• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.177-189
• /
• 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 Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.73-85
• /
• 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
• /
• v.25 no.4
• /
• pp.141-154
• /
• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Korean Journal of Poultry Science
• /
• v.32 no.4
• /
• pp.291-300
• /
• 2005

Two experiments were carried out to assess the appropriate incubation conditions namely; duration, moisture content and the ideal microbial inoculant for fermented dried food waste(EW) offered to broilers. The nutrient utilization of birds fed the FW diets at varying dietary inclusion rates was also compared with a control diet. In Experiment 1, different moisture contents(MC) of 30, 40, 50 and $60\%$ respectively were predetermined to establish the ideal duration of incubation and the microbial inoculant. A 1mL Aspergillus oryzae(AO) $(1.33\times10^5\;CFU/mL)$ was used as the seed inoculant in FW. This results indicated that the ideal MC for incubation was $40\~50\%$ while the normal incubation time was > 72 hours. Consequently, AO seeds at 0.25, 0.50, 0.75 and 1.00mL were inoculated in FW to determine its effect on AO count. The comparative AO count of FW incubated for 12 and 96 hours, respectively showed no significant differences among varying inoculant dosage rates. The FW inoculated with lower AO seeds at 0.10, 0.05 and 0.01mL were likewise incubated for 72 and 96 hours, respectively and no changes in AO count was detected(p<0.05). The above findings indicated that the incubation requirements for FW should be $%40\~50\%$ for 72 hours with an AO seed incoulant dosage rate of 0.10mL. Consequently, in Experiment II, after determining the appropriate processing condition for the FW, 20 five-week old male Hubbard strain were used in a digestibility experiment. The birds were divided into 4 groups with 5 pens(1 bird per pen). The dietary treatments were; Treatment 1 : Control(Basal diet), Treatment 2 : $60\%$ Basal+4$40\%$ FW, Treatment 3 : $60\%$ $Basal+20\%\;FW+20\%$ AFW(Aspergillus oryzae inoculate dried food-waste diet) and Treatment 4: $60\%$ Basal+$40\%$ Am. Digestibility of treatment 2 was lowed on common nutrients and amino acids compared with control(p<0.05) and on crude fat and phosphorus compared with AFW treatments(T3, T4)(plt;0.05). Digestibility of treatment 3 and 4 increased on crude fiber and crude ash compared treatment 2 (p<0.05). Digestibility of control was high on agrinine, leucine, and phenylalnine of essential amino acids compared with treatment 3 and 4(p<0.05), and diestibility of treatment 3 and 4 was improved on arginine, lysine, and threonine of essential amino acids. Finally, despite comparable nutrient utilization among treatments, birds fed the dietary treatment containing AO tended to superior nutrient digestion to those fed the $60\%$ Basa1+$40\%$ FW.

• The Korean Journal of Petroleum Geology
• /
• v.14 no.1
• /
• pp.1-11
• /
• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.5 no.3
• /
• pp.200-206
• /
• 1985

