• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.295-299
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• 2021

Recently, interest in maintenance has been increasing due to the enlargement and aging of infra structures. Therefore, a new paradigm is required to secure and improve the durability of structures differentiated from the past. Accordingly, research on smart concrete incorporating the concept of self-healing into concrete is being actively conducted. In this study, the crack healing performance and durability performance of self-healing concrete applied with a hydrogel containing biomineral-forming microorganisms were evaluated. As a result of evaluating the dispersion of the hydrogel in concrete, it was confirmed that the hydrogel was well distributed in concrete matrix with a dispersion coefficient of 0.35 to 0.46. The crack healing performance evaluation was verified by a water permeability test, and showed a recovery rate of 95% or more at the age of 28 days, confirming the applicability of self-healing concrete. The durability performance of self-healing concrete was evaluated in terms of resistance to penetration of chloride ion and freezing and thawing. Regardless of the mixing of the hydrogel, the same level of durability performance was shown for various compressive strength level. Therefore, it was confirmed that the microbial admixture did not affect concrete durability. In the future, long-term crack healing performance and durability verification studies should be supplemented.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.72-75
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• 2023

Carbon neutrality has been emerged as important mission for all the manufacturing industry to reduce energy usage and carbon emission equivalent. Korean semiconductor and display manufacturing industries are also in huge interest by minimize the energy usage as well as to find a less global warming product gases in both etch and cleaning. In addition, Korean government is also investing long term research and development plan for the safe environment in various ways. In this paper, we revisit previous research activities on carbon emission equivalent and current research activities performed in semiconductor process diagnosis research center at Myongji University with respect to the reduction of NF3 usage for the PECVD chamber cleaning, and we present the analytical result of the exhaust gas with residual gas analysis in both 6 inches and 12 inches PECVD equipment. The presented result can be a reference study of the development of new substitution gas in near future to compare the cleaning rate of the silicon oxide deposition chamber.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.413-440
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• 2010

Since 2000, as importance of sourcing energy emphasized caused by instability of international oil price, interests toward Caspian countries as an alternative markets has increased. Especially, Azerbaijan, as middle Asian emerging exporting country, has performed drastic economic boom because of massive amount of foreign capital flowed in and construction of BTC pipeline. However, despite this economic surge, there are unbalanced economy which is merely focusing on energy industry and pressure from increase in real exchange rate and inflation. In order to analyze the sustainability of Azerbaijan economy, the total sample time period of this paper is from January 2001 to December 2007 and the term is divided into before and after BTC line construction. Vector Error-Correction Model has been applied to analysis confirming short-term and long-term effect. As a result, Azerbaijan now face the symptoms of the recession during the time period and this is due to high oil price and increase in export influenced by BTC oil pipeline resulting in decrease in real interest rate. This conclusion is to affect competitiveness of manufacturing industry, base industry for economic proliferation, in a negative way.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.449-458
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• 2007

Bipolar disorder, also known as manic-depressive illness, is a brain disorder that causes unusual shifts in person's mood, energy, and ability to function. Compared with manic episode, the depression episode causes more serious results such as restless, loss of interest or pleasure, or thoughts of death or suicide and the cure rate of depression episode is lower than that of manic episode. Furthermore, a long term use of antidepressants in bipolar patients may result in manic episode. Our interest is to investigate the effect of antidepressant on switch of moods of bipolar patients and to estimate the transition probabilities of switch between moods, depression and (hypo) manic. In this study, three approaches are applied in terms of multi state model. Parametric model is applied using left censoring data and nonparametric model is implemented under illness-death model with counting process. In order to estimate the effect of covariates, a multiplicative model is used. These all methods have similar results.

