• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.85-110
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• 2015

The purpose of this paper is to show the clustering trend and the empirical comparison and to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the Fuzzy(Average Index Transformation) DEA and Cross-efficiency models for 38 Asian ports during 11 years(2001-2011) with 4 input variables(birth length, depth, total area, and number of crane) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, clustering results by using Fuzzy(AIT)DEA show that 3 Korean ports[Busan(56.29%), Incheon(57.96%), and Gwangyang(66.80%) each]can increase the efficiency. Second, according to Cross-efficiency model, Busan(Hongkong, Kobe, Manila, Singapore, and Kaosiung etc.), Incheon(Aquaba, Dammam, Karachi, Mohammad Byin Oasim and Davao), and Gwangyang(Damman, Yokohama, Nogoya, Keelong, Kaosiung, and Bangkok) should be clustered with those ports in parentheses. Third, when both Fuzzy(AIT)DEA and Cross-efficiency models are mixed, the empirical result shows that 3 Korean ports[Busan(71.38%), Incheon(103.89%), and Gwangyang(168.55%) each]can increase the efficiency. The efficiency ranking comparison among the three models by using Wilcoxon Signed-rank Test was matched with the average level of 66%-67%. The policy implication of this paper is that Korean port policy planner should introduce the Fuzzy(AIT)DEA, and Cross-efficiency models with the mixed two models when clustering is needed among the Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT analysis among the clustering ports should be considered.

• Journal of Korea Port Economic Association
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• v.33 no.4
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• pp.73-82
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• 2017

Korea is the fifth largest producer of automobiles in the world, and this industry accounts for the highest portion of the entire manufacturing industry. It is an especially important industry occupying second place in the top 10 export items in Korea. Korea exports about 3 million units of cars produced in the country and abroad, based on new cars and excluding second hand cars. Japan, along with Korea, represents a high portion of the global automobile industry, and it exports more than 4 million cars to the rest of the world. In particular, both Korea and Japan export automobile and used cars produced within the country, almost all of them by PCC(Pure Car Carrier) or PCTC(Pure Car Truck Carrier). Therefore, automobile export ports are located near automobile factories, and are being used in export to foreign countries. However, there are inefficient problems, such as poor port facilities, yard space shortage for loading and unloading operations and lack of proficiency of cargo handling companies. As a result, there are delays in cargo operations, or ships waiting have occurred. Therefore, the purpose of this study is to measure and compare the efficiency of automobile export ports in Korea and Japan. To measure the efficiency of automobile export port, we used CRS and VRS models from DEA. The input and output parameters were set as length of quay, yard area and throughput of cars, and DMUs are 25 ports for evaluating the efficiency. As a result of the efficiency measurements, two Korean ports (Gwangyang and Ulsan) and three Japanes ports (Kanda, Omaezaki, Kanmon-Shimonoseki) showed high efficiency in both models. These results can be used to establish strategies for enhancing efficiency and competitiveness of automobile export ports in Korea and Japan.

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

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.636-642
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• 2019

In this paper, we analyzed BER (Bit Error Rate) communication performance according to the detection order of MMSE (Minimum Mean Square Error) based soft decision interference cancellation. As the detection order method, antenna index order method, absolute value magnitude order method of channel elements, absolute value sum order method of channel elements, and SNR (Signal Noise Ratio) order method are proposed. BER performance for the scheme was measured and analyzed. As a simulation environment, 16-QAM (Quadrature Amplitude Modulation) modulation is used in an uncoded environment of an M×M multiple-input multiple-output system, and an independent Rayleigh attenuation channel is considered. The simulation results show that the performance gain is about 1.5dB when the SNR-based detection order method is M=4, and the performance gain is about 3.5dB when M=8 and about 3.5dB when M=16. The more BER performance was confirmed, the more the detection order method of the received signal prevented the interference and error spreading occurring in the detection process.

• Journal of Distribution Science
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• v.13 no.4
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• pp.45-53
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• 2015

