• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.40-53
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• 2021

Research vessels(R/Vs) used for ocean research move to the planned research area and perform ocean observations suitable for the research purpose. The five research vessels of the Korea Institute of Ocean Science & Technology(KIOST) are equipped with global positioning system(GPS), water depth, weather, sea surface layer temperature and salinity measurement equipment that can be observed at all times during cruise. An information platform is required to systematically manage and utilize the data produced through such continuous observation equipment. Therefore, the data flow was defined through a series of business analysis ranging from the research vessel operation plan to observation during the operation of the research vessel, data collection, data processing, data storage, display and service. After creating a functional design for each stage of the business process, KIOST Underway Meteorological & Oceanographic Information System(KUMOS), a Web-Geographic information system (Web-GIS) based information platform, was built. Since the data produced during the cruise of the R/Vs have characteristics of temporal and spatial variability, a quality management system was developed that considered these variabilities. For the systematic management and service of data, the KUMOS integrated Database(DB) was established, and functions such as R/V tracking, data display, search and provision were implemented. The dataset provided by KUMOS consists of cruise report, raw data, Quality Control(QC) flagged data, filtered data, cruise track line data, and data report for each cruise of the R/V. The business processing procedure and system of KUMOS for each function developed through this study are expected to serve as a benchmark for domestic ocean-related institutions and universities that have research vessels capable of continuous observations during cruise.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• (The)Study of the Eastern Classic
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• no.70
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• pp.435-466
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• 2018

"Hajaeilgi (荷齋日記)" was written by Ji Gyu-sik, a gongin of Saongwon (司饔院)'s branch, almost everyday for 20 years and 7 months from January 1st, 1891 until the leap month of June 29th, 1911. It deals with many different areas including domestic and foreign circumstances, custom, rituals, all the affairs related to the branch, and also everyday life. Particularly, Ji Gyu-sik did not belong to the yangban class, and we can hardly find diaries written by such class' people. Here, what this author pays attention to among the things written in "Hajaeilgi" is the contents about rituals, especially coming of age, wedding, funeral and ancestral rites. Ji Gyu-sik did write in his "Hajaeilgi" about coming of age, wedding, funeral and ancestral rites that were actually performed then as a person not belonging to the yangban class. Such diaries are very rare, and its value is highly appreciated as a material. Particularly, from the late 19th to the early 20th century of this author focuses on the a study of coming of age, wedding, funeral and ancestral rites as we can see some aspects about it from his diary. Coming-of-age rites were carried out in the first month of the year generally, and in this period, we can see the transformation of their performing period as it was diversified then. This was not exceptional in yangban families. About wedding, while it was discussed, it came to be canceled more often than before maybe because they were going through the process of enlightenment then. It seems that choosing the day was not done in the bride's family always. Jungin or commoners had a weeding in the bride's house, but when it was needed, it was also performed in the groom's house. Ji Gyu-sik followed the traditional wedding procedure for his children rather faithfully, but it was applied flexibly according to the two families' situations or conditions. Ignoring the traditional manners, they had a wedding in the period of mourning or performed a wedding in the groom's house bringing the bride there. It seems that this was related to the decline of Confucian order in the society in the process of modernization. Also, the form of donations changed, too. Gradually, it was altered to the form of money gifts. Moreover, unlike before, divorcing seems to have been allowed then. Remarriage or divorce was the custom transformed from before. Funeral rites had different durations from death up to balin (carrying out a bier for burial) and hagwan (lowering a coffin into the grave), and so it means that they also went through transformation. Sa-daebu used usually 3 months but here was 7 days from death to balin normally, but it seems that there were yangban families not following it. The traces of 3-iljang (burial on the third day after death) most commonly found these days and chowoo jaewoo samwooje can be also found in "Hajaeilgi". Such materials are, in fact, very highly evaluated nowadays. Meanwhile, donations also changed gradually to the form of money. Regarding ancestral rites, time for memorial service was not fixed. Ji Gyu-sik did not follow jaegye (齋戒) before carrying out gijesa, and in some worse case, he went to pub the day before the memorial service to meet his lover or drink. This is somewhat different from the practice of yangban sadaebu then. Even after entering Christianity, Ji Gyu-sik performed memorial service, and after joining Cheondogyo, he did it, too. Meanwhile, there were some exceptions, but in Hansik or Chuseok, Ji Gyu-sik performed charye (myoje) before the tomb in person or sent his little brother or son to do it. But we cannot find the contents that tell us Ji Gyu-sik carried out myoje in October. Ji Gyu-sik performed saengiljesa calling it saengsincharye almost every year for his late father. But it is noticeable that he performed saengsincharye and memorial service separately, too, occasionally. The gijesa, charye, myoje, and saengsincharye carried out by jungin family from Gyeonggi Gwangju around the time that the status system was abolished and the Japanese Empire took power may have been rather different and less strict than yangban family's practice of ancestral rites; however, it is significant that we can see with it the aspects of ancestral rites performed in family not yangban. As described above, the contents about the a study of coming of age, wedding, funeral and ancestral rites found in "Hajaeilgi" are equipped with great value as material and meaningful in the perspective of forklore.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Journal of radiological science and technology
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• v.32 no.3
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• pp.335-341
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• 2009

