• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.40-51
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• 2019

Ginseng has a unique production system that is different from those used for other crops. It is subject to the Ginseng Industry Act., requires a long-term cultivation period of 4-6 years, involves complicated cultivation characteristics whereby ginseng is not produced in a single location, and many ginseng farmers engage in mixed-farming. Therefore, to bring the production of Ginseng in line with GAP standards, it is necessary to better understand the on-site practices of Ginseng farmers according to established control points, and to provide a proper action plan for improving efficiency. Among ginseng farmers in Korea who applied for GAP certification, 77.6% obtained it, which is lower than the 94.1% of farmers who obtained certification for other products. 13.7% of the applicants were judged to be unsuitable during document review due to their use of unregistered pesticides and soil heavy metals. Another 8.7% of applicants failed to obtain certification due to inadequate management results. This is a considerably higher rate of failure than the 5.3% incompatibility of document inspection and 0.6% incompatibility of on-site inspection, which suggests that it is relatively more difficult to obtain GAP certification for ginseng farming than for other crops. Ginseng farmers were given an average of 2.65 points out of 10 essential control points and a total 72 control points, which was slightly lower than the 2.81 points obtained for other crops. In particular, ginseng farmers were given an average of 1.96 points in the evaluation of compliance with the safe use standards for pesticides, which was much lower than the average of 2.95 points for other crops. Therefore, it is necessary to train ginseng farmers to comply with the safe use of pesticides. In the other essential control points, the ginseng farmers were rated at an average of 2.33 points, lower than the 2.58 points given for other crops. Several other areas of compliance in which the ginseng farmers also rated low in comparison to other crops were found. These inclued record keeping over 1 year, record of pesticide use, pesticide storages, posts harvest storage management, hand washing before and after work, hygiene related to work clothing, training of workers safety and hygiene, and written plan of hazard management. Also, among the total 72 control points, there are 12 control points (10 required, 2 recommended) that do not apply to ginseng. Therefore, it is considered inappropriate to conduct an effective evaluation of the ginseng production process based on the existing certification standards. In conclusion, differentiated certification standards are needed to expand GAP certification for ginseng farmers, and it is also necessary to develop programs that can be implemented in a more systematic and field-oriented manner to provide the farmers with proper GAP management education.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• 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.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.116-137
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• 2024

This study quantitatively explored the interrelationship between water features and surrounding waterscape elements through a literature review and observational study targeting nine waterscapes of Suzhou Classical Garden in Jiangsu Province, China, which is designated as a UNESCO World Heritage Site. The purpose was to understand the objective characteristics of classical Chinese gardens and seek a basis for their differences from Korean gardens. The average area of water space in Suzhou gardens was 1,680.7㎡, which accounted for 21.3% of the total garden area, showing large variation by garden. Most of the Suzhou Gardens use springs and wells as their water sources. The Surging Waves Pavillion uses surface water, and Retreat & Reflection Garden uses seasonal water as its water source. The water pipes in Suzhou Garden are divided into a water outlet and a water outlet(water holes). Of these, the water outlet is a water outlet that imitates the water outlet just to induce a visual effect, and focuses on the meaning of the water system. It is judged to have been combined with the trend of Suzhou gardens. In addition, it was confirmed that, semantically, the arrangement of the water polo in Suzhou Garden is based on the traditional 'Gamyeo(堪輿) theory'. Meanwhile, there are five types of methods for bringing water to Suzhou Garden: Jiginbeop(直引法), Myeonggeobeop(明渠法), Invasionbeop(滲透法), Gwandobeop(管道法), and Chakjeongbeop(鑿井法). Suzhou Classical Garden mainly applies the infiltration method and the irrigation method as a method of securing water in the garden, which can be classified and defined as the water catchment method(集水法) and the water pulling method(引水法) in the domestic classification method. Among the watering techniques in Korean traditional gardens, watering methods such as 'suspension waterfall(懸瀑)', 'flying waterfall(飛瀑)' and water eluted(湧出), have not been found, and it is believed that they mainly 'rely on hide with dignity(姿逸)' and 'submerged current(潛流)' techniques. As for the watering technique, no watering technique was found that uses a Muneomi, which is applied in traditional Korean gardens. As this was applied, the seal method, penetration method, and Gwandobeop were also used in water extraction techniques. And at the inlet and outlet of Suzhou Garden, the main static water bodies were lakes, swamps, and dams. While the eastern water bodies are classified into streams, waterfalls, and springs, the water spaces in the three gardens reflect the centrifugal distributed arrangement, and the water spaces in the six places reflect the water landscape effect due to the centripetal concentrated arrangement. And as a water space landscape design technique, the techniques of 'Gyeok(隔)' and 'Pa(破)' were mainly applied at the inlet, and the techniques of 'Eom(隔)' and 'Pa(破)' were mainly applied at the outlet. For example, most bridges were built around the inlet, and sa(榭), heon(軒), gak(閣), pavilion(亭), and corridor(廊) were built, and the outlet was concealed with a stone wall. Therefore, it is understood to have embodied Suzhou Garden's idea of water(理水), which says, "Although it was created by humans, it is as if the sky is mine(雖由人作，宛自天開)."A trend was detected. Lastly, as a result of analyzing the degree of concealment and exposure in the visual composition of the inlet and outlet, it was confirmed that the water outlet was exposed only at the Eobijeong and Mountain Villa with Embracing Beauty view points of The Surging Waves Pavillion and the water outlet was hidden at other view points. Looking at these results, the 'Hyang-Hyang-Ba-Mi-Bob(向向發微法)' from the perspective of left-orientation theory of Feng Shui, which is applied in Korean traditional gardens in classical Chinese garden water management, "makes water visible as it comes in, but invisible as it goes out." It is judged that the technique was barely matched.

