• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.3
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• pp.168-177
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• 2008

Trafficablility of a miner and potential environmental impacts due to mining activities should be considered in the selection of a commercial manganese nodule mining site. These two factors can be evaluated comparatively with physical properties and shear strength of sea-bed sediments. For the qualitative comparison of potential minig sites in terms of these two factors, physical properties such as water contents, void ratios, porosities, and grain densities, and shear strengths of surface sediments were determined for the three potential manganese nodule mining sites(KR1, KR2, and KR5) in the Korean manganese nodule contract area, northeast Pacific. For the study, sediment samples were collected from 107 stations from 2004 to 2006. The physical properties of surface sediments showed more significant differences between northern(KR1, KR2) and southern(KR5) blocks than between northern blocks(KR1 vs. KR2). Water content, void ratio, and porosity of sediments from KR5 were relatively higher than those from KR1 and KR2. Grain density of sediments from KR5 was relatively lower than those from KR1 and KR2. Shear strengths of the top 10cm sediments were higher in KR1 and KR2, whereas those of the deeper part were highest in KR5 block. Generally, sediments of high water contents are less suspendible than those of the low water contents by benthic disturbances, thus less disturbance is expected in the sediments of high water content by mining activities. In terms of trafficability, the shear strength of sediment below 10 cm deep is more important than shallower part because miner will disturb at least top 10 cm interval of the surface sediments. Base on these results, we conclude that KR5 area will be the best site for commercial mining among three investigated sites in this study.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.278-284
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• 2023

Recently, a closed-type plant factory has been receiving attention as a advanced agricultural method. It has diverse advantages such as climate-independence, high productivity and stable year-round production. However, high energy cost caused by environmental control system is considered as a challenges of a closed-type plant factory. In order to reduce the energy cost, investigation about energy load which is directly connected to energy consumption needs to be conducted. In this study, energy load changes of a plant factory have been analytically analyzed according to the environmental changes. The target plant factory was a lettuce growing container farm. Firstly, the impact of photoperiod, set temperature and relative humidity change were examined. Under the climate condition of Daejeon in South Korea, increase of photoperiod and set temperature rose a yearly energy demand of a container farm. However, increase of set relative humidity decreased a yearly energy demand. Secondly, the climate environment effect was compared by investigating the energy demand under 9 different climate conditions. As a result, the difference between maximum and minimum value of the yearly energy demand showed 21.7%. Lastly, sensitivity analysis of each parameter (photoperiod, set temperature and relative humidity) has been suggested under 3 different climate conditions. The ratio of heating and cooling demand was varied depending on the climate, so the effect of each parameter became different.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.1 no.1
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• pp.56-78
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• 1998

