• Journal of Families and Better Life
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• v.32 no.5
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• pp.87-105
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• 2014

The purpose of this study was to investigate the factors associated with instrumental support (i.e., economic and practical support) from parents to their adult children. We examined both parents' attitudes toward instrumental support for adult children and parents' actual provision of instrumental support. From the data of the 2010 second National Survey of Korean Families, we selected 532 mothers and 524 fathers who were married and had at least one adult child aged over 25. Multiple regression analyses by the parents' gender showed that fathers were more likely to agree with instrumental support for adult children in general when they had unmarried children, had a lower household income level, had a lower evaluation of their socio-economic class, were satisfied with their own household economic situation, had positive attitudes toward caregiving for elderly parents, and were satisfied with their couple relationships. For mothers, they were more likely to agree with instrumental support for adult children in general when they had positive attitudes toward caregiving for elderly parents, were satisfied with their couple relationships, and perceived their child as someone to rely on in times of difficulties. Our analyses of the actual provision of support indicated that fathers tended to provide more support when they perceived that they were healthy, had unmarried children, were less satisfied with their household economic situation, had negative attitudes toward child-rearing, and reported a higher quality of parent-child relationship. For mothers, they were more likely to provide actual support when they were healthy, had unmarried children, had a higher level of household income, were financially preparing for later life, and less satisfied with their couple relationships. The findings of this study imply that it is imperative to distinguish the attitudes toward support from the actual provision of support and to also consider parents' gender in the literature on instrumental support for adult children.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.132-144
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• 2009

In this study, the basic data for calculating the proper construction cost as minimizing the uncertainty at the stage of forecasting construction cost with the basis of the analysis on the actual construction cost within completed domestic public apartment house. In this regard, 23 public apartment houses by each region which were ordered by the Korea National Housing Corporation and completed from 2004 to 2007 were selected as the objects of study. Four works such as common temporary installation, construction work, civil work and machine/equipment work which are the important direct cost items based on the actually inputted and settled construction costs were classified by completion year, region, architectural area, and the distribution type considering inflation rate. The sequent actual construction costs per 3.3m2 were compared and analyzed by each work, the proper construction costs were analogized and the calculating formula were presumed with the basis of average actual construction costs to be analyzed and presented.

• Journal of the Korea Institute of Building Construction
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• v.16 no.2
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• pp.133-140
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• 2016

The amount of labor input in a construction project is used as source data to estimate construction cost and to understand the productivity of the construction industry. However, there is a significant difference between the standard of estimation and the actual amount of labor input, and a plan is needed to resolve this problem. For this reason, to establish a system with which the actual amount of labor input can be inputted in a more accurate and simpler manner, a new method is proposed in this study. In the new method, a digital pen is used to minimize the difference from traditional handwriting on paper using a pen, and eliminate the redundant input of information. This study is expected not only to reduce the actual amount of labor input but also to contribute to the productivity of construction cost estimate through the sharing or utilization of the information on the web.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.499-507
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• 2021

This study compares the educational effect using real equipment, virtual reality, and video to improve the educational and training effect of the army and verifies which method of education is excellent. The Army has made a lot of efforts to realize the actual training environment, however, it is increasingly difficult to provide the actual training environment because of 1) restrictions on securing training sites and urbanization, 2) deepening conflicts with the people, and 3) difficulties in acquiring defense budget. To resolve these issues, the use of virtual reality(VR) has the advantage to experience actual battlefield indirectly and could save budget by training in a virtual battlefield environment. In particular, in the case of dangerous or expensive weapons systems, is further required. Hence this paper studies how effective virtual reality is compared to the actual weapons system. virtual reality(VR) education is less effective than actual equipment education, but it is higher than video education. Based on this research result, it will be used as a basic data for the analysis of educational effects based in virtual reality(VR).

• The Research Journal of the Costume Culture
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• v.30 no.3
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• pp.429-443
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• 2022

The purpose of this study is to verify how similar the virtual fit pants are to the actual fit of stretchable pants. Data is produced using a virtual model to apply movements. The results show that in the upright position, the similarity between the appearance of the actual fit and the virtual fit is high. Results are 4.47, 4.13 and 4.33 out of 5 on the front, side, and back, respectively. The base line of the front and back, and the amount of allowance in each part were well reproduced by the model. The texture of the virtual fit was evaluated and found to be similar to the actual fabric. In terms of shape and number of wrinkles with the virtual fit pants, large wrinkles were better expressed than fine wrinkles. After applying movements to the virtual model, the front and side results were similar to the actual fit, but the back results were different. As a result of multiple comparisons, the greatest difference in similarity by movements is found in the center front line. The similarity difference was lower on the side than on the front. The only significant difference after applying movements is in the hip circumference margin. According to movements, the similarity of virtual fit is lower on the back than on the front and side, and the back also has the largest similarity differences to the movements type.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.41-49
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• 2022