• 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 Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• International Commerce and Information Review
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• v.10 no.4
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• pp.457-491
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• 2008

As stage equipment export markets along with special lighting service lack the attraction for already globally established businesses, such markets can be viewed as an advantageous opportunity for SMEs as in general. In reality, global businesses tend to focus on large construction projects and this indicates relatively less substantial markets such as stage equipment and special lighting service export are more suitable for SME businesses. However, possible problems may be recognized as following; doubtful capabilities by such businesses to join in the vast and competitive global market and pursue manufacturing and service based export. This point is also supported by the fact that such in general SME businesses have substantially less experience in exporting products and services abroad. Realizing the distinctive features of the Korean economy, it is unarguable that every sector and area of global market must be regarded and monitored closely. Hence, it can be argued that there is an imminent need for establishment of supportive institution to assist export process of combination of stage equipments and special lighting service. This study emphasizes the need to improve export process of stage equipments, special lighting services as well as other related products and services which have been focused in domestic market only until now. Further, it also analyzed the potential prospect of such direction reconciling current crisis our manufacturing industry is facing. Even though it maybe regarded as one of the niche market for export of Korea in the short term view, stage equipment and special lighting service industry may rapidly grow as the global cultural industries have grown along with the increase of national income earnings overall. Due to such advantageous features, it can be expected that such industries will show strong growth in the near future. After analyzing the fact that Korea's plants (eg. powerplants) export sector is at its boom, there is a need to transform stage equipment and special lighting service export market into a primary market from a secondary(niche) market for SMEs. This study is viewed from the Korean economic and export sector aspect in the aim of seeking a solution to conquest our realistic limit in our export sector by developing a suitable export model. There have been cases of very few attempts to expand abroad by SMEs who have failed miserably due to their failure to adapt to foreign culture, practice and languages as well as substantial lack in experience in export marketing. Despite this, neglecting our manufacturing industry as it is which is showing its limit and problems is out of option therefore, it is imminent that we come up with an effective measure to address this problem and service export can be suggested as one of them. This study reveals manufacturing-service export model of stage equipment and special lighting service and its related areas is recognized as a field with a very strong future and furthermore, it is expected to bring synergy effects in manufacturing and services sector as well. Further, the operation strategy contains combination, composition and fusion(convergence) of manufacturing and service sectors which could derive various of export products which displays greater success probability or this export model. The outcome of this research is expected to become a useful source for enterprises related to such industry which are seeking a possible global expansion. Furthermore, it is also expected to become a catalyst which fastens the process of global expansion and not only that, we are firmly assured that this study will become an opportunity to improve our current policies and institutions related to this area's export market.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of Korean Society of Archives and Records Management
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• v.5 no.2
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• pp.27-48
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• 2005