Objective: Chronic hepatitis B infection (CHB) occurs in 6% to 10% of population in Korea. In ethinic communities where prevalence of chronic infection is high such as Korea, transmission of hepatitis B infection is either vertical (ie, by perinatal infection) or by close family contact (usually from mothers or siblings) during the first 5 years of life. The development of chronic hepatitis B infection is increasingly more common the earlier a person is exposed to the virus, particularly in fetal and neonatal life. And it progress to cirrhosis and hepatocellular carcinoma, especially in severe liver damage and perinatal infection. Histopathology of CHB is important when evaluating the final outcomes. A numerical scoring system which is a semiquantitatively assessed objective reproducible classification of chronic viral hepatitis, is a valuable tool for statistical analysis when predicting the outcome and evaluating antiviral and other therapies. In this study, a numerical scoring system (Ludwig system) was applied and compared with the conventional histological classification of De Groute. And the comparative analysis of cinical findings, family history, serology, and liver function test by histopathological findings in chronic hepatitis B of children was done. Methods: Ninety nine patients [mean age=9 years (range=17 months to 16 years)] with clinical, biochemical, serological and histological patterns of chronic HBV infection included in this study. Five of these children had hepatocelluar carcinoma. They were 83 male and 16 female children. They all underwent liver biopsies and histologic evaluation was performed by one pathologist. The biopsy specimens were classified, according to the standard criteria of De Groute as follows: normal, chronic lobular hepatitis (CLH), chronic persistent hepatitis (CPH), mild to severe chronic active hepatitis (CAH), or active cirrhosis, inactive cirrhosis, hepatocellular carcinoma (HCC). And the biopsy specimens were also assessed and scored semiquantitatively by the numerical scoring Ludwig system. Serum HBsAg, anti-HBs, HBeAg, anti-HBe, anti-HBc (IgG, IgM), and HDV were measured by radioimunoassays. Results: Male predominated in a proportion of 5.2:1 for all patients. Of 99 patients, 2 cases had normal, 2 cases had CLH, 22 cases had CPH, 40 cases had mild CAH, 19 cases had moderate CAH, 1 case had severe CAH, 7 cases had active cirrhosis, 1 case had inactive cirrhosis, and 5 cases had HCC. The mean age, sex distribution, symptoms, signs, and family history did not differ statistically among the different histologic groups. The numerical scoring system was correlated well with the conventional histological classification. The histological activity evaluated by both the conventional classification and the scoring system was more severe as the levels of serum aminotransferases were higher. In contrast, the levels of serum aminotransferases were not useful for predicting the degree of histologic activity because of its wide range overlapping. When the histological activity was more severe and especially the cirrhosis more progressing, the prothrombin time was more prolonged. The histological severity was inversely related with the duration of seroconversion of HBeAg. Conclusions: The histological activity could not be accurately predicted by clinical and biochemical findings, but by the proper histological classification of the numerical scoring system for the biopsy specimen. The numerical scoring system was correlated well with the conventional histological classification, and it seems to be a valuable tool for the statistical analysis when predicting the outcome and evaluating effects of antiviral and other therapies in chronic hepatitis B in children.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.52-61
