• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of The Korean Society of Grassland and Forage Science
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• v.27 no.1
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• pp.9-20
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• 2007

This experiment was conducted to investigate effects of application of diluted and undiluted cattle slurry with water on seasonal and annual dry matter yields and feed values of tall fescue in the uncultivated rice paddy and it was compared with chemical fertilizer in order to determine optimal application season and dilution level of cattle slurry. When diluted or undiluted cattle slurry with water was applied to uncultivated rice paddy, annual dry matter yields showed 11.31 to 14.81 ton DM/ha (average 13.13 ton DM/ha) for diluted and 10.57 to 12.51 ton DM/ha (average 11.50 ton DM/ha) for undiluted cattle slurries, these had a higher dry matter yield than those of no fertilizer (9.21 ton DM/ha). Furthermore, separate application of early spring and summer (SA plots), separate application of early and late spring, and summer (SUA plots) fur undiluted cattle slurries, and whole application of spring (DS plots), separate application of early spring and summer (DSA plots), separate application of early and late spring, and summer (DSUA plots) for diluted cattle slurries were significantly (P<0.05) higher for annual dry matter yield than no fertilizer plots. Plots applied chemical fertilizer with nitrogen (N), phorphorus (P) and potassium (K) had 15.38 ton DM/ha annually, resulted in significantly (P<0.05) higher DM yield than chemical fertilizer containing P and K, and no fertilizer plots. Moreover, average annual DM yield for the chemical fertilizer with P and K was lower than that of cattle slurry applications. The efinciency of DM production for mineral nitrogen of chemical fertilizers was annually average 31.3 kg DM/kg N. In terms of cutting time of tall fescue, it was lowered in the order of 2nd growth followed by 1st and 3rd growth. However, efficiencies of annual DM production of nitrogen for diluted and undiluted cattle slurries were 26.1 and 15.3 kg DM/kg N, respectively, especially, highest in 2nd growth. While, efficiencies of DM production for cattle slurry versus for mineral nitrogen were 48.9 (undiluted) and 83.4% (diluted), respectively. For annual crude protein (CP) contents of tall fescue, aqueous cattle slurry applications showed 9,9 to 11.6%, which were significantly (P<0.05) higher than no fertilization (9.5%) and chemical fertilizer (9.0 to 9.8%), but annual average NDF and ADF contents were lowest in no fertilization. On the contrary, relative feed value (RFV) and total digestible nutrients (TDN) of no fertilizer plots were significantly (P<0.05) higher than the other plots. The application of cattle slurry and their dilution significantly increased yields of crude protein and total digestible nutrients compared with no and/or P and K fertilizers (P<0.05). These trends were much conspicuous in water-diluted cattle slurries applied in the early and late spring and summer, separately (DSUA plots).

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.1-26
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• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.

• Journal of agricultural medicine and community health
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• v.26 no.2
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• pp.59-78
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• 2001

Data on reported cancer mortality in the Gyeongsangbuk- do province from 1991 to 1998 were collected and analyzed using the existing mortality reporting system as well as the public health network to furnish accurate data on reported cancer death and to collect data to establish a high quality district health plan. The overall crude death rate in Gyeongsangbuk province in 1991 was 74.56 deaths per 100,000-person but this rate increased to 79.22 in 1998. Among the deaths, the overall death rate of cancer was 16.7% in 1991, which increased to 19.3% in 1998; specifically the death rate of men increased from 19.4% in 1991 to 22.3% in 1998 while that of women increased from 12.4% in 1991 to 15.5% in 1998, showing a more increase among women. The types of cancer and associated death rates in 1991 were gastric cancer(41.5%), followed by liver cancer (28.8%), and lung and bronchogenic carcinoma(8.7%) and in 1998, gastric cancer (24.7%), followed by liver cancer(22.7%), lung and bronchogenic carcinoma(19.3%), showing the same order. For men and women, gastric cancer(40.2% and 44.7%, respectively) was the most common cancer death, followed by liver cancer(33.7% and 16.7%, respectively), and lung and bronchogenic carcinoma(10.2% and 5.0%, respectively) in 1991. However, in 1998, gastric cancer(27.8%) was still the most common type among both men and women, followed by liver cancer (18.5%) and lung and bronchogenic carcinoma(12.7%), showing the most decrease in gastric cancer but most increase in lung and bronchogenic carcinoma. The age- adjusted mortality rates by gastric cancer, hepatoma, laryngeal carcinoma were decreased in both male and female, and also uterine cancer was decreased in female. The age- adjusted mortality rates by lung and bronchogenic carcinoma, pancreatic cancer, rectal cancer were increased in both male and female, and also breast cancer was increased in female. The calculated overall age-adjusted death rate based on the 1995 population was 84.25 in 1991, which decreased to 77.67 in 1998. Male death rate decreased significantly from 119.81 in 1991 to 101.82 in 1998 while the female death rate increased from 48.64 in 1991 to 53.80 in 1998. A census of cancer death rate using accurate death records is important for the establishment of proper and high-quality district health and medical plan and policy. The effort to improve the accuracy of death reports using the health facility network, as had been attempted by this study, can be continued. Furthermore, there must be a way for the Health and Welfare Department to use the death reports to improve the present reporting system. Lastly, additional studies need to be conducted to investigate how much the accuracy was improved by the supplemented death reports in this study.

