• Management & Information Systems Review
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• v.36 no.1
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• pp.115-141
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• 2017

This study is to find the key factors of the Internet of Things for development in public sector. In previous studies, it is said that Internet of Things can work digital system without human operation and gives a lot of outputs(information) users. Generally, people are a subject of operating digital system in traditional way, while people are an object on the internet of things. In other words, it is possible to work digital system with only networking from things to things. After all, it is reported that these advantages of the Internet of Things make possible to reduce social costs significantly in public sector. However, despite the strengths of the Internet of Things, there is a specific user acceptance of the technology factor for the Internet of Things rarely. It means that developing of the Internet of Things only focuses on the final purpose. If the focus on development meet this purpose, the user is ignored for the specific reason that using a technique. As a result of this, many users gradually decrease the continuous using of the Internet of Things. Thus, in this study, we need to find what critical factors should reflect to the Internet of Things in public sector. To find this result, there is no choice to use Technology Acceptance Model(TAM). Many researchers have proved that Technology Acceptance Model is valid through the four process in model introduction, confirmation, expansion and refinement from 1986 to 2003. The results of this study showed that the result explanatory power of Internet of Things in public sector is the most important factor affecting only perceived social usefulness and ease of use. Finally, it can be seen that the user has a positive attitude toward use, which has a positive effect on the intention to use continuously. The implications of this study are summarized as follows: When the public Internet of Things service is provided, it means that the user can easily understand the result, and when the person and the object communicate the result to each other, they should be able to communicate with each other. This means that a lot of user effort is needed to understand the outcome of the public Internet of Things being provided.

• Atmosphere
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• v.20 no.4
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• pp.467-482
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• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.153-169
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• 2020

A new way of shopping based on virtual assistant, so called voice shopping, is drawing attention. The voice shopping market is growing around the world, and Korea is on the verge of full-scale commercialization of this new shopping. For the development of voice shopping-related industries, it is necessary to research on specific issues related to this new shopping methods, such as the quality of services, efficient processes tailored to new ways, and ways to build customer relationships. As part of such an attempt, the study seeks to determine the factors that affect consumers' perception and attitudes toward voice shopping. The study conducted the analysis based on survey response data of 171 online shopping users. In addition to the typical factors of the technology acceptability model(TAM) such as perceived usefulness and ease of use, the impact of perceived playfulness was included for analyzing the intention on the acceptance of voice shopping. In particular, this study focuses on the impact of user attributes. For the spread of voice shopping, it is necessary to set up a valid target customer and understand users for establishing an effective customer relationship. Therefore, this study tries to analyze how the perceptions on the voice shopping(perceived usefulness, ease of use, and perceived playfulness) are affected by users' attributes, such as user innovativeness and user knowledge level. The result of analysis shows that user innovativeness have a positive relationship with all of perceived usefulness, ease of use, and perceived playfulness. The user knowledge base, however, was not significant to all these three variables. The user knowledge base is shown to have a positive effect on user innovativeness which is the source of positively significant factor for the variable of the perceptions on the voice shopping. Meanwhile, among the variables of extended technology acceptance model, perceived usefulness and perceived playfulness have positive effects on the acceptance of voice shopping, while ease of use has no significant impact on the voice shopping acceptance. Ease of use has a positive relationship with perceived usefulness and playfulness. This study is meaningful in providing implications on the development of voice shopping platforms and related services, and establishment of customer relationship.

• Science of Emotion and Sensibility
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• v.5 no.4
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• pp.59-66
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• 2002

This study was proposed as an exploratory study for understanding the biological bases and structures of three personality models: Eysenck's PEN model, Gray's BIS/BAS model, and Costa & McCrae's Five Factor Model, which was chosen as the major descriptive model regardless of its biological bases. Besides, Eysenck's impulsivity scale, IVE, was added to demonstrate the relationship of P and impulsivity. Concerning personality, most previous reports have explored the relationships between P300 and the introversion-extraversion of Eysenck's theory because of its putative biological bases. In the present study, forty-eight undergraduate took four personality batteries (ERQ-R, NEO-Pl-R, BIS/BAS, and IVE). Two types of oddball tasks including different stimulus duration were used to induce ERPs (50ms for task 1, 300ms for task 2). Distributional topographies of correlation coefficients with personality traits and ERP components were drawn, and considered for the consistent interpretation of the personality model structures. Even though all equivalences for extraversion of personality batteries showed similarities for their intra-correlation, their correlations with P3 amplitudes were dissociate. Eysenck's E might not be the proper psychometric measure for elucidating its biological bases. The present study supported the negative relationship of P3 amplitude and extraversion, which is the consensus of previous studies. Neuroticism and Psychoticism showed correlations with the earlier sensory processing components such as N1 and P2. This result might explain the reason why most of studies have failed to find biological connections relating them. Interaction between gender and personality traits should be considered for the interpretation of correlations. Two types of auditory stimulus duration had different sensitivity to personality traits.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.12-21
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• 2017

