• Journal of the Korea Organic Resources Recycling Association
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• v.3 no.2
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• pp.25-36
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• 1995

It is important to separate the compostables from waste for successful operation of composting plant, since various compositions are mixed in it. For the separation of compostables, it is necessary to estimate total amounts of compostables from several sources. Based on it, required capacity and number of composting plant as well as proper waste collection and transportation system can be determined. So, amounts of garbage, major target material for composting. were estimated in this study. In survey of unit garbage generation(UGG). different estimation results would be obtained depending on the basis of its measurement. However, previous researches did not consider it. In this paper, the correlations between area and the number of user of garbage source were analyzed to find the related equations which were apllyed to estimation of total generation. Obtained results are as the following. Relative variations of measured UGG based on area and custumer are 62.5 and 52.8, respectively. In linear regression, related equation between area and custumer was Y=0.244X+59.0 (X=area, Y=custumer). The correlation factor r is 0.904. Equation Y=616.5X/(X+1215.4) was also obtained from linear regression using Monod equation (r=0.720). From the first order equation and measured data of UGG based on custumer, amounts of garbage generation from restaurant in Seoul and the whole country were calculated to 2043.9 ton/d and 9014.0 ton/d, respectively. But, the values calculated from measured data of UGG based on area were as low as 821.3 ton/d Cin Seoul) and 3821.0 ton/d(in the whole country). Consequently, the measurement of unit garbage generation based on the number of custumer was more favorable to lessen the points of survey and to guarantee the representative values. Especially, it would fit well on restaurant having statistics of area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.1
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• pp.103-113
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• 2020

Jack-up drilling rigs are widely used in the offshore oil and gas exploration industry. Although originally designed for use in shallow waters, trends in the energy industry have led to a growing demand for their use in deep sea and harsh environmental conditions. To extend the operating range of jack-up units, their design must be based on reliable analysis while eliminating excessive conservatism. In current industrial practice, jack-up drilling rigs are designed using the working(or allowable) stress design (WSD) method. Recently, classifications have been developed for specific regulations based on the load and resistance factor design (LRFD) method, which emphasises the reliability of the methods. This statistical method utilises the concept of limit state design and uses factored loads and resistance factors to account for uncertainly in the loads and computed strength of the leg components in a jack-up drilling rig. The key differences between the LRFD method and the WSD method must be identified to enable appropriate use of the LRFD method for designing jack-up rigs. Therefore, the aim of this study is to compare and quantitatively investigate the differences between actual jack-up lattice leg structures, which are designed by the WSD and LRFD methods, and subject to different environmental load-to-dead-load ratios, thereby delineating the load-to-capacity ratios of rigs designed using theses methods under these different enviromental conditions. The comparative results are significantly advantageous in the leg design of jack-up rigs, and determine that the jack-up rigs designed using the WSD and LRFD methods with UC values differ by approximately 31 % with respect to the API-RP code basis. It can be observed that the LRFD design method is more advantageous to structure optimization compared to the WSD method.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.63-86
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• 2020

The tax lease scheme for ships is an advanced ship financing tool that generates tax benefits through accelerated depreciation of capital allowances and transferring them to the ship operator (leasee) via reductions in rental payments. The scheme was introduced by Japan in 1978 and by France in 1998 to support their shipping and shipbuilding industries. The size of tax benefits varies by country depending on the depreciation rate for ships, corporate tax rate, and the tax system on profits from the sale of ship. This study uses a virtual model of the Korean tax lease scheme for ships based on the French tax lease scheme. The size of tax benefits is calculated and compared to those in the French and Japanese tax lease schemes. According to the analysis, the size of the tax benefit was approximately 19% for France, 14% for Japan, and 12% for Korea. This is differentiated by the country's depreciation rate and corporate tax rate, which have the greatest impact on the size of tax benefits. For the Korean virtual model, if the tax benefits are distributed by the operator and the investor at the rate of 75:25, the operator is expected to enjoy tax benefits equivalent to about 9% of the ship price and the investor to enjoy 3%. Despite limited information and data regarding the tax lease scheme for ships, this study was the first attempt in Korea to design a virtual model of the Korean tax lease scheme based on some predictable assumptions. Therefore, a group of shipping, financing, and legal experts will follow up on more professional and practical reviews of the model in the near future. Hence, this study will serve as a small contribution to the early introduction of the Korean tax lease scheme for ships.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.37-57
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• 2018