• Journal of Korean Academy of Nursing
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• v.12 no.2
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• pp.1-26
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• 1982

The main purpose of this study was to test the effect of the structured information on the sleep amount of the patients undergoing open heart surgery. This study has specifically addressed to the Following two basic research questions: (1) Would the structed in formation influence in the reduction of sleep disturbance related to anxiety and Physical stress before and after the operation? and (2) that would be the effects of the structured information on the level of preoperative state anxiety, the hormonal change, and the degree of behavioral change in the patients undergoing an open heart surgery? A Quasi-experimental research was designed to answer these questions with one experimental group and one control group. Subjects in both groups were matched as closely as possible to avoid the effect of the differences inherent to the group characteristics, Baseline data were also. collected on both groups for 7 days prior to the experiment and found that subjects in both groups had comparable sleep patterns, trait anxiety, hormonal levels and behavioral level. A structured information as an experimental input was given to the subjects in the experimental group only. Data were collected and compared between the experimental group and the control group on the sleep amount of the consecutive pre and post operative days, on preoperative state anxiety level, and on hormonal and behavioral changes. To test the effectiveness of the structured information, two main hypotheses and three sub-hypotheses were formulated as follows; Main hypothesis 1: Experimental group which received structured information will have more sleep amount than control group without structured information in the night before the open heart surgery. Main hypothesis 2: Experimental group with structured information will have more sleep, amount than control group without structured information during the week following the open heart surgery Sub-hypothesis 1: Experimental group with structured information will be lower in the level of State anxiety than control group without structured information in the night before the open heart surgery. Sub-hypothesis 2 : Experimental group with structured information will have lower hormonal level than control group without stuctured information on the 5th day after the open heart surgery Sub-hypothesis 3: Experimental group with structured information will be lower in the behavioral change level than control group without structured information during the week after the open heart surgery. The research was conducted in a national university hospital in Seoul, Korea. The 53 Subjects who participated in the study were systematically divided into experimental group and control group which was decided by random sampling method. Among 53 subjects, 26 were placed in the experimental group and 27 in the control group. Instruments; (1) Structed information: Structured information as an independent variable was constructed by the researcher on the basis of Roy's adaptation model consisting of physiologic needs, self-concept, role function and interdependence needs as related to the sleep and of operational procedures. (2) Sleep amount measure: Sleep amount as main dependent variable was measured by trained nurses through observation on the basis of the established criteria, such as closed or open eyes, regular or irregular respiration, body movement, posture, responses to the light and question, facial expressions and self report after sleep. (3) State anxiety measure: State Anxiety as a sub-dependent variable was measured by Spi-elberger's STAI Anxiety scale, (4) Hormornal change measure: Hormone as a sub-dependent variable was measured by the cortisol level in plasma. (5) Behavior change measure: Behavior as a sub-dependent variable was measured by the Behavior and Mood Rating Scale by Wyatt. The data were collected over a period of four months, from June to October 1981, after the pretest period of two months. For the analysis of the data and test for the hypotheses, the t-test with mean differences and analysis of covariance was used. The result of the test for instruments show as follows: (1) STAI measurement for trait and state anxiety as analyzed by Cronbachs alpha coefficient analysis for item analysis and reliability showed the reliability level at r= .90 r= .91 respectively. (2) Behavior and Mood Rating Scale measurement was analyzed by means of Principal Component Analysis technique. Seven factors retained were anger, anxiety, hyperactivity, depression, bizarre behavior, suspicious behavior and emotional withdrawal. Cumulative percentage of each factor was 71.3%. The result of the test for hypotheses show as follows; (1) Main hypothesis, was not supported. The experimental group has 282 minutes of sleep as compared to the 255 minutes of sleep by the control group. Thus the sleep amount was higher in experimental group than in control group, however, the difference was not statistically significant at .05 level. (2) Main hypothesis 2 was not supported. The mean sleep amount of the experimental group and control group were 297 minutes and 278 minutes respectively Therefore, the experimental group had more sleep amount as compared to the control group, however, the difference was not statistically significant at .05 level. Thus, the main hypothesis 2 was not supported. (3) Sub-hypothesis 1 was not supported. The mean state anxiety of the experimental group and control group were 42.3, 43.9 in scores. Thus, the experimental group had slightly lower state anxiety level than control group, howe-ver, the difference was not statistically significant at .05 level. (4) Sub-hypothesis 2 was not supported. . The mean hormonal level of the experimental group and control group were 338 ㎍ and 440 ㎍ respectively. Thus, the experimental group showed decreased hormonal level than the control group, however, the difference was not statistically significant at .05 level. (5) Sub-hypothesis 3 was supported. The mean behavioral level of the experimental group and control group were 29.60 and 32.00 respectively in score. Thus, the experimental group showed lower behavioral change level than the control group. The difference was statistically significant at .05 level. In summary, the structured information did not influence the sleep amount, state anxiety or hormonal level of the subjects undergoing an open heart surgery at a statistically significant level, however, it showed a definite trends in their relationships, not least to mention its significant effect shown on behavioral change level. It can further be speculated that a great degree of individual differences in the variables such as sleep amount, state anxiety and fluctuation in hormonal level may partly be responsible for the statistical insensitivity to the experimentation.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.1
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• pp.124-136
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• 2002

