• The Journal of Korean Society for Radiation Therapy
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• v.29 no.1
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• pp.37-48
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• 2017

Purpose: The most basic conditions of radiation therapy is to prevent unnecessary exposure of normal tissue. The risk factors that are important o evaluate the dose emitted to the lung and heart from radiation therapy for breast cancer. Therefore, comparing the dose factors of a normal tissue according to the radion treatment position and Seeking an effective radiation treatment for breast cancer through the analysis of the correlation relationship. Materials and Methods: Computed tomography was conducted among 30 patients with left breast cancer in supine and prone position. Eclipse Treatment Planning System (Ver.11) was established by computerized treatment planning. Using the DVH compared the incident dose to normal tissue by position. Based on the result, Using the SPSS (ver.18) analyzed the dose in each normal tissue factors and Through the correlation analysis between variables, independent sample test examined the association. Finally The HI, CI value were compared Using the MIRADA RTx (ver. ad 1.6) in the supine, prone position Results: The results of computerized treatment planning of breast cancer in the supine position were V20, $16.5{\pm}2.6%$ and V30, $13.8{\pm}2.2%$ and Mean dose, $779.1{\pm}135.9cGy$ (absolute value). In the prone position it showed in the order $3.1{\pm}2.2%$, $1.8{\pm}1.7%$, $241.4{\pm}138.3cGy$. The prone position showed overall a lower dose. The average radiation dose 537.7 cGy less was exposured. In the case of heart, it showed that V30, $8.1{\pm}2.6%$ and $5.1{\pm}2.5%$, Mean dose, $594.9{\pm}225.3$ and $408{\pm}183.6cGy$ in the order supine, prone position. Results of statistical analysis, Cronbach's Alpha value of reliability analysis index is 0.563. The results of the correlation analysis between variables, position and dose factors of lung is about 0.89 or more, Which means a high correlation. For the heart, on the other hand it is less correlated to V30 (0.488), mean dose (0.418). Finally The results of independent samples t-test, position and dose factors of lung and heart were significantly higher in both the confidence level of 99 %. Conclusion: Radiation therapy is currently being developed state-of-the-art linear accelerator and a variety of treatment plan technology. The basic premise of the development think normal tissue protection around PTV. Of course, if you treat a breast cancer patient is in the prone position it take a lot of time and reproducibility of set-up problems. Nevertheless, As shown in the experiment results it is possible to reduce the dose to enter the lungs and the heart from the prone position. In conclusion, if a sufficient treatment time in the prone position and place correct confirmation will be more effective when the radiation treatment to patient.

• Cartoon and Animation Studies
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• s.39
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• pp.215-231
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• 2015

The Cultural Revolution in the history of Chinese animation hinder the development of the initial animation, and after a negative assessment instrument provided the cause is to become sluggish growth of the Chinese animation. So this time animation are things that are the subject of academic research studies or analysis has been depreciating almost uniformly without evaluation. However, of all the cultural and artistic creation it is developing in its own specific historical conditions and has the aesthetic results. This paper puts the primary purpose is to hold in consideration the aesthetic principles that led to cultural and artistic creativity and objective perspective the achievements the Chinese animation of the time period of the Cultural Revolution. Cultural Revolution is avoided to the previous period in accordance with the socialist ideology of Mao Ze-dong(毛澤東) sikindaneun highlight the culture of the proletariat and placed our goal to create a new class culture. Therefore, cultural and artistic creation of this period is often inconsistent with this part of our aesthetic principles generally accepted character has a non- elitist and anti properties. Best drama is a creative one hand as a model to implement the principles of aesthetics, art and culture Cultural Revolution period kkophimyeo reference for understanding the aesthetic principles that animated the Chinese Cultural Revolution period of orientation. This paper has San Tu Chu(三突出), Hong Guang Liang(紅光亮), and Gao Da Quan(高大全) at the time of the Cultural Revolution aesthetic principles are reflected in how the concrete work, the Cultural Revolution when the animation is how to accommodate these aesthetic principles and placed emphasis on comparative studies on best pole and correlation of the Cultural Revolution when the Chinese animation to ensure that adaptation in own way. First, after analyzing whether the aesthetic principles of focusing on the similarities of the best pole time of the Cultural Revolution and China, and how to implement animation in the works, these aesthetic principles according to the analysis of positive and negative influence on the creation of Chinese animation It was described as neutral. The detailed analysis and comparative study courses were trying to access in two significant aspects of the characters and scenes directing. In terms of character animation of the Cultural Revolution in China when a young boy or girl, emphasis should emphasize the health tinged with red lips and cheek blush to highlight the desired Gong Nong Bing(工農兵) shape as the main character and smooth texture and sophisticated highlights the glittering feeling to the touch, it was confirmed focused hayeoteum to implement the principle of 'Hong Guang Liang', highlighting the brilliant colors with a clean, bright colors. Highlighting a number of protagoniste compared to the antagonist in the animated scene of the Cultural Revolution a few times in terms of production and, among a number of protagoniste also emphasizes the outstanding hero figure, "yet three outstanding heroes heroic figures also emphasize the leading figures among the the director of the extrusion step-by-step approach "('San Tu Chu')was used. In addition, the hero figure is generally high and low angle by directing a large and perfect aesthetic appearance was to faithfully implement the principle of 'high-charged'('Gao Da Quan').