With the spread of smart phones, interest in mobile media is on the increase as useful media recently. Mobile media is assessed as having differentiated advantages from existing media in that not only can they provide consumers with desired information anytime and anywhere but also real-time interaction is possible in them. So far, studies on mobile advertising were mostly researches analyzing satisfaction with, and acceptance of, mobile advertising based on survey, researches focusing on the factors affecting acceptance of mobile advertising messages and researches verifying the effect of mobile advertising on brand recall, advertising attitude and brand attitude through experiments. Most of the domestic mobile advertising studies related to advertisement effect and advertisement attitude have been conducted through experiments and surveys. The advertising effectiveness measure of the mobile ad used the attitude of the advertisement, purchase intention, etc. To date, there have been few studies on the effects of mobile advertising on actual advertising data to prove the characteristics of the advertising platform and to prove the relationship between the factors influencing the advertising effect and the factors. In order to explore advertising effect of mobile advertising platform currently commercialized, this study defined advertising characteristics and media characteristics from the perspective of advertiser, advertising platform and publisher and analyzed the influence of each characteristic on advertising effect. As the advertisement characteristics, we classified advertisement format classified by bar type and floating type, and advertisement material classified by image and text. We defined advertisement characteristics of advertisement platform as Hedonic and Utilitarian media characteristics. As a dependent variable, we use CTR, which is the ratio of response (click) to ad exposure. The theoretical background and the analysis of the mobile advertising business, the hypothesis that the advertisement effect is different according to the advertisement specification, the advertisement material, In the ad standard, bar ads are classified as static framing, Floating ads can be categorized as dynamic framing, and the hypothetical definition of floating advertisements, which are high-profile dynamic framing ads, is highly responsive. In advertising, images with high salience are defined to have higher ad response than text. In the media characteristics classified as practical / hedonic type, it is defined that the hedonic type media has a more relaxed tendency than the practical media, and there is a high possibility of receiving various information because there is no clear target. In addition, image material and hedonic media are defined to be highly effective in the interaction between advertisement specification and advertisement material, advertisement specifications and media characteristics, and advertisement material and media characteristics. As the result of regression analysis on each characteristic, material standard, which is a characteristic of mobile advertisement, and media characteristics separated into 'Hedonic' and 'Utilitarian' had significant influence on advertisement effect and mutual interaction effect was also confirmed. In the mobile advertising standard, the advertising effect of the floating advertisement is higher than that of the bar advertisement, Floating ads were more effective than text ads for image ads. In addition, it was confirmed that the advertising effect is higher in the practical media than the hedonic media. The research was carried out with the big data collected from the mobile advertising platform, and it was possible to grasp the advertising effect of the measure index standard which is used in the practical work which could not be grasped in the previous research. In other words, the study was conducted using the CTR, which is a measure of the effectiveness of the advertisement used in the online advertisement and the mobile advertisement, which are not dependent on the attitude of the ad, the attitude of the brand, and the purchase intention. This study suggests that CTR is used as a dependent variable of advertising effect based on actual data of mobile ad platform accumulated over a long period of time. The results of this study is expected to contribute to establishment of optimum advertisement strategy such as creation of advertising materials and planning of media which suit advertised products at the time of mobile advertisement.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.25-39
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• 2015

$CO_2$ geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing $CO_2$ safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of $CO_2$ storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the $CO_2$ sequestration initiative. More detailed characterization of the geological storage and the simulation of $CO_2$ migration might be an essential for the CCS demonstration.

• Journal of Hospice and Palliative Care
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• v.8 no.2
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• pp.190-199
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• 2005

Purpose: Objectives of this study was to investigate the level of anxiety and depression according to the stages of autologous and allogeneic hematopoietic stem cell transplantation (HSCT). It would be provide the basis for effective psycho-emotional nursing intervention. Methods: We report on 52 patients, including 19 with autologous HSCT, and 33 with allogeneic HSCT from August 2002 to August 2003, at a university hospital. Spielberger's State-Trait Anxiety Inventory and Jung's Depression Inventory were used to measure levels of anxiety and depression, respectively, at admission time, the day before HSCT, and discharge time. Data was analyzed using SAS program that included Chi-square test, Fisher's exact test, repeated measures ANOVA and Stepwise multiple regression analysis. Results: In all stages of HSCT, the level of anxiety of patients who underwent allogeneic HSCT was significantly higher than that of autologous HSCT (P=0.047). The depression at the day before HSCT was significantly higher than that at admission. The major variable affecting anxiety in autologous HSCT was depression. Specially depression and gender were significant predictors to explain anxiety in allogeneic HSCT at admission time (61%). Experience of relapse and gender were significant predictors to explain anxiety in allogeneic HSCT at discharge time (36%). Conclusion: We recommend that the anxiety and depression be researched during the stages of allogeneic HSCT, specifically in the day before HSCT. It is necessary to develop an effective psycho-emotional nursing intervention according to the stages of HSCT.