Purpose - Online shopping enables consumers to conveniently purchase products irrespective of the time and place. As a result, several online shopping companies have emerged to cater to this growing market and, therefore, the competition among them has become increasingly intense. This paper evaluates the comparative efficiency of online shopping companies for a multi-year period (2009-2013), in order to help online shopping managers identify major drivers for enhancing management efficiency and the subsequent competitiveness. Research design, data, and methodology - The researchers collected the data from 2009 to 2013 from the distribution yearbook. This paper analyzes the marketability (sales figures), profitability (business profits), and management conditions (net profits) of domestic online shopping enterprises by incorporating information on human resources (number of employees) and material resources (total assets and capital). Therefore, the number of employees, total assets, and capital are selected as input variables, and sales figures, business profits, and net profits as the output variables. In this study, Data Envelopment Analysis (DEA) was used to measure the comparative efficiency of domestic online shopping companies. In addition, the Malmquist Productivity Index was used to evaluate the trend of change of Decision Making Units' (DMUs') efficiency for a multi-year period. Results - First, as of 2013, Interpark (2.415) was found to be the most efficient online shopping enterprise, followed by Aladdin Communications (2.117), Hyundai Home shopping (1.867), Home&Shopping (1.176), NS Home shopping (1.170), Commerce Planet (1.126), CJ O Shopping (1.105), Ebay Korea (1.088), and GS Home Shopping (1.051). Second, this study recognizes how the management efficiency has changed for the period 2009-2013. Third, the lesser the capital and employees, the more are the net profits, and the better is the management efficiency of domestic online shopping companies. Lastly, the productivity of such companies is influenced by endogenous factors rather than exogenous factors such as shifts in business environment and technological advances. Conclusions - DHC Korea influenced various distribution channels to reach customers through the Internet. Consequently, this helped in increasing the awareness about its products, in addition to an increase in sales. These achievements can be attributed to the characteristics of online shopping companies. Although it is easy for these companies to suggest goods for one-off purchases, they however have difficulties in retaining customers. Overcoming this challenge can be one of the ways to benchmark a successful case of an efficient company. For example, an online shopping company can attract customers by developing a corresponding mobile application as a convenient way to shop online. Additionally, they can satisfy customers by quick delivery of purchased products, which is possible by building an effective logistics network. Our study indicates that the productivity of an online shopping company was influenced by endogenous factors driven by improvements in managerial practices rather than exogenous factors. Accordingly, online shopping companies should adopt strategies to improve their operational efficiency rather than sales volume-oriented management.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.385-391
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• 2013

Big Data is data of big size which is not processed, collected, stored, searched, analyzed by the existing database management system. The parallel genetic algorithm using the Hadoop for BigData technology is easily realized by implementing GA(Genetic Algorithm) using MapReduce in the Hadoop Distribution System. The previous study that the genetic algorithm using MapReduce is proposed suitable transforming for the GA by MapReduce. However, they did not show good performance because of frequently occurring data input and output. In this paper, we proposed the MRPGA(MapReduce Parallel Genetic Algorithm) using improvement Map and Reduce process and the parallel processing characteristic of MapReduce. The optimal solution can be found by using the topology, migration of parallel genetic algorithm and local search algorithm. The convergence speed of the proposal method is 1.5 times faster than that of the existing MapReduce SGA, and is the optimal solution can be found quickly by the number of sub-generation iteration. In addition, the MRPGA is able to improve the processing and analysis performance of Big Data technology.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1161-1166
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• 2010

Tapered roller bearings are core components of rotating machine parts and are simultaneously subjected to axial and radial loads. Life-shortening effect was particularly evident in the case of tapered roller bearings used in the input and output shafts of transmission; this shortening of life was a result of excessive axial pre-load, which is common in the transmission assembly line. In this study, we derived an equation for evaluating the life of tapered roller bearings subjected to excessive pre-load by using accelerated life test data. The DOE(Design Of Experiment) method and FEA(Finite Element Analysis) was used for determining the condition for performing an accelerated life test. This equation for evaluating the service life of the bearings was derived by analyzing the Weibull distribution of the test results. Using the derived equation the life evaluated was 6-7 times longer than that evaluated by the conventional $L_{10}$ bearing-life equation. The results of this study will be helpful in predicting the life of tapered roller bearings subjected to excessive pre-load and in designing reliable rotating machines.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.155-166
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• 2009

Road design safety assessment by existing tools and methods have normally been examined by expert judgements using design documents and on-site inspections. The existing methods, however, have two main problems such as insufficiency of objectiveness and inability to measure effects of accident countermeasures. This paper studies ways to develop a road safety assessment system through reviewing the IHSDM developed in USA. The crash prediction module of IHSDM calculate accident frequency and rate of roadway segments using accident prediction models and accident modification factors for safety evaluation. The methodology of evaluation and development of accident modification factors somewhat overcome the problems of the existing methods. In spite of these advantages, IHSDM could not relevantly reflect characteristics of domestic rural roadways since it overestimate the number of accidents and rate of korean rural roadways. Especially, IHSDM may not evaluate or consider land use patterns of Korean roadways, and futhermore, original environment on base conditions used to develop IHSDM may not be different from ours. The user requirements being developed for a road safety assessment system for Korean roadways include enhanced flexibility and diversity of data input-output processes.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.63-76
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• 2006

For a private toll road project, deciding optimal toll is an important element of economic analysis for the project and a challengeable work. In this study, the optimal toll of a private toll bridge, Geoga Bridge which connects Geoje Island of Gyeongnam Province and Gaduk Island of Busan was estimated using Stated Preference (SP) data. The SP data were collected by interviewing the passenger car drivers travelling on the National Road 14. They are latent users of the bridge. A fuzzy approximate reasoning model to estimate the optimal toll was built using the SP data. For the input variable of the model, the saved travel time and toll level were employed and the diversion rate to the bridge was employed for the output variable. The diversion rates for each toll level and saved travel time were estimated and the toll level which had maximized the toll revenue was decided as optimal toll. The optimal toll was tested by comparing with the average pay rate of passenger car drivers. Since the optimal toll for passenger cars at one hour saving, the 6,250 won is about 50 % of the average pay rate of passenger car divers, the toll was evaluated not to be high. The technique employed in this study may be used for the estimation of the optimal tolls for other kinds of vehicles.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.