As an official journal of the Asian-Australasian Association of Animal Production Societies (AAAP), the Asian-Australasian Journal of Animal Sciences (AJAS) was born in February 1987 and the first issue (Volume 1, Number 1) was published in March 1988 under the Editorship of Professor In K. Han (Korea). By the end of 2001, a total of 84 issues in 14 volumes and 1,761 papers in 11,462 pages had been published. In addition to these 14 volumes, a special issue entitled "Recent Advances in Animal Nutrition" (April, 2000) and 3 supplements entitled "Proceedings of the 9th AAAP Animal Science Congress" (July, 2000) were also published. Publication frequency has steadily increased from 4 issues in 1988, to 6 issues in 1997 and to 12 issues in 2000. The total number of pages per volume and the number of original or review papers published also increased. Some significant milestones in the history of the AJAS include that (1) it became a Science Citation Index (SCI) journal in 1997, (2) the impact factor of the journal improved from 0.257 in 1999 to 0.446 in 2000, (3) it became a monthly journal (12 issues per volume) in 2000, (4) it adopted an English editing system in 1999, and (5) it has been covered in "Current Contents/Agriculture, Biology and Environmental Science since 2000. The AJAS is subscribed by 842 individuals or institutions. Annual subscription fees of US$ 50 (Category B) or US$ 70 (Category A) for individuals and US$ 70 (Category B) or US$ 120 (Category A) for institutions are much less than the actual production costs of US$ 130. A list of the 1,761 papers published in AJAS, listed according to subject area, may be found in the AJAS homepage (http://www.ajas.snu.ac.kr) and a very well prepared "Editorial Policy with Guide for Authors" is available in the Appendix of this paper. With regard to the submission status of manuscripts from AAAP member countries, India (235), Korea (235) and Japan (198) have submitted the most manuscripts. On the other hand, Mongolia, Nepal, and Papua New Guinea have never submitted any articles. The average time required from submission of a manuscript to printing in the AJAS has been reduced from 11 months in 1997-2000 to 7.8 months in 2001. The average rejection rate of manuscripts was 35.3%, a percentage slightly higher than most leading animal science journals. The total number of scientific papers published in the AJAS by AAAP member countries during a 14-year period (1988-2001) was 1,333 papers (75.7%) and that by non- AAAP member countries was 428 papers (24.3%). Japanese animal scientists have published the largest number of papers (397), followed by Korea (275), India (160), Bangladesh (111), Pakistan (85), Australia (71), Malaysia (59), China (53), Thailand (53), and Indonesia (34). It is regrettable that the Philippines (15), Vietnam (10), New Zealand (8), Nepal (2), Mongolia (0) and Papua New Guinea (0) have not actively participated in publishing papers in the AJAS. It is also interesting to note that the top 5 countries (Bangladesh, India, Japan, Korea and Pakistan) have published 1,028 papers in total indicating 77% of the total papers being published by AAAP animal scientists from Vol. 1 to 14 of the AJAS. The largest number of papers were published in the ruminant nutrition section (591 papers-44.3%), followed by the non-ruminant nutrition section (251 papers-18.8%), the animal reproduction section (153 papers-11.5%) and the animal breeding section (115 papers-8.6%). The largest portion of AJAS manuscripts was reviewed by Korean editors (44.3%), followed by Japanese editors (18.1%), Australian editors (6.0%) and Chinese editors (5.6%). Editors from the rest of the AAAP member countries have reviewed slightly less than 5% of the total AJAS manuscripts. It was regrettably noticed that editorial members representing Nepal (66.7%), Mongolia (50.0%), India (35.7%), Pakistan (25.0%), Papua New Guinea (25.0%), Malaysia (22.8%) and New Zealand (21.5%) have failed to return many of the manuscripts requested to be reviewed by the Editor-in-Chief. Financial records show that Korea has contributed the largest portion of production costs (68.5%), followed by Japan (17.3%), China (8.3%), and Australia (3.5%). It was found that 6 AAAP member countries have contributed less than 1% of the total production costs (Bangladesh, India, Indonesia, Malaysia, Papua New Guinea and Thailand), and another 6 AAAP member countries (Mongolia, Nepal and Pakistan, Philippine and Vietnam) have never provided any financial contribution in the form of subscriptions, page charges or reprints. It should be pointed out that most AAAP member countries have published more papers than their financial input with the exception of Korea and China. For example, Japan has published 29.8% of the total papers published in AJAS by AAAP member countries. However, Japan has contributed only 17.3% of total income. Similar trends could also be found in the case of Australia, Bangladesh, India, Indonesia, Malaysia and Thailand. A total of 12 Asian young animal scientists (under 40 years of age) have been awarded the AJAS-Purina Outstanding Research Award which was initiated in 1990 with a donation of US$ 2,000-3,000 by Mr. K. Y. Kim, President of Agribrands Purina Korea Inc. In order to improve the impact factor (citation frequency) and the financial structure of the AJAS, (1) submission of more manuscripts of good quality should be encouraged, (2) subscription rate of all AAAP member countries, especially Category B member countries should be dramatically increased, (3) a page charge policy and reprint ordering system should be applied to all AAAP member countries, and (4) all AAAP countries, especially Category A member countries should share more of the financial burden (advertisement revenue or support from public or private sector).