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.1
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• pp.46-56
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• 2012

The research results of tracing the Landscape Philosophy of Hageowon garden(何去園) in Musu-dong, Daejon of Youhwadang, Kwon, Iijin(權以鎭, 1668-1734) is as below. The ideological background of the protagonist reflected in Hageowon is the Hyoje Ideology(filial piety and brotherly love, 孝弟) of Sinjongchuwon(painstakingly caring for one's ancestors), Musil ideology(pursuing ethical diligence and truthful mind, 務實) based on sadistic tradition and ethical rationalism, Confucionist Eunil Ideology(ideology on seclusion, 隱逸) of Cheonghanjiyeon(quiet relaxation, 淸閒之燕), and the Pungryu ideology(appreciation for the arts, 風流) of Taoism in the Taoist style. Thus, by substituting these ideological values into a space called Hageowon, the Byulup gardens(別業) such as the Symbolic garden(象徵園), meaning gaeden(意園), and miniascape garden(縮景園) were able to be constructed. 2) The space organization system of Hageowon is generally classified into three phases considering the hierarchy. The first territory is the transitional space having residential features, which is an area to reach peach tree - road(Taoist world 桃經) from Youhwadang(有懷堂). The second territory is a monumental memorial space where the Yocheondae(繞千臺), Jangwoodam(丈藕潭), Hwagae(花階), and the ancestral graves take place, centering on the yards of Sumanheon(收漫軒), and the third territory is the secluded space in the eastern outer garden where the mountain stream flows from the north to south and which is the vein of the left-hand blue dragon(靑龍) of the guardian mountain of Hageowon. 3) Symbolically, the first phase has symbolized the space as a meaningful scenery by overlapping the Confucionist place of Youhwadang - Gosudae(孤秀臺) - Odeokdae(五德臺), and the mystic world of Jukcheondang(竹遷堂) - peach tree - road(桃徑). The second phase, which is the space of Sumanheon(收漫軒), Yocheondae, and Jangwoodam, the symbolical value of Sinjongchuwon(愼終追遠) and the remembrance and longing for one's parents are reflected. The third phase, which is the eastern outer garden of Hageowon and where the mountain stream flows from the north to south, is composed of the east valley(東溪) - Hwalsudam(活水潭) - Sumi Waterfall(修眉瀑布). More specifically, (1) Mongjeong symbolizes the life of gaining knowledge through studying to realize one's foolishness, (2) Hwalsudam symbolizes a transcending attitude in life refusing to pursue wealth and fame, and (3) Jangwoodam symbolizes the gateway to the fairyland to enter the world of mystic gods. 4) The rationale behind Hageowon is that the two algorithms of Confucionism and Taoist Theory appear repeatedly and in an overlapping way. The Napoji(納汚池) and Hwalsudam, which pertains to the prelude of space development, has symbolized Susimyangseong(修心養成, meditating one's mind and improving one's nature), which is based on ethical rationalism. Moreover, if the Monjeong sphere pertaining to the eastern outer garden of Hageowon takes the Confucionist value system as its theme, including moral training, studying, and researching, Jangwudam, Sumi Waterfalls, and Unwa can be understood as a taste of Cheokbyeon(滌煩, eliminating troubles) for the arts where the mystic world is substituted as a meaningful scenery. 5) The miniascape technique called artificial mountain was substituted to Hageowon to construct a mystic world like the 12 peaks of Mt. Mu(巫山). By borrowing the symbolic meaning expressed in old poems, it has been named 'Habang(1/何放), Hwabong(2, 3/和峯), Chulgun(4, 5, 6/出群), Sinwan(7/神浣), Chwhigyu(8, 9, 10/聚糾), Cheomyo(11/處杳), Giyung(12/氣融).' The representative poet reciting artificial mountain were Wangeui(汪醫), Nosamgang(魯三江), Dubo(杜甫), Hanyou(韓愈), Jeonheaseong(錢希聖), and Beomseokho(范石湖). They related themselves with literature by transcending time and space and attempted to sing about the richness of the mental world by putting the mystic world and culture of appreciating the arts they pursued in the vacation home called Hageowon.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Korean Journal of Poultry Science
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• v.16 no.3
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• pp.175-192
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• 1989

