• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.46-58
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• 2024

Pollinators are organisms that carry out the pollination process of plants and include Hymenoptera, Lepidoptera, Diptera, and Coleoptera. Among them, bees not only pollinate plants but also improve urban green spaces damaged by land use changes, providing a habitat and food for birds and insects. Today, however, the number of pollinating plants is decreasing due to issues such as early flowering due to climate change, fragmentation of green spaces due to urbanization, and pesticide use, which in turn leads to a decline in bee populations. The decline of bee populations directly translates into problems, such as reduced biodiversity in cities and decreased food production. Urban beekeeping has been proposed as a strategy to address the decline of bee populations. However, there is a problem asurban beekeeping strategies are proposed without considering the complex structure of the socio-ecological system consisting of bees foraging and pollination activities and are therefore unsustainable. Therefore, this study aims to analyze the socio-ecological system of honeybees, which are pollinators, structurally using system thinking and propose a green space planning strategy to revitalize urban beekeeping. For this study, previous studies that centered on the social and ecological system of bees in cities were collected and reviewed to establish the system area and derive the main variables for creating a causal loop diagram. Second, the ecological structure of bees' foraging and pollination activities and the structure of bees' ecological system in the city were analyzed, as was the social-ecological system structure of urban beekeeping by creating an individual causal loop diagram. Finally, the socio-ecological system structure of honey bees was analyzed from a holistic perspective through the creation of an integrated causal loop diagram. Citizen participation programs, local government investment, and the creation of urban parks and green spaces in idle spaces were suggestedas green space planning strategies to revitalize urban beekeeping. The results of this study differ from previous studies in that the ecological structure of bees and the social structure of urban beekeeping were analyzed from a holistic perspective using systems thinking to propose strategies, policy recommendations, and implications for introducing sustainable urban beekeeping.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.1-19
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• 2013

This study tries to review 'Sakuteiki(作庭記)', the Book of Garden Making, compiled at the end of the 11th Century during the Heian Period of Japan, from the East-Asian perspective. 