• The Journal of the Korea Contents Association
• /
• v.16 no.8
• /
• pp.651-660
• /
• 2016

This study analyzed the contribution of the national economy, China's textile industry by 2010 I-O Table issued by the Chinese Bureau of Statistics 2013. The results shows that the production inducement coefficient of China's textile industry is the column total 3.6228 and in line total 3.5452, is a key industry that leads the industry in China. Second, the index of the power of dispersion of the Chinese textile industry is 1.1982, index of the sensitivity of dispersion is 1.1725. Third, income inducement coefficient of China's textile industry 0.5228, tax inducement coefficient 0.1522, a value-added inducement coefficient 1. Especially China's textile industry induce 2993.6 trillion yuan(textile industry of 8.6 trillion yuan, up 3.0%) in the national production, value-added inducement 97.1 trillion yuan (textile industry 1.7 trillion yuan, up 2.0%), income inducement 42.8 trillion yuan (textile industry 0.9 one trillion yuan, 2.0%), also tax inducement 15.4 trillion yuan (textile industry 0.3 one trillion yuan, 2.0%).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.512-520
• /
• 2020

This study analyzed the relative operational efficiency and impact factors of regional public hospitals to present benchmarking points for enhancing the efficiency of inefficient regional public hospitals. The survey targets collected and utilized the internal resources and management performance data from 34 regional public hospitals in Korea over the past five years, from 2014 to 2018. The final 33 regional public hospitals were surveyed, excluding Jinan Regional Public Hospital, which opened in 2015, the middle of the survey period. The general characteristics and input/output variables were analyzed by frequency analysis and technical statistics analysis, and Data Envelopment Analysis was performed to measure the operational efficiency index and relative comparison. According to the study, there were 11 efficient hospitals (33.3%) and 22 inefficient hospitals (66.7%). Of the 22 inefficient hospitals, 13 (IRS: Increasing Returns to Scale) required scale expansion, and nine (DRS: Decreasing Returns to Scale) required scale reduction or rebalancing. The significance of this study was that an analysis of the relative efficiency and influencing factors presented specific alternatives or directions that could help enhance the efficiency of the growth of regional public hospitals, sustainable management, and expansion of publicness.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.5
• /
• pp.59-67
• /
• 2017

This study analyzes the efficiency of oriental hospitals using DEA(Data Envelopment Analysis). The input variables include the numbers of doctors, nurses, medical technicians, and beds. The output variable iscomprised of the sales account. The analysis tools used are EnPas and IBM SPSS Statistics 19. As a result of efficiency analysis, the private hospitals(establishment), less than 10 years in operation(operating period), containing less than 50 beds (number of the beds), located in the metropolitan area(location) showed high efficiency in the BCC(Banker, Charnes & Cooper) model, but indicated relatively low efficiency in CCR(Charnes, Cooper & Rhodes) model. This contradictory result is caused by inefficiencies in hospital size. The logistic regression analysis conducted to analyze the variables that affect the efficiency of oriental hospitals found that the efficiency decreased by 0.955 with each increase of 1 bed in the hospital.

• Journal of the Economic Geographical Society of Korea
• /
• v.22 no.4
• /
• pp.488-512
• /
• 2019

This study examines the 'Asia Decoupling' hypothesis, focusing on changes in trade patterns between regions and countries, based on the latest value added trade statistics. As an analytical tool, indicators that can directly measure the degree of distribution of actual value added were used. Main findings are: Firstly, creating potential at regional level which used to be the growth engine of East Asia until the mid-2000s declined sharply after the global financial crisis. Secondly, in the development pattern of the value added distribution network, no positive change has been detected in the give-out or gain capacity of emerging countries that can generate future growth in East Asia through GVC development. Lastly, China's value added contributing capacity, as different from the hub countries in other regions such as US and Germany, has declined significantly since the mid 2000s, while its capability to benefit greatly increased, and the gain potential of advanced group countries in competition with China is decreasing. We suggest the establishment of intra-regional economic cooperation mechanism including all countries in East Asia for expanding the value creating capacity in the region.