• Journal of Korean Neurosurgical Society
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• v.42 no.3
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• pp.159-167
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• 2007

Vestibular schwannoma (VS) is a benign tumor typically originated in the schwann cell of vestibular nerve and usually accompany hearing symptom. Microsurgical removal and radiosurgery have a great role for the treatment of VS. Recently radiosurgery has been considered as an alternative or primary treatment for VS with the tremendous increase of patients who were treated with gamma knife radiosurgery (GKS) though microsurgery still takes the premier. By many published results, it is proved that GKS is a effective and noninvasive technique for VS, especially small sized tumors with satisfactory tumor control rate. The authors assumed that GKS can be expected to achieve satisfactory tumor control rate for small VS under 5cc in volume. A major interest regarding radiosurgery nowadays is to determine the optimal radiation dose for hearing preservation to improve the quality of life of patients. The more high radiation dose are used for effective tumor growth control, the more radiation-related complications like as hearing deficit, the impairment of other cranial nerve function are increased. Since 1990's the mean radiation dose for tumor margin was more than 18 Gy, but there were high complication rate in spite of good tumor growth control. After the year of 2000, under the influence of advanced neuro-imaging techniques and radiosurgical planning system which enable clinicians to do more precise planning, marginal dose for VS has been decreased to 12-13 Gy and the radiation-related complications has been reduced. But because there may be a unexpected radiation induced complications as time goes by after the latency period, optimal radiation dose for VS should be established on the basis of more long term follow-up observation.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Economic Analysis
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• v.27 no.3
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• pp.1-32
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• 2021

This study empirically analyzes whether bank capital channel and risk-taking channel for monetary policy work for domestic banks in South Korea by analyzing the impact of the expansionary monetary policy on the rate spread between deposit and loan, capital ratio, and loan amount. For the empirical analysis, the Uhlig (2005)'s sign-restricted SVAR(Structural Vector Auto-Regression) model is used. The empirical results are as follows: the bank's interest rate margin increases, the capital ratio improves, risk-weighted asset ratio increases, and the amount of loans increases in response to expansionary monetary shock. This empirical results confirm that bank capital channel and risk-taking channel work in domestic banks, similar to the previous research results. The implications of this study are as follows. Although the expansionary monetary policy has the effect of improving the bank's financial soundness and profitability in the short term as bank capital channel works, it could negatively affect the soundness of banks by encouraging banks to pursue risk in the long run as risk-taking channel works. It is necessary to note that the capital ratio according to the BIS minimum capital requirement of individual banks may cause an illusion in supervising the soundness of the bank. So, the bank's aggressive lending expansion may lead to an inherent weakness in the event of a crisis. Since the financial authority may have an illusion about the bank's financial soundness if the low interest rate persists, the authority needs to be actively interested in stress tests and concentration risk management in the pillar 2 of the BIS capital accord. In addition, since system risk may increase, it is necessary to conduct regular stress tests or preemptive monitoring of assets concentration risk.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• KDI Journal of Economic Policy
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• v.45 no.4
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• pp.57-77
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• 2023

The Chonsei component holds the highest level of weight (5.4%) in the composition of the Korean consumer price index (CPI). The variations in Chonsei prices are directly reflected in the CPI as a representation of cost swings. The Chonsei refers to a deposit that accumulates the costs related to housing services and is mostly affected by variations in rental rates. Nevertheless, it is important to note that Chonsei prices are also susceptible to fluctuations in interest rates, regardless of the rent prices. Therefore, if Chonsei were directly and one-to-one indexed to the CPI, they could include changes other than residential service prices. After analyzing the time series data of the Chonsei index and rent index inside the CPI, it becomes apparent that the Chonsei index displays an average annual growth rate of 2.3%, whilst the rent index reveals a growth rate of 0.9%. The observed disparity in growth rates indicates a divergence in trends between the two indices. It is posited that the Chonsei index, when capitalized, has had a more rapid increase compared to the rental index, owing to the gradual drop in interest rates. To effectively reflect fluctuations in the housing service costs, proxies for the Chonsei index were utilized in the construction of a consumer price index. The findings of our study suggest that, overall, the newly developed CPI demonstrates a comparatively lower rate of inflation when compared to the official CPI. Furthermore, the inclusion of imputed rents for owner-occupied housing in CPI amplifies this effect.