• Journal of Korean Academy of Nursing
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• v.4 no.1
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• pp.162-178
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• 1974

The present study is purported to provide a basic information to be utilized by nurses to care and attend effectively for patients nearing the moment of death. Therefore, the primary purpose of the study has been placed upon grasping an understanding of the trends of death in general. For this purpose: 1. By utilizing the schneidman questionnaire, the trend of death has been categorized by 6 parts and analyzed. 2. A search has been conducted to find out dying patient's needs, nurse's attitudes viewed by the patient, and nurse attitudes to dying patient. The followings are itemized results of analysis: 1. Analysis by the schneidman questionnaire. (1) In general concepts of death. the first sighting of the occurrence of death was experienced upon strangers, grandfather and great grandfather. The death is openly discussed among people of all ages and sex. Ages in which the death is mostly feared were from 12 to well over 70 yews old that are evenly distributed regardless of difference in age. (2) As to the attitudes toward death the occurrence of death to most closely associated person influenced most upon the attitude of their own termination of lives. Among the reading materials, the maximum influence was effected by the Bible. In terms of religion, the thoughts of death were Influenced by religions education in case of the believers of the western religions (36%), and by their own health and physical conditions in case of the believers in the oriental religions (35%). In case of non-believer, their attitude toward death were largely determined through their own thinking meditation (45%). People aged 20 or thereunder revealed that they wished to know the day of their own death to be occurred (58%). However, the older the less thor wanted to know. (3) As to the choosing the time of death, 57% preferred senility, and 30% preferred the time in mediately following the prime period of their lives in general. In terms of religion, 85% of the believer in the oriental religion preferred senility, and 67% in the western religion, 58% in others, Therefore. the desiring of their lives to be terminated in earlier stage, not by the natural senility. sequenced as follows : Others, western religions and oriental religions. (4) Referring to the disposal of the corpse under the assumption that it had already occurred, majority desired the burial system. There has been seen a slight tendency to consider the importance of holding funeral services for the sake of survivors. Concerning the life insurance policy, it showed that the nurse had less belief in it than the patient (5) Upon the subject of life-after-death. religion wise, 72% of western religion believers preferred to have an existence of life-after-death: Among the believers of oriental regions, 35% desired this category, 30% did not mind either way. and 35% did not desire the existence of such a life-after-death. In others, 53% did not mind whether or not such a life existed. (6) In general, serious thoughts were not being attended to the commitment of suicide. 37% emphasized that such an act should be prevented. However, 30% insisted that such commitment should not be bothered, and that society possesses no right to prevented it. More male wished to commit suicide (13%) than females (9%). 2. Nurse's attitudes toward terminal patients and patient's needs. In the instance where the patient realized that their death is imminent, most of them showed desire to discuses mainly on the problems of life. When faced a situation of this nature, it is revealed that 40% of nurses could not furnish appropriate care for them.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.352-362
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• 2023

Harvest time is one of the most important determining factors of seed quality, especially for species that produce seeds over irregular and long-term periods, such as Larix kaempferi. A cone collection plan must be established to increase seed production efficiency and stable mass production. We investigated seed qualities such as seed efficiency, germination rate, and T₅₀ (germination speed), with 7 or 8 cone collection times at a clonal seed orchard of L. kaempferi in Chungju between 2021 and 2022. A multivariate analysis was then performed for the collected data. In early August, decreases in the moisture contents and browning of cones were observed. These were followed by a decrease in germination rate, with a peak at the end of September, but no clear trend was observed. The later the cones were harvested, the better the seed vigor (T₅₀). However, the seed yield and efficiency decreased owing to increases in seed scattering and the number of insect-damaged seeds. As a result, the optimal time of seed harvest for the seed orchard was in early August. To produce uniform seedlings, insect damage must be reduced through timely control and harvest cones in early September. This shows that the degree of browning and moisture content of cones can be used as indicators of the timing of cone collection in L. kaempferi seed orchards.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• Korean Journal of Social Welfare
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• v.56 no.3
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• pp.159-181
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• 2004