Recently interests on the application of thermal cameras have increased with the advance of image analysis technology. Aside from a simple image acquisition, applications such as digital twin and thermal image management systems have gained popularity. To this end, we studied the effect of emissivity on the DN (Digital Number) value in the process of derivation of a relational expression for converting DN to an actual surface temperature. The DN value is a number representing the spectral band value of the thermal image, and is an important element constituting the thermal image data. However, the DN value is not a temperature value indicating the actual surface temperature, but a brightness value indicating high and low heat as brightness, and has a non-linear relationship with the actual surface temperature. The reliable relationship between DN and the actual surface temperature is critical for a thermal image processing. We tested the relationship between the actual surface temperature and the DN value of the thermal image, and then the radiation adjustment was performed to better estimate actual surface temperatures. As a result, the relation graph between the actual surface temperature and the DN value similarly show linear pattern with the relation graph between the radiation-controlled non-contact thermometer and the DN value. And the non-contact temperature after adjusting the emissivity was closer to the actual surface temperature than before adjusting the emissivity.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.276-279
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• 2015

Along with the increase of the quantity of data in various industries, the construction industry has also developed various systems focusing on collecting data related to the construction performance such as productivity and costs achieved in construction job sites. Numerous researchers worldwide have been focusing on developing efficient methodologies to analyze such data. However, applications of such methodologies have shown serious limitations on practical applications due to lack of data and difficulty in finding appropriate analytic methodologies which were capable of implementing significant insights. With development of information technology, the new trend in analytic methodologies has been introduced and steeply developed with the new name of "big data analysis" in various fields in academia and industry. The new concept of big data can be applied for significant analysis on various formats of construction data such as structured, semi-structured, or non-structured formats. This study investigates preliminary application methods based on data collected from actual construction site. This preliminary investigation in this study expects to assess fundamental feasibility of big data analytic applications in construction.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.89-97
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• 2019

Recently, there is an increasing demand for applications utilizing maps and locations such as autonomous vehicles and location-based services. Since these applications are developed based on spatial data, interest in spatial data processing is increasing and various studies are being conducted. In this paper, I propose a parallel mining algorithm using the CUDA library to efficiently analyze large spatial data. Spatial data includes both geometric (spatial) and non-spatial (aspatial) attributes. The proposed parallel spatial data mining algorithm analyzes both the geometric and non-spatial relationships between two layers. The experiment was performed on graphics cards containing CUDA cores based on TIGER/Line data, which is the actual spatial data for the US census. Experimental results show that the proposed parallel algorithm using CUDA greatly improves spatial data mining performance.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.515-526
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• 2019

In the real world, the user's preference for a particular product is determined by many factors besides the quality of the product. The reflection of these external factors was very difficult because of various fundamental problems including lack of data. However, access to external factors has become easier as the infrastructure for public data is opened and the availability of evaluation platforms with diverse and vast amounts of data. In accordance with these changes, this paper proposes a recommendation system structure that can reflect the collectable factors that affect user's preference, and we try to observe the influence of actual influencing factors on preference by applying case. The structure of the proposed system can be divided into a process of selecting and extracting influencing factors, a process of supplementing insufficient data using sentence analysis, and finally a process of combining and merging user's evaluation data and influencing factors. We also propose a validation process that can determine the appropriateness of the setting of the structural variables such as the selection of the influence factors through comparison between the result group of the proposed system and the actual user preference group.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.79-86
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• 2019

This paper describes a time-series data prediction based on artificial neural networks (ANN). In this study, a batch based ANN model and a stochastic ANN model have been implemented using TensorFlow libraries. Each model are evaluated by comparing training and testing errors that are measured through experiment. To train and test each model, tax dataset was used that are collected from the government website of indiana state budget agency in USA from 2001 to 2018. The dataset includes tax incomes of individual, product sales, company, and total tax incomes. The experimental results show that batch model reveals better performance than stochastic model. Using the batch scheme, we have conducted a prediction experiment. In the experiment, total taxes are predicted during next seven months, and compared with actual collected total taxes. The results shows that predicted data are almost same with the actual data.