This field experiment was undertaken to assess the effects of three levels of inclination ($10^{\circ},\;20^{\circ},\;and\;30^{\circ}$) and four rates of $N-P_2O_5-K_2O$ (0-0-0-, 14-10-10, 28-25-25, and 42-40-40kg/10a) on establishment, yield and quality, and botanical compositions of mixed grass-clover sward. This second part is concerned with the soil chemical properties, concentrations and uptake of mineral nutrients, and percent recovery and efficiency of NPK. The results obtained after a two-year experiment are summarized as follows: 1. The pH, exchangeable Mg and Na, and base saturation in the surface soils were decreased by increasing the grade of inclination, whereas organic matter and available $P_2O_5$ tended to be increased. However, the changes in the Ca content and equivalent ratio of $K\sqrt{Ca+Mg}$ were not significant. The pH, exchangeable Ca and Mg, and base saturation were reduced by increasing the NPK rate, whereas available $P_2O_5$, exchangeable K, and equivalent ratio of $K\sqrt{Ca+Mg}$ tended to be increased. 2. The concentrations of mineral nutrients in grasses and weeds were not significantly affected by increasing the grade of slope in hilly pasture, whereas the concentrations of N, K, and Mg in legume were the lowest with the steep slope, which seemed to be related to the low legume yield. The Mg concentrations of all forage species were below the critical level for good forage growth and likelihood of grass tetany. 3. The increase of NPK rate resulted in the increment of N, K and Na concentrations, and the decrease of Mg and Ca in grasses. The P concentration was increased with P application, but there were no differences in that among the P rates applied. It resulted also in a slight increase of K, and a decrease of Mg in legume, but the contents of N, Ca, and Na were not affected by that. On the other hand, it has not affected the mineral contents in weeds except a somewhat increase of N. The mixed forages showed a increase of N and K contents, a decrease of Ca and Mg, and a slight change in P and Na. 4. The percent recovery of N, P and K by mixed forages were greatly decreased by increasing the grade of inclination and NPK rate. They were high in the order; K>N>P. The efficiency of mixed NPK applications was decreased by that. The efficiency of mixed NPK fertilizers absorbed was slightly decreased by the increased rate of NPK, but it was not affected by the grade of inclination.

• Horticultural Science & Technology
• /
• v.33 no.1
• /
• pp.39-46
• /
• 2015

Objective of this research was to investigate the influence of compositions and concentrations of fertilizer solutions on the vegetative growth and nutrient uptake of 'Seolhyang' strawberry. To achieve this, the solutions of acid fertilizer (AF), neutral fertilizer (NF), and basic fertilizer (BF) were prepared at concentrations of 100 or $200mg{\cdot}L^{-1}$ based on N and applied during the 100 days after transplanting. The changes in chemical properties of the soil solution were analysed every two weeks, and crop growth measurements as well as tissue analyses for mineral contents were conducted 100 days after fertilization. The growth was the highest in the treatments with BF, followed by those with NF and AF. The heaviest fresh and dry weights among treatments were 151.3 and 37.8 g, respectively, with BF $200mg{\cdot}L^{-1}$. In terms of tissue nutrient contents, the highest N, P and Na contents, of 3.08, 0.54, and 0.10%, respectively, were observed in the treatment with NF $200mg{\cdot}L^{-1}$. The highest K content was 2.83%, in the treatment with AF $200mg{\cdot}L^{-1}$, while the highest Ca and Mg were 0.98 and 0.42%, respectively, in BF $100mg{\cdot}L^{-1}$. The AF treatments had higher tissue Fe, Mn, Zn, and Cu contents compared to those of NF or BF when fertilizer concentrations were controlled to equal. During the 100 days after fertilization, the highest and lowest pH in soil solution of root media among all treatments tested were 6.67 in BF $100mg{\cdot}L^{-1}$ and 4.69 in AF $200mg{\cdot}L^{-1}$, respectively. The highest and lowest ECs were $5.132dS{\cdot}m^{-1}$ in BF $200mg{\cdot}L^{-1}$ and $1.448dS{\cdot}m^{-1}$ in BF $100mg{\cdot}L^{-1}$, respectively. For the concentrations of macronutrients in the soil solution of root media, the AF $200mg{\cdot}L^{-1}$ treatment gave the highest $NH_4$ concentrations followed by NF $200mg{\cdot}L^{-1}$ and AF $100mg{\cdot}L^{-1}$. The K concentrations in all treatments rose gradually after day 42 in all treatments. When fertilizer concentrations were controlled to equal, the highest Ca and Mg concentrations were observed in AF followed by NF and BF until day 84 in fertilization. The BF treatments produced the highest $NO_3$ concentrations, followed by NF and AF. The trends in the change of $PO_4$ concentration were similar in all treatments. The $SO_4$ concentrations were higher in treatments with AF than those with NF or BF until day 70 in fertilization. These results indicate that compositions of fertilizer solution should to be modified to contain more alkali nutrients when 'Seolhyang' strawberry is cultivated through inert media and nutri-culture systems.

