• Journal of the Korean Solar Energy Society
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• v.38 no.1
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• pp.1-11
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• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.165-170
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• 2021

This study analyzed the effect of housing price changes on the performance of Korean regional banks using DOLS model. The analysis shows that housing price changes does not have a statistically significant effect on the loan growth, profitability and soundness of regional banks. Among macroeconomic variables, only short-term interest rates have a significant positive effect on any model. This means that a rise in short-term interest rates significantly increases loans by regional banks, which leads to a significant increase in profitability, but has a significant negative impact on soundness. On the other hand, bank characteristics variables are found to have a significant negative effect on the loan growth, profitability and soundness of Korean regional banks.

• Atmosphere
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• v.31 no.1
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• pp.73-83
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• 2021

Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.719-740
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• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Journal of Distribution Science
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• v.18 no.6
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• pp.77-82
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• 2020

Purpose: In the period of international integration, how is the implementation of intellectual property regulation in developing countries? Do intellectual property rights help attract more Foreign direct investment (FDI)? This study aims to show the effect of intellectual property rights, reflect in the number of patent registered (Patent distribution into two components: Patent_residents and Patent_non-residents) on FDI attraction in Vietnam. Research design, data and methodology: Using Autoregressive distributed lag (ARDL) model for the data collected from 1990 to 2018 with EViews version 9 software. Conclusions: The results indicate that the number of patent protection has a positive effect on FDI in both short term and long term. In particular, only patent registration of foreign individuals and organizations has a significant positive effect on attracting FDI, while that of Vietnamese patents is not statistically significant. From the results of this study, we provide some recommendations to help attract FDI based on raising awareness of intellectual property rights: Increase international cooperation for innovation to learn and encourage patent; Improve the capac ity of inventing as well as the ability to register patents of Vietnamese people; Government agencies are tasked to support a nd review registration procedures; Encouraging patent registration based on the patent.

• Asia-Pacific Journal of Business
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• v.2 no.1
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• pp.1-22
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• 2011

Chamber of commerce and industry plays important role for development of business community and creating vibrant competition. Present paper compares chambers operations in Bangladesh, especially, Sylhet Chamber of Commerce and Industry(SCCI) by reviewing global models of chambers practices. The study identifies important gaps between international standards and Bangladesh practices. Mostly practiced chambers model in the world are: Continental Model, Anglo-Saxon Model and Mixed model or Asian model. Like other Asian countries, chambers in Bangladesh including SCCI, have been following Mixed Model. The empirical study found that SCCI is performing different developmental functions like accumulating members, collecting revenue, fulfilling corporate social responsibility and providing business development services to its members and business community. The notable constraining factors of SCCI operations are: short term orientation in assembling members, limited functional activities, lack of creative endeavors in diversifying services, linkage between SCCI and academic institutions, poor research involvement etc. The necessary suggestions for improvement of chambers performance include adoption of creative measures in various operations, providing training to the members, assisting entrepreneurs in obtaining industrial finance and extending support in the establishment of specialized industrial zone for attaining long term developmental objectives.

• Management & Information Systems Review
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• v.27
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• pp.53-69
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• 2008

In this paper we analyse performance of value strategy and moving average method among the non-financial listed companies whose fiscal year ends at December in the Korean Stock Exchange between 1996 and 2005. And we analyse combination investment performance of value investment and moving average method. After the analysis objective enterprises divide with the value stock and the growth stock, in accordance with moving average method we divide ascending stock and descending stock. And we compose 6 portfolios with combination of value stock, growth stock, ascending stock and descending stock. Using the difference of investment performance of these portfolios, when fundamental analysis and technical analysis method all considering we measure investment performance. The major findings of this research are as follows: First, the value strategy of buying value stocks and selling growth stocks were effective in the long-term investment. Second, using the moving average method, technical analysis were effective in the case of the short-term investment. Third, the portfolios combined fundamental analysis and technical analysis were more effective than investment performance of technical analysis.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.251-258
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• 2011

The existing evaluation systems based on financial performance summarize the information about past results and focus on short-term performance, and so they have the limits to explain the future value of firms and to make a long-term strategic performance. By this reason, as a way to increase the future value, the development of the integrated performance evaluation system with which we may manages financial performance and knowledge assets together has been required recently. This study puts together various researches for the evaluation of knowledge assets, and analyzes the existing studies for the domestic medical devices industry and the tendency of introduction for business practice. Under this analysis, this study develops the knowledge asset evaluation indexes for medical devices industry by using the Balanced Score Card (BSC) of Kaplan & Norton(1992), and then presents the evaluation model by applying the Analytic Hierarchy Process (AHP) of Saaty(1980) to get the weight for each index. With the final evaluation model, we can calculate the evaluation score combined with both the quantitative indexes and the qualitative indexes at once.

• Korea Journal of Hospital Management
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• v.8 no.2
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• pp.5-23
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• 2003

To survive in the competitive environment, hospitals pay more attention to patient satisfaction than ever before. Nurses are the employee that have frequent interactions with patients in a hospital, and therefore, the effective management of nursing staff is crucial to maintain high level of patient satisfaction. Searching for a way to an effective human resource management in nursing, this study attempted to investigate the pre-dispositional factors of customer orientation of registered nurses in a hospital. The customer orientation concept is originated from marketing literature and defined as the attitude of employee that focus on establishing a long term relationship rather than short term gains in dealing with customers. The study hypothesized that the personal trait of individual and the perceived level of empowerment affect the level of customer orientation of nurses. We tested the hypothesis 10 a teaching hospital. Three-hundred seventy two nurses were surveyed and 235 responses were collected. Out of the 235 responses, 24 responses were discarded due to the incomplete answers to the questionnaire and 211 responses were analyzed. The data were analyzed using factor analysis and multiple regression analysis. The results showed that the enjoyment dimension of customer orientation was affected by the agreeableness, consciousness, and openness of personal traits and the need dimension of customer orientation was affected by the agreeableness and level of empowerment. Based on the results the research and nursing resources management implications were discussed.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.49-60
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• 2023

The study attempts to examine the relationship among revenue growth factors from different angles and provides a comprehensive overview of tax revenue collection for developing countries. The impact of income tax, customs duty, and value-added tax on the gross domestic product is examined using the ordinary least-square (OLS) multiple regression approach. To confirm the association, a multiple regression model is applied to time-series data. SPSS software, MS Excel, is used to draw the empirical results, trend analysis, and some graphical presentation to reach the study's objective. The findings show that while the value-added tax has a significant impact and the highest coefficient, regardless of country, income tax and customs duty may or may not be significant depending on the circumstances. It triggers effectual and efficacious economic growth. The paper has implications in policy-making areas where governments are seeking how to stimulate revenue growth effectively and efficiently. To promote economic growth, the tax net and tax rate on luxury goods should be increased along with human resources in the tax administration for the short term. But in the long term, decentralization & digitization of tax administration, dismantling the existing tax barriers and good governance are necessary.