• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Journal of Food Hygiene and Safety
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• v.25 no.4
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• pp.410-417
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• 2010

Various functional foods, marketing health and functional effects, have been distributed in the market. These products, being in forms of foods, tablets, and capsules, are likely to be mistaken as drugs. In addition, non-experts may sell these as foods, or use these for therapy. Efforts for creating health food regulations or building regulatory system for improving the current status of functional foods have been made, but these have not been communicated to consumers yet. As a result, problems of circulating functional foods for therapy or adding illegal medical to such products have persisted, which has become worse by internet media. The cause of this problem can be categorized into (1) product itself and (2) its use, but in either case, one possible cause is lack of communications with consumers. Potential problems that can be caused by functional foods include illegal substances, hazardous substances, allergic reactions, considerations when administered to patients, drug interactions, ingredients with purity or concentrations too low to be detected, products with metabolic activations, health risks from over- or under-dose of vitamin and minerals, and products with alkaloids. (Journal of Health Science, 56, Supplement (2010)). The reason why side effects related to functional foods have been increasing is that under-qualified functional food companies are exaggerating the functionality for marketing purposes. KFDA has been informing consumers, through its web pages, to address the above mentioned issues related to functional foods, but there still is room for improvement, to promote proper use of functional foods and avoid drug interactions. Specifically, to address these issues, institutionalizing to collect information on approved products and their side effects, settling reevaluation systems, and standardizing preclinical tests and clinical tests are becoming urgent. Also to provide crucial information, unified database systems, seamlessly aggregating heterogeneous data in different domains, with user interfaces enabling effective one-stop search, are crucial.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Korean Security Journal
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• no.29
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• pp.139-162
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• 2011

The purpose of this study is to compare with the general and behavioral characteristics between simple and serial arsonists using the data derived from Scientific Crime Analysis System, Criminal Filing Search System, and Crime Information Management System. The analysis and findings reported here are derived from data extracted from 160 arsonists arrested by police officer. The independent variables included such socio-economic characteristic as arsonists' gender, age, occupation, education level, and previous criminal records of arsonists, and finally the general characteristics of the scene of fire settings. The dependent variable is whether or not serial fire setter. To achieve the purpose, the analysis of frequencies and cross-tab were conducted. According to frequence and cross-tab analysis, there are great differences of the general and behavior characteristics between two groups. In the comparison of simple and serial arsonists, serial arsonists are more likely to have previous criminal records, low socio-economic status, unmarried and no cohabitants than simple arsonists. furthermore, serial arsonists are more likely to use garbage papers for fire setting in the scene of the crime, to have mental or psychological problems, and to get involved in fire setting for the psychological pleasure than simple arsonists do. The present research has some obvious limitations. First, the analysis is based only on arsonists arrested by police officers. These may be considerable differences in arsonists arrested by police officers and fire setters not arrested by them. Additional research is needed to assess the extent to which these findings would apply to fire setters not arrested by police officer in Korea. Secondly, the data in this study are cross-sectional and simple cross-tab analysis are used. Potential limitation of cross-sectional data concerns the inability to specify the changes in measures as arsonists behavioral characteristics. Therefore, further studies need to use longitudinal data and more complicate statistical techniques such as correlation analysis, multiple regression analysis, or LISREL models to specify the casual relationships between dependent and independent variables for fire settings. Even if this study has some limitations, it is meaningful in which it first investigated the comparison of simple and serial arsonists focusing on the general and behavioral characteristics between two groups in Korea.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.829-837
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• 2014

The KOMPSAT-3 can acquire panchromatic stereo image with 0.7 m spatial resolution, and provides Rational Polynomial Coefficient (RPC). In order to determine ground coordinate using the provides RPC, which include interior-exterior orientation errors, its adjustment is needed by using the Ground Control Point (GCP). Several thousands of national Unified Control Points (UCPs) are established and overall distributed in the country by the Korean National Geographic Information Institute (NGII). UCPs therefore can be easily searched and downloaded by the national-control-point-record-issues system. This paper introduced the point-extraction method and the distance-bearing method to detect of UCPs. As results, the distance-bearing method was better detected through the experiment. RPC adjustment using this method was compared with that by only one UCP and GCPs using GPS. The proposed method was more accurate than the other method in the horizontal. As demonstrated in this paper, the proposed UCPs detection method could be replaced GPS surveying for RPC adjustment.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.139-145
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• 2011

