• Information Systems Review
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• v.23 no.3
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• pp.177-200
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• 2021

Recently, the use of prepaid electronic payments such as electronic wallets, digital currency and prepaid points is gradually increasing. Prepaid electronic payments has the characteristic of being used after charging first. This study empirically investigated the factors affecting the intention to use online charging in order to help improve the service that require prepaid recharge by applying transformed TAM. Since there are not many previous studies for the intention to use online charging, we extract factors through preceding researches for electronic cash and mobile easy payment. Also we analyze the intention to use online charging for transportation card users, focusing on the moderating effects. As a result of the study, it was found that 'convenience', 'ubiquity', and 'self-efficacy' among the independent variables had a positive (+) effect on mediation variable 'perceived usefulness'. 'Perceived usefulness' was analyzed to have a significant influence on the dependent variable 'usage intention'. According to users' gender, internet usage time, internet shopping frequency, online charging frequency and transportation card usage type, the moderating effect was significant on 'perceived usefulness' and 'usage intention'. As an implication, it was suggested that service improvement and differentiated marketing are needed in direction of increasing the usefulness of services. Additional research directions were proposed for services such as e-wallets, prepaid points and digital currencies by adding other factors and moderate variables.

• Information Systems Review
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• v.24 no.1
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• pp.157-181
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• 2022

As competition in the airline industry intensifies, effective airline service quality evaluation has become one of the main challenges. In particular, as big data analytics has been touted as a new research paradigm, new research on service quality measurement using online review analysis has been attempted. However, these studies do not use review titles for analysis, relyon supervised learning that requires a lot of human intervention in learning, and do not consider airline characteristics in classifying service quality dimensions.To overcome the limitations of existing studies, this study attempts to measure airlines service quality and to classify it into the AIRQUAL service quality dimension using online review text as well as title based on self-trainingand sentiment analysis. The results show the way of effective extracting service quality dimensions of AIRQUAL from online reviews, and find that each service quality dimension have a significant effect on service satisfaction. Furthermore, the effect of review title on service satisfaction is also found to be significant. This study sheds new light on service quality measurement in airline industry by using an advanced analytical approach to analyze effects of service quality on customer satisfaction. This study also helps managers who want to improve customer satisfaction by providing high quality service in airline industry.

• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.107-116
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• 2024

This study is a descriptive research study to determine the extent to which end-of-life care stress, death awareness, and prior decision-making attitudes of nurses at a hospice and palliative nursing institution have an impact on end-of-life care performance. The subjects of this study were 200 nurses working at a hospice and palliative nursing institution. Data collection for this study was conducted from August 9 to September 30, 2021, using two methods: written questionnaire and internet survey. The data analysis method used Pearson's correlation coefficient to analyze the relationship between the subjects' end-of-life care stress, death awareness, prior decision-making attitude, and end-of-life care performance. Hierarchical Regression was used to identify factors affecting the subject's end-of-life care performance. The results of this study showed a significant correlation between end-of-life care performance and death awareness (r=.22, p=.002), and end-of-life care performance and prior decision-making attitude (r=.20, p=.004). And prior decision-making attitude and death awareness had a significant impact on end-of-life care performance. As death awareness and prior decision-making attitudes increased, end-of-life care performance increased, and end-of-life care stress did not appear to be a statistically significant factor influencing end-of-life care performance. In order to improve hospice nurses' ability to provide end-of-life care, intervention that takes into account the influencing factors is required.

• Information Systems Review
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• v.22 no.2
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• pp.43-52
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• 2020

The mobile game industry has become the one of the fastest growing industries with its astonishing market size. Despite its industrial importance, a few studies empirically considered actual purchasing behavior in mobile games rather than the intention to purchase. Therefore, this paper investigates the key drivers of in-app purchase by analyzing the game-log dataset provided from a mobile game company in Korea. Specifically, the effects of goal-directed, habitual and social-interacted playing behavior are analyzed on in-app purchase. Furthermore, the recursive relationship with playing and purchasing behaviorsis also considered. The result shows that all suggested factors have positive impacts on in-app purchase in the current period. In addition, the effect of previous habitual playing has a positive impact, but the effect of social-interacted playing and in-app purchase in the previous period have negative impacts on in-app purchase of the current period. These findings can improve our understanding of the impact of game playing on in-app purchase in mobile games, and provide meaningful insights for researchers and practitioners.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.8-15
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• 2024

In this study, nitrogen plasma treatment was performed in 5, 10, and 15 minutes to improve the tetracycline adsorption performance of activated carbon. All nitrogen plasma-treated activated carbons showed improved tetracycline adsorption compared to untreated activated carbons. The nitrogen functional groups in activated carbon lead to chemisorption with tetracycline via π-π interactions and hydrogen bonding. In particular, in the nitrogen plasma treatment at 80 W and 50 kHz, the activated carbon treated for 10 minutes had the best adsorption performance. At this time, the nitrogen content on the surface of the activated carbon was 2.03% and the specific surface area increased to 1,483 m²/g. As a result, nitrogen plasma treatment of activated carbon improved its physical and chemical adsorption capabilities. In addition, since the adsorption experimental results were in good agreement with the Langmuir isotherm and pseudo-second order model, it was determined that the adsorption of tetracycline on the nitrogen plasma-treated activated carbon was dominated by chemical adsorption through a monolayer. As a result, nitrogen plasma-treated activated carbon can be used as an adsorbent to efficiently remove tetracycline from water due to the synergistic effect of physical adsorption and proactive chemical adsorption.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.89-100
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• 2022

Objective: To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). Materials and Methods: A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer's disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test. Results: The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer's continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer's disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD. Conclusion: We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.1
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• pp.22-29
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• 2024

In this study, we summarized the definition of smart vegetable seedling production technology, analysis of smart seedling production system, a hardware and software configuration model for smart seedling production system, research and development trends in smart seedling production system, and proposed future research and development plans for smart seedling production technology. Smart vegetable seedling production is a data-based seedling production, management, and distribution system that utilizes 4th Industrial Revolution technology to improve seedling productivity and quality. The production of vegetable seedlings using smart seedling production technology can be efficiently managed by collecting, analyzing, and managing information on seedlings, environment, and tasks at each stage of production by linking with the smart seedling integrated management system. However, there is still a lack of standardization of seedling standards and quality for each vegetable crop to establish smart seeding production technology, as well as development of smart seedling production element technology, which requires national wide R&D support.