• Journal of Korean Society of Archives and Records Management
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• v.1 no.1
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• pp.69-94
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• 2001

The purpose of this paper is to provide an overview of the current status of the records management science education in Japan, and to examine the implications of the rapid growth of this filed while noting some of its significant issues and problems. The goal of records management science education is to improve the quality of information services and to assure an adequate supply of information professionals. Because records management science programs prepare students for a professional career, their curricula must encompass elements of both education and practical training. This is often expressed as a contrast between theory and practice. The confluence of the social, economic and technological realities of the environment where the learning takes place affects both. This paper reviews the historical background and current trends of records management science education in Japan. It also analyzes the various types of curriculum and the teaching staff of these institutions, with focus on the status of the undergraduate program at Surugadai University, the first comprehensive, university level program in Japan. The Faculty of Cultural Information Resources, Surugadai University, a new school toward an integrated information disciplines, was opened in 1994, to explore the theory and practice of the management diverse cultural information resources. Its purpose was to stimulate and promote research in additional fields of information science by offering professional training in archival science, records management, and museum curatorship, as well as librarianship. In 1999, the school introduced a master program, the first in Japan. The Faculty has two departments and each of them has two courses; Department of Sensory Information Resources Management; -Sound and Audiovisual Information Management, -Landscape and Tourism Information Management, Department of Knowledge Information Resources Management; -Library and Information Management, -Records and Archives Management The structure of the entire curriculum is also organized in stages from the time of entrance through basic instruction and onwards. Orientation subjects which a student takes immediately upon entering university is an introduction to specialized education, in which he learns the basic methods of university education and study, During his first and second years, he arranges Basic and Core courses as essential steps towards specialization at university. For this purpose, the courses offer a wide variety of study topics. The number of courses offered, including these, amounts to approximately 150. While from his third year onwards, he begins specific courses that apply to his major field, and in a gradual accumulation of seminar classes and practical training, puts his knowledge grained to practical use. Courses pertaining to these departments are offered to students beginning their second year. However, there is no impenetrable wall between the two departments, and there are only minor differences with regard requirements for graduation. Students may select third or fourth year seminars regardless of the department to which they belong. To be awarded a B.A. in Cultural Information Resources, the student is required to earn 34 credits in Basic Courses(such as, Social History of Cultural Information, Cultural Anthropology, History of Science, Behavioral Sciences, Communication, etc.), 16 credits in Foreign Languages(including 10 in English), 14 credits on Information Processing(including both theory and practice), and 60 credits in the courses for his or her major. Finally, several of the issues and problems currently facing records management science education in Japan are briefly summarized