This study examines the realities and causes of youth and new college graduate unemployment, and seeks some assignments for mitigating youth and new college graduate unemployment. An analysis of the realities and causes of youth and new college graduate unemployment is summarized as follows. First, youth unemployment rate, which rapidly increased after the IMF economic crisis, slowly decreased after 2000, but was still somewhat higher in 2002 than that before the IMF. Second, new college graduate unemployment rate, which rapidly increased after the IMF economic crisis, slowly decreased after 2000 and became a similar level to that before the IMF economic crisis, but the number of the unemployed new college graduates highly increased after the IMF. Third, an analysis of the causes of youth unemployment shows that economic growth and the employment elasticity of economic growth negatively affect the unemployment rate, and the rate of entrance into colleges positively affects the unemployment rate. Fourth, an analysis of the causes of new college graduate unemployment demonstrates that economic growth and the employment elasticity of economic growth negatively affect the unemployment rate, and the increase rate of new college graduates, the college graduate/youth population ratio, and the time trend positively affect the unemployment rate. These results suggest several implications for mitigating the unemployment rate of the youth and new college graduates. First, in order to increase labor demand, emphasis must be placed on preparing economic conditions which can raise economic growth rate and on fostering industries and occupations which have high employment elasticity. Second, in the aspect of labor supply, it is necessary to adjust the number of new college graduates corresponding to labor demands in industries. Third, in order to redress the mismatch between the demand and the supply of the youth labor market, attention should be paid to remedying educational systems such as the activation of vocational education and training in middle and high schools and the reformation of college education to match the education and training provided in colleges and the skills requirements of the world of work, and preparing a unified program to support the youth unemployed systematically and synthetically.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.257-280
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• 2022

In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

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

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

• Childhood Kidney Diseases
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• v.8 no.2
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• pp.186-194
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• 2004

Purpose: Membranoproliferative glomeulonephritis(MPGN) has been diagnosed in an increasing number of asymptomatic cases. These cases have been detected by school urinary screening test even though the total cases of MPGN show a decreasing trend. We have analyzed the clinical and pathological characteristics of children with MPGN according to the clinical manifestations at the time of disease presentation. Methods: A total of 18 patients who had been diagnosed with idiopathic MPGN by percutaneous renal biopsy from January 1990 to February 2004 were involved in our study. The patients were divided into 2 groups as the school urinary screening(A) group and the symptomatic(S) group according to the clinical manifestations at the time of disease presentation. Results: Out of the total 18 patients, 8(44.4%) were in the S group and 10(55.6%) were in the A group. The mean serum total protein, albumin and $C_3$ levels in the S group were significantly lower than those levels of the A group, respectively($4.9{\pm}1.2\;g/dL,\;vs\;7.0{\pm}0.5\;g/dL\;P=0.002,\;2.8{\pm}0.9\;g/dL\;vs.\;4.1{\pm}0.3\;g/dL\;P=0.002,\;63.9{\pm}36.4\;mg/dL\;vs.\;100.8{\pm}39.5\;g/dL\;P=0.041$). The mean total protein amount of 24 hour collected urine in the S group were significantly higher than that of the A group($3684.0{\pm}2601.3\;mg/m^2\;vs.\;559.4{\pm}4.6.9\;mg/m^2$, respectively, P=0.001). Hypocomplementemia was observed in 11(61.1%) out of 18 patients at the time of disease onset, 7(87.5%) in the S group and 4(40%) in the A group. However the hypocomplementemia was decreased in 6(33.3%) out of 18 patients at the time of final follow-up, 3(37.5%) in the S group and 3(30%) in the A group. According to the pathologic type, hypocomplementemia was observed 8 patients(61.5%) with type I disease, 1 patients (100%) with type II disease, 2 patients(50%) in type III disease at the disease onset, but 4 patients(30.8%) in type I disease, 1 patient(100%) in type II disease, 1 patient(33.3%) with type III disease at the time of last follow-up. The incidence of cellular crescent formation and tubular atropy. as observed on light microscopy, were higher in the S group compared to the A group. Mean grade of capillary wall thickening and, mesangial proliferation were significantly higher in the S group. Conclusion: MPGN, as diagnosed in patients with only asymptomatic urinary abnormalities, has been increasing, it is more frequent in asymptomatic patients than in patients with presenting symptoms. Our result suggests that MPGN should be considered in the renal biopsy diagnosis regardless of serum $C_3$ level when urinary abnormalities are found by school urinary screening test.