• Journal of Korean Home Economics Education Association
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• v.16 no.2
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• pp.37-53
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• 2004

The purpose of this study is to observe the developmental Process of interaction and attitude of children through instruction for “making fabric doll”. Based on the theory of “Waldorf Education”, instruction of 8 hours for 3 weeks exercised against 40 children(18 boys, 22 girls) of 6th grade, especially focused two group(10 children), in K elementary school in Chunchoen. The results of the study by qualitative research method through observing, recording, interpretation are as follows 1. The changes in interaction among children were observed in increase of quantity and quality of conversation among children, of reliability and dependence among children, of intimacy and cooperation among children, and of intimacy between teacher and children. 2. The changes in the attitude toward instruction were observed in increase of confidence and satisfaction, of active and attentive attitude to instruction via more interest about own fabric doll, of positive attitude through attachment to the doll. Therefore, the instruction of “making fabric doll” based on “Waldorf Education” seems to be efficient to child development and Practical Arts Education.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.75-89
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• 2007

This study has its aim at suggesting new direction of our education to search different ways in housing contents by comparing the necessity perception and demands between teachers and students for housing contents in Technology Home Economics curriculum of middle school. To achieve this aim, I chose middle school teachers in charge of Technology Home Economics and male and female students who are in the first grade in high school in Ulsan. I sent e-mail, mail, and visited researcher to gather the data. I used SPSS +12 statistical package for frequency, percentage, mean, standard deviation, and t-test to analyze the data. Here is the result. First, In the part of application of living place, teachers had necessity perception in use and placement of furniture, and arrangement of objects. Students had necessity perception in the use and placement of furniture, the kind and choice of furniture. Also in the indoor environment and equipment part, both teachers and students had necessity perception in controlling of ventilation, temperature, and humidity. In the part of maintenance repair of housing, teachers had necessity perception in the need for maintenance management but students had necessity perception in house equipments and repair had high necessity perception Second, In housing-related general part, teachers demanded housing for elderly, disabled people, information about future housing and students demanded environmentally friendly living environment, housing for elderly, disabled people. In interior design part, teachers demanded in the expression of interior places through computer, the kind and characteristic of housing material and students demanded the way to reuse old furniture, kind and characteristic of housing material. In the part of housing preparation and occupation, teachers demanded the kind of housing-related occupation and students demanded the housing tax and the process of house purchase or concerned matter. Third, there were some difference of necessity perception and degree of demand between teachers and students. Teachers had higher necessity perception and demand in all part except in demand for housing equipment, maintenance, and environmentally friendly living environment.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.17-36
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• 2007

The purpose of this study was to develop health belief model based various milk education program as print education media and apply to elementary, middle, and high schools. The subjects were 432 students(124 elementary, 122 middle, 186 high school students). We designed one group pretest-posttest study model. The data were obtained from pre and post-study with self-administered questionnaires. Before applying this education program, we evaluated the degree of awareness on milk. Their awareness on milk was very low, 35.5% lower elementary, 32.7% higher elementary, 52.5% middle, and 54.3% high school students were answered they don't know the milk well. After they had implemented milk education program, their recognition on milk had changed that milk is nutritious as supplementary food. And their reasons for drinking milk were also changed that 'they want to eat it' in elementary school students, 'they want to be healthier' in middle school students, and 'they want to be taller' in high school students. Their nutrition knowledge score showed a significant increase(p<0.05). As a results. milk nutrition education has improved nutrition knowledge and recognition on milk in elementary, middle, and high school students. To improve their milk eating behaviors, nutrition education programs will have to be continued.

• Korea Journal of Hospital Management
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• v.7 no.1
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• pp.64-87
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• 2002