• Journal of Korean Home Economics Education Association
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• v.27 no.3
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• pp.79-97
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• 2015

Curriculum may be defined as everything students learn at school or the specific plan of a subject that students are supposed to learn. The purpose and goals of the curriculum or who is in charge of developing the curriculum may differ by country. This study aimed at comparing the mechanisms in which the Home Economics curriculum is implemented in Korea and the Unite States at different levels. Considering that Korean government now supports increased autonomy of schools, allowing them to execute curricula according to their educational environments, it is meaningful that the advantages and disadvantages of the implementation mechanisms of two countries are explored. Specifically, middle schools in a City of Kyung-gi Province in South Korea and three states(Wisconsin, Ohio, and Washington states) in the United States are examined. The curriculum documents at different levels as well as study plans used by actual teachers are compared for this purpose. In case of South Korea, the nation state is in charge of curriculum development and the curriculum document defines the educational contents to detail in order to provide standardized learning experience to students. This type of closely controlled system warrants standardized educational contents and thus allows nation-wide assessment using standardized measures. On the other hand, it is difficult to accommodate diversities among students in terms of aptitudes and learning styles, and also limits creativity enhancement or integrative approach to teaching and learning. In comparison, curriculum in the United States is rather loosely defined, and more autonomy is granted to schools and teachers. Each of these two different systems may have advantages and disadvantages of their own. The findings of this study is expected to provide implications to curriculum development as well as to the development of framework and guidelines to the curriculum implementation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.5
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• pp.1-13
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• 2015

The purpose of this research is to do exploratory analysis on the relationships between demographic characteristics of entrepreneurial candidates and their developmental level of entrepreneurial traits as well as the choice of business field. We analyzed gender, age, and educational level of the entrepreneurial candidates and their developmental level of entrepreneurial traits such as achievement tendencies, degree of awareness, planning skills, sincerity, interpersonal relationship, and problem-solving skills. Industry fields were classified into 4 types: restaurants, retail, services, internet business. Descriptive statistical analyses, logistic regressions, and variance analyses were performed about the sample data gathered from 1,441 persons since the year 2002 to 2014. Males and highly educated above university preferred service industry than restaurant, retail, and internet business. Females preferred internet business, retail, and restaurants than service industry field. The young persons under 20 showed higher probability to choose internet business. The college level and high school graduates preferred retail and restaurants than service industry. The developmental level of entrepreneurial traits were higher in male and highly educated. By this study, we could find the divide between groups with high and low probabilities of failure: restaurants and retail field showed higher failure probability than service industry in the business fields of self-employed. Furthermore, we could identify that entrepreneurial traits also had been developed differently depending on the groups. It is necessary to refrain from entering into the fields with high failure probabilities as well as to provide supporting policies to build the systems and environment to reduce the cases to begin new business without special knowledges and know-hows. The competency development training should be provided in the early stage of start-ups considering their entrepreneurial traits and aptitudes. Not only the assessment of the entrepreneurial traits but also professional counseling from initial stage are necessary.

• Progress in Medical Physics
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• v.22 no.1
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• pp.35-41
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• 2011

For overall system test, hidden-target test have been used using film which leads to inherent analysis error. The purpose of our study is to quantify this error and to propose gel dosimeter based verification technique for 3-dimensional target point error. The phantom was made for simulation of human head and this has ability to equip 10 gel-dosimeter. $BANGkit^{TM}$ which we are able to manufacture whenever it is needed as well as to easily change the container with different shapes was used as a gel dosimeter. The 10 targets were divided into two groups based on shapes of areas with a planned 50% isodose line. All treatment and analysis was performed three times using Novalis and $BrainSCAN^{TM}$. The target point error is $0.77{\pm}0.15mm$ for 10 targets and directional target point error in each direction is $0.54{\pm}0.23mm$, $0.37{\pm}0.08mm$, $0.33{\pm}0.10mm$ in AP (anterior-posterior), LAT (lateral), and VERT (vertical) direction, respectively. The result of less than 1 mm shows that the treatment was performed through each precise step in treatment procedure. In conclusion, the 3-dimensional target point verification technique can be one of the techniques for overall system test.