'Sakuteiki' is a Garden Theory Book, the oldest in the world as well as in Asia, and it contains the traditional knowledge of Japanese ancient garden culture, which originated from the continent(Korea and China). Traditional knowledge related to East-Asian garden culture reviewed in this paper is "Fungsu Theory"(風水, Asian traditional ecology: Fengshui in Chinese; Fusui in Japanese), stemmed from the culture to seek sound and blessed places to live in. Viewed from modern landscape architecture, the Fungsu Theory corresponds to ecology(science). The Fungsu Theory was established around the Han Dynasty of China together with the Yinyangwuxing(陰陽五行) Theory and widely used for making human residences including gardens. It was transmitted to Japan via Korea as well as through direct transaction between Japan and China. This study reinterprets garden design principles represented in Sakuteiki, which were selected in 5 key words according to the Fungsu Theory. The 5 key words for the Fungsu Theory are "the place in harmony of four guardian gods(四神相應地)", "planting trees in the four cardinal directions", "flow of Chi(氣)", "curved line and asymmetry", and "mountain is the king, water is the people". Garden design principles of "the place in harmony of four guardian gods(四神相應地)" and "planting trees in the four cardinal directions" are corresponding to "Myeongdang-ron(明堂論, Theory of propitious site)". The place in harmony of four guardian gods mentioned in Sakuteiki is a landform surrounded by the flow of water to the east, the great path to the west, the pond to the south, and the hill to the north. And the Theory originated from Zhaijing(宅經, Classic of dwelling Sites) of China. According to this principle, the city was planned and as a miniature model, the residence of the aristocrat during the Heian period was made. At the residence the location of the garden surrounded by the four gods(the flow of water, the great path, the pond, and the hill) is the Myeongdang(明堂, the propitious site: Mingtang in Chinese; Meido in Japanese). Sakuteiki explains how to substitute for the four gods by planting trees in the four cardinal directions when they were not given by nature. This way of planting originated from Zhaijing(宅經) and also goes back to Qiminyaoshu (齊民要術), compiled in the 6th Century of China. In this way of planting, the number of trees suggested in Sakuteiki is related to Hetu(河圖) and Luoshu(洛書), which are iconography of Yi(易), the philosophy of change, in ancient China. Such way of planting corresponds to that of Yongdoseo(龍圖墅, the villa based on the principle of Hetu) presented in Sanrimgyeongje (山林經濟), an encyclopedia on agriculture and living in the 17th Century of Korea. And garden design principles of "the flow of Chi(氣)", "curved line and asymmetry" is connected to "Saenggi Theory(生氣論, Theory of vitality)". Sakuteiki explains the right flow of Chi(氣) through the proper flow and the reverse flow of the garden stream and also suggests the curved line of the garden stream, asymmetric arrangement of bridges and stones in the garden, and indented shape of pond edges, which are ways of accumulating Chi(氣) and therefore lead to "Saenggi Theory" of the Fungsu Theory. The last design principle, "mountain is the king, water is the people", is related to "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory. Sakuteiki explains the meaning of garden through a metaphor, which views mountain as king, water as the people, and stones as king's retainers. It compares the situation in which the king governs the people with the help of his retainers to the ecological phenomena in which mountain(earth) controls water with the help of stones. This principle befits "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory which explains landform on the analogy of social systems, people, animals and things. As above, major garden design principles represented in Sakuteiki can be interpreted in the context of the Fungsu Theory, the traditional knowledge system in East Asia. Therefore, we can find the significance of Sakuteiki in that the wisdom of ancient garden culture in East-Asia was integrated in it, although it described the knowhow of a specific garden style in a specific period of Japan.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• The Korean Nurse
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• v.20 no.4 s.112
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• pp.50-59
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• 1981

간호학생들이 당연하고 있는 문제점 미래의 간호학생들이 교육문제를 논하기 위하여는 간호학생들이 가지고 있는 문제점을 파악하고 또 이해하는 것이 우선순위가 될 것이다. 간호학생들이 문제점에 대한 연구는 한국에서 뿐아니라 미국에서도 꽤 많이 시행되어져 왔으며 특히 간호학과정에서 중간 탈락되는 중퇴자들에 대한 연구들 중에 이러한 문제점에 대해서 언급한 것이 많다. 고등학교를 졸업하고 곧 대학과정에 진학한 학생들을 대상으로 조사 보고될 Munro의 자료에 의하면 전문대학과정에서 27$\%$, 대학과정에서는 41$\%$의 간호학생들이 간호학과정에서 중간 탈락하고 있음이 보고되고 있다. 이들이 중간탈락하는 데에는 여러 가지 이유가 있으나 그 중 ''간호학에 흥미를 잃어서''가 가장 큰 이유로 보고되고 있다. 이곳 한국사회에서도 역시 비슷한 현상을 보이고 있다. 그러나 대학입시경쟁과 대학내에서의 전과가 거의 허용되지 않는 특수여건이기 때문에 학교를 중간 탈락하는 율은 미국이 보고만큼 높지는 않으나 역시 ''간호학에 흥미를 잃는다''는 것이 간호학생들의 가장 큰 문제점으로 대두되고 있다. 최근 한국에서 시행된 간호학생들에 관한 연구(표 1 참조)에 의하면 간호학생들의 학문에 대한 만족도는 조사자의 35$\~$50$\%$정도에 불과하였고 더우기 이 비율은 고학년에 올라갈수록 더욱 감소되고 있는 경향을 보이고 있다. 한국에서 시행된 어느 연구보고에 의하면 간호학에 실망했다고 생각하는 학생이 전체의 67$\%$였으며, 다른 학교로 전과를 희망한 경험이 있다는 학생이 71$\%$나 되는 것으로 보고되고 있다. 그러나 왜 흥미를 잃게 되는지 그 이유에 대하여 설명해 주는 연구는 많지 않았다. 미국의 한 저자는 간호학생들이 간호학에 흥미를 잃게 되는 원인을 간호원의 역할에 대한 이해가 정확하지 못한 것과 졸업 후 진로기회에 대한 인식부족 때문이라고 추측하고 있다. 간호학에 흥미를 잃게 되는 이유는 크게 다음의 세 가지로 분류 요약될 수 있다. 첫째, 간호학을 전공으로 택한 동기이다. 간호학의 특수성으로 인하여 학생들이 간호학을 전공으로 택한 동기도 다른 전공분야보다는 훨씬 다른 여러 종류를 보이고 있다. 즉, 종교적 이유, 다른 사람들에게 봉사할 수 있는 직업이기 때문에, 쉽게 취업을 할 수 있어서, 결혼 후에도 직업을 가질 수 있기 때문에, 외국으로 쉽게 취업할 수 있어서 등이 간호학을 선택한 이유로 보고되고 있다. 흥미나 적성에 맞다고 생각하기 때문에 간호학을 택한 학생의 수는 다른 과에 비하여 훨씬 적다. 이러한 흥미나 적성 때문이 아닌 여러 가지 다른 이유들로 인하여 간호학을 택한 경우에 특히 간호학에 쉽게 흥미를 잃어버리는 것을 볼 수 있다. 간호학에 현실적인 개념을 가지고 있는 학생들일수록 추상적이고 현실적인 개념을 가지고 있는 학생들보다 더 간호학에 지속적인 흥미를 가지며 중간에 탈락하는 율이 훨씬 적다는 것이 많은 연구에서 보고되었다. 또한 흥미나 적성 때문에 간호학을 택하였다는 학생들이 다른 과로 전과를 희망하는 율이 낮다는 것도 보고되었다. 둘째, 교과내용자체나 실습에 대한 불만족이다. 간호학에 대한 체계적인 교과내용의 결여, 과중한 과제물, 임상실습에서의 욕구불만, 실습으로 인한 부담, 지식과 실습의 차이점에 대한 갈등 등이 주요 이유로 보고되고 있다. 대부분의 연구들이 이 교과목이나 실습에 대한 불만족, 특히 실습경험에서의 갈등을 학생들이 흥미를 잃는 가장 중요한 요인이 되는 것으로 보고하고 있다. 어느 한 연구에서는 응답자의 90$\%$가 임상실습에 만족하지 못한다고 응답하였으며 그들 중의 88$\%$가 실습감독에 문제가 있다고 생각한다고 보고하였다. 셋째, 교수들에 대한 불만족이다. 대부분의 연구들이 학년이 올라가면 갈수록 교수에 대한 신뢰도가 낮아지며 또한 그에 비례하여 간호학에 대한 만족도가 낮아진다고 보고하고 있다. 교육내용에 대한 전문지식의 결여, 학생들과의 인간적인 관계의 결여, 교수법에 대한 불만족 등이 교수에 대한 불만의 주요내용으로 보고되었다. 미래의 간호에 부응할 학생교육 계속적인 사회적 변동과 더불어 급격하게 변화하고 있는 일반인들의 건강에 대한 요구도와 앞에서 기술한 문제점 등을 감안할 때 학생들에게 동기를 부여하고 간호학에 확신감을 가질 수 있도록 준비시키므로써 간호환경에서 실망하기보다는 오히려 그것을 받아들여 변화하는 사회요구에 책임감을 느낄 수 있도록 교육시키는 것이 미래의 간호학생을 준비시키는데 가장 중요한 요인이라고 할 수 있겠다. 이러한 교육을 위하여 다음의 두가지 안을 제시한다. 1. 교수와 학생간의 관계-서로의 좋은 동반자 : 교수들이 학생에게 미치는 영향, 특히 학생들의 성취도에 대한 영향에 대하여는 이미 많은 연구가 시행되었다. Tetreault(1976)가 간호학생들의 전문의식에 영향을 미치는 요인에 대하여 연구한 바에 의하면 다른 어느 것보다도 교수의 전문의식여부가 학생들의 전문의식 조성에 가장 큰 영향을 미친다고 하였다. 