• The Journal of Engineering Geology
• /
• v.29 no.2
• /
• pp.137-151
• /
• 2019

Geophysical exploration techniques are effective for monitoring changes in the ground condition around the excavation project to prevent subsidence risks during excavation work, therefore, improving analysis techniques is required for applying and supplementing various geophysical exploration technologies. In this study, a field-scale on-site test was conducted to detect possible ground subsidence hazards and areas of relaxation zone that may occur during excavation work and due to underground water level changes. In order to carry out the field test, a real-scale excavation test bed was constructed and the geophysical exploration methods, such as electrical resistivity survey and multi-channel analysis of surface wave (MASW) survey for urban sites condition, have researched for optimal geophysical exploration parameter, design and correlation analysis between the results by reviewing the validity of each individual geophysical exploration and modeling. The results of this study showed the impact of each geophysical exploration on the relaxation zone and, in particular, the location of the underground water surface and the effects of excavation were identified using electrical resistivity survey. Further research on modeling will be required, taking into account the effects of excavation and groundwater.

• The Journal of the Korea Contents Association
• /
• v.19 no.9
• /
• pp.593-600
• /
• 2019

The aim of this study is to enhance the level of life satisfaction of the elderly as the aging population grows in readiness for increased old age, beginning with interest in improving the quality of life of the elderly. For this purpose, the subtype of preparation for aging was set as multi-independent variables by organizing it into physical preparation for aging, economic preparation for aging, and emotional & social preparation for aging. Structural relationships between variables was identified by social support a parameter variable and life satisfaction a dependent variable. It was also verified that the social support between subtypes of preparation for aging and life satisfaction had a mediating effect. The subjects of this study are 4,058 elderly people who are over the age of 65. They were originally extracted from the 3rd and 5th additional survey of Korean Retirement and Income Study. For data analysis purposes, SPSS 25.0 and SPSS PROCESS macro v2.16 were used. The results of this study are as followed. The emotional & social preparation for aging not only had a significant direct effect on successful aging, but also resulted in indirect effect on successful aging through life satisfaction. On the basis of the results, this study provided the social welfare policy and practical suggestions to enhance the preparation for aging and social support, which are the key to improving life satisfaction of the elderly.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_2
• /
• pp.1493-1507
• /
• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.1
• /
• pp.76-86
• /
• 2022

Personal hearing devices, such as hearing aids, may be fine-tuned by allowing the users to conduct self-adjustment. Two self-adjustment procedures were developed to collect the listener preferred gains in six octave-frequency bands from 0.25 kHz to 8 kHz. These procedures were designed to allow rapid exploration of a multi-dimensional parameter space using a simple, one-dimensional user control interface (i.e., a programmable knob). The two procedures differ in whether the user interface controls the gains in all frequency bands simultaneously (Procedure A) or only the gain in one frequency band (Procedure B) on a given trial. Monte-Carlo simulations suggested that for both procedures the gain preference identified by simulated listeners rapidly converged to the ground-truth preferred gain profile over the first 20 trials. Initial behavioral evaluations of the self-adjustment procedures, in terms of test-retest reliability, were conducted using 20 young, normal-hearing listeners. Each estimate of the preferred gain profile took less than 20 minutes. The deviation between two separate estimates of the preferred gain profile, conducted at least a week apart, was about 10 dB ~ 15 dB.

• Journal of Korean Society of Forest Science
• /
• v.111 no.4
• /
• pp.603-612
• /
• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.

• Journal of Practical Engineering Education
• /
• v.14 no.1
• /
• pp.37-48
• /
• 2022

This study analyzed the effect of internal audit on the performance of the IATF 16949 automotive quality management system to understand the internal audit of companies and propose measures to activate the company's internal audit process. It was identified with the empirical analysis that 'The internal auditor competence, internal audit planning, internal audit implementation, infrastructure, culture/environment, and CEO support' to characterize IATF 16949 internal audit of automotive quality management system affects the internal performance and business performance of the company. In addition, I checked the size of the company and the period of certification period as moderating variables according to the sales based on the presented as factors that can improve the performance of the company, and how the moderating effects are seen in the relationship with the performance of the organization. I did analysis of technical statistics, exploratory factors, reliability, and multi-regression analysis with SPSS program. I summarized the results of the study, as a result of that, it was found that the internal audit planning, internal audit implementation, culture/ environment, and CEO support of independent variables affected the parameter and dependent variables (the internal performance and management performance of companies).