This study investigates the current preservation and management of four records and documentary heritage in Korea that is in the UNESCO's Memory of the World Register. The study analyzes their problems and corresponding solutions in digitizing those world records heritages. This study also reviews additional four documentary books in Korea that are in the wish list to add to UNESCO's Memory of the World Register. This study is organized as the following: Chapter 2 examines the value and meanings of world records and documentary heritage in Korea. The registry requirements and procedures of UNESCO's Memory of the World Register are examined. The currently registered records of Korea include Hunmin-Chongum, the Annals of the Choson Dynasty, the Diaries of the Royal Secretariat (Seungjeongwon Ilgi), and Buljo- Jikji-Simche-Yojeol (vol. II). These records heritage's worth and significance are carefully analyzed. For example, Hunmin-Chongum("訓民正音") is consisted of unique and systematic letters. Letters were delicately explained with examples in its original manual at the time of letter's creation, which is an unparalleled case in the world documentary history. The Annals of the Choson Dynasty("朝鮮王朝實錄") are the most comprehensive historic documents that contain the longest period of time in history. Their truthfulness and reliability in describing history give credits to the annals. The Royal Secretariat Diary (called Seungjeongwon-Ilgi("承政院日記")) is the most voluminous primary resources in history, superior to the Annals of Choson Dynasty and Twenty Five Histories in China. Jikji("直指") is the oldest existing book published by movable metal print sets in the world. It evidences the beginning of metal printing in the world printing history and is worthy of being as world heritage. The review of the four registered records confirms that they are valuable world documentary heritage that transfers culture of mankind to next generations and should be preserved carefully and safely without deterioration or loss. Chapter 3 investigates the current status of preservation and management of three repositories that store the four registered records in Korea. The repositories include Kyujanggak Archives in Seoul National University, Pusan Records and Information Center of National Records and Archives Service, and Gansong Art Museum. The quality of their preservation and management are excellent in all of three institutions by the following aspects: 1) detailed security measures are close to perfection 2) archiving practices are very careful by using a special stack room in steady temperature and humidity and depositing it in stack or archival box made of paulownia tree and 3) fire prevention, lighting, and fumigation are thoroughly prepared. Chapter 4 summarizes the status quo of digitization projects of records heritage in Korea. The most important issue related to digitization and database construction on Korean records heritage is likely to set up the standardization of digitization processes and facilities. It is urgently necessary to develop comprehensive standard systems for digitization. Two institutions are closely interested in these tasks: 1) the National Records and Archives Service experienced in developing government records management systems; and 2) the Cultural Heritage Administration interested in digitization of Korean old documents. In collaboration of these two institutions, a new standard system will be designed for digitizing records heritage on Korean Studies. Chapter 5 deals with additional Korean records heritage in the wish list for UNESCO's Memory of the World Register, including: 1) Wooden Printing Blocks(經板) of Koryo-Taejangkyong(高麗大藏經) in Haein Temple(海印寺); 2) Dongui-Bogam("東醫寶鑑") 3) Samguk-Yusa("三國遺事") and 4) Mugujeonggwangdaedaranigyeong. Their world value and importance are examined as followings. Wooden Printing Blocks of Koryo-Taejangkyong in Haein Temple is the worldly oldest wooden printing block of cannon of Buddhism that still exist and was created over 750 years ago. It needs a special conservation treatment to disinfect germs residing in surface and inside of wooden plates. Otherwise, it may be damaged seriously. For its effective conservation and preservation, we hope that UNESCO and Government will schedule special care and budget and join the list of Memory of the Word Register. Dongui-Bogam is the most comprehensive and well-written medical book in the Korean history, summarizing all medical books in Korea and China from the Ancient Times through the early 17th century and concentrating on Korean herb medicine and prescriptions. It is proved as the best clinical guidebook in the 17th century for doctors and practitioners to easily use. The book was also published in China and Japan in the 18th century and greatly influenced the development of practical clinic and medical research in Asia at that time. This is why Dongui Bogam is in the wish list to register to the Memory of the World. Samguk-Yusa is evaluated as one of the most comprehensive history books and treasure sources in Korea, which illustrates foundations of Korean people and covers histories and cultures of ancient Korean peninsula and nearby countries. The book contains the oldest fixed form verse, called Hyang-Ka(鄕歌), and became the origin of Korean literature. In particular, the section of Gi-ee(紀異篇) describes the historical processes of dynasty transition from the first dynasty Gochosun(古朝鮮) to Goguryeo(高句麗) and illustrates the identity of Korean people from its historical origin. This book is worthy of adding to the Memory of the World Register. Mugujeonggwangdaedaranigyeong is the oldest book printed by wooden type plates, and it is estimated to print in between 706 and 751. It contains several reasons and evidence to be worthy of adding to the list of the Memory of the World. It is the greatest documentary heritage that represents the first wooden printing book that still exists in the world as well as illustrates the history of wooden printing in Korea.

