• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.73-93
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• 2023

This study provides a prospect for the fast growing the smartwatch market by investigating the relationship between the satisfaction and the continuous use intention of Apple watch users, as well as the factors influencing their satisfaction. Based on the TAM, this study uses system quality, information quality, and self-efficacy as independent variables, perceived usefulness, perceived ease of use, and satisfaction as mediators, and continuous use intention as the dependent variable. We analyze the data of 256 individuals who completed an online survey with SPSS 26.0 and AMOS 26.0 software. This study conducts several tests and analyses to empirically evaluate the data including reliability analysis, factor analysis, feasibility analysis, path analysis, hypothesis verification, and mediation analysis. Our results investigate which factors may influence consumers' intention to continuously using Apple Watch devices in the future. In summary, satisfaction has a positive effect on the intention to continuously use smartwatchs. Perceived usefulness and perceived ease of use have a positive effect on satisfaction. Among the three factors (system quality, information quality, and self-efficacy), only self-efficacy has no significant impact on perceived usefulness but had a positive effect on perceived ease of use. In addition, system quality and information quality positively affect perceived usefulness, perceived ease of use, satisfaction, and continuous intention to use an Apple Watch. Taking the Apple Watch as the subject of our research topic, this study provides theoretical value by exploring the impact of user's satisfaction with their smartwatch on their continuous usage intention. This study further explains the influence of system quality, information quality, and self-efficacy on user satisfaction. Additionally, this research offers valuable insight to practitioners by confirming that information quality, system quality, and self-efficacy are important features for enhancing satisfactory user experiences which in turn may increase users' intention to continued using smartwatches.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.96-106
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• 2002

this paper, we propose a flexible, reusable, and extensible HL7 encoding and decoding framework using a Message Object Model (MOM) and Message Definition Repository (MDR). The MOM provides an abstract HL7 message form represented by a group of objects and their relationships. It reflects logical relationships among the standard HL7 message elements such as segments, fields, and components, while enforcing the key structural constraints imposed by the standard. Since the MOM completely eliminates the dependency of the HL7 encoder and decoder on platform-specific data formats, it makes it possible to build the encoder and decoder as reusable standalone software components, enabling the interconnection of arbitrary heterogeneous hospital information systems(HISs) with little effort. Moreover, the MDR, an external database of key definitions for HL7 messages, helps make the encoder and decoder as resilient as possible to future modifications of the standard HL7 message formats. It is also used by the encoder and decoder to perform a well formedness check for their respective inputs (i. e., HL7 message objects expressed in the MOM and encoded HL7 message strings). Although we implemented a prototype version of the encoder and decoder using JAVA, they can be easily packaged and delivered as standalone components using the standard component frameworks like ActiveX, JAVABEAN, or CORBA component.

• Journal of Family Resource Management and Policy Review
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• v.25 no.2
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• pp.41-52
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• 2021

The purpose of this study is to examine how female labor force participation, family policies, and gender equality are related to fertility rate across countries. Multiple measures has been collected from various data sources(such as OECD, UNDP, and WVS) and the panel data set which includes (mostly) OECD countries range from 1990 to 2019 are analyzed. The major findings are as follows. First, based on OECD countries samples, female labor force participation is positively associated with the fertility rate, which implies that women's labor force participation does not lead to a reduction in fertility rate. Second, the length of paternity leave is positively associated with fertility rate whereas the direction is the opposite for the relationship between the length of maternity leave and fertility rate. This is attributed to the possibility that a longer period of maternity leave incurs the a higher opportunity cost of earning income, which leads to a reduced fertility rate. Third, countries with higher gender inequality index tend to have a higher fertility rate. Similarly, countries with higher gender equality value have a lower fertility rate. When the gender equality value is devideed into three sub-categories, education, politics, and employment, the gender equality value in education is the only sub-category which is negatively associated with the fertility rate. This study confirms that female labor force participation may not be a contributing factor in the lowering of fertility rate but instead can be positively associated with the fertility rate. Also, the results show that family policies or gender equality values can be significantly affect fertility rate.