The purpose of this study is aimed to grasp the factors, which may influence the harmonized organizational efficiency of the objects of hospital structure as well as its structural constituents of each departments of administration, nursing, and para-medical personnels, in order to provide basic data enable to contribute in the development of hospital. The survey data involved in the study was derived from 385 personnels working in 5 medium and small sized hospitals in Seoul area. The main finding of the study can be summarized as follows; 1. The organizational efficiency in accordance with the general characteristics of subjects in order of male, over 30 years of age, university graduates, long-term tenure and high position is higher, whereas, in as much as wage and well trained personnels in administration departments are higher, its organizational efficiency is higher in comparison with those of nursing and para-medical departments. 2. The organizational efficiency in accordance with satisfaction and the motive contributional factors is higher as much as the high satisfactory level in every departments in general. 3. The organizational efficiency in accordance with the factors of job characteristics is higher in as much as difficulty of the jobs is lesser, however there was not statically significance between administration and para-medical departments. In as much as the job circulation is intact, job standard level is higher and the more job responsibility the higher organizational efficiency, while the more workload and the more work feud resulted lower organizational efficiency. It was obvious that the higher professional expertise as well as the training and application level are improving the organizational efficiency. 4. The organizational efficiency in accordance with the factors of structural characteristics was higher in as much as the intercommunication was smooth and the structural formalization level are higher, however there was not statically significance between the participation level of decision making and the organizational efficiency. 5. In as much as higher educational level of over university graduates, management of organization and the job level are satisfied, the psychological motive contributional level is higher, while the lesser job difficulty, the smooth job performance, the higher level of professional expertise, the higher structural formalization level, the smooth intercommunication, have affected as major influence factors of the structural characteristics of organizational efficiency. 6. As the management of hospital organization, the job level and personal relation are satisfied or psychological motive is provided, especially when there are no difficult jobs or smooth job circulation and no job feud are prevailing, it was apparent that the organizational efficiency is improving accordingly. The nursing departments has high educational standard and is satisfied in the management and job level of hospital organization as there are no difficult jobs while the level of hospital's organizational formality is high and the intercommunication is smooth, which are improving the organizational efficiency. The para-medical departments is also satisfied the management and job level of hospital organization and it was apparent that the organizational efficiency is higher in as much as the level of job standardization is high and the intercommunication is smooth. As a result of this study, in order for improving the organizational efficiency of the medium and small sized hospitals, the management and job level as well as personal relation are preferably satisfied, whereas the level of job circulation, job responsibility, the expertise and formalization of organization, intercommunication and etc. should be satisfied, and, therefore, it is advisable to buildup discriminated organizational management and environment for different division on the basis above factors. Since this study is carried on several hospitals in Seoul area, there is a certain limit to generalize its result to all domestic hospitals, nevertheless the gallop poll was made by developing the questionnaires with reasonability and reliability. Especially, as the study was carried by analyzing the comparison of influence factors' difference of organizational efficiency in accordance with the divisional characteristics of the medium and small sized hospitals.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of the Korean Institute of Landscape Architecture
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• v.16 no.3
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• pp.21-37
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• 1989

Environmental design pattern of the nine Small Urban Spaces at C.B.D. in City of Seoul are surveyed and analyzed for user's satisfaction and behavior under the environmental design evaluation by using Christopher Alexander's Pattern Language. Small Urban Spaces as a part of streetscape are formed by physical factors as well as visual environment and interacting user's behavior. Therefore, user's satisfaction and behavior at the nine Urban Small Spaces were investigated under the further search for some possibilities of application of those Pattern Languages. A pattern language has a structure of a network. It is used in sequence, going through the patterns, moving always from large patterns to smaller, always from the ones which create comes simply from the observation that most of the wonderful places of the city were not blade by architects but by the people. It defines the limited number of arrangements of spaces that make sense in any given culture. And it actually gives us the power to generate these coherent arrangement of space. As a results, 'Plaza', 'Seats'and 'Aecessibility' related design Patterns are highly evaluated by Pattern Frequency, Pattern Interaction and their Composition ranks, thus reconfirm Whyte's Praise of urban Small Spaces in our inner city design environments. According to the multiple regression analysis of user's evaluation, the environmental functions related to the satisfaction were 'Plaza', 'Accessibility' and 'Paving'. According to the free response, user's prefer such visually pleasing environmental design object as 'Waterscape' and 'Setting'. In addition to, the basic needs in Urban Small Spaces are amenity facilities as bench, drinking water and shade for rest.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.15-22
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• 2010

Today's rapid shifts toward a new paradigm are combining city spaces with reality and technology, which is known as a ubiquitous environment. An ubiquitous environment means that 'whenever' and 'wherever' become connected. It is a great possibility that this will change our future lifestyle. Korea has the biggest advantage in the implementation of this new environment, such as having an excellent network infrastructure. Using these attributes of a ubiquitous environment, changes are being made toward ubiquitous cities within developing fields of construction, landscaping, streets, art, and the environment. This research is based on background of research that activated media pole in public city space has been done research about reality of digital skill, fusion, and sense of ubitizen, and Kang-Nam U-street applied by ubiquitous technique. While reflecting an environment that can be utilized in a modern digital society, the application of ubiquitous technology to media pole can be a space for the two-way communication of the current paradigm. It would also be meaningful to create a new cultural space through media pole. Through evaluation, citizens of the ubiquitous age are going to interact to raise the satisfaction that media pole in city space can prevent giving direction to develop and trial and error about service ability, identity, and publicity. Finally, the media pole can be used as a fundamental element to suggest directions for change when viewed as future development.