• Journal of Nutrition and Health
• /
• v.50 no.3
• /
• pp.270-283
• /
• 2017

Purpose: This study was conducted to examine coffee consumption behaviors, dietary habits, and nutrient intakes by coffee intake amount among university students. Methods: Questionnaires were distributed to 300 university students randomly selected in Gongju. Dietary survey was administered during two weekdays by the food record method. Results: Subjects were divided into three groups: NCG (non-coffee group), LCG (low coffee group, 1~2 cups/d), and HCG (high coffee group, 3 cups/d) by coffee intake amount and subjects' distribution. Coffee intake frequency was significantly greater in the HCG compared to the LCG (p < 0.001). The HCG was more likely to intake dripped coffee with or without milk and/or sugar than the LCG (p < 0.05). More than 80% of coffee drinkers chose their favorite coffee or accompanying snacks regardless of energy content. More than 75% of coffee takers did not eat accompanying snacks instead of meals, and the HCG ate them more frequently than LCG (p < 0.05). Breakfast skipping rate was high while vegetable and fruit intakes were very low in most subjects. Subjects who drank carbonated drinks, sweet beverages, or alcohol were significantly greater in number in the LCG and HCG than in the NCG (p < 0.01). Energy intakes from coffee were $0.88{\pm}5.62kcal/d$ and $7.07{\pm}16.93kcal/d$ for the LCG and HCG. For total subjects, daily mean dietary energy intake was low at less than 72% of estimated energy requirement. Levels of vitamin C and calcium were lower than the estimated average requirements while that of vitamin D was low (24~34% of adequate intake). There was no difference in nutrient intakes by coffee intake amount, except protein, vitamin A, and niacin. Conclusion: Coffee intake amount did not affect dietary nutrient intakes. Dietary habits were poor,and most nutrient intakes were lower than recommend levels. High intakes of coffee seemed to be related with high consumption of sweet beverages and alcohol. Therefore, it is necessary to improve nutritional intakes and encourage proper water intake habits, including coffee intake, for improved nutritional status of subjects.

• Korean Journal of Soil Science and Fertilizer
• /
• v.9 no.1
• /
• pp.17-23
• /
• 1976

In order to investigate the fate of nitrogen in the paddy soil, Suchang, Hwasoon and Susan soil which have different properties, were treated with several nitrogen fertilizers such as ammonium chloride, ammonium sulfate, urea and SCU (sulfur-coated urea), and incubated under water-logged condition in $30^{\circ}C$ incubator. $NH_4-N$, $NO_3-N$, $Fe^{++}$ and pH in soil and stagnant water, were determined at 10, 20, 30, 40 and 50 days after incubation. The obtained results were summarized as follows: 1. The effect of rising temperature was increased in order of Hwasoon>Suchang>Susan and the effect of air drying soil was risen in order of Susan>Hwasoon>Suchang, while the rate of ammonication was in order of Susan>Suchang>Hwasoon. 2. The changes of $NH_4-N$ in stagnant water was dependent upon the nitrogen concentration of $NH_4Cl$ and $(NH_4)SO_4$ plat was high and decreased after 30 days incubation, but increased after 40 days and then decreased again. In contrast with the above, $NH_4-N$ concentration of urea and SCU plot was low but the change showed slightly through the incubation period. 3. Accumulation of $NH_4-N$ in the oxidative layer of the $NH_4Cl$ and $(NH_4)_2SO_4$ plot was higher than that of urea and SCU plot and $NH_4-N$ content was decreased with the incubation period. The change of $NH_4-N$ in the reductive layer showed the same pattern. 4. The changes of $NO_3-N$ in the stagnant water were different according to soil properties and nitrogen fertilizer. $NO_3-N$ concentration in stagnant water of urea and SCU plot was higher than in the $NH_4-Cl$ $(NH_4)_2SO_4$ plot and nearly disappeared after 30 to 40 days incubation. 5. The $NO_3-N$ concentration in the oxidative layer of soil was higher than reductive layer. The pattern of change was different in accordance with soil properties and nitrogen fertilizers. In general, nitrification in urea and SCU plot was more increased than $(NH_4)_2SO_4$ plot. In reductive layer, the concentration of $NO_3-N$ was very low until 30 days incubation and thereafter increased slightly. 6. Upon the concentration of $NH_4-N$ and $NO_3-N$ in stagnant water and soil, it was assumed that denitification of urea and SCU plot was higher than $NH_4Cl$ and $(NH_4)_2SO_4$ plot and denitrified nitrogen in incubation period was above 50%.

