• Journal of Korea Technology Innovation Society
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• v.18 no.3
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• pp.387-415
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• 2015

In this study, we have proposed an estimation model of domestic market size using the linking between standard statistical classification systems, and reviewed the practical applicability of the model. The results of the mining and manufacturing survey of Statistics Korea conducted on the basis of KSIC (Korea Standard Industrial Classification) and Korea trade statistics based on HS (The Harmonized Commodity Description and Coding System; Harmonized System) classification were linked for the model by using the correspondence tables provided by Statistics Korea and United Nations Statistics Division. The most serious problem to adopt the integrated KSIC-ISIC-HS correspondence table for the estimation of domestic market size is the complex multiple linkages among KSIC and HS codes. In this study, we have suggested the method to divide the amount of trade corresponding to the HS codes linked to more than two ISIC codes based on the ratio of shipments corresponding to the ISIC codes