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- 제42권2호
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- pp.33-40
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- 2014
본 연구는 제주도를 비롯하여 온대남부지방 성벽 벽면녹화에 적절한 식물종 선정을 위한 기초자료 제시를 목적으로 시도되었다. 제주 정의읍성 외곽 성벽의 식생을 조사 분석하여, 그 벽면식생의 가치특성과 문제점을 진단한 본 연구의 주요 결론은 다음과 같다. 성벽에 자생하는 식물은 총 52분류군이며, 이 중 방가지똥, 약모밀, 주홍서나물, 개망초, 자주광대나물 등 5분류군은 귀화식물로 분류되었다. 한편, 조사구별 출현종수는 3~14분류군이며, 평균 자생식물은 7.1분류군으로 나타났다. 상재도 III등급 이상의 식물은 말똥비름, 하늘타리, 송악, 모시풀이었으며, 종조성표 조작 결과, 정의읍성 성벽에 자생하는 식물종은 군락구분종 11분류군, 수반종 41분류군으로 총 52분류군으로 밝혀졌다. 자료 고찰 결과, 성벽 벽면식재를 위해 활용성이 높은 식물은 송악, 왕모람, 줄사철나무 등의 상록성 만경식물과 담쟁이덩굴, 하늘타리, 계요등 등의 낙엽성 만경식물로 밝혀졌다. 특히 왕모람은 남향의 성벽에 더욱 유용한 법면식생 재료로 추천한다. 이밖에 으름덩굴, 푼지나무, 가새잎개머루, 장딸기, 사위질빵 등의 목본식물과 각시마, 단풍마, 부채마, 거지덩굴 그리고 좁은잎계요등 등의 초본식물은 남부지방의 성벽을 비롯한 벽면식재용 재료로 활용 가능성이 높은 것으로 판단된다. 이밖에 콩짜개덩굴을 비롯하여 봉의꼬리, 도깨비 쇠고비, 실고사리 등의 양치식물은 제주도를 비롯하여 남부지방 성벽 고유의 지역성 반영을 위해 매우 유용한 식물로 판단된다.
We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.
Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.
자가부식 접착제는 사용하기 쉽고, 술식 민감성이 적은 장점이 있으나 특히 산도가 약한 자가부식 접착제의 법랑질에 대한 결합력은 논란이 되고 있다. 본 연구에서는 2단계 자가부식 접착제인 Clearfil SE Bond (Kuraray, Okayama, Japan)의 연마 법랑질에 대한 미세인장 결합강도를 측정하여 3단계 산부식수세 접착제인 Scotchbond Multi-Purpose (3M ESPE, St. Paul, MN, USA) 및 1단계 자가부식 접착제인 iBond (Heraeus Kulzer Gmbh, Hanau, Germany)의 결합강도와 비교하고자 하였고, 2단계 자가부식 접착제에 산부식 전처리를 시행하는 것이 법랑질에 대한 결합강도를 높일 수 있는지 알아 보고자 하였다. 실험군은 2단계 자가부식 접착제인 Clearfil SE Bond만 사용한 비산부식 군과 35% 인산 (Scotchbond Etchant, 3M ESPE)으로 산부식 후 Clearfil SE Bond를 사용한 산부식 군, 그리고 1단계 자가부식 접착제인 iBond를 사용한 군으로 나누었다. 대조군은 3단계 산부식수세 접착제인 Scotchbond Multi-Purpose를 사용한 군으로 정하였다. Bovine 전치의 순면을 십자가형으로 4등분하여 각 군으로 무작위로 배분하였다. 각 치아의 순면을 800-grit 실리콘 카바이드 지로 연마한 후 삭제된 법랑질면에 제조사의 설명서에 따라 각 군의 접착제를 적용하고 Light-Core (Bisco)로 적층 충전하였다. 시편은