• Journal of IKEEE
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• v.23 no.1
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• pp.80-90
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• 2019

Even though Non-Volatile Memory (NVM) is used for data storage, a page table should be built to access data in it. And this observation leads us to the Persistent Page Table (PPT) scheme that keeps the page table in NVM persistently. By the way, processors have different page table structures and really operational page table cannot be built without virtual and physical addresses of NVM. However, those addresses are determined dynamically when NVM storage is attached to the system. Thus, the PPT should have system-independent and also address-independent structure and really working system-dependent page table should be built from the PPT. Moreover, entries of PPT should be updated atomically and, in this paper, we describe the design of PPT that meets those requirements. And we investigate how file systems can decrease the journaling overhead with the swap operation, which is a new operation created by the PPT. We modified the Ext4 file system in Linux and experiments conducted with Filebench workloads show that the swap operation enhances file system performance up to 60%.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.368-377
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• 2021

This study analyzed the determinants of capital structure based on the financial statements of agricultural corporations disclosed on the DART(data analysis, retrieval and transfer system) of the Financial Supervisory Service since 2011, when the Korea international financial reporting standards (K-IFRS) was introduced. There have been many empirical studies on the capital structure so far, but there are no studies targeting agricultural corporations. The sample period of agricultural corporations was from 2015 to 2019, with the debt ratio as the dependent variable, and among the variables suggested as meaningful in existing empirical studies, ROA(profitability), SIZE(corporate size), LIQ(liquidity), TA(tangible asset ratio), FA(fixed long-term suitability ratio), and GROWTH(growth potential) were selected as independent variables and panel data analysis was performed. As a result of the analysis, it was found that the debt ratio decreased as the ROA and SIZE of agricultural corporations increased. This can be interpreted as supporting the pecking order theory rather than the static trade-off theory in the relationship between the ROA and SIZE of Korean agricultural corporations with the capital structure. In addition, it was found that the debt ratio increased as the FA increased. These results suggest that Korean agricultural corporations need to establish a financing policy in consideration of ROA, SIZE, and FA.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.63-68
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• 2022

This After the debut of 5G, our lives have changed a lot. In particular, the proliferation of wireless network services through smartphones and LTE has completely changed the existing mobile communication services that are limited to voice/text communication between individuals and individuals, and new innovative services have emerged in all aspects of personal and corporate activities. This study verified the relationship between the social characteristics of 5G services and users' willingness to use 5G services. It analyzed the influence relationship between independent variables (social reality, subjective norms), media variables (perceived usefulness) and dependent variables (use intention), set hypotheses, and identified the media effects of perceived usefulness. The measurement items of variables are defined, and the research model of 5G service usage intention is designed. A questionnaire survey was conducted on the measurement items for users who have experience in using 5G services. Based on this result, among the social factors of users of 5G services, social reality and subjective norms are suitable factors to improve users' intentions. And through this research we put forward the enlightenment, discussed the limitations of the research and future research directions.

• Information Systems Review
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• v.26 no.2
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• pp.45-57
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• 2024

This study develops a deep learning-based methodology for predicting Crude Palm Oil (CPO) prices. Palm oil is an essential resource across various industries due to its yield and economic efficiency, leading to increased industrial interest in its price volatility. While numerous studies have been conducted on palm oil price prediction, most rely on time series forecasting, which has inherent accuracy limitations. To address the main limitation of traditional methods-the absence of stationarity-this research introduces a novel model that uses the ratio of future prices to current prices as the dependent variable. This approach, inspired by return modeling in stock price predictions, demonstrates superior performance over simple price prediction. Additionally, the methodology incorporates the consideration of lag values of independent variables, a critical factor in multivariate time series forecasting, to eliminate unnecessary noise and enhance the stability of the prediction model. This research not only significantly improves the accuracy of palm oil price prediction but also offers an applicable approach for other economic forecasting issues where time series data is crucial, providing substantial value to the industry.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.63-70
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• 2011

In this paper, we proposed a method for estimating energy expenditure using the unfixed axis of the accelerometer. Most studies adopted waist-placement because of the fact that the waist is close to the center of mass of a whole human body. But we adopted pocket-placement, which is capable of using unfixed axis of sensor, that is more convenient than conventional methods. To evaluate the proposed method, 28 male subjects performed walking and running on a motor driven treadmill. All of subject put on the indirect calorimeter and fixed accelerometer, then data were simultaneously measured during exercise. The regression analysis was performed using the test group(n=20) and the regression equation was applied to the control group(n=8). A strong linear relationship between energy expenditure and unfixed accelerometer signal was found. Futhermore, the coefficient of determination was significantly reliable($R^2$=0.98) and showed zero of p-value. The error of energy expenditure estimation between indirect calorimeter and two types of accelerometer was 15.0%(fixed) and 17.0%(unfixed) respectively. These results show the possibilities that the unfixed accelerometer can be used in estimating the energy expenditure during exercise.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.