From 1960, the government decided to build apartment houses on a large scale in order to resolve the rising housing problems. However, the maintenance issues that have arisen from the deterioration of housing has not received adequate attention. The policy focuses only on the supply of housing. By passing new laws, the durable period during which buildings allowed reconstruction was increased, and long term maintenance plans were treated as important issues. The government was then obligated to establish certain long term maintenance plans and costs by legislating a Housing Act and requiring it be adjusted every three years. However, when planning long-term repair costs, doing so without considering the time value of money would become a problem. In addition, if differences between the planned repair costs and actual costs occur, it becomes necessary to adjust the long-term repair costs but, as of yet, the criteria to adjust such things does not exist. For these reasons, if there is lack of money to execute large-scale repair work, a building is unlikely to respond to deterioration of housing; on the other hand, an unnecessary reserve or pool of money can lead to conflict among residents. Therefore, this paper will propose estimation and adjustment models considering the time value of money for long term maintenance costs of apartment houses.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.583-590
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• 2015

Submarine cable installation is essentials for grid connection between existing power grid and newly produced electricity which will be from offshore wind farm in Southwest sea area of Korea. Especially, submarine cable route and protection method is designed in order to ensure the economical efficiency, workability and stability of submarine cable installation. On this paper, we will give the basic information about the submarine cable route and protection method of offshore wind farm which will be built in Southwest sea area of Korea. For this, we have a numerical simulation at high and low tide based on the third-generation wave model SWAN(Simulating WAves Nearshore) using the long term wave data from Korea Institute of Ocean Science and Technology(KIOST). The results of the study, year mean Hs is 1.03m, Tz is 4.47s and dominant wave direction is NW and SSW When the incident wave direction is NW(Hs: 7.0 m, Tp: 11.76s), the distribution of shallow water design wave height Hs was calculated about 4.0~5.0m at high tide and 2.0~3.0m at low tide. When the incident wave direction is SSW(Hs: 5.84 m, Tp: 11.15s), the distribution of shallow water design wave height Hs was calculated about 3.5~4.5m at high tide and 1.5~2.5m at low tide. The wave direction on a dominant influence in the section of longitude UTM 249749~251349(about 1.6 km) and UTM 251549~267749(about 16.2 km) in the submarine cable route are each NW and SSW. Prominently, wave focusing phenomenon appears between Wi-do and Hawangdeung-do, in this sea area is showing a relatively high wave hight than the surrounding sea areas.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.1
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• pp.81-91
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• 2010

IMO(International Maritime Organization) and the Shipping World rave complied with various kinds of international regulations for maritime safety and marine environmental protection, but the main reason of maritime accidents is that developing countries cannot implement maritime safety related regulations. Although Korea has been a member of the "A group" council of IMO, maritime technology transfer records of Korea are not good. To promote the project of official development assistance in Korea, it is required to select the technology which has a high degree of importance in the fields of maritime safety and has a high degree of demand on the transfer to developing countries, and to concentrate on the selected technology. So, it is necessary to draw valuation factors for maritime safety technology and to decide the priority in order among maritime safety technologies on the basis of valuation factors. Because the weights which show the degree of importance among valuation factors are different from factor to factor, interdependent relationship between factors should be considered on evaluation. In this study, the valuation factors were divided into three groups as the maturity of maritime safety technology, the promotion probability of projects and the degree of importance of technology, and the detailed factors of each group were drawn. A model which used Fuzzy AHP and limiting probability to consider the weights of importance and correlation among valuation factors was developed. To adopt this model, nine types of maritime safety technology in the field of maritime safety information were selected and points were scored for each technology through evaluation. In conclusion, first, ENC related technology was scored to be the highest as 0.0139. Second, the point of ship monitoring technology was scored as 0.0133. Last, oil spill response technology was scored as 0.0132.

• Journal of the Korean Geographical Society
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• v.28 no.4
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• pp.285-297
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• 1993

For the application of the diffusion equation, slope height and maximum slope angle are calculated from the plotted slope profile. Using denudation rate as a solution for the diffusion equation, an apparent age index can be calculated, which is the total amount of denudation through total time. Plots of slope angle versus slope height and apparent age index versus slope height are useful for determining relative or absolute ages and denudation rates. Mathematical simulation plots of slope angle versus slope height can generate equal denudation-rate lines for a given age. Mathematical simulations of slope angle versus age for a given slope height, for equal denudation-rate at a particular profile site, and for comparing to other sites having controlled ages.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.