• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.109-117
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• 2011

The exhibition industry, as technology-intensive, eco-friendly industry, contributes to regional and national development and enhancement of its image as well, if it joins cultural and tourist industry. Therefore, We need to revitalize the exhibition industry, as actively holding an exhibition event. However, to attract a number of exhibition audience, the work of enhancing audience satisfaction and awareness of value for participation should be prioritized after improving quality of service within exhibition hall. As one way to enhance the quality of service, it is thought that the way providing personalized service geared toward each audience is needed. that is, if audience avoids the complexity in exhibition space and it affords them service to enable effective time and space management, it will improve the satisfaction. All such personalized service affordable lets the audience's preference on the basis of each audience profile registered in advance online grasp. and Based on this information, it is provided with exhibition-related information suited their purpose that is the booth for the interesting audience, the shortest path to go to the booth and event via audience's smart phone. and it collects audience's reaction information, such as visiting the booth, participating the event through offered the information in this way and location information for the flow of movement, the present position so that it makes revision of existing each audience profile. After correcting the information, it extracts the individual's preference. hereunder, it provides recommend booth and event information. in other words, it provides optimal information for individual by amendment based on reaction information about recommending information built on basic profile. It provides personalized service dynamic and interactive with audience. This paper will be able to provide the most suitable information for each audience through circular and interactive structure and designed smart-phone application supportable for updating dynamic and interactive personalized service that is able to afford surrounding information in real time, as locating movement position through sensing. The proposed application collects user‘s context information and carrys information gathering function collecting the reaction about searched or provided information via sensing. and it also carrys information gathering function providing needed data for user in exhibition hall. In other words, it offers information about recommend booth of position foundation for user, location-based services of recommend booth and involves service providing detailed information for inside exhibition by using service of augmented reality, the map of whole exhibition as well. and it is also provided with SNS service that is able to keep information exchange besides intimacy. To provide this service, application is consisted of several module. first of all, it includes UNS identity module for sensing, and contain sensor information gathering module handling and collecting the perceived information through this module. Sensor information gathered like this transmits the information gathering server. and there is exhibition information interfacing with user and this module transmits to interesting information collection module through user's reaction besides interface. Interesting information collection module transmits collected information and If valid information out of the information gathering server that brings together sensing information and interesting information is sent to recommend server, the recommend server makes recommend information through inference with gathered valid information. If this server transmit by exhibition information process, exhibition information process module is provided with user by interface. Through this system it raises the dynamic, intelligent personalized service for user.

• The Korean Society of Law and Medicine
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• v.15 no.1
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• pp.335-373
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• 2014

According to one Medicare report, in the US, total federal spending on health care expends almost 18 percent of the nation's GDP, about double what most industrialized nations spend on health care. And in 2011, Medicare spending reached close to $554 billion, which amounted to 21 percent of the total spent on U.S. health care in that year. Of that $554 billion, Medicare spent 28 percent, or about $170 billion, on patients' last six months of life. So what are the reasons of this high cost in EOL care and its possible solutions? Much spendings of Medicare on End-of-Life care for the terminally ill/chronically ill in the US has led health economics experts to assess the characteristics of the care. Decades of study shows that EOL care is usually supply-sensitive and poor in cost-effectiveness. The volume of care is sensitively depending on the supply of resources, rather than the severity of illness or preferences of patients. This means at the End-of-Life care, the medical resources are being overused. On the other hand, opposed to the common assumption, "The more care the better utility", the study shows that the outcome is very poor. Actually the patient preference and concerns are quite the opposite from what intense EOL care would bring about. This study analyzes the reasons for the supply-sensitiveness of EOL care. It can be resulted from the common misconception about the intense care and the outcome, physicians' mission for patients, lack of End-of-Life Care Decision which helps the patients choose their own preferred treatment intensity. It also could be resulted from physicians' fear of legal liabilities, and the management strategy since the hospitals are also seeking for financial benefits. This study suggests the possible solutions for over-treatment at the End-of-Life resulting from supply-sensitiveness. Solutions can be sought in two aspects, legal implementation and management strategy. In order to implement advance directive properly, active ethics education for physicians to change their attitude toward EOL care and more conversations about end-of-life care between physicians and patients is crucial, and incentive system for the physicians who actively have the conversations with patients will also help. Also, the general education towards the public is also important in the long run, and easy and official advance directive registry system-such as online registry-has to be built and utilized more widely. Alternative strategies in management are also needed. For example, the new strategic cost management and management education, such as cutting unnecessary costs and resetting values as medical providers have to be considered. In order to effectively resolve the problem in EOL care for the terminally ill/chronically ill and provide better experience to the patients, first of all, the misconception and the wrong conventional wisdom among doctors, patients, and the government have to be overcome. And then there should be improvements in systems and cultures of the EOL care.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.45-62
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• 2011