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.6
• /
• pp.29-43
• /
• 2019

This paper empirically analyzed the relationship between the characteristics of venture business founders and management performance, setting the management strategy as a parameter to provide a suggestion for the survival and development of venture companies that play an important role in the national economy and job creation. Previous studies in Korea have analyzed the relationship between the characteristics of business founders, management strategies and management performance in a single dimension. This paper, however, explained the business performance of a company from a multi-dimensional perspective while setting the characteristics of business founders as independent variables and setting the business strategy of the enterprise as a parameter. The first result of the analysis shows that the characteristics of venture business founders have a positive effect on business performance. In particular, among the characteristics of venture business founders, a progressive spirit has had the greatest impact on business performance. On the other hand, the influence of risk sensitivity was very weak. Second, the characteristics of venture business founders were found to have a positive effect on business strategy. In particular, innovation was an important variable that affected the technological innovation differentiation strategy, and a progressive spirit was the most influential factor in the marketing differentiation strategy. Third, management strategies of venture firms were found to have a positive effect on business performance. In particular, the technology innovation differentiation strategy has a greater impact on business performance than the marketing differentiation strategy. Fourth, it was revealed that management strategy partially has a mediated effect on the relationship between the characteristics of venture business founders and management performance. In other words, it was found that the characteristics of the founders have a direct impact on business performance but if it is linked to management strategy it has an indirect effect on business performance. The results of this study show that business performance improves when venture business founders' personal characteristics and the firms' management strategy are combined.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.10 no.1
• /
• pp.63-75
• /
• 2012

This paper gives some basic requirements and preferences of various geological environmental conditions for the final deep geological repository of spent nuclear fuel (SNF). This study also indicates how the requirements and preferences are to be considered prior to the selection of sites for a site investigation as well as the final disposal in Korea. The results of the study are based on the knowledge and experience from the IAEA and NEA/OECD as well as the advanced countries in SNF disposal project. This study discusses and suggests preliminary guideline of the disposal requirements including geological, mechanical, thermal, hydrogeological, chemical and transport properties of host rock with long term geological stabilities which influence the functions of a multi-barrier disposal system. To apply and determine whether requirements and preferences for a given parameter are satisfied at different stages during a site selection and suitability assessment of a final disposal site, the quantitative criteria in each area should be formulated with credibility through relevant research and development efforts for the deep geological environment during the site screening and selection processes as well as specific studies such as productions of safety cases and validation studies using a generic underground research laboratory (URL) in Korea.

• Korean Journal of Remote Sensing
• /
• v.30 no.2
• /
• pp.241-249
• /
• 2014

The continuous observations for atmospheric aerosol were carried out during 3 years (2009-2011) by using a multi-wavelength Raman lidar at the Gwangju Institute of Science and Technology (GIST), Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The particle depolarization ratios were retrieved from the observations in order to distinguish the Asian dust layer. The vertical information of Asian dust layers were used as input parameter for the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for analysis of its backward trajectories. The source regions and transport pathways of the Asian dust layer were identified. The most frequent source region of Asian dust in Korea was Gobi desert during observation period in this study. The statistical analysis on the particle depolarization ratio of Asian dust was conducted according to their transport route in order to retrieve the variation of optical properties of Asian dust during long-range transport. The transport routes were classified into the Asian dust which was transported to observation site directly from the source regions, and the Asian dust which was passed over pollution regions of China. The particle depolarization ratios of Asian dust which were transported via industrial regions of China was ranged 0.07-0.1, whereas, the particle depolarization ratio of Asian dust which was transported directly from the source regions to observation site were comparably higher and ranged 0.11-0.15. It is considered that the pure Asian dust particle from source regions were mixed with pollution particles, which is likely to spherical particle, during transportation so that the values of particle depolarization of Asian dust mixed with pollution was decreased.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.221-241
• /
• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.