• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9B
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• pp.610-618
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• 2005

As developed Internet and Computer Capability, Many Users take the many information through the network. So requirement of User that use to network was rapidly increased and become various. But it spend much time to accept user requirement on current network, so studied such as Active network for solved it. This Active node on Active network have the capability that stored and processed execution code aside from capability of forwarding packet on current network. So required execution code for executed packet arrived in active node, if execution code should not be in active node, have to take by request previous Action node and Code Server to it. But if this execution code take from previous active node and Code Server, bring to time delay by transport execution code and increased traffic of network and execution time. So, As used execution code stored in cache on active node, it need to increase execution time and decreased number of request. So, our paper suggest ANC caching technique that able to decrease number of execution code request and time of execution code by efficiently store execution code to active node. ANC caching technique may decrease the network traffic and execution time of code, to decrease request of execution code from previous active node.

• 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.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.171-193
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• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.165-183
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• 2016

Over the past decade, there has been a rapid diffusion of technological devices and a rising number of various devices, resulting in an escalation of virtual reality technology. Technological market has rapidly been changed from smartphone to wearable devices based on virtual reality. Virtual reality can make users feel real situation through sensing interaction, voice, motion capture and so on. Facebook.com, Google, Samsung, LG, Sony and so on have investigated developing platform of virtual reality. the pricing of virtual reality devices also had decreased into 30% from their launched period. Thus market infrastructure in virtual reality have rapidly been developed to crease marketplace. However, most consumers recognize that virtual reality is not ease to purchase or use. That could not lead consumers to positive attitude for devices and purchase the related devices in the early market. Through previous studies related to virtual reality, there are few studies focusing on why the devices for virtual reality stayed in early stage in adoption & diffusion context in the market. Almost previous studies considered the reasons of hard adoption for innovative products in the viewpoints of Typology of Innovation Resistance, MIR(Management of Innovation Resistant), UTAUT & UTAUT2. However, product-based antecedents also important to increase user intention to purchase and use products in the technological market. In this study, we focus on user acceptance and resistance for increasing purchase and usage promotions of wearable devices related to virtual reality based on headgear products like Galaxy Gear. Especially, we added a variables like attitude confidence as a dimension for user resistance. The research questions of this study are follows. First, how attitude confidence and innovativeness resistance affect user intention to use? Second, What factors related to content and brand contexts can affect user intention to use? This research collected data from the participants who have experiences using virtual rality headgears aged between 20s to 50s located in South Korea. In order to collect data, this study used a pilot test and through making face-to-face interviews on three specialists, face validity and content validity were evaluated for the questionnaire validity. Cleansing the data, we dropped some outliers and data of irrelevant papers. Totally, 156 responses were used for testing the suggested hypotheses. Through collecting data, demographics and the relationships among variables were analyzed through conducting structural equation modeling by PLS. The data showed that the sex of respondents who have experience using social commerce sites (male=86(55.1%), female=70(44.9%). The ages of respondents are mostly from 20s (74.4%) to 30s (16.7%). 126 respondents (80.8%) have used virtual reality devices. The results of our model estimation are as follows. With the exception of Hypothesis 1 and 7, which deals with the two relationships between brand awareness to attitude confidence, and quality of content to perceived enjoyment, all of our hypotheses were supported. In compliance with our hypotheses, perceived ease of use (H2) and use innovativeness (H3) were supported with its positively influence for the attitude confidence. This finding indicates that the more ease of use and innovativeness for devices increased, the more users' attitude confidence increased. Perceived price (H4), enjoyment (H5), Quantity of contents (H6) significantly increase user resistance. However, perceived price positively affect user innovativeness resistance meanwhile perceived enjoyment and quantity of contents negatively affect user innovativeness resistance. In addition, aesthetic exterior (H6) was also positively associated with perceived price (p<0.01). Also projection quality (H8) can increase perceived enjoyment (p<0.05). Finally, attitude confidence (H10) increased user intention to use virtual reality devices. however user resistance (H11) negatively affect user intention to use virtual reality devices. The findings of this study show that attitude confidence and user innovativeness resistance differently influence customer intention for using virtual reality devices. There are two distinct characteristic of attitude confidence: perceived ease of use and user innovativeness. This study identified the antecedents of different roles of perceived price (aesthetic exterior) and perceived enjoyment (quality of contents & projection quality). The findings indicated that brand awareness and quality of contents for virtual reality is not formed within virtual reality market yet. Therefore, firms should developed brand awareness for their product in the virtual market to increase market share.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Korea journal of population studies
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• v.11 no.2
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• pp.54-66
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• 1988