• Journal of agricultural medicine and community health
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• v.19 no.2
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• pp.141-158
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• 1994

To provide better health care services to the rural population, the government has made the Community Health Practitioner(CHP) a regular government official from April 1, 1992. This study was carried out to study the impact of officialization of CHP on the activities and management system of Primary Health Post(PHP). Fifty PHPs were selected by two stage sampling, cluster and simple random, from 595 PHPs in Kyungnam and Kyungpook provinces. Data were collected by a personal interview with CHPs and review of records and reports kept in the PHPs. The study was done for the periods of January 1-March 31, 1992 (before officialization) and January 1-March 31, 1993 (after officialization). Ninety-six percent of the CHPs wanted to become a regular government official in the hope of better job security and higher salary. The proportion of CHPs who were proud of their iob was increased from 24% to 46% after officialization. Those CHPs who felt insecure for their job decreased from 30% to 10%. Monthly salary was increased by 34% from 802,600 Won to 1,076,000 Won and 90% of the CHPs were satisfied with their salary, also more CHPs responded that they have autonomy in their work planning, implementation of plan, management of the post, and evaluation of their activity. There were no appreciable changes in such CHPs' activities as assessment of local health resources, drawing map for the catchment area, utilization of community organization, grasping the current population structure in the catchment area, keeping the family health records, individual and group health education, and school health service. However, the number of home visits was increased from 13.6 times on the average per month per CHP to 27.5 times. More mothers and children were referred to other medical facilities for the immunization and family planning services. Average number of patients of hypertension, cancer, and diabetes in three months period was decreased from 12.7 to 11.6, from 1.5 to 1.2, and 4.3 to 3.4, respectively. Records for the patient care, drug management, and equipment were well kept but not for other records. The level of record keeping was not changed after officialization. The proportion of PHPs which had support from the health center was increased for drug supply from 14.0% to 30.0%, for consumable commodities from 22.0% to 52.0%, for maintenance of PHP from 54.0% to 68.0%, for supply of health education materials from 34.0% to 44.0%, and supply of equipment from 54.0% to 58.0%. Total monthly revenue of a PHP was increased by about 50,000 Won; increased by 22,000 Won in patient care and 34,700 Won in the government subsidy but decreased in the membership due and donation. However, there was no remarkable changes in the expenditure. The proportion of PHPs which had received official notes from the health center for the purpose of guidance and supervision of the CHPs was increased from 20% to 38% during three months period and the average number of telephone call for supervision from the health center per PHP was increased from 1.8 to 2.1 times(p<0.01). However, the proportion of PHPs that had supervisory visit and conference was reduced from 79% to 62%, and from 88% to 74%, respectively. The proportion of CHPs who maintained a cooperative relationship with Myun Health Workers was reduced from 42% to 36%, that with the director of health center from 46% to 24%, that with the chief of public health administration section from 56% to 36%, and that with the chairman of PHP management council from 62% to 38%. Most of the CHPs (92% before and 82% after officialization) stated that the PHP management council is not helpful for the PHP. CHPs who considered the PHP management council unnecessary increased from 4% to 16%(p<0.05). Suggestions made by the CHPs for the improvement of CHP program included emphasis on health education, assurance of autonomy for PHP management, increase of the kind of drugs that can be dispensed by CHPs, and appointment of an experienced CHP in the health center as the supervisor of CHPs. The results of this study revealed that the role and function of CHPs as reflected in their activities have not been changed after officialization. However, satisfaction in job security and salary was improved as well as the autonomy. Support of health center to the PHP was improved but more official notes were sent to the PHPs which required the CHPs more paper works. Number of telephone calls for supervision was increased but there was little administrative and technical guidance for the CHP activities.