• Journal of the Korean housing association
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• v.23 no.4
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• pp.59-67
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• 2012

Developing the modern design of Hanok and providing support for the commercialization model development in recent years propelled by the New Hanok Support Strategies of the central government in conjunction with the New Hanok revitalization related projects reflecting local goverments. New Hanok revitalization, the rekindling and revaluing of human behaviors and interests in local goverments following the social and cultural changes of the past decades, has emeraged as an increasingly traditional area of concerning in New Hanok planning. In this paper we attempt to this discussion by describing recent projects in New Hanok revitalization in Jeollanam-do Province. Therefore, this study aims to examine the classification of compound knowledges based multidimensional relationship by using Self-Organizing Maps (SOM). SOM is an unsupervised learning neural network model for the analysis of high-dimensional input data. By using SOM, we were able to create a cluster map reflecting the characteristics of the New Hanok. In this case the pattern of the preference data was easily understood by visual analysis. Liking for compound knowledge deduced from this data was classified into 8 categories according to the compound knowledge properties of New Hanok. As a result, a systematic approach for analysis the characteristics of individual family and living environment of New Hanoks and 10 space usage patterns the changes in some aspects of New Hanok.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• Journal of the Korean earth science society
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• v.23 no.5
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• pp.397-405
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• 2002

This study investigated science gifted middle school students' philosophical views on scientific knowledge, and the effects of discussing and reading related to the knowledge. Ten eighth-graders in a science gifted class participated in this study. The results can be summarized as follows: 1, At the beginning, the students had one of six positions: (a) relativism (n = 2); (b) falsificationism (n = 2); (c) borderline between relativism and eclecticism (n = 1); (d) borderline between falsificationism and eclecticism (n = 3); (e) borderline among relativism, falsificationism, and eclecticism (n = 1); and (f) borderline inductivism and eclecticism (n = 1). This result indicated that most students had on almost modern philosophical view of scientific knowledge. 2, Some students, who had chosen the item of inductivism in some questions of the instrument at the beginning, maintained their selection despite discussions and readings related to scientific knowledge. The data were examples which indicated the difficulty of changing from a traditional view to a modern view of scientific knowledge.

• 모자간호학회지
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• v.2 no.1
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• pp.70-86
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• 1992

What is the meaning of menopause experienced by urban Korean women? Nurses need an under standing of menopause as it is experienced by women themselves. Nursing needs to build knowledge of womens' health experiences. This phenomenological study examined what menopause means to modern Korean woman to build a structure of knowledge useful for practice to enhance the quality of life of women throughout this experience. Traditional definition of menopause according to physiological changes, as illness and more recently as psychosociocultural phenomena were examined along with the folk lore information generally available in the society A review of the research and scientific literature was done from the perspectives of four models including the medical model of menopause as disease, the psychosocial model as positive and negative behavioral responses to menopause, a feminist model of menopause as a time of rebirth and a nursing model of the changing patterns of meaning, rythms and transformation women experience through menopause. Van Kaam's method was used to analyse data audio-recorded during interviews by the investigator with 65 women, 40 to 60 years of agey whose confidentility was assured. Interpretation of the data was enhanced luther by consultation with professional colleugues and with informants. Four rhythmical patterns of process emerged : from suffering to comfort, from oppression to freedom from being a good wife and wise mother to becoming a woman and from a hard life to an abundant life. The detailed common elements making up each of the four patterns and definitions of each pattern were presented. Each pattern was discussed critically from the point of view of medical, psychosociocultural, womens' and nursing models. The structural definition of the synthesis of the four process patterns was stated as : in spite of suffering the middle-aged urban Korean woman find she is able to help herself to feel comfortable and to realize release as she moves from oppression to liberation and freedom from being a good wife and wise mother she experiences rebirth as a woman : she begins to live a profitable and valuable life : her life becomes one of transformed abundant living. The definition transcends the medical and phychosociocultural model to embody a nursing model. The analysis was critiqued by using Parse' Human Becomming theory of nursing because the emerging themes were process patterns. Parse' theory provides and explanation of the experience of menopause consistant with the data which enhances nursing understanding of womens' experience of menopause. Parse' practice methodology provide guidance for promoting womens' quality of life throughout the experience of menopause. Feminist analysis contributes valuable critique to nursing research, richly expanding the perspective from traditional approaches to promote understanding of the meaning of womens' health experiences.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.305-313
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• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.415-423
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• 2009

Because of the fast changing car design and increasing facilities, manufacturing process of cars is getting more complex now a days. Particularly, car manufacturing system that consist of automated devices, applies various simulation techniques to validate device motion and detect collision. To cope with this problem, traditional manufacturing system deployed test-run with the real devices. However, increased computing power in a contemporary manufacturing system changes it into realistic 3D simulation environment. Similarly, managed device data that was generated using 2D traditionally, can be converted to 3D realistic simulation. The existing problem with 3D simulation is disjoint data interaction between different work stations. Consequently, JIGs, fixing the car part accurately, are changed according to fixing position on the part or a part shape properties. In practice, the 3D JIG data has to be managed according to kinematic information, but not of its features. However, generating kinematic information to the 3D model repeatedly according to frequent change in part is not explained in current literatures. To fill this knowledge gap, this paper suggests an improving method of rendering 3D JIG kinematics information to simulation model. Thereafter, it shows the result of implementation.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.353-359
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• 1999

We present a matrix-based inference algorithm suitable for electronic commerce applications. For this purpose, an Extended AND-OR Graph (EAOG) was developed with the intention that fast inference process is enabled within the electronic commerce situations. The proposed EAOG inference mechanism has the following three characteristics. 1. Real-time inference: The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation: All the subjective knowledge is delineated in a matrix form. so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference: Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency. We have proved the validity of our approach with several propositions and an illustrative EC example.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.53-73
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• 1996

Thesedays more collaboration is required of scholars than before, because some complex problems are beyond the individuals' research capability. Traditional print-based journal systems have been playing a role of supporting scientific collaboration, in that they provide the state-of-the-art knowledge. Those journal systems, however, are known to have some problems. To cope with some of those problems of the print-based journal systems, electronic journal systems have been suggested and implemented. Investigation shows us that electronic journal systems still have some problems. This paper proposes a new form of electronic journal system, structured electronic journal system, which is believed to better support the scientific collaboration. It is designed so that it is easier to figure out the synopsis of an article and so that authors and referees of a submitted paper can participate in the discussion for verifying the significance of the paper. Object-oriented design of a structured electronic journal system which is to be built on top of a object-oriented database system is explained with example structures.

• Journal of the Korean housing association
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• v.16 no.5
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• pp.39-48
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• 2005

The purpose of this study was to analyze environment-behavior concepts included in environmental design characteristics of facilities for elderly with dementia. Major method was contents analysis of actual environmental designs. For comparison between the environment-behavior concepts and actual cases, an analytical framework was developed. Eleven cases of facilities designed for people with dementia were analyzed. Those were published ones in periodicals in USA. The analytical data used included floor plans, texts, and visual materials including photographs. Under the framework for analysis, a total of 296 criteria were used to analyze the actual cases of environmental design. This study was expected to offer a knowledge base for better environmental design for elderly with dementia and to help establish guidelines for designing such facilities which can meet the cultural characteristics and traditional conditions of Korea.