Purpose : To assess the frequency and severity of acute adverse reactions to intravenous administration of gadolinium-based contrast agents using computerized reporting system at a single large academic institution. Materials and Methods : We assessed data from electronic hospital information system from October 2008 to December 2010. Reactions were classified as mild, moderate, or severe. We compared the frequency of adverse reactions among three contrast agents (Gd-BT-DO3A, Gd-DTPA and Gd-EOB-DTPA). Results : The total number of administrated contrast agents was 33,600, and the number of administration of Gd-BT-DO3A, Gd-DTPA and Gd-EOB-DTPA were 20,824 (62%), 10,417 (31%) and 2,359 (7%), respectively. Total 39 adverse reactions were reported accounting for 0.1161% of all administrations. The incidences of adverse reactions were 0.1248% (26/39, 67%) for Gd-BT-DO3A, 0.0768% (8/39, 21%) for Gd-DTPA, and 0.2120% (5/39, 13%) for Gd-EOB-DTPA. The difference of frequencies of adverse reaction among three contrast agents was not significant. Most cases of the adverse effect were mild (35/39, 89.7%). Moderate and severe adverse reactions were encountered in two patients, respectively. Conclusion : Among Koreans, adverse effects were rare, and especially, moderate to severe adverse reactions were much rarer. There was no difference among the frequencies of adverse reactions caused by three different contrast agents.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.97-106
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• 2004

It is a Known fact that driving through long tunnel increases possibility of traffic accident because of psychological feeling of insecurity and dispersion of drivers' concentration since driving in narrow and limited space for a longtime. It, therefore, results in raising transportation and environment problems, such as traffic accident difficult to be properly dealt with and ventilation. This study aims at proposing a method of augmenting driving amenity by improving the internal lighting facilities in the tunnel. The study is conducted by investigating internal landscapes of tunnels by lighting colors, which are currently being operated. The Color Planning System (CPS), developed by SHARP Co. Ltd, is exploited for selecting adjective that express the sensitivity image on lighting colors. The CPS is an example that applies to sensitivity of human body for products design development. The CPS takes the following process to define the color : 1) expressing "Pvoduct's Image" as "A Word (adjective)" and 2) referring "A Word" to "Image Scale", and 3) determining the color through this "Image Panel". The study is processed by making a questionnaire using the semantic differential (SD) scale, grasping the consciousness structure of experimental persons through the Factor Analysis, and building a model in which dependent variable is "Degree of Preference" about internal landscape in tunnel using LISREL(LInear Structural RELations).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.826-833
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• 2017

It is important to localize trains precisely for the purpose of controlling them and there have been many studies designed to accomplish this without the need for wayside systems. Since trains run on fixed railway lines, it is possible to search in one direction to localize them. Moreover, it is also possible to know the shape of the line in advance. In the case of high speed trains, their speed and, therefore, their Doppler frequency is relatively high and the railway line is either linear or circular with a large radius. In this study, we utilize these features and propose a train localization method using the Doppler frequency of the signals transmitted from two points (base stations). We derive localization equations for a linear line, circular line, and mixed line (linear plus circular) respectively. Though Doppler radars are usually used to measure speed, the proposed method obtains the location information and the speed successively using the ratio of the doppler frequencies of two signals without knowing the location information or the speed. Computer simulations are performed to show the variation of the estimation error according to the train's location and the measurement error level. The conditions required to obtain the target error level and the increase in the estimation error according to the measurement error are compared between the proposed and conventional methods. The results show the superior performance and robustness of the proposed method.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.661-675
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• 2009

The carelessly and illegally copied contents are raising serious social problem as internet and multimedia technologies are advancing. Therefore, development of video copy detection system must be settled without delay. In this paper, we propose the hierarchical video copy detection method that estimates similarity using statistical characteristics between original video and manipulated(transformed) copy video. We rank according to luminance value of video to be robust to spacial transformation, and choose similar videos categorized as candidate segments in huge amount of database to reduce processing time and complexity. The copy videos generally insert black area in the edge of the image, so we remove rig black area and decide copy or not by using statistical characteristics of original video and copied video with center part of frame that contains important information of video. Experiment results show that the proposed method has similar keyframe accuracy to reference method, but we use less memory to save feature information than reference's, because the number of keyframes is less 61% than that of reference's. Also, the proposed method detects if the video is copied or not efficiently despite expansive spatial transformations such as blurring, contrast change, zoom in, zoom out, aspect ratio change, and caption insertion.