• Journal of Korea Port Economic Association
• /
• v.28 no.1
• /
• pp.143-157
• /
• 2012

By strengthening the market control and expanding the networks, providers of global logistics are expanding their service scope. The warehouses connect networks to internal and external warehouses by using logistics providers. The paper focuses on analyzing the efficiency of warehouses on each district. Therefore, the study classifies the factors which specify the efficiency of a total logistics of warehouse industry and warehouses' employees and the number of warehouses on district. Furthermore, the most recently published reports by National Center for Statistics in 2012 was used in order to guarantee credibility of the study. This study utilizes five years of materials, which are from 2005 to 2009. By applying SBM (Slack Based Measure), DEA Window model, and the Malmquist productivity model, the trend in efficiency and stableness were analyzed. The principal purpose of the paper is evaluating the efficiency. Also, analyzing its determinants and illustrating a long-term relationship between the regional warehouses and annual turnover of the warehouses were used as output measures. In addition, the number of warehouses of each region, employees, warehouses equipments, and the Logistics Warehouses Providers were used as input measurements. As a result, Malmquist productivity model and annual stableness has shown a continuous increasing. Ultimately, to be approved as product of Korea, a new stratiges that meet the standards and Rules of Origins by FTA should be developed. Therefore, there must be a development that takes regional characteristics into consideration.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5C
• /
• pp.527-539
• /
• 2009

In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

• KDI Journal of Economic Policy
• /
• v.34 no.3
• /
• pp.187-214
• /
• 2012

Korea's national income statistics have been compiled by the Bank of Korea since 1953. However, there is a break in the time series. The current time series (1970 onward) is based on the '1993 SNA (System of National Accounts)' suggested by the UN, and the previous time series (1953~1970) was based on the '1953 SNA'. The difference between the previous and current time series is 4.8% in 1970 when the two series overlap. The difference is even greater in terms of comparisons across industries. In addition, it has now become even more difficult to connect the current and the previous time series because, in 2009, the Bank of Korea introduced a chain weighted method for calculating the current time series (1970 onward). Under the chain weighted method, the time series underwent substantial modification; for instance, the economic growth rate during 1970~2005 is 0.9%p higher than the rate under the general method. This paper applies chain weighted values and the '1993 SNA' to the previous time series (1953~1970) by utilizing various national account manuals published by the UN and previous Korean input-output tables in order to calculate a long term time series from 1953 to 2010 based on the same criteria as the current time series (1970 onward). In the revised time series, it appears that 1953 GDP at current basic prices is 3.5% higher and the growth rate for the period of 1953~1970 is 1.5%p higher each year than under the previous time series. Under the revised time series the size of the Korean economy as of 2010 is 50-fold bigger than that of 1953. In terms of industries, manufacturing and SOC show significant expansion whereas the extent of that of the service industry is relatively small.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.685-693
• /
• 2021

This study examined the fire risk of the region in Goyang City using the spatial information data of buildings. The economic damage by industry was assessed according to the probability of fire risk. The study area was confined to Goyang-si, Gyeonggi-do, and the same fire risk reduction rate was applied to each region for the convenience of analysis. The possibility of fire was derived based on the buildings' density and usage in the area by National GIS building-integrated information standard data. The calculation of economic damage by industry in Goyang City due to the fire risk was calculated by combining the Goyang-si industry-related model produced by matching with 30 industrial categories in Input-Output Statistics of Korea Bank and 20 industrial categories in the Goyang-si business survey and the possibility of fire. The basic scenario of production impossibility during six months and business loss due to fire was established and analyzed based on the supply model. The analysis showed that Ilsan-dong-gu, Ilsan-seo-gu, and Deokyang-gu suffered the most economic damage. The "electricity, gas, steam, and water business" showed the greatest loss by industry.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.57-73
• /
• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Korean Society of Forest Science
• /
• v.105 no.2
• /
• pp.247-252
• /
• 2016

This study was conducted to evaluate the technical efficiency of Annual Chestnut production in South Korea. In this study, technical efficiency is the maximum possible production for which a certain amount of costs is inputted. For analysis on the technical efficiency we used output-oriented BCC Model, and then we analyzed correlation among input costs, production, gross income, net income, and market price per unit in order to determine the cause of variation in the technical efficiency. As study materials, we used statistics for the forestry production costs for 7 years from 2008 to 2014. The study results showed that the maximum possible production and actual production in 2008, 2009, and 2010 were 1,568 kg, 1,745 kg, and 1,534 kg by hectares in the order which were the same values. Consequently, the technical efficiency of those was all evaluated as 1.00. On the other hand, actual production from 2011 to 2014 was 1,270 kg 1,047 kg, 1,258 kg, and 1,488 kg by hectares in the order and the maximum possible production was 1,524 kg, 1,467 kg, 1,635 kg, and 1,637 kg by hectares in the analysis. From those values, the technical efficiency was evaluated in the following order:0.83, 0.71, 0.75, 0.91. The lowest value of the technical efficiency was 0.71 in 2012, and the values of this increased gradually since 2013. It is indicated that the cause of variation in the technical efficiency was related to the relationship between production and market price, and there was a negative correlation with r = -0.821 (p<0.05). The level of maximum available production per unit area was between 1,488kg in lower limit and 1,745 kg in upper limit, and the average was turned out as 1,548 kg.