I. Introduction Since the 1970's drug abuse among young people has increasingly become a social problem in Korea. In the 1980's, drug abuse, especially glue sniffing, has become the cause of many unfortunated incidents resulting in harm to others as well as the abusers themselves. Taking into consideration of the seriousness of this problem, the Republic of Korea National Red Cross initiated a nation-wide research programme, to understand the present situation and to raise the level of public awareness. The goal of this research was to begin a nation - wide campaign against drug abuse. The research team was composed of the Advisary Committee members and the staff of the Youth Department of the Republic of Korea National Red Cross. The data were collected in February 1988 with the collaboration of the staff and volunteers in the local Chapters. The respondents were allocated nation-wide by the quota sampling method. The questionnaires were distributed to the respondents in three groups :2, 700 to junior and senior high school students, 605 to working youths, and 916 to delinquent youths. A total of 4, 221 questionnaires were collected. II. Characteristics of the Respondents The respondents in each group were selected evenly from rural and urban areas. The general characteristics of the respondents can be described as follow: in case of students, the proportions between male and female respondents, and between senior high school and junior high school students were almost evenly distributed. In case of working youths, the proportion of females (80.5%) was higher than those of the students and the delinquents groups. Delinquent youths were defined as those currently being under custody of the centers for juvenile delinquents. Of this number, 38.8% and 68.2% were junior and senior high school drop-outs respectively. The majority of them (92.6%) were male. As for the family background of the respondents, the proportion of those residing in poverty - stricken areas, and the proportion of those from broken families were higher in case of working youths and delinquent youths than those in case of students. III. Present Patterns of Drug Abuse The following summarizes the presents of drug abuse, as tabulated from the results of the survey. 1. Smoking The percentage of youths who smoke was 36% in the student group, 32% m the working youths group, and 94.4% in the delinquent youths group. 2. Alcohol 50.3% of students, 71.6% of working youths, and 93.3% of delinquent youths has experienced drinking alcohol beverages. 3. Tonic: non - alcoholic, caffeinated beverages popular in Korea and Japan The percentage of those who have used tonic at least once was over 90% in all of the three groups. 4. Sedative About 70% of each group has used sedative with the proportion of working youths use higher than those in other groups. 5. Stimulants Those who have used stimulants comprised around 15% in each group. 6. Tranquilizers Somewhat less than 5% of students and working youths, and 28% of delinquent youths, have used tranquilizers. 7. Hypnotics The users of hypnotics amounted to 0.4% of students, 2.6% of working youths and 7.1% of delinquent youths. 8. Marihuana Those who have used marihuana indicated 0.7% of students, 0.8% of working youths, and 13% of delinquent youths. 9. Glue-sniffing The percentage of glue-sniffing was 3.7%, 5% in the students group and in the youths group respectively, but the proportion was unusually high, at 40.7% in the delinquent youths group. From the results of the survey the present situation of drug abuse in Korea can be summarized as follows: 1. A high percentage of Korean youths have experienced smoking cigarettes and drinking alcoholic beverages. 2. Tonics (non - alcoholic, caffeinated beverages), antipyretic analgesics and stimulants quite regularly used. 3. Tranquilizers, hypnotics, marihuana and glue-sniffing are more widely used among delinquent youths than the other youths. From this fact, there exists a correlation between drug abuse and juvenile delinquency. IV. Time-series Analysis of the First Experience of Drug Abuse and Deviant Behaviour The respoundents were asked when they were first exposed to drugs and when they committed deviant acts. By calculating the average age of each experience, the following pattern was found (See Figure 1). Youths are first exposed to drugs by abuse of tonic(non - alcoholic, caffeinated beverages). At the age of 13, they amoke cigarettes, the use of antipyretic analgesics begins at 14 year old, while at the age of 15, they use tranquilizers, and at 16 hynotics. The period of drug abuse which starts from drinking caffeinated beverages and smoking cigarettes and ends in the use of hypnotics takes about three years. During this period, other delinquent behaviours begin to surface, that is, at the age of 13 when smoking cigarettes begins, the delinquent behaviour pattern starts with truancy. Next, they start taking money from others by using physical force. Prior to the age of 15, they are suspended from school, become hostile to adults, begin running away from home, and start using stimulants and alcohol. Soon they become involved even in glue-sniffing and in the use of marihuana. At the age of 15, they begin to see adult videos and carry weapons. Sexual promiscuity and usage of tranquilizers follows the viewing of adult videos. Consequently, by the time they reach the age of 16, they visit drinking establishments, and are picked up by police for committing delinquent acts. And finally, they come to use hypnotic - type drugs. From the above descriptions, drug abuse can be assumed to have a close correlation with delinquent behaviour. V. Social Factors Related to Drug Abuse As for the Korean youths, glue-sniffing is found to he related to aggressive delinquency, in such cases as run - aways, being picked up by the police, and taking money by force. Smoking cigarettes and drinking alcohol is found to be related to seeing adult videos and visiting drinking establishments. Hypnotics and marihuana were found to be representive of drugs which are related to degenerational delinquency, irrespective of social delinquency. The social factors connected with these drug abuse are as follows: 1. Individual factors Male students were more heavily involved in the usage of drug than females. Youths who do not attend church were more likely to be involved in drugs than those who attend. 2. Family factors The youths who were displeased with their mothers smoking and those who thought their parents did not love each other, or those whose parents had used drugs without prescription, were more likely to he drug users. 3. School factors Those youths who found school life boring, were unsuccessful in their studies, spend most of their time with friends, feel their teachers smoke too much, those who had a positive perception of their teachers smoking were likely to he drug users. To sum up, drug abusers depend on the influence of their parents, teachers and peers. IV. Reasons for Drug Abuse Korean students have mainly used drugs to release stress (42.8%), to stay awake (19.7%), and because of the easy accessibility of drugs( 16.6%). Other reasons are due to their ignorance of the side effects of the drugs (3.6%), natural curiosity (4.2%), and to increase strength(3.O%). From the above facts, the major reasons for drug abuse among Korean youths are to release stress and to stay awake in order to prepare exams. Furthermore, since drugs are readily available, we can conclude that drug abuse is caused by the school system(such as entrance exams) in Korea. VII. Conclusion Drug usage among Korean youths are relatively less common than those of western youths. In some cases, such as, glue-sniffing and use of stimulants, the pattern of drug abuse is found. Moreover, early drug abuse is evident, and it has a close connection with deviant behaviour, resulting in juvenile delinquency. Drug abuse cannot be attributed to any one social factor. Specifically, drug abuse depends on parents, peers, teachers and other members of the community, and also is influenced by social institutions such as the entrance exam system. Every person and organization concerned with youth must participate collectively in restraining drug abuse. Finally, it is suggested that social agencial working for youth welfare should make every effort to tackle this serious problem confronted by the Korean youths today.