Purpose : The medical imaging issuance is changed from conventional film method to Digital Compact Disk solution because of development on IT technology. However other medical record department's are undergoing identification check through and through whereas medical imaging department cannot afford to do that. So, we examine present applicant's recognition of private intelligence safeguard, and medical imaging issuance condition by CD & DVD medium toward various medical facility and then perform comparative analysis associated with domestic and foreign law & recommendation, lastly suggest standard for medical imaging issuance and process relate with internal environment. Materials and methods : First, we surveyed issuance process & required documents when situation of medical image issuance in the metropolitan medical facility by wire telephone between 2008.6.1$\sim$2008.7.1. in accordance with the medical law Article 21$\sim$clause 2, suggested standard through applicant's required documents occasionally - (1) in the event of oneself $\rightarrow$ verifying identification, (2) in the event of family $\rightarrow$ verifying applicant identification & family relations document (health insurance card, attested copy, and so on), (3) third person or representative $\rightarrow$ verifying applicant identification & letter of attorney & certificate of one's seal impression. Second, also checked required documents of applicant in accordance with upper standard when situation of medical image issuance in Kyung-hee university medical center during 3 month 2008.5.1$\sim$2008.7.31. Third, developed a work process by triangular position of issuance procedure for situation when verifying required documents & management of unpreparedness. Result : Look all over the our manufactured output in the hospital - satisfy the all conditions $\rightarrow$ 4 place(12%), possibly request everyone $\rightarrow$ 4 place(12%), and apply in the clinic section $\rightarrow$ 9 place(27%) that does not medical imaging issuance office, so we don't know about required documents condition. and look into whether meet or not the applicant's required documents on upper 3month survey - satisfy the all conditions $\rightarrow$ 629 case(49%), prepare a one part $\rightarrow$ 416 case(33%), insufficiency of all document $\rightarrow$ 226case(18%). On the authority of upper research result, we are establishing the service model mapping for objective reception when image export situation through triangular position of issuance procedure and reduce of friction with patient and promote the patient convenience. Conclusion : The PACS is classified under medical machinery that mean indicates about higher importance of medical information therefore medical information administrator's who already received professional education & mind, are performer about issuance process only and also have to provide under ID checking process exhaustively.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.79-90
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• 2014