A total of 9, 012 cases was submitted for diagnosis of chicken diseases to Veterinary Research Institute, Rural Development Administration from domestic chicken farms during 18 years from 1971 to 1988. Of them, 6, 181 cases diagnosed as the infectious disease were investigated for the detection rate of infections on basis of you, season , and chicken age. The results obtained were summarized as followings：1. Detection rate or the infections was lowest as 49.3% in the year 1973, and highest as 78.6% in 1985 (average 68.6%). 2. Of infections detected, bacterial diseases were most frequent (32.6%), and followed in order by viral (26.3%), parasitic (7.7%), and fungal diseases (2.1%) in geneal. 3. The most frequently detected bacterial diseases in order of prevalence were mycoplasmosis (8.8%), colibacillosis (8.5%), and staphylococcosis (5.8%), and followed by salmonellosis pullorum disease , yolk sac disease, and salpingitis (0.8-1.5%). 4. In viral diseases, 7.5% of infections detected was lymphoid leukosis and 7.2%-Marek's disease, 4.4%-Newcastle disease, 2.0%-infectious laryngotracheitis, 1.7%-infectious bursal disease, and 1.0%-avian encephalomyelitis, while detection rate of infectious bronchitis, egg drop syndrome '76, and inclusion body hepatitis was less than 1.0%, respectively. 5. The most prevalent parasitic disease was coccidiosis (4.5%), followed by ascariasis (1.4%). The detection rate of other parasitic diseases including leucocytozoonosis, black head , heterakiasis, and ectoparasitosis was very as 0.2-0.7%, respectively： In fungal diseases, 2.0% of infections was detected as aspergillosis, and followed by candidiasis (0.1%). 6. Detection rate of the infections on basis of season was somewhat higher in summer. (27.7%), and autumn (27.7%) than in winter (23.5%), and spring (21.5%) in general. In bacterial, viral, and fungal diseases, there were the similar tendencies of detection rate as in infections, while parasitic diseases were much highly detected in summer (34.3%), and autumn (39.5%) than in any other season. 7. Among bacterial diseases colibacillosis was most frequently detected in summer, and staphylococcosis in autumn. In detection rate of viral diseases, Marek's disease, infectious laryngotracheitis, and infectious bursal disease was highest in summer, lymphold leukosis, fowl pox and egg drop syndrome '76 in autumn, and infectious trachitis in winter, repectively. The majority of important parasitic diseases including coccidiosis were highly detected in summer and autumn. 8. On basis of chicken age, detection rate of infections were highest in chicken of growing period between 30 and 150 days of age (41.4%), and followed by 35.3% in laying chicken over 150 days of age, and 17.3% in chicken of brooding age under 30 days of age. Bacterial, and parasitic diseases were most frequently detected in chicken of growing period, viral diseases in chicken of growing, and laying period as nearly equal rate of detection, and fungal diseases in chicken of brooding age.