• Journal of Yeungnam Medical Science
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• v.8 no.2
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• pp.185-201
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• 1991

A household survey was conducted to compare the patterns of morbidity and medical care utilization between medical aid beneficiaries and medical insurance beneficiaries. The study population included 285 medical aid beneficiaries that were completely surveyed and 386 medical insurance benficiaries selected by simple random sampling from a Dong(Township) in Taegu. Well-trained surveyers mainly interviewed housewives with a structured questionnaire. The morbidity rates of acute illness during the 15-day period, were 63 per 1,000 medical aid beneficiaries and 62 per 1,000 medical insurance beneficiaries. The rates for chronic illness were 123 per 1,000 medical aid beneficiaries and 73 per 1,000 medical insurance beneficiaries. The most common type of acute illness in medical aid and medical insurance beneficiaries was respiratory disease. In medical aid beneficiaries, musculoskeletal disease was most common, but in medical insurance beneficiaries, gastrointestinal disease was most common. The mean duration of acute illness of medical aid beneficiaries was 3.8 days and that of medical insurance beneficiaries was 6.8 days. During the one year period, mean duration of medical aid beneficiaries chronic illnesses was 11.5 months which was almost twice as long compared to medical insurance beneficiaries. Pharmacy was most preferrable facility among the acute illness patient in medical aid beneficiaries, but acute cases of medical insurance beneficiaries visited the clinic most commonly. Chronic cases of both groups visited the clinic most frequently. There were some findings suggesting that much unmet need existed among the medical aid beneficiaries. In acute cases, the average number of days of medical aid users utilized medical facilities was less than medical insurance users. On the other hand, the length of medical care utilization of chronic cases was reversed. Geographical accessibility was the most important factors in utilization of medical facilities. Almost half of the study population answered the questions about source of funds on medical security correctly. Most respondents considered that the objective of medical security was afford ability. The chief complaint on hospital utilization was the complicated administrative procedures. These findings suggest that there were some problems in the medical aid system, especially in the referral system.

