• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of Genetic Medicine
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• v.8 no.2
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• pp.89-99
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• 2011

Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.

• The Korean Journal of Air & Space Law and Policy
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• v.21 no.1
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• pp.215-236
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• 2006

This article focused on the meaning of the 1979 Moon Treaty and its future. Although the Moon Treaty is one of the major 5 space related treaties, it was accepted by only 11 member states which are non-space powers, thus having the least enfluences on the field of space law. And this article analysed the relationship between the 1979 Moon Treay and 1967 Space Treaty which was the first principle treaty, and searched the meaning of the "Common Heritage of Mankind(hereinafter CHM)" stipulated in the Moon treaty in terms of international law. This article also dealt with the present and future problems arising from the Moon Treaty. As far as the 1967 Space Treaty is concerned the main standpoint is that outer space including the moon and the other celestial bodies is res extra commercium, areas not subject to national appropriation like high seas. It proclaims the principle non-appropriation concerning the celestial bodies in outer space. But the concept of CHM stipulated in the Moon Treaty created an entirely new category of territory in international law. This concept basically conveys the idea that the management, exploitation and distribution of natural resources of the area in question are matters to be decided by the international community and are not to be left to the initiative and discretion of individual states or their nationals. Similar provision is found in the 1982 Law of the Sea Convention that operates the International Sea-bed Authority created by the concept of CHM. According to the Moon Treaty international regime will be established as the exploitation of the natural resources of the celestial bodies other than the Earth is about to become feasible. Before the establishment of an international regime we could imagine moratorium upon the expoitation of the natural resources on the celestial bodies. But the drafting history of the Moon Treaty indicates that no moratorium on the exploitation of natural resources was intended prior to the setting up of the international regime. So each State Party could exploit the natural resources bearing in mind that those resouces are CHM. In this respect it would be better for Korea, now not a party to the Moon Treaty, to be a member state in the near future. According to the Moon Treaty the efforts of those countries which have contributed either directly or indirectly the exploitation of the moon shall be given special consideration. The Moon Treaty, which although is criticised by some space law experts represents a solid basis upon which further space exploration can continue, shows the expression of the common collective wisdom of all member States of the United Nations and responds the needs and possibilities of those that have already their technologies into outer space.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• The Korean Journal of Physiology
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• v.20 no.1
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• pp.53-63
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• 1986

Carbon monoxide(CO) poisoning has been one of the major environmental problems because of the tissue hypoxia, especially brain tissue hypoxia, due to the great affinity of CO with hemoglobin. Inhalation of the pure oxygen$(0_2)$ under the high atmospheric pressure has been considered as the best treatment of CO poisoning by the supply of $0_2$ to hypoxic tissues with dissolved from in plasma and also by the rapid elimination of CO from the carboxyhemoglobin(HbCO). Hydrogen peroxide $(H_2O_2)$ was rapidly decomposed to water and $0_2$ under the presence of catalase in the blood, but the intravenous administration of $H_2O_2$ is hazardous because of the formation of methemoglobin and air embolism. However, it was reported that the enema of $H_2O_2$ solution below 0.75% could be continuously supplied $0_2$ to hypoxic tissues without the hazards mentioned above. This study was performed to evaluate the effect of $H_2O_2$ enema on the elimination of CO from the HbCO in the recovery of the acute CO poisoning. Rabbits weighting about 2.0 kg were exposed to If CO gas mixture with room air for 30 minutes. After the acute CO poisoning, 30 rabbits were divided into three groups relating to the recovery period. The first group T·as exposed to the room air and the second group w·as inhalated with 100% $0_2$ under 1 atmospheric pressure. The third group was administered 10 ml of 0.5H $H_2O_2$ solution per kg weight by enema immediately after CO poisoning and exposed to the room air during the recovery period. The arterial blood was sampled before and after CO poisoning ana in 15, 30, 60 and 90 minutes of the recovery period. The blood pH, $Pco_2\;and\;Po_2$ were measured anaerobically with a Blood Gas Analyzer and the saturation percentage of HbCO was measured by the Spectrophotometric method. The effect of $H_2O_2$ enema on the recovery from the acute CO poisoning was observed and compared with the room air group and the 100% $0_2$ inhalation group. The results obtained from the experiment are as follows: The pH of arterial blood was significantly decreased after CO poisoning and until the first 15 minutes of the recovery period in all groups. Thereafter, it was slowly increased to the level of the before CO poisoning, but the recovery of pH of the $H_2O_2$ enema group was more delayed than that of the other groups during the recovery period. $Paco_2$ was significantly decreased after CO poisoning in all groups. Boring the recovery Period, $Paco_2$ of the room air group was completely recovered to the level of the before CO Poisoning, but that of the 100% $O_2$ inhalation group and the $H_2O_2$ enema group was not recovered until the 90 minutes of the recovery period. $Paco_2$ was slightly decreased after CO poisoning. During the recovery Period, it was markedly increased in the first 15 minutes and maintained the level above that before CO Poisoning in all groups. Furthermore $Paco_2$ of the $H_2O_2$ enema group was 102 to 107 mmHg and it was about 10 mmHg higher than that of the room air group during the recovery period. The saturation percentage of HbCO was increased up to the range of 54 to 72 percents after CO poisoning and in general it was generally diminished during the recovery period. However in the $H_2O_2$ enema group the diminution of the saturation percentage of HbCO was generally faster than that of the 100% $O_2$ inhalation group and the room air group, and its diminution in the 100% $O_2$ inhalation group was also slightly faster than that of the room air group at the relatively later time of the recovery period. In conclusion, the enema of 0.5% $H_2O_2$ solution is seems to facilitate the elimination of CO from the HbCO in the blood and increase $Paco_2$ simultaneously during the recovery period of the acute CO poisoning.