The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.144-170
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• 2010

This paper considers the effect of various types of procurement auction system on competition focusing on the rate of successful bidding. We analyze the number of bidders and the rate of successful bids using online procurement data of the Public Procurement Service. The average number of bidders is 301 and the average rate of successful bids is 87.42% while the weighted average rate is 75.13%. These numbers show that there is quite strong competition among bidders and the rate is lower as the expected price is higher. When we analyze the data of price procurement auction, the rate is also shown to be lower as the expected price is higher. Furthermore, the rate decreases as the number of bidders increases which naturally makes the competition stronger. Meanwhile, the analysis finds that the inclusion of the onsite bidding, the PQ(Pre-Qualification) result, or major-10 winning companies cannot explain the rate much in our data. In case of turnkey-alternative, the average rate of successful bidding for 484 cases record 90.20%. The average is 84.89% with 120 alternatives and 91.97% with 364 cases of turnkey. The reason why the rate of turnkey-alternative is lower than that of price procurement auction is the lack of competition as well as the systematic difference. By setting up a model, we are able to explain the difference in rate caused by the respective reason. When we suppose there are 3 bidders in case of price procurement auction for a project that exceeds 100 billion won, the rate is expected to be around 64%. This implies that difference of 26% is caused by the systemic difference and 3% by the lack of competition. Therefore, we conclude that the difference in rate between turnkey-alternative and price procurement auction is caused mainly by the systemic difference. In case of PPP(Public Private Partnership) projects, among 154 projects in total, only 40% has more than 2 bidders that compete. The average number of bidders is 1.88 which is less than 2, and the average rate of successful bids is 90%. In sum, under the price procurement auction, there is strong competition which is reflected by the rate of successful bids. However, there is room to decrease the rate by strengthening the competition under the turnkey-alternative. Also with PPP projects, we expect the rate can be steadily reduced with revived competition among bidders.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.127-136
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• 2008

To identify the potential area of gas hydrate in the Ulleung Basin, 2-D and 3-D seismic surveys using R/V Tamhae II were conducted in 2005 and 2006. Seismic survey equipment consisted of navigation system, recording system, streamer cable and air-gun source. For reliable velocity analysis in a deep sea area where water depths are mostly greater than 1,000 m and the target depth is up to about 500 msec interval below the seafloor, 3-km-long streamer and 1,035 $in^3$ tuned air-gun array were used. During the survey, a suite of quality control operations including source signature analysis, 2-D brute stack, RMS noise analysis and FK analysis were performed. The source signature was calculated to verify its conformity to quality specification and the gun dropout test was carried out to examine signature changes due to a single air gun's failure. From the online quality analysis, we could conclude that the overall data quality was very good even though some seismic data were affected by swell noise, parity error, spike noise and current rip noise. Especially, by checking the result of data quality enhancement using FK filtering and missing trace restoration technique for the 3-D seismic data inevitably contaminated with current rip noises, the acquired data were accepted and the field survey could be conducted continuously. Even in survey areas where the acquired data would be unsuitable for quality specification, the marine seismic survey efficiency could be improved by showing the possibility of noise suppression through onboard data processing.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• The Korean Society of Law and Medicine
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• v.19 no.2
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• pp.235-261
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• 2018