User authentication based on ID and PW has been widely used. As the Internet has become a growing part of people' lives, input times of ID/PW have been increased for a variety of services. People have already learned enough to perform the authentication procedure and have entered ID/PW while ones are unconscious. This is referred to as the adaptive unconscious, a set of mental processes incoming information and producing judgements and behaviors without our conscious awareness and within a second. Most people have joined up for various websites with a small number of IDs/PWs, because they relied on their memory for managing IDs/PWs. Human memory decays with the passing of time and knowledges in human memory tend to interfere with each other. For that reason, there is the potential for people to enter an invalid ID/PW. Therefore, these characteristics above mentioned regarding of user authentication with ID/PW can lead to human vulnerabilities: people use a few PWs for various websites, manage IDs/PWs depending on their memory, and enter ID/PW unconsciously. Based on the vulnerability of human factors, a variety of information leakage attacks such as phishing and pharming attacks have been increasing exponentially. In the past, information leakage attacks exploited vulnerabilities of hardware, operating system, software and so on. However, most of current attacks tend to exploit the vulnerabilities of the human factors. These attacks based on the vulnerability of the human factor are called social-engineering attacks. Recently, malicious social-engineering technique such as phishing and pharming attacks is one of the biggest security problems. Phishing is an attack of attempting to obtain valuable information such as ID/PW and pharming is an attack intended to steal personal data by redirecting a website's traffic to a fraudulent copy of a legitimate website. Screens of fraudulent copies used for both phishing and pharming attacks are almost identical to those of legitimate websites, and even the pharming can include the deceptive URL address. Therefore, without the supports of prevention and detection techniques such as vaccines and reputation system, it is difficult for users to determine intuitively whether the site is the phishing and pharming sites or legitimate site. The previous researches in terms of phishing and pharming attacks have mainly studied on technical solutions. In this paper, we focus on human behaviour when users are confronted by phishing and pharming attacks without knowing them. We conducted an attack experiment in order to find out how many IDs/PWs are leaked from pharming and phishing attack. We firstly configured the experimental settings in the same condition of phishing and pharming attacks and build a phishing site for the experiment. We then recruited 64 voluntary participants and asked them to log in our experimental site. For each participant, we conducted a questionnaire survey with regard to the experiment. Through the attack experiment and survey, we observed whether their password are leaked out when logging in the experimental phishing site, and how many different passwords are leaked among the total number of passwords of each participant. Consequently, we found out that most participants unconsciously logged in the site and the ID/PW management dependent on human memory caused the leakage of multiple passwords. The user should actively utilize repudiation systems and the service provider with online site should support prevention techniques that the user can intuitively determined whether the site is phishing.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• Journal of Embryo Transfer
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• v.20 no.1
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• pp.55-62
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• 2005

This study was undertaken to access the effect of collection methods on the collection efficiency, blastocyst rate and pregnancy rate after IVP embryo transfer. The ovaries of Hanwoo were obtained from an abattoir and kept on 25 to $28^{\circ}C$ and transported to laboratory within 4 hrs. The oocytes were collected by aspiration of follicles $(2\~6\;mm)$ with or without slicing of ovaries after aspiration. The oocytes were matured in vitro (IVM) for 20 to 24 hrs in TCM-199 supplemented with $10\%$ fetal bovine serum at $39^{\circ}C$ under $5\%\;CO_{2}$ in air. Following routine IVM/IVF procedure, the oocytes and presumed zygotes were cultured for three day in CRlaa medium with BSA. The cumulus cells at 2 to 8-cell stage of embryos removed then the embryos and were cultured in CRlaa medium containing $10\%$ fetal bovine serum in $5\%\;CO_{2}$ at $39^{\circ}C$. The fresh blastocysts cultured for 7 to 9 days were transferred into recipients. The numbers of oocytes recovered form two different methods, the aspiration and slicing after aspiration, were compared to know what. The number of oocytes per ovary was 8.2 and 6.5 in aspiration combining slicing, and aspiration groups, respectively (p<0.05). The cleavage rate in aspiration method are significantly (p<0.05) high than those in slicing post aspiration $(27.9\%)$, and aspiration $(25.5\%)$. The pregnancy .ate in aspiration method $(62.5\%)$ was high than that in slicing method after aspiration $(54.4\%)$. The pregnancy rates of aspiration method and slicing method after aspiration in nullipara $(58.1\%\;vs\;68.2\%)$ was high than that in pluripara $(49.5\%\;vs\;53.2\%)$. The results obtained that the increased number of oocytes per ovary in slicing method after aspiration could be better than that in aspiration method. Pregnancy rate in aspiration method was slightly higher in than that in slicing method after aspiration.