또한 학생들이 교수에게 신뢰감을 가지고 있을때, 교수들이 전문가로서의 행동을 하는 것을 보았을때 비로서 배움이 증가된다고 하였다. Banduras는 엄격하고 무서운 교수보다는 따뜻하고 인간적인 교수에게 학생들이 더 Role Model로서 모방하려는 경향을 나타낸다고 보고 하였다. 그러면 어떻게 학생에게 신뢰받는 교수가 될 수 있겠는가? apos;학생들의 요구에 부응할 때apos;라고 한마디로 표현할 수 있을 것이다. Lussier(1972)가 언급한 것처럼 학생들의 요구에 부응하지 못하는 교육은 Piaget이 언급한 교육의 기본 목표, 즉 개인에게 선배들이 한 것을 그대로 반복하여 시행하도록 하는 것이 아니라 새로운 것을 시도할 수 있는 능력을 가지게 하는 목표에는 도달할 수 없으며 이러한 목표는 간호학에도 가장 기본이 되어야 할 기본목표이기 때문이다. 학생들이 현재 어떤 요구를 가지고 있으며 또 어떤 생각을 하고 있는지 계속 파악하고 있는 것이 학생요구에 부응하는 교육을 할 수 있는 기본조건이 될 것이다. 의외로 많은 교수들이 학생들을 이해하고 있다고 생각하고 있으나 잘못 이해하고 있는 경우가 많다. 표 2는 현 간호학생들이 생각하고 있는 가치관과 문제점을 파악하고 또 교수가 그 가치관과 문제점을 어느 정도 파악하고 있는지 알아보기 위하여 일개 4년제 대학 200여명의 학생과 그 대학에 근무하는 18명의 교수진을 대상으로 질문한 결과를 간략하게 보고한 것이다. 또한 여기에서 학생이 보고하는 가치관, 문제점, 교수에게 바라는 점이 교수가 이해하고 있는 것과 차이가 있다는 것도 보여주고 있다. 우리가 학생들의 요구를 파악할 수 있도록 귀를 기울이고 이해하며, 그 요구에 부응하려고 노력할때 진정한 교수와 학생간의 관계가 이루어질 수 있을 것이며 이때 비로서 우리는 apos;partnershipapos;을 이룰 수 있을 것이다. 이때 간호학에 대한 실망은 줄어들 수 있을 것이며 우리도 학생들에게 전문가적인 태도를 함양시켜줄 수 있는 기회를 부여할 수 있을 것이다. 이렇게 될때 앞으로 기다리고 있는 미지의 의무에 효과적으로 또 적극적으로 대처할 수 있는 자질을 형성한 학생들을 준비해 낼 수 있을 것이다. 2. 간호모델에 의한 교과과정의 확립과 임상실습에의 적용 : 교과과정이 학생들의 모양을 만들어주는 하나의 기본틀이라고 말할 수 있다면 미래의 요구에 부응하는 학생들을 준비시키기 위하여 지금까지와는 다른 새로운 방향의 교과과정이 필요하다는 것은 재론할 필요가 없을 것이다. 이미 진취적인 간호대학에서는 guided design systems approach 또는 integrated curriculum 등의 새로운 교과과정을 시도하고 있음은 알려진 사실이다. 물론 간호모델에 준한 교과과정을 발전시키는데 대한 장점과 이에 수반되는 여러가지 새로운 문제점에 대하여 많은 논란이 있으나 모든 교과과정이 처음 시도될 때부터 완전한 것이 있을 수 없으며 시간이 지남에 따라 성숙되는 것임을 감안해 볼 때 이러한 새로운 교과과정에의 시도는 미래의 새로운 간호방향에 필수적인 사업이라고 하겠다. 이러한 교과과정을 개발하는데 몇가지 게안점을 첨부하려 한다. (1) 새로운 교과과정의 개발은 처음부터 끝까지 모든 교수진의 협력과 참여로 이루어져야 한다. (2) 비록 처음에는 어렵고 혼란이 있더라도 교과과정은 의학모델이 아닌 간호모델을 중심으로 이루어져야 한다. (3) 간호모델에서 다루어지는 개념들은 모두 직접 간호업무에 적용될 수 있는 것으로 선택되어야 한다. (4) 교과과정의 결과로 배출되는 학생들의 준비정도는 그 지역사회에 적합하여야 한다. (5) 그 지역사회의 고유한 문화적 요소가 포함되어야 한다. 아직 우리는 간호분야 내부의 갈등을 해결하지 못하고 있는 시기에 있다. 우리 내부의 문제점을 잘 해결할 수 있을때 외부와의 갈등에 잘 대처할 수 있을 것이다. 내부의 갈등을 잘 해결하기 위한 힘을 모으기 위하여는 동반자, 즉 교수와 학생, 간호교육자와 임상간호원 등이 서로 진정한 의미의 동반자 될때 가장 중요한 해결의 실마리가 될 것이다.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• Journal of Yeungnam Medical Science
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• v.12 no.2
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• pp.347-365
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• 1995

A survey was conducted to study perception and attitudes of health workers towards health center's activities and organization of health services, from August 15 to September 30, 1994. The study population was 310 health workers engaged in seven urban health centers in Taegu City area. A questionnaire method was used to collect data and response rate was 81.3 percent or 252 respondents. The following are summaries of findings: Profiles of study population: Health workers were predominantly female(62.3%); had college education(60.3%); and held medical and nursing positions(39.6%), technicians(30.6%) and public health/administrative positions(29.8%). Perceptions on health center's resources: Slightly more than a half(51.1%) of respondents expressed that physical facilities of the centers are inadequate; equipments needed are short(39.0%); human resource is inadequate(44.8%); and health budget allocated is insufficient(38.5%) to support the performance of health center's activities. Decentralization and