The Medical law stipulates regulations about the physician's duty to inform to contribute to patient's self-determination. This law was most recently revised on December 20, 2016, and came into effect on June 21, 2017. There has been much controversy about this, and it has been questioned whether or not it will be effective for physicians to comply with the duty to inform. Therefore, this study investigated perceptions of physicians of whether they observed the duty to inform and their legal judgment about that duty, and analyzed how the revision of the medical law may have affected the legal cognition of physician's duty to inform. This study was conducted through an online questionnaire survey involving 109 physicians over 2 weeks from March 29 to April 12, 2018, and 108 of the collected data were used for analysis. The questionnaire was developed by revising and supplementing the previous research (Lee, 2004). It consisted of 41 items, including 26 items related to the experience of and legal judgment about the duty to inform, 6 items related to awareness of revised medical law, and 9 items on general characteristics. The data were analyzed using SAS 9.4 program and descriptive statistics, Chi-square test, Fisher's exact test and Binary logistic regression were performed. The results are as follows. • Out of eight situations, the median number of situations that did not fulfill the duty to inform was 5 (IQR, 4-6). In addition, 12 respondents (11%) answered that they did not fulfill the duty to inform in all eight cases, while only one (1%) responded that he/she performed explanation obligations in all cases. • The median number of the legal judgment score on the duty to inform was 8 out of 13 (IQR, 7-9), and the scores ranged from a minimum of 4 (4 respondents) to a maximum of 11 (3 respondents). • More than half of the respondents (n=26, 52%) were unaware of the revision of the medical law, 27 (25%) were aware of the fact that the medical law had been revised, 20(18%) had a rough knowledge of the contents of the law, and only 5(5%) said they knew the contents of the law in detail. The level of awareness of the revised medical law was statistically significant difference according to respondents' sex (p<.49), age (p<.0001), career (p<.0001), working type (p<.024), and department (p<.049). • There was no statistically significant relationship between the level of awareness of the revised medical law and the level of legal judgment on the duty to inform. These results suggest that efforts to improve the implementation and cognition of physician's duty to inform are needed, and it is difficult to expect a direct positive effect from the legal regulations per se. Considering the distinct characteristics of medical institutions and hierarchical organizational culture of physicians, it is necessary to develop a credible guideline on the duty to inform within the medical system, and to strengthen the education of physicians about their duty to inform and its purpose.

• The Korean Journal of Archival Studies
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• no.42
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• pp.135-183
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• 2014

Korea has a high standard of IT environment to serve exhibit programs through the web with internet propagation and IT technology. However, the web exhibition of public institutions not only seem to introduce off-line exhibitions but also not to invigorate. It is caused by the lack of awareness, the cost of system installation and the lack of professional manpower. In this situation, OMEKA could suggest practical solutions to archives where need their own exhibition through the web. Especially, it would helpful for small record management organizations which are not enough budget and personal. OMEKA is an open source software program for digital collection and contents management. It has an affinity with users unlike traditional archives service programs. It also has been variously used by libraries, museums and schools because of exceptional exhibit functions. In this article, we introduce to the installation of a practical use about OMEKA. Regarding to OMEKA features, we consider it to raise exhibit effects. OMEKA would reduce the cost related to plans of exhibitions because it could display various contents and programs which reflecting characteristics of institutions. In addition, the availability of installation and widespread technological environment would lessen burden of public institutions. Using OMEKA, they would improve service level of public institutions and, make users satisfy. Therefore, they can change the social recognition of public institutions. OMEKA can contribute to various exercises of public records. It is not just the stereotypical system but, serves exhibition and collections with the strategy which each public institution would like to display. After all, it not only to connect to users with producers but also to improve the public image of institutions positively. Then, OMEKA would bring the great result through this interaction between public institutions and users.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.177-192
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• 2021

The Development Assistance Committee of the Organization for Economic Cooperation and Development discusses the reorganization of the five evaluation criteria of the Public Development Assistance Committee, which are used internationally, and the five evaluation criteria including adequacy, efficiency, effectiveness, impact, and sustainability when assessing public development assistance in 1991. This study is to derive alternatives by applying the evaluation criteria of the Development Assistance Committee of the Organization for Economic Cooperation and Development in the evaluation of the inclusive business program being implemented in Nepal since 2019. As a result of the study, the adequacy of Nepal's inclusive business program was consistent with continuous employment and job creation for vulnerable groups such as disabled and orphan women. Efficiency can be said to be efficient in that processes such as work order and work confirmation are made with an electronic management tool, and delivery of the result is transmitted online, saving time and cost compared to other industries. The effectiveness of this project can be said to be an effective program in that it provides high-quality jobs such as providing specialized computer graphics education for the vulnerable, such as disabled and orphan women in Nepal, and hiring graduates as employees. Sustainability is the point that KOICA's inclusive business program has enabled vulnerable groups in the existing fields of agriculture and manufacturing to engage in the computer graphics industry, and the scalability of movies, characters, education businesses, and role models in other countries.However, considering that the scale of public development assistance will continue to increase in the future, it is necessary to establish a systematic monitoring system and a recirculation system so that the project between the donor and recipient countries can continue.