• Korean Journal of Applied Biomechanics
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• v.31 no.2
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• pp.87-94
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• 2021

Objective: Identification of meaningful patterns and trends in large volumes of unstructured data is an important task in various research areas. In the present study, we gathered golf swing image data and did quantitative analysis of swing image. Method: We collected golf swing images of 30 novice players and 30 professional players in this study. Results: We selected important features of swing posture and employed data mining algorithm to classify whether a player is an expert or a novice. Moreover, our proposed method could offer quantitative advices for golf beginners for correcting their swing. Conclusion: Finally, we found a possibility that our proposed method can be expanded to golf swing correction system

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.226-247
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• 2024

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

• Atmosphere
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• v.31 no.3
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• pp.311-326
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• 2021

To improve the predictability of high-impact weather phenomena around Seoul, where a larger number of people are densely populated, KMA conducted the intensive observation from 22 June to 20 September in 2020 over the Seoul area. During the intensive observation period (IOP), the dropsonde from NIMS Atmospheric Research Aircraft (NARA) and the radiosonde from KMA research vessel Gisang1 were observed in the Yellow Sea, while, in the land, the radiosonde observation data were collected from Icheon and Incheon. Therefore, in this study, the effects of radiosonde and dropsonde data during the IOP were investigated by Observing System Experiment (OSE) based on Korean Integrated Model (KIM). We conducted two experiments: CTL assimilated the operational fifteen kinds of observations, and EXP assimilated not only operational observation data but also intensive observation data. Verifications over the Korean Peninsula area of two experiments were performed against analysis and observation data. The results showed that the predictability of short-range forecast (1~2 day) was improved for geopotential height at middle level and temperature at lower level. In three precipitation cases, EXP improved the distribution of precipitation against CTL. In typhoon cases, the predictability of EXP for typhoon track was better than CTL, although both experiments simulated weaker intensity as compared with the observed data.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.939-947
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• 2016

As the number of legacy database systems and the size of data to manipulate have been vastly increased, it has become more difficult and complex to analyze characteristics of data. To improve the efficiency of data analysis and help administrators to make decisions in business life, BI(Business Intelligence) system is used. To construct data warehouse and cube from legacy database systems makes it easy and fast to transform raw data into integrated and categorized meaningful information. In this paper, we built a BI system for an University administration. Several source system databases were integrated to data warehouse to build data cubes. The implemented BI system shows much faster data analysis and reporting ability than the manipulation in legacy systems. It is especially efficient in multi dimensional data analysis, nonetheless in single dimensional analysis.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.95-104
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• 2020

This study examines the effect of fintech on retail banks stock return listed in Indonesia Stock Exchange for the period of 2016-2018 as today's new technology lead to the emergence of fintech companies playing the same role as retail banks in the financial industry. This study is conducted quantitatively using monthly data from January 2016 to October 2018 and uses fintech as independent variable, proxied by fintech funding frequency and fintech funding value. Data transformation is conducted due to data volatility. The data of fintech funding, both frequency and value, is transformed into standardized fintech funding and growth of fintech funding. The data is obtained from Crunchbase, while the data of stock returns is obtained from Investing. This study further analyzes the data using Fama French Three-Factor Model and panel data regression. We found that fintech has no significant effect on retail banks' stock returns listed in Indonesia Stock Exchange for the period of 2016-2018. The findings of the study provide some useful insights in understanding fintech companies' current position to retail banks in Indonesia. This study also suggests banking institutions, fintech companies, policy-makers, and others to take advantageous steps in building inclusive financial sectors.

• ETRI Journal
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• v.28 no.2
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• pp.191-204
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• 2006

Many previous studies of data quality have focused on the realization and evaluation of both data value quality and data service quality. These studies revealed that poor data value quality and poor data service quality were caused by poor data structure. In this study we focus on metadata management, namely, data structure quality and introduce the data quality management maturity model as a preferred maturity model. We empirically show that data quality improves as data management matures.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.1-13
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• 2020

This study aims to measure the efficiency and productivity change of 30 domestic construction companies from 2010 to 2018 using data envelopment analysis(DEA) and Malmquist productivity index (MI). In particular, we used the number of employees, capital stock, and non-current assets as input variables, and sales and net income as ouput variables for the analysis. The dataset used for the analysis of efficiency and productivity changes is the employee profile and financial statements for the companies from 2010 to 2018. We found that the MI of the 30 companies is greater than one since 2013. This is because many years of TEC (Technical Efficiency Change) is greater than 1, which means that the productivity index increases as the TEC increases. In addition, the MI value was less than 1, which lowered the productivity of construction firms in 2018. The results of the study may help decision makers to find effective future management plans by analyzing the internal and external factors.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.3
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• pp.487-495
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• 2001

Purpose : In this study, task performance and job satisfaction of nurses in non-life insurance companies were examined to improve the personnel management in their companies. Method : Data collection was done with 119 nurses in non-life insurance companies in October and November, 1999. Data analyses were performed using SPSS Win 8.0 package. Result: The Results were as follows: 1. The tasks most commonly performed by nurses were 'medical fee inspection', 'education for staves', 'management of the injured', 'management of injury and disablement'. 2. The mean score of total job satisfaction was 3.2(interaction. 3.8; professional status, 3.6; autonomy, 3.4; task requirements, 3.1; administration, 2.8; pay and advancement, 2.6). 3. Task performance was significantly correlated with job satisfaction total score(r=0.478, p<.01). The item, 'executing statistical works and data analyses related with injury and disablement', was highly correlated with job satisfaction total score(r=0.418, p<.01). 4. The amount of task performance was significantly correlated with educational background and position. The job satisfaction level significantly correlated with personal experience and position. Conclusion : To improve the work efficiency and job satisfaction in the companies, it is necessary to set the bounds of task performance and to enlarge the promotion opportunities to higher positions.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.35-38
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• 2004

We developed a Near Real-Time Validation System (NRVS) for the Level-2 Products of AQUA Satellite. AQUA satellite is the second largest project of Earth Observing System (EOS) mission of NASA. This satellite provides the information of water cycle of the entire earth with many different forms. Among its products, we have used five kinds of level-2 geophysical parameters containing rain rate, sea surface wind speed, skin surface temperature, atmospheric temperature profile, and atmospheric humidity profile. To use these products in a scientific purpose, reasonable quantification is indispensable. In this paper we explain the near real-time validation system process and its detail algorithm. Its simulation results are also analyzed in a quantitative way. As reference data set in-situ measured meteorological data which are periodically gathered and provided by the Korea Meteorological Administration (KMA) is processed. Not only site-specific analysis but also time-series analysis of the validation results are explained and detail algorithms are described.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.351-362
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• 2020

This research investigates the credit management guidelines to strengthen Thai industrial sector. The research has been simulated from the findings of both qualitative and quantitative of 500 questionnaires distributed to industrial business executives in Thailand. The data were analyzed by descriptive analysis categorized into SME and large enterprises, and SEM to conduct the model in consistent with the empirical data. The results show that: (1) the credit management guidelines consist of 4 factors: a) characteristics management b) financial management c) operations management and d) assets management. The business executives gave overall importance on the guidelines at a high level with an average of 3.86. (2) The development of SEM shows that the model fits with the empirical data at Chi-Square probability level = 0.084, CMIN/DF = 1.164, GFI = 0.965 and RMSEA = 0.018. (3) The characteristics management directly influences the financial management and the operation management. The financial management directly influences on the assets management. The assets management has direct influence on the operations management. The findings show that the characteristics management is the essential starting component in SEM and the financial management factor has the most influence in the assets management variable with standard regression weight of 0.990.