health services: The majority revealed that the decentralization of government system would affect the future activities of health centers(51.9%) which may have to change. However, only one quarter of respondents(25.4%) seemed to view the decentralization positively as they expect that it would help perform health activities more effectively. The majority of the respondents(78.6%) insisted that the function and organization of the urban health centers should be changed. Target workload and job satisfaction: A large proportion (43.3%) of respondents felt that present target setting systems for various health activities are unrealistic in terms of community needs and health center's situation while only 11.1 percent responded it positively; the majority(57.5%) revealed that they need further training in professional fields to perform their job more effectively; more than one third(35.7%) expressed that they enjoy their professional autonomy in their job performance; and a considerable proportion (39.3%) said they are satisfied with their present work. Regarding the personnel management, more worker(47.3%) perceived it negatively than positive(11.5%) as most of workers seemed to think the personnel management practiced at the health centers is not fair or justly done. Health services rendered: Among health services rendered, health workers perceived the following services are most successfully delivered; they are, in order of importance, Tb control, curative services, and maternal and child health care. Such areas as health education, oral health, environmental sanitation, and integrated health services are needed to be strengthening. Regarding the community attitudes towards health workers, 41.3 percent of respondents think they are trusted by the community they serve. New areas of concern identified which must be included in future activities of health centers are, in order of priority, health care of elderly population, home health care, rehabilitation services, and such chronic diseases control programs as diabetes, hypertension, school health and mental health care. In conclusion, the study revealed that health workers seemed to have more negative perceptions and attitudes than positive ones towards organization and management of health services and activities performed by the urban health centers where they are engaged. More specifically, the majority of health workers studied revealed to have the following areas of health center's organization and management inadequate or insufficient to support effective performance of their health activities: Namely, physical facilities and equipments required are inadequate; human and financial resources are insufficient; personnel management is unsatisfactory; setting of service target system is unrealistic in terms of the community needs. However, respondents displayed a number of positive perceptions, particularly to those areas as further training needs and implementation of decentralization of government system which will bring more autonomy of local government as they perceived these change would bring the necessary changes to future activities of the health center. They also displayed positive perceptions in their job autonomy and have job satisfactions.