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• 2013

This study was conducted to investigate the effects of pergola's shading on the thermal comfort index in the summer. The 3 type of pergolas($4m{\times}4m{\times}h2.7m$) which were screened overhead(I)/overhead west(II)/overhead west north(III) plane with reed blind for summer shading and winter wind break, were constructed on the 4th floor rooftop. Thereafter the meteorological variables(air temperature, humidity, radiation, and wind speed) of pergola I, III and rooftop were measured from 14 to 16 August 2013(1st experiment), those of pergola I, II and rooftop were measured from 26 to 28 August 2013(2nd experiment). The effects of pergola's shading on the radiation environment and mean radiant temperature($T_{mrt}$), standard effective temperature($SET^*$) were as follows. The maximum 1 h mean values of differences ${\Delta}$ of the sums of shortwave radiant flux densities absorbed by the human body (${\Delta}K_{abs,max}$) between pergola I, III and nearby sunny rooftop were $-119W/m^2$, $-158W/m^2$, those between pergola I, II and rooftop were $-145W/m^2$, $-159W/m^2$. The maximum 1 h mean values of differences ${\Delta}$ of the sums of long wave radiant flux densities absorbed by the human body (${\Delta}L_{abs,max}$) between pergola I, III and nearby sunny rooftop, were $-15W/m^2$, $-17W/m^2$, those between pergola I, II and nearby rooftop, were $-8W/m^2$, $-7W/m^2$. The response of the direction dependent long wave radiant flux densities $L_1$ on the pergola's shading turned out to be distinctly weaker as compared to shortwave radiant flux densities $K_1$. The pergola's shading leads to a lowering of $T_{mrt}$ and $SET^*$. The peak values of $T_{mrt}$ absorbed by the human body were decreased $16^{\circ}C$ and $21.4^{\circ}C$ under pergola I and III as compared to that of nearby rooftop in the 1st experiment. Those were decreased $18.8^{\circ}C$ and $20.8^{\circ}C$ under pergola I and II as compared to that of nearby rooftop in the 2nd experiment. The peak values of $SET^*$ absorbed by the human body were decreased $2.9^{\circ}C$ and $2.6^{\circ}C$ under pergola I and III as compared to that of nearby rooftop in the 1st experiment. Those were decreased $3.5^{\circ}C$ and $2.6^{\circ}C$ under pergola I and II as compared to that of nearby rooftop in the 2nd experiment. The relative $SET^*$ decrease in pergola II, III compared to nearby sunny rooftop $SET^*$ were lower than that in pergola I, revealing the influence of the wind speed. Therefore it is essential to design pergola to maximize wind speed and minimize solar radiation to achieve comfort in the hot summer. The $SET^*$ under pergola I, III were exceeded $28.7^{\circ}C$ and $30.4^{\circ}C$ which were the upper limit of thermal comfort and tolerable zone during all most daytimes in the 1st experiment(maximum air temperature $37.5^{\circ}C$). The $SET^*$ under pergola I was exceeded $28.7^{\circ}C$ which was the upper limit of thermal comfort zone at 13h, that under pergola II was exceeded $28.7^{\circ}C$ from 8h to 14h, meanwhile the $SET^*$ under pergola I, II were within thermal tolerable zone during most daytimes in the 2nd experiment(maximum air temperature $34.4^{\circ}C$). Therefore to ensure the thermal comfort of pergola for summer hottest days, pergola should be shaded with not only reed blind but also climbing and shade plants. $T_{mrt}$ and $SET^*$ were suitable index for the evaluation of pergola's shading effects and outdoors.

