• Korean Journal of Social Welfare Studies
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• v.45 no.3
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• pp.71-95
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• 2014

The purpose of this study is to examine the effects of household income types and sources on the depressions and self-respect of the old aged. Although household income types and sources are supposed to be important to the mental health of the old aged as well as income level, there have been little policy interests to them. This study analyze the relationship between the household income types & sources and the mental health of the old aged, using the 8th data from the Korean Welfare Panel Study. Major findings are as follows. First, we find that there are considerable variations in the household income sources composition among the old aged, and that types of household income are related to the individual and family features of the old aged. Second, the results of regression analyses show that the household income types are associated with the depression and self-respect of the old aged. And, we find that some income sources affects the mental health of the old aged. The results of this study suggest that there should be policy attentions to the mental health effects of the household income sources so as to increase the adequacy of the income security system for the aged in Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.191-198
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• 2021

Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.18-23
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• 2018

FPSO consists of topside modularized plants for production of crude oil, and hullside structures that serve as support for the topside and storage of produced crude oil. The structural behavior of the FPSO topside module and its supporting hull depends on the interface structure that connects them, and the interface structure consists of a combination of individual unit support structures called Module Support Seat (MSS). Types of interface structures are various and, accordingly, the basic design of the FPSO topside module structure is greatly influenced, so various design methods should be considered from the initial design phase. Structural design of FPSO topside module requires consideration of the number of MSSs, connection type, and structural analysis options such as the range of finite element models, load conditions, and boundary conditions for verification of structural strength. In this study, the comparison combination cases for the above considerations were derived and the strength evaluation was performed, and the structural behavior characteristics of the topside module were compared and analyzed through a detailed review of the analysis results. The results of this study are considered to be a good reference for designing a more reliable topside module structure.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.1-9
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• 2019

In the recent marine sector, the development and standardization regarding S-100, which is the universal hydrographical data model standard for development of marine space information, was progressed, and for the effectiveness of marine chart production work and the multi-purpose use of water level data in S-100, S-102(Bathymetric Surface grid) standard development and various studies of BAG formats combined with water level and uncertainty, property information is being progressed. Since the water level information that is important in the operation of the ship is provided based on S-102, the calibration method of the location information when producing S-102 is an important factor in deciding the water level. In this study, the hydrographical surveying was conducted by piloting the standardized method for the production of S-102 in Korea, and have compared the accuracy of water level information according to the GNSS post treatment calibration method. As a result of comparing the water level in 2 places in the rocky terrain of the study area, the northern water level of Namu-do was shown as DL 0.79~0.83m, the eastern water level of Daeho-do was DL 12.63~12.91m, and the horizontal position errors of the intermittent sunshine water level were confirmed to be within 1m. As a result, the intermittent sunshine water level according to the location calibration method when producing the BAG was confirmed that it was in the available range for a ship's safe voyage. However, the accuracy verification for the location of the ship when conducting hydrographical surveying was judged that there is a need for a various additional study about regional characteristics and environment factor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.1-6
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• 2019

The objective of this study was to investigate performance characteristics of thermal management system(TMS) in a fuel cell electric vehicle with 100kW Fuel Cell(FC) system. In order to build up analytic modelling for TMS, each component was installed and tested under various operating conditions, such as water pump, radiator, 3-Way valve, COD heater, and FC stack etc. and as the results of them, correlations reflecting component's characteristics with flow rate, air velocity were developed. Developed analytic modelling was carried out under various operating conditions on the road. To verify modelling's accuracy, after prediction for optimum coolant flow rate was fulfilled under certain operating conditions, such as FC system, water pump speed, opening of 3-way valve, and pipe resistance, analytic and experimental values were compared and good agreement was shown. In order to predict cold-start operating performance for analytic modelling, coolant temperature variation was analyzed with $-20^{\circ}C$ ambient temperature and duration was predicted to rise in optimum temperature for FC. Because there is appropriate temperature difference between inlet and outlet of FC stack to operate FC system properly, related analysis was performed with respect to power consumption for TMS and heat rejection rate and performance map was depicted along with FC operating conditions.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.23-36
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• 1999

As the blind signature(10) does not reveal any information about the message or its signature it has been used for preventing the information leakage and for providing the anonymity in secure electronic payment systems. Unfortunately this perfect anonymity could be misused by criminals as blind signatures prevent linking the withdrawal of money nd the payment made 표 the same customer. Therefore we should provide publicly verifiable mechanism if it is required for the judge to trace the blackmailed messages. In this paper we propose a modified blind signature scheme which additionally provides the role of message recovery after analyzing the existing meta-ELGamal scheme(12) suggested by Horster. And we suggest a new fair blind multi-signature scheme based on the oblivious transfer protocol with which a judge can publicly verify its fairness and correctness if needed. Proposed scheme can also applicable to the diverse electronic payment applications.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.87-103
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• 2021

The government is trying to create jobs by providing 160 billion won in 2021 to revitalize youth start-ups, but the number of youth unemployment and potential unemployment is hitting a record high of 1.2 million due to the shock of employment due to COVID-19. Although start-ups are encouraged as an alternative to revitalizing jobs, the success rate of young start-ups is low due to lack of start-up funds and experience. The purpose of this study is to understand the need to diversify start-up education and career education by understanding start-up policies through one-time funding and short-term education. The results of the study on the factors affecting the willingness to start a business were as follows, by sampling 344 students from specialized high schools preparing for employment and 344 young people in their 20s who are seeking jobs. First, among the entrepreneurship subvariables, innovation, autonomy of job value, and desire for economic achievement are significant, and the older the person surveyed, the more positive the perception of the entrepreneur was. Second, as you get older, your will to start a business decreases, and your experience in successful start-up models and start-up education has an impact on your will to start a business. Third, perception of entrepreneurs is a partial medium effect, which indirectly influences the willingness to start a business and directly or indirectly influences the willingness to start a business through the autonomy of job values, the desire to achieve economic and entrepreneurship.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.