• Korean Journal of Social Welfare
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• v.36
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• pp.199-228
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• 1998

This study is designed to find out the determinants of dual-earner wives' needs for family-supportive services. For this purpose, a hypothetical model which explains the relationships among 6 stressors, role overload, stress and needs for 4 family-supportive services is developed. Using the data collected by purposive sampling from 234 professional women and 208 blue-collar women living in Chinju and Sacheon, the hypothetical model developed in this study was tested. In order to examine occupational class differences, a model for professionals and another model for blue-collars were developed separately and compared. For data analysis, a covariance structure analysis was used. The best-fitting model for professional women (df=141, GFI=0.928, CFI=0.965) and the model for blue collar women (df=141, GFI=0.902, CFI=0.912) were found. As a result of comparing two models, 9 common relationships were found:l)Greater dissatisfaction with child care service increases role overload; 2)Longer work hours increases role overload; 3) Higher level of role overload increases stress; 4)Higher level of stress increase needs for leaves; 5)Older child increases needs for flexible work pattern; 6)Younger child increases needs for finalcial assistance for child care fee; 7)needs for financial assistance for child care increases needs for on-site child care services; 8)needs for on-site child care services increases needs for leaves; 9)needs for leaves increases needs for flexible work pattern. With the exception of these 9 common relationships, the analyses revealed substantial differences between professional and blue-collar dual-earner wives. Based on the common and differential needs between 2 groups of wives, the effective ways to provide family-supportive services according to the needs of individual dual-earner wives who are in different familial, financial, and work conditions were suggested.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.169-181
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• 1997

In this paper, we propose and discuss about image enhancement techniques for MPEG-4. which represents very low bit-rate, content-based. and object-based hierarchical audio-visual coding standard. The proposed enhancement technique removes undesired artifacts arising in the compression procedure and increase resolution in both spatial and temporal domains. In order to remove undesired artifacts. we divide the MPEG-4 video algorithm in two parts: MPEG-2 like part and the new part. For removing artifacts caused by the first part. we adopt the conventional blocking artifacts algorithm developed for MPEG-2. On the other hand for removing artifacts caused by the second part. we provide a new degradation model. and propose the corresponding image restoration method. For increasing resolution of the MPEG-4 images, we propose a general framework of multichannel image interpolation process. which includes both spatial and temporal interpolations. As the MPEG-4 standard is under development. various sophisticated techniques are considered. but research on image enhancement techniques is relatively underestimated. By this reason. additional image enhancement techniques will become very important issue in realization phase of MPEG-4.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.583-588
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• 2010

The nonlinearity and high deformability of rubber make accurate analysis of the behavior of cord-rubber composites a challenging task. Some researchers have adopted the third phase between cord and rubber and have carried out three-phase modeling. However, it is difficult to determine the thickness and properties of the interface in cord-rubber composites. In this study, a two-dimensional finite-element method (2D FEM) is used to investigate the effective and normalized moduli of cord-rubber composites having interfaces of various thicknesses; this model takes into account the 2D generalized plane strain and a plane strain element. The neo-Hookean model is used for the properties of rubber, several interface properties are assumed and three loading directions are selected. It is found that the properties and thickness of the interface can affect the nonlinearity and the effective modulus of cord-rubber composites.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.837-848
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• 2005

A multi-scale database is a set of spatial database, covering same geographic area with different scales and it can be derived from pre-existing databases. In the derivation processes of a new multi-scale spatial database, the geometries and topological relations on the source database can be transformed and the transformation can be the cause of the lack of integrity Therefore, it is necessary to assess the transformation whether it is consistent or not after the derivation process of a new multi-scale database. Thus, we propose assessment methods for the topological consistency between a source database and a derived multi-scale database in this paper. In particular, we focus on the case that 2-dimensional objects are collapsed to 1-dimensional ones in the derivation process of a multi-scale database. We also describe implementation of the assessment methods and show the results of the implementation with experimental data.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.205-214
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• 2013

Team collaboration is becoming commonplace and it is spotlighted in agile software development projects as well. More efficient teamwork in terms of effective team operation and project performance is very important. Heuristic software development staffing method has been used, but algorithm approach is needed to compensate for it. In this paper, we propose a mathematical approaches for staffing developers in teamwork-based software development projects. This consist of six process, and activities in each processor is defined as a mathematical function placement, and functional deployment matrix is used. A case study is presented in order to prove the usefulness of this approach. This paper is a significant research because a mathematical approach of work assignment is developed for human resources by quantitative logic and it deviate from intuitive or heuristic methods used previously.

• Journal of the Korean Society for Railway
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• v.15 no.6
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• pp.572-578
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• 2012

In the electric railway vehicles, securing stable current collection performance is an important factor which determines the quality of operation and the maximum speed. In order to predict such current collection performance, various analysis methods have been proposed for a long time. Also, investigations for improving the accuracy of the results and the efficiency of the analysis process have been performed. In this paper, a method for the efficiency improvement has been proposed. This method is based on the basic concept that the system equations of motion of a catenary numerical model include only interactive range with a pantograph. In this paper, an algorithm and generalized process for applying proposed method are introduced. Also, validity of the results and utility of the method was verified and studied.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.287-297
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• 2012

In order to prepare for the introduction of the E-Discovery system from the United States and to cope with some causable changes of legal systems, we propose a general E-Discovery process and essential tasks of the each phase. The proposed process model is designed by the analysis of well-known projects such as EDRM, The Sedona Conference, which are advanced research for the standardization of E-Discovery task procedures and for the supply of guidelines to hands-on workers. In addition, Machine Learning Algorithms, Open-source libraries for the Information Retrieval and Distributed Processing technologies based on the Hadoop for big data are introduced and its application methods on the E-Discovery work scenario are proposed. All this information will be useful to vendors or people willing to develop the E-Discovery service solution. Also, it is very helpful to company owners willing to rebuild their business process and it enables people who are about to face a major lawsuit to handle a situation effectively.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.105-114
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• 2017

Because the concepts and components of computational thinking included in the Information Education Curriculum and the Software Education Guidelines are different, it has been difficult to establish computational thinking-based software education in schools. Therefore, this study, which is based on the Delphi survey results from 39 experts, we defined computational thinking as 'computing thinking' and separated the components of computational thinking into five main categories: (1) problem definition, (2) data analysis, (3) abstraction, (4) automation, and (5) generalization. In addition, we selected software areas that are strongly related to computational thinking in the KAIE's information Curriculum Standard Model and surveyed experts to decide which computing thinking components are related to the achievement criteria of the software areas.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.729-733
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• 2006

Short message service (SMS) is a Popular mobile data service in cellular networks. One SMS message can carry 50 Korean alphabets. Cellular operators standard and develop multimedia message service (MMS) based on P2P as color phones having multimedia solutions such as MIDI, MP3, JPG, PNG, and MPEG have been developed. MMS can be a key cash flow in the non-voice mobile revenue together with SMS. Copyrights protection of contents in a MMS message can be issued as MMS can be the popular P2P service such as MMS. In this paper, we propose MMS DRM system to protect copyrights of contents in MMS with the minimum change of MMS system. The proposed MMS DRM system protect copyrights of contents using DRM Packager, DRM Server, and DRM Agent and support various use cases to activates MMS in mobile networks.