• Korean Journal of Soil Science and Fertilizer
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• v.15 no.1
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• pp.49-50
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• 1982

The objective of this paper is to review the changes in fertilizer use pattern and to discuss some aspects of the fertilizer development in Korea. Fertilizer consumption in Korea have steadily increased to triple the application rates of N, P and K during the 15 years from 1965 to 1980, and Korea became one of the countries which apply fertilizers at the highest rate. The ratio of N: $P_2O_5$: $K_2O$ in fertilizer consumption changed from 55.4 : 31.4 : 13.1 in 1965 to 54.0 : 23.8 : 22.2 in 1980. It can be said that Korean farmers practise a balanced fertilization at least in view of fertilizer consumption as compared to other developing countries. However, differences in soil properties, crops, and climate varying as region were not reflected on fertilization. In the technological development of fertilizer, the chemical form and composition of the fertilizer as well as the suitability to the specific crops must be taken into consideration for the efficient use of fertilizers. Although organic fertilizers and manure are accepted as minor element suppliers, it is necessary to add minor elements into chemical fertilizers on the industrial process. Industrial waste may be used for the agricultural production as a measure of pollution control providing careful study on the waste.

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

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

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.211-232
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• 2014

Recently, there is a growing interest toward social commerce using SNS(Social Networking Service), and the size of its market is also expanding due to popularization of smart phones, tablet PCs and other smart devices. Accordingly, various studies have been attempted but it is shown that most of the previous studies have been conducted from perspectives of the users. The purpose of this study is to derive user-centered CSF(Critical Success Factor) of social commerce from the previous studies and analyze the CSF perception gap between social commerce service providers and users. The CSF perception gap between two groups shows that there is a difference between ideal images the service providers hope for and the actual image the service users have on social commerce companies. This study provides effective improvement directions for social commerce companies by presenting current business problems and its solution plans. For this, This study selected Korea's representative social commerce business Ticket Monster, which is dominant in sales and staff size together with its excellent funding power through M&A by stock exchange with the US social commerce business Living Social with Amazon.com as a shareholder in August, 2011, as a target group of social commerce service provider. we have gathered questionnaires from both service providers and the users from October 22, 2012 until October 31, 2012 to conduct an empirical analysis. We surveyed 160 service providers of Ticket Monster We also surveyed 160 social commerce users who have experienced in using Ticket Monster service. Out of 320 surveys, 20 questionaries which were unfit or undependable were discarded. Consequently the remaining 300(service provider 150, user 150)were used for this empirical study. The statistics were analyzed using SPSS 12.0. Implications of the empirical analysis result of this study are as follows: First of all, There are order differences in the importance of social commerce CSF between two groups. While service providers regard Price Economic as the most important CSF influencing purchasing intention, the users regard 'Trust' as the most important CSF influencing purchasing intention. This means that the service providers have to utilize the unique strong point of social commerce which make the customers be trusted rathe than just focusing on selling product at a discounted price. It means that service Providers need to enhance effective communication skills by using SNS and play a vital role as a trusted adviser who provides curation services and explains the value of products through information filtering. Also, they need to pay attention to preventing consumer damages from deceptive and false advertising. service providers have to create the detailed reward system in case of a consumer damages caused by above problems. It can make strong ties with customers. Second, both service providers and users tend to consider that social commerce CSF influencing purchasing intention are Price Economic, Utility, Trust, and Word of Mouth Effect. Accordingly, it can be learned that users are expecting the benefit from the aspect of prices and economy when using social commerce, and service providers should be able to suggest the individualized discount benefit through diverse methods using social network service. Looking into it from the aspect of usefulness, service providers are required to get users to be cognizant of time-saving, efficiency, and convenience when they are using social commerce. Therefore, it is necessary to increase the usefulness of social commerce through the introduction of a new management strategy, such as intensification of search engine of the Website, facilitation in payment through shopping basket, and package distribution. Trust, as mentioned before, is the most important variable in consumers' mind, so it should definitely be managed for sustainable management. If the trust in social commerce should fall due to consumers' damage case due to false and puffery advertising forgeries, it could have a negative influence on the image of the social commerce industry in general. Instead of advertising with famous celebrities and using a bombastic amount of money on marketing expenses, the social commerce industry should be able to use the word of mouth effect between users by making use of the social network service, the major marketing method of initial social commerce. The word of mouth effect occurring from consumers' spontaneous self-marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers; in this context, the word of mouth effect should be managed as the CSF of social commerce. Third, Trade safety was not derived as one of the CSF. Recently, with e-commerce like social commerce and Internet shopping increasing in a variety of methods, the importance of trade safety on the Internet also increases, but in this study result, trade safety wasn't evaluated as CSF of social commerce by both groups. This study judges that it's because both service provider groups and user group are perceiving that there is a reliable PG(Payment Gateway) which acts for e-payment of Internet transaction. Accordingly, it is understood that both two groups feel that social commerce can have a corporate identity by website and differentiation in products and services in sales, but don't feel a big difference by business in case of e-payment system. In other words, trade safety should be perceived as natural, basic universal service. Fourth, it's necessary that service providers should intensify the communication with users by making use of social network service which is the major marketing method of social commerce and should be able to use the word of mouth effect between users. The word of mouth effect occurring from consumers' spontaneous self- marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers. in this context, it is judged that the word of mouth effect should be managed as CSF of social commerce. In this paper, the characteristics of social commerce are limited as five independent variables, however, if an additional study is proceeded with more various independent variables, more in-depth study results will be derived. In addition, this research targets social commerce service providers and the users, however, in the consideration of the fact that social commerce is a two-sided market, drawing CSF through an analysis of perception gap between social commerce service providers and its advertisement clients would be worth to be dealt with in a follow-up study.

