• Journal of Korean Home Economics Education Association
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• v.29 no.4
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• pp.161-193
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• 2017

The purpose of this study was to develop and evaluate pre-parenthood education program(PPEP) based on Home Economics(HE) subject for high school students. The development and evaluation of PPEP based on HE subject in this study followed ADDIE model except implementation through 4 processes such as analysis, design, development, and evaluation. First, program development directions were set in three aspects such as 'general development', 'contents', and 'teaching and learning methods'. Themes of the program are 11 in total such as '1. Parenting, what is being a parent', '2. Choosing your spouse, happy marital relationship, the best gift to your children', '3. Pregnancy and birth, a moving meeting with a new life', '4. Taking care of a new born infant for 24 hours', '5. Taking care of infants, relationship with my lovely baby, attachment', '6. Taking care of young children, my child from another planet', '7. Parents and children in healthy family', '8. Parent-child relationship, wise parents to make effective interaction with their children', '9. Parents safety manager at home,', '10. Practice to take care of infants', and '11. Practice of community nurturing support service development'. In particular, learning activities of the program have major characteristics such as 1) utilization of cases including practice problems related to parenting, 2) community exchange activities utilizing learned knowledge and techniques, 3) actual life project activities utilizing learning contents related with parenting, 4) activities inducing positive changes in current life of high school students, and 5) practice activities for the necessities of life such as food, clothing and shelter supporting development of children. Second, the program was developed according to the design. Teaching-learning plans and materials for 17 classes were developed according to 11 themes. The developed plans include class flow and teacher's reference. It starts with receiving a class-related message from a virtual child at the introduction stage and ended with replying to the message by summarizing contents of the class and making a promise as a parent-to-be. That is the basic frame of class flow. Learning materials included various plans and reports necessary for learning activities and they are prepared in details so that they can be play the role of textbooks in regular curriculum. Third, evaluation of developed program was executed by a 5 point Likert scale survey on 13 HE experts on two aspects of program development process and program development results. In the evaluation of development process, mean value was 4.61 and index of content validity was 97.4%. For development results, mean value was 4.37 and index of content validity was 86.9%. These values showed that validity in the development process and results in this study was highly secured and confirmed that PPEP based on HE was appropriate and valid to enhance parent qualifications of high school learners.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of dental hygiene science
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• v.9 no.3
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• pp.327-338
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• 2009

This study was to develop an instrument for multidimensional measurement of Korean scaling fear (KSF)-1.0 and analyze related factors. A sample of 720 subjects(scaling patients and community people) was studied in Daegu city from November in 2008 to March in 2009. Authors first conceptualized the KSF, item generation, item reduction, and questionnaire formatting were performed in the stage of the development. Item descriptive, missing%, item internal consistency, and item discriminant validity were analyzed in the item-level, also descriptive, floor and ceiling effect were analyzed in the scale-level. Cronbach's alpha, test-retest, inter-dimension correlations, and factor analysis were performed to evaluate the validity and reliability in the new instrument. Confirmative factor analysis was did to evaluate the fit of model. The results for item-level and scale-level were acceptable except item discriminant validity. The reliability for 0.92~0.96 of corelation coefficient range(Cronbach's alpha 0.96~0.98) was high in the test-retest, and there was no significant difference in paired t-test. Item internal consistency(range of pearson corelation coefficient 0.39~0.95) was also high. The result of explanatory factor analysis was the same as the intended dimension structure, also confirmatory factor analysis results revealed that the dimensional structure model were fined well in the evaluation of model fit($x^2$= 1245.66, df=146, p=0.0000; GFI=0.85; AGFI=0.80; RMSEA=0.10). Factors related to KSF by multiple regression were gender($\beta$=0.28, p=0.0004) and teeth brush method($\beta$=-0.15, p=0.0053) in scaling patients, also gender($\beta$=0.25, p=0.0002), educational level($\beta$=0.14, p=0.0155), teeth brush method($\beta$=-0.09, p=0.0229) and time of daily work out($\beta$=-0.10, p=0.0055) were significantly associated with KSF in no scaling group. In conclusion, The results of this study reveal that the new developed measurement scale was reliable and val id instrument for measuring the KSF in dental hygiene patients and community people. We recommend that further research should develop more the instrument for the Korean scaling fear.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.78-95
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• 2011

This study has developed various DEMs with different spatial resolutions using many different interpolation methods with the aid of a 1:5,000 digital map. In addition, this study has evaluated the vertical accuracy of various DEMs constructed by check point data obtained from the network RTK GPS survey. The obtained results suggest that a DEM developed from the TIN-based Terrain method performs well in evaluating height restriction of buildings in a flying safety area considering general RMSE values, land-type RMSE values and profile evaluation results, etc. And, it has been found that three meters is the right spatial resolution for a DEM in evaluating height restriction of buildings in a flying safety area. Meanwhile, elevation values obtained by the DEM are not point estimation values but interval estimation values. This can be used to check whether the height of buildings in the vicinity of an airfield violates height limitation values of the area. To check whether the height of buildings measured in interval estimation values violates height limitation values of the area, this study has adopted three steps: 1) high probability of violation, 2) low probability of violation, 3) inconclusiveness about the violation. The obtained results will provide an important basis for developing a GIS related to the evaluation of height restriction of buildings in the vicinity of an airfield. Furthermore, although results are limited to the study area, the vertical accuracy values of the DEM constructed from a two-dimensional digital map may provide useful information to researchers who try to use DEMs.

• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• Journal of Animal Science and Technology
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• v.46 no.3
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• pp.335-346
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• 2004

Factors associated with milk urea nitrogen on milk yield and milk composition were investigated in this study regarding feeding management and Physiological status of lactating cows. The data for 3 years between 1999 and 2002 for this study were collected from 129,645 cows by Korean Agricultural Cooperatives Federation. The objectives of this study were to describe the relationships between milk urea concentrations and seasonal factors, cow factors and production of milk, milk fat, protein and somatic cell score(SCS). Milk urea was highest in summer and it also showed a nonlinear association with milk yield. Milk yield was higher at milk urea concentrations of 21 ${\sim}$ 24mg/dl, however it decreased at higher level of milk urea concentrations than 24mg/dl. Milk urea was higher with increased parities of cows and in particular, at 3 to 4 parities. There was a negative association between milk urea and SCS in milk. SCS in milk was lowest at milk urea concentrations of 2l${\sim}$24mg/dl. Milk fat and milk protein were greatly affected by days in milk(DIM), year of birth, season and milk urea concentrations, respectively. While milk urea increased in summer, milk fat and protein were decreased. Milk protein decreased according to longer days in milk. With regard to the influences of parity, milk protein in overall was negatively correlated to milk urea in all lactations, however the extent of decrease of milk protein at high concentrations of milk urea was bigger at third lactation. The balanced supply of energy and protein to the animals might have greatly affected the urea concentrations and protein content of milk.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.543-560
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• 2018

With the increased development in downtown underground space facilities that vertically cross under a railway at a shallow depth, the demand for non-open cut method is increasing. However, most construction sites still adopt the pipe roof method, where medium and large diameter steel pipes are pressed in to form a roof, enabling excavation of the inside space. Among the many factors that influence the loosening region and loads that occur while pressing in steel pipes, the size of the pipe has the largest impact, and this factor may correspond to the magnitude of load applied to the underground structure inside the steel pipe roof. The super equilibrium method (SEM) has been developed to minimize ground disturbance and loosening load, and uses small diameter pipes of approximately 114 mm instead of conventional medium and large diameter pipes. This small diameter steel pipe is called an SEM pile. After SEM piles are pressed in and the grouting reinforcement is constructed, a crossing structure is pressed in by using a hydraulic jack without ground subsidence or heaving. The SEM pile, which plays the role of timbering, is a fore-poling pile of approximately 5 m length that prevents ground collapse and supports surface load during excavation of toe part. The loosening region should be adequately calculated to estimate the spacing and construction length of the piles and stiffness of members. In this paper, we conducted a comparative analysis of calculations of loosening load that occurs during the press-in of SEM pile to obtain an optimal design of SEM. We analyzed the influence of factors in main theoretical and empirical formulas applied for calculating loosening regions, and carried out FEM analysis to see an appropriate loosening load to the SEM pile. In order to estimate the soil loosening caused by actual SEM-pile indentation and excavation, a steel pipe indentation reduction model test was conducted. Soil subsidence and soil loosening were investigated quantitatively according to soil/steel pipe (H/D).

• Korean Journal of Social Welfare
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• v.54
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• pp.5-33
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• 2003

This study is about the re-validation evaluation of the family Relationship Scale (FRS), developed to measure the family relationship in the social work practice. This study aims at re-validating the FRS, developed and validated in by Yang in 2001 for more general utilization. The sample was married mates and females residing in Seoul. For Face Validity, the content analysis was performed, and the FRS was re-validated in the dimensions of Love & Caring, Acceptance, and Recognition, positive affection, empathy, and autonomy and flexibility for each area. Internal reliability was .93, and internal consistency among three dimensions was 93%. For Empirical Validity, the Construct validity, the Criterion validity, and the Discriminant validity were performed. Construct Validity was validated through factor analyses. Commonalities for the factor analysis was 54%, and the factor loading for each factor was over .45. The confirmative factor analysis also confirmed the fitness of the scale. For Predictive Validity of Criterion Validity, regression analysis showed that the family stress scores became lower as the scores of the family relationship became higher; the discriminant analysis revealed that the family stress turned low ill tile group of high scores of family relationship. The Correlation analysis for Concurrent Validity was performed and the results showed the positive and significant relationship with a couple communication level (r=54) and a parent-child communication level (r=64). Life satisfaction and mental health level also revealed significantly positive correlation to prove Convergent Validity. Physical health level revealed a weak relationship with family relationship providing the evidence of Discriminant Validity. Discriminance was also proved by the analysis of variance with demographics. Thus, Cross Validation was confirmed the validation of the FRS through the various analyses with the married population. This study result improved the validity generalization of the Scale and verify the generalized usage of this sociometric scale in the field of social work practice.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.