below; -Integration and Incorporation of related areas and similar programs, -Curriculum Improvement, -Insufficient of Textbooks, -Lack of qualified Teachers, -Problems of the employment of Graduates. As we moved toward more sophisticated, integrated, multimedia information services, information professionals will need to work more closely with colleagues in other specialties. It will become essential to the survival of the information professions for librarians to work with archivists, record managers and museum curators. Managing the changes in our increasingly information-intensive society demands strong coalitions among everyone in cultural Institutions. To provide our future colleagues with these competencies will require building and strengthening partnerships within and across the information professions and across national borders.

• Korean Journal of Ecology and Environment
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• v.35 no.1 s.97
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• pp.52-61
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• 2002

This research was conducted to evaluate the effect of forest management practices on pH and electrical conductivity to get fundamental information on water purification capacity after forest operation. Rainfall, throughfall and stemflow　were　sampled at the study sites which consist of Abies holophylla and Pinus koraiensis　in Gwangreung Experimental Forest for S months from May to November 1999. Mean pH of the throughfall of the beginning of the event was higher in management (thinning and pruning) sites of Abies holophylla and Pinus koraiensis stands than nonmanagement site of Abies holophylla and Pinus koraiensis stands. In addition, pH of the throughfall of the total amount of the event showed similar trends which are higher pH in the management sites compared with the non- management sites. This result indicates that managements such as thinning and pruning improve tree butler capacity of rainfall pH. According to the linear regression results, pH of the throughfall of the total amount of the event in non-management sites = 0.735${\times}$pH of the throughfall of the beginning of the event in non-management sites+1.849 ($R^2\;=\;0.82$) and pH of the throughfall of the total amount of the event in management sites= 0.863${\times}$pH of the throughfall of the beginning of the event in management sites +1.0242 ($R^2\;=\;0.87$). In case of stemflow pH, pH of the sternflow of the total amount of　the event in non-management sites = 0.53${\times}$pH of the stemflow of the beginning of　the event in non- management sites+2.7709 ($R^2\;=\;0.64$) and pH of the stemflow of the total amount of the event in management sites = 0.5854${\times}$pH of the stemflow of the beginning of the event in management sites+2.7045 ($R^2\;=\;0.65$). Electrical conductivity (EC) of the throughfall of the beginning and total amount of the event was highest in non- management site in Abies holophylla, followed by management sites in fsies Abies holophylla, non-management site in Pinus koraiensis, and management sites in Pinus koraiensis stands, respectively. According to the linear regression results, EC of the throughfall of the total amount of the event in non-managementsites = 0.4045${\times}$EC of the throughfall of the beginning of the event in non-management sites+26.766 ($R^2\;=\;0.69$) and EC of the throughfall of the total amount of the event in management sites = 0.6002${\times}$EC of the throughfall of the beginning of the event in management sites+8.0184 ($R^2\;=\;0.54$). In case of stemflow EC, EC of thestemflow of the total amount of the event in non-management sites = 0.6298${\times}$EC of the stemflow of the beginning of the event in non-management sites+11.582 ($R^2\;=\;0.72$) and pH of the stemflow of the total amount of the event in management sites =0.602${\times}$pH of the stemflow of the beginning of the event in management sites+20.783($R^2\;=\;0.49$).