• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Journal of Nutrition and Health
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• v.50 no.4
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• pp.402-414
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• 2017

Purpose: The purpose of the study was to evaluate the status of safety accidents and importance-performance analysis (IPA) between regular and non-regular employees in industry foodservices. Methods: The participants were regular employees (n = 119) and non-regular employees (n = 163) in industry foodservices in the Jeonbuk area. Demographic characteristics, status of safety accidents, safety education, and importance and performance status were assessed using a self-administered questionnaire. Results: Approximately 66.4% of regular employees and 53.4% of non-regular employees experienced safety accidents (p < 0.05). Types of safety accidents of regular and non-regular employees were mostly burns, and causes were mostly from their own negligence. Approximately 98.3% of regular employees and 95.1% of non-regular employees experienced safety education. Approximately 88.9% of regular employees and 96.8% of non-regular employees received safety education from dietitians. Approximately 41.9% of regular employees and 50.0% of non-regular employees had difficulty applying the contents of safety education due to lack of time during work. As a result of IPA, regular and non-regular employees were aware of the importance of the following and performed them well: 'Clean the floor of the work place', 'Arrange in the work area', 'Wear safety shoes', 'Check for heater cord', and 'Safety cooking when using oil'. On the other hand, they were not aware of the importance of the following and performed them insufficiently: 'Check for the MSDS', 'Aware of chemical signs', 'Wear protection gloves etc.', 'Do stretching exercise', and 'Using ancillary tools'. Conclusion: Therefore, it is necessary to improve the consciousness of dietitians for effective application of safety education contents, development of contents, especially MSDS, and related things.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.381-391
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• 1997

In an epidemiological study of metal workers exposed to metalworking fluids (MWF), the prevalence time of Evolution, seasonal occurrence and clinical type of contact dermatitis were investigated. Compostional analysis of MWF with HPLC, dermatological examination and two consecutive questionnaire surveys were conducted. Study population was divided into two groups ; workers contact to cutting oil and workers contact to rust preventive oil. In the analysis of MWF, aliphatic hydrocarbons, having 12-20 carbons, was most common composition(49.04%) of cutting oil otherwise, major contents (90.99%) of the rust preventives oil were aliphatic hydrocarbons composed of 6-9 carbons. The frequency (point prevalence) of contact dermatitis(CD) was 7(12.7 per 100 subjects) in the dermatological examination of 55 workers. As the result of second survey for contact dermatitis, cumulative prevalence of oil working full-time and recent 1 year prevalence in two groups were 28.0, 16.7 and 15.1, 12.5 per 100 subjects. There were no difference in the prevalence of CD by oil, age, oil contact duration. Summer is the most common evolution season in workers exposed to cutting oil, but not in workers exposed to rust preventive oil. Major clinical type of CD was erythematous papules in both groups. It presents the importance of preventive measures that 51.1% suffer from contact dermatitis had medical care at their own expense, and 47.1% of them felt serious about their contact dermatitis. From the fact that 68.6% think cotton gloves protective apparatus, we emphasize the need for health education.

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

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

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

• Journal of The Korean Society of Grassland and Forage Science
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• v.18 no.2
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• pp.79-88
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• 1998

