• Journal of radiological science and technology
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• v.26 no.4
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• pp.39-46
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• 2003

Digital radiographic systems based on solid-state detectors, commonly referred to as flat-panel detectors, are gaining popularity in clinical practice. Large area, flat panel solid state detectors are being investigated for digital radiography. The purpose of this work was to evaluate the active matrix flat panel digital x-ray detectors in terms of their modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). In this paper, development and evaluation of a selenium-based flat-panel digital x-ray detector are described. The prototype detector has a pixel pitch of $139\;{\mu}m$ and a total active imaging area of $14{\times}8.5\;inch^2$, giving a total 3.9 million pixels. This detector include a x-ray imaging layer of amorphous selenium as a photoconductor which is evaporated in vacuum state on a TFT flat panel, to make signals in proportion to incident x-ray. The film thickness was about $500\;{\mu}m$. To evaluate the imaging performance of the digital radiography(DR) system developed in our group, sensitivity, linearity, the modulation transfer function(MTF), noise power spectrum (NPS) and detective quantum efficiency(DQE) of detector was measured. The measured sensitivity was $4.16{\times}10^6\;ehp/pixel{\cdot}mR$ at the bias field of $10\;V/{\mu}m$ : The beam condition was 41.9\;KeV. Measured MTF at 2.5\;lp/mm was 52%, and the DQE at 1.5\;lp/mm was 75%. And the excellent linearity was showed where the coefficient of determination ($r^2$) is 0.9693.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.74-83
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• 2005

The Riparian Buffer Zone has many potential values including the preservation of water quality as well as being ecologically friendly. This study aims to quantitatively analyze the landscape structure index of the Riparian Buffer Zone in the Kyoung-an stream and to produce base information necessary for proper management. The study used aerial images that were applied to geometric corrections for a time series from 1966 to 2000 for land data and also used FRAGSTATS, which is a type of ARCVIEW extension module, as an analysis tool. An analysis of land use change and the Landscape Index revealed that the area of farm land has decreased and that the area of residential property has increased. In addition, there was a slight change for land used for purposes other than farming or for residence. The results of analyzing the Landscape Structure Index, revealed that the NP has increased from 437 in 1966 to 695 in 2000. This data reveals that the change of land use is influenced by various artificial factors. The NPS, which represents the declining degree of patch, decreased from 9.441 to 5.934, revealing that the change of land use has been progressing considerably. In regard to forest areas, land use reduced somewhat but did not indicate a significant change. Therefore, an analysis of the total index reveals that the edge of patch has become more complicated and that the variation index of patch has increased significantly. However, this study reveals that barriers to block pollution have weakened as a result and that there is a need to concentrate on the implementation and the management of the Riparian Buffer Zone. Consequently, this study reveals that substantial research is necessary in order to carry out the proper management of the Riparian Buffer Zone, especially in light of the distribution type of each patch and the change in conditions regarding them.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.31-40
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• 2014

The Korean government made the 2nd Energy Basic Plan to achieve 11% of new and renewable energies distribution rate until 2035 as a response to cope with international discussion about greenhouse gas emission reduction. Renewable energies include solar thermal, photovoltaic, bioenergy, wind power, small hydropower, geothermal energy, ocean energy, and waste energy. New energies contain fuel cells, coal gasification and liquefaction, and hydrogen. As public and private investment to enhance the distribution of new and renewable energies, it is necessary to clarify the economic effects of the new and renewable energies sector. To the end, this study attempts to apply an input-output analysis and analyze the economic effects of new and renewable energies sector using 2012 input-output table. Three topics are dealt with. First, production-inducing effect, value-added creation effect, and employment-inducing effect are quantified based on demand-driven model. Second, supply shortage effects are analyzed employing supply-driven model. Lastly, price pervasive effects are investigated applying Leontief price model. The results of this analysis are as follows. First, one won of production or investment in new and renewable energies sector induces 2.1776 won of production and 0.7080 won of value-added. Moreover, the employment-inducing effect of one billion won of production or investment in new and renewable energies sector is estimated to be 9.0337 persons. Second, production shortage cost from one won of supply failure in new and renewable energies sector is calculated to be 1.6314 won, which is not small. Third, the impact of the 10% increase in new and renewable energies rate on the general price level is computed to be 0.0123%, which is small. This information can be utilized in forecasting the economic effects of new and renewable energies sector.

• Applied Biological Chemistry
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• v.14 no.3
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• pp.213-220
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• 1971

In order to investigate chemical components of edible marine algae in Korea, the present work is carried out with ten edible and two non-edible species of brown algae, collected from Cheju-island during October, 28-30 in 1970. Among the general components, water content is about 14-16% to dry weight and the crude protein about 16%, which are almost similar in content compared with several non-cultivate edible land plants. The content of crude fat is about 0.7-2.0%, and that of crude fiber about 3-8%, while the content of crude ash is 9.17-16.89%. The last one is more than two times in content compared with the land plants. The reducing sugar is about 0.27-2.49% in general. On the other hand, among the minerals Ca content is the most abundant, 1.73-2.51%, and the next is S, 1.0-1.8%. Mg and I are around 0.1-1%, while K and Na are about 1% in content. Among the micro-elements, Fe and Zn are about 0.01-0.03%, and Cu and Mn 0.001-0.005% in content. There is no special significant difference in chemical components between the edible and non-edible species of brown algae. Moreover, so far as the present investigation is concerned, there can be found no significant inter-species relationship on the taxonomical or phylogenetical points of view, considering their components.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.