• MISULJARYO - National Museum of Korea Art Journal
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• v.104
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• pp.40-69
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• 2023

This paper examines the relationship between celadon wine vessels and royal banquets by focusing on their unique forms. It explores the symbolism in their forms and designs and the changes that took place in the composition of these vessels. By examining the royal annals in Goryeosa (The History of the Goryeo Dynasty), the relation of celadon wine vessels and royal banquets is examined in terms of the number of banquets held in the respective reigns of the Goryeo kings, the number of banquets held by type, and the purpose of holding them. A royal banquet was a means of strengthening the royal authority by reinforcing the hierarchy and building bonds between the king and his vassals. It was also an act of ruling that demonstrated the king's authority and power through praise of his achievements and virtues. Royal banquets were held most often during the reigns of King Yejong (r. 1105-1122), King Uijong (r. 1146-1170), King Chungnyeol (r. 1274-1308), and King Gongmin (r. 1351-1374). Particular attention is paid here to the changes in the types and forms of celadon wine vessels that occurred starting in the reigns of King Yejong and King Chungnyeol, which is also the period in which the number of royal banquets increased and royal banquet culture evolved. The king and his subjects prayed for the king's longevity at royal banquets and celebrated peaceful reigns by drinking and performing various related acts. Thus, the visual symbolism of vessels for holding, pouring, or receiving alcohol were emphasized. Since the manner of drinking at a banquet was exchanges of pouring and receiving alcohol between the king and his subjects, the design of the ewers and cups had a significant visual impact on attendees. It can be seen, therefore, that decorating wine vessels with Daoist motifs such as the immortals, luan (a mythological bird), turtle dragons, fish dragons, and gourd bottles or with Confucian designs like hibiscus roots was intended as a visual manifestation of the purpose of royal banquets, which was to celebrate the king and to pray for both loyalty and immortality. In particular, the Peach Offering Dance (獻仙桃) and Music for Returning to the Royal Palace (還宮樂), which correspond to the form and design of celadon wine vessels, was examined. The lyrics of the banquet music embodied wishes for the king's longevity, immortality, and eternal youth as well as for the prosperity of the royal court and a peaceful reign. These words are reflected in wine vessels such as the Celadon Taoist Figure-shaped Pitcher housed in the National Museum of Korea and the Bird Shaped Ewer with Daoist Priest in the Art Institute of Chicago. It is important to note that only Goryeo celadon wine vessels reflect this facet of royal banquet culture in their shape and design. The composition of wine vessel sets changed depending on the theme of the banquet and the types of liquor. After Goryeo Korea was incorporated into the Mongol Empire, new alcoholic beverages were introduced, resulting in changes in banquet culture such as the uses and composition of wine vessel sets. From the reign of King Chungnyeol (r. 1274-1308), which was under the authority of the Yuan imperial court, royal banquets began to be co-hosted by kings and princesses, Mongolian-style banquets like boerzhayan (孛兒扎宴) were held, and attendees donned the tall headdress called gugu worn by Mongol women. During the reign of King Chungnyeol, the banquet culture changed 132 banquets were held. This implies that the court tried to strengthen its authority by royal marriage with the Yuan court, which augmented the number of banquets. At these banquets, new alcoholic drinks were introduced such as grape wine, dongnak (湩酪), and distilled liquor. New wine vessels included stem cups, pear-shaped bottles (yuhuchunping), yi (匜), and cups with a dragon head. The new celadon wine vessels were all modeled after metal wares that were used in the Yuan court or in the Khanates. The changes in the celadon wine vessels of the late Goryeo era were examined here in a more specific manner than in previous studies by expanding the samples for the study to the Eurasian khanates. With the influx of new types of wine vessels, it was natural for the sets and uses of Goryeo celadon wine vessels to change in response. The new styles of celadon wine vessels linked the Goryeo court with the distant Khanates of the Mongol Empire. This paper is the beginning of a new study that examines the uses of Goryeo celadon by illuminating the relations between royal banquets and these unique celadon wine vessels that are stylistically different from everyday vessels. It is to be hoped that more studies will be conducted from diverse perspectives exploring both the usage of Goryeo celadon vessels and their users.