This experiment was conducted from May to August in 1997 to selected the wrn hybrids being suitable for silage at farm in the Kongju National University through the comparison of growth characteristics, forage yield and growth analysis about native and imported corn hybrids for silage production. In this experiment, trial design was a randomized block design with three replication, testing varieties were 4 hybrids (Suwon 19, Kwanganok, Whengsungok, Suwonok ) of native corn hybrids and 13 hybrids (P 3156, P 3352, P 3144w, DK 501, DK 689, DK 713, DK 729, H 643.99, H 545.64, H 645.12, HC 7466, H 644.18, H ALISEO) of imported corn hybrids. The results obtained are summarized as follows; 1. The emergence rate of H643.99 was the highest with 97.0%. In rice black streaked dwarf virus(RBSOV), the hybrid of HC 7466 was lower infected with 1.6% than other hybrids. The plant hight of P 3144w was the highest with 339 cm and the stem length of P 3156 was the highest with 261 cm. In native com hybrids, the plant height and stem length of Kwanganok were recorded with 306 cm and 235 cm, respectively. 2. Leaf number and leaf area of Kwanganok were the greatest with 16 sheet per plant and $5,180\;{\textrm{m}^2}/l0a$, respectively. H 645.12 and H 545.64 had the greatest in ear to total dry matter ratio with 49.5% and 49.4%, respectively. 3. The fresh matter yield was significantly difference between growth stage, So Suwon 19 had the most level at 15 days before silking, P 3352 had the most level at silking date, Kwananok had the most level at 35 days a after silking. The fresh matter yield of native com hybrids such as Suwon 19 and Kwanganok was not apparent diffreences as compared with imported corn hybrids. 4. As the results of survey with dry weight, the quantity of dry matter accumulation were increase after silking. The varieties of P 3352, P 3156, Kwanganok, OK 713 were more quantity of dry matter production than DK 501, HC 7466. The Kwanganok of native com hybrid and Pioneer strain with high percentage of dry matter were higher dry weight than Limagrain strain. 5. HC 7466 had the largest LAR with $6.53\;{\textrm{cm}^2}/g$, H545.12 had the lowest LAR with $3.30\;{\textrm{cm}^2/g}$. P 3144 had the largest LAI, DeKalb strain including DK 713 were larger apparently than Limagrain strain including HC 7466 with 3.15. 6. The RGR of testing varieties was little difference of statistical significantly, but DK 501, and HC 7466 were lower than other corn hybrids. The CGR of native and American varieties was no apparent differences, but that of Limagrain strains were a large variation. According to the results obtained by this experiment, the eary growth such as emergence rate and RBSDV infection rate of Limagrain strains was more excellent than other strains. P 3156, P 3352, P 3144w, DK 713 and HC 7466 were suitable for silage condition such as dry matter yield, percentage of dry matter and % ear to total dry matter. The fresh and dry matter yield of native corn hybrids such as Suwon 19 and Kwanganok were not apparent differences as compared with imported corn hybrids, but percentage of dry matter was lower than other imported corn hybrids.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.6
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• pp.511-522
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• 1984

The Nagdong is one of the biggest rivers in Korea, which is very important water source not only for tap water of Pusan city but also for the industrial water. Therefore, authors tried to check the water quality year by year. In this experiment one hundred and twenty water samples collected from August 1983 to July 1984 were analyzed bacteriologically and physiologically. Fifteen sampling stations were established between near Samrangjin and estuary of the river. To evaluate the water quality, temperature, pH, chloride ion, salinity, chemical oxygen demand (COD), electrical conductivity, nutrients, total coliform, fecal coliform, fecal streptococcus, viable cell count and bacterial flora were observed. The variation of water temperature was ranged $-1.5{\sim}29.0^{\circ}C$ (Mean value $13.9{\sim}16.5^{\circ}C$), it in spring was higher as $10{\sim}15^{\circ}C$ about $10^{\circ}C$ than in winter and it in autumm was very stabilized as about $20^{\circ}C$ at each station. The pH variation of the samples was ranged $6.68{\sim}9.15$. The range of concentration of chloride ion and salinity varied $7.4{\sim}l,020.5$ mg/l and $1.05{\sim}33.0\%0$, respectively. Especially, salinity of the 3rd water war was the higher than others as $25.76{\sim}31.58\%0$. COD was ranged $1.45{\sim}14.94$ mg/l and the lower part of the Nagdong River was heavily contaminated by domesitc sewage and waste water from the adjacent factor area. The range of electrical conductivity was $1.360{\times}10^2{\sim}5.650{\times}10^4{\mu}{\mho}/cm$ and that was by far higher the estuary than the upper. Concentration of nutrients were $0.008{\sim}0.040$ mg/l (Mean value $0.019{\sim}0.068$ mg/l) for $NO_2-N,\;0.038{\sim}5.253$ mg/l ($0.351{\sim}2.347$ mg/l) for $NO_3-N,\;0.100{\sim}2.685$ mg/l($0.117{\sim}1.380$ mg/l) for $NH_4-N,\;0.003{\sim}0.084$ mg/l($0.014{\sim}0.065$ mg/l) for $PO_4-P$ and $0.154{\sim}6.123$ mg/l ($1.165{\sim}3.972$ mg/l) for $SiO_2-Si$, respectively. Usually nutrients contents of the water in the upper part(included station 1 to 5) were higher than those of the estuarine area. The bacterial density of the samples ranged 7.3 to 460,000/100 ml for total coliforms, 3.6 to 460,000/100 ml for fecal coliform, $0{\sim}46,000/100ml$ for fecal streptococcus and $<30{\sim}1.2{\times}10^5/ml$ for viable cell count. Composition of coliform was $28\%$ Escherichia coli group, $18\%$ Citrobacter freundii group, $31\%$ Enterobacter aerogenes group and $22\%$ others. Predominant species among the 659 strains isolated from the samples were Pseudomonas spp. ($42\%$), Flavobacterium spp. ($20\%$) and Moraxella spp. ($12\%$).