• Korean Journal of Mineralogy and Petrology
• /
• v.34 no.2
• /
• pp.107-120
• /
• 2021

The Komdok Pb-Zn deposit, which is the largest Pb-Zn deposit in Korea, is located at the Hyesan-Riwon metallogenic zone in Jiao Liao Ji belt included Paleoproterozoic Macheolryeong group. The geology of this deposit consists of Paleoproterozoic metasedimentary rocks, Jurassic Mantapsan intrusive rocks and Cenozoic basalt. The Komdok deposit which is a SEDEX type deposit occurs as layer ore and vein ore in the Paleoproterozoic metasedimentary rocks. Based on mineral petrography and paragenesis, dolomites from this deposit are classified four types (1. dolomite (D₀) as hostrock, 2. early dolomite (D₁) associated with tremolite, actinolite, diopside, sphalerite and galena from amphibolite facies, 3. late dolomite (D₂) associated with talc, calcite, quartz, sphalerite and galena from amphibolite facies, 4. dolomite (D₃) associated with white mica, chlorite, sphalerite and galena from quartz vein). The structural formulars of dolomites are determined to be Ca_1.00-1.20Mg_0.80-0.99Fe_0.00-0.01Zn_0.00-0.02(CO₃)₂(D₀), Ca_1.00-1.02M_0.97-0.99Fe_0.00-0.01Zn_0.00-0.02(CO₃)₂(D₁), Ca_0.99-1.03Mg_0.93-0.98Fe_0.01-0.05Mn_0.00-0.01As_0.00-0.01(CO₃)₂(D₂) and Ca_0.95-1.04Mg_0.59-0.68Fe_0.30-0.36Mn_0.00-0.01 (CO₃)₂(D₃), respectively. It means that dolomites from Komdok deposit have higher content of trace elements (FeO, MnO, HfO₂, ZnO, PbO, Sb₂O₅ and As₂O₅) compared to the theoretical composition of dolomite. These trace elements (FeO, MnO, ZnO, Sb₂O₅ and As₂O₅) show increase and decrease trend according to paragenetic sequence, but HfO₂ and PbO elements no show increase and decrease trend according to paragenetic sequence. Dolomites correspond to Ferroan dolomite (D₀, D₁ and D₂), and Ferroan dolomite and ankerite (D₃), respectively. Therefore, 1) dolomite (D₀) as hostrock was formed by subsequent diagenesis after sedimentation of Paleoproterozoic (2012~1700 Ma) silica-bearing dolomite in the marine evaporative environment. 2) Early dolomite (D₁) was formed by hydrothermal metasomatism origined metamorphism (amphibolite facies) associated with intrusion (1890~1680 Ma) of Paleoproterozoic Riwon complex. 3) Late dolomte (D₂) was formed from residual fluid by a decrease of temperature and pressure. and dolomite (D₃) in quartz vein was formed by intrusion (213~181 Ma) of Jurassic Mantapsan intrusive rocks.