• Journal of Nutrition and Health
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• v.48 no.1
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• pp.46-57
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• 2015

Purpose: The aim of this study was to determine an appropriate energy level of breakfast with less risk of chronic disease for Korean adults. Methods: Using data from the 2007~2009 Korean National Health & Nutrition Examination Survey, from a total of 12,238 adults aged 19~64, the final 7,769 subjects were analyzed except subjects who were undergoing treatment for cancer or metabolic disorder. According to the percent of breakfast energy intake versus their estimated energy requirement (EER), the subjects were divided into four groups: < 10% (very low, VL), 10~20% (low, L), 20~30% (moderate, M), ${\geq}30%$ (sufficient, S). All data were analyzed on the metabolic risk and nutritional state after application of weighted value and adjustment of sex, age, residential area, income, education, job or jobless, and energy intake using a general linear model or logistic regression. Results: The subjects of group S were 16.9% of total subjects, group M 39.2%, group L 37.6%, and group VL 6.3%. The VL group included more male subjects, younger-aged (19 to 40 years), urban residents, higher income, higher education, and fewer breakfasts eaters together with family members. Among the 4 groups, the VL group showed the highest waist circumference, while the S group showed the lowest waist circumference, body mass index, and serum total cholesterol. The groups of VL and L with lower intake of breakfast energy showed high percent of energy from protein and fat, and low percent of energy from carbohydrate. With the increase of breakfast energy level, intake of energy, most nutrients and food groups increased, and the percentage of subjects consuming nutrients below EAR decreased. The VL group showed relatively higher intake of snacks, sugar, meat and eggs, oil, and seasonings, and the lowest intake of vegetable. Risk of obesity by waist circumference was highest in the VL group by 1.90 times of the S group and the same trend was shown in obesity by BMI. Risk of dyslipidemia by serum total cholesterol was 1.84 times higher in the VL group compared to the S group. Risk of diabetes by Glu-FBS (fasting blood sugar) was 1.57 times higher in the VL group compared to the S group. Conclusion: The results indicate that higher breakfast energy level is positively related to lower metabolic risk and more desirable nutritional state in Korean adults. Therefore, breakfast energy intake more than 30% of their own EER would be highly recommended for Korean adults.

• The Journal of Engineering Geology
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• v.28 no.2
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• pp.217-246
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• 2018

During the selection and characterization of target formations in the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin, we have carefully investigated the possibility of induced earthquakes and leakage of $CO_2$ during the injection, and have designed the storage processes to minimize these effects. However, people in Pohang city have a great concern on $CO_2$-injection-intrigued seismicity, since they have greatly suffered from the 5.4 magnitude earthquake on Nov. 15, 2017. The research team of the project performed an extensive self-investigation on the safety issues, especially on the possible $CO_2$ leakage from the target formation and induced earthquakes. The target formation is 10 km apart from the epicenter of the Pohang earthquake and the depth is also quite shallow, only 750 to 800 m from the sea bottom. The project performed a pilot injection in the target formation from Jan. 12 to Mar. 12, 2017, which implies that there are no direct correlation of the Pohang earthquake on Nov. 15, 2017. In addition, the $CO_2$ injection of the storage project does not fracture rock formations, instead, the supercritical $CO_2$ fluid replaces formation water in the pore space gradually. The self-investigation results show that there is almost no chance for the injection to induce significant earthquakes unless injection lasts for a very long time to build a very high pore pressure, which can be easily monitored. The amount of injected $CO_2$ in the project was around 100 metric-tonne that is irrelevant to the Pohang earthquake. The investigation result on long-term safety also shows that the induced earthquakes or the reactivation of existing faults can be prevented successfully when the injection pressure is controlled not to demage cap-rock formation nor exceed Coulomb stresses of existing faults. The project has been performing extensive studies on critical stress for fracturing neighboring formations, reactivation stress of existing faults, well-completion processes to minimize possible leakage, transport/leakage monitoring of injected $CO_2$, and operation procedures for ensuring the storage safety. These extensive studies showed that there will be little chance in $CO_2$ leakage that affects human life. In conclusion, the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin would not cause any induced earthquakes nor signifiant $CO_2$ leakage that people can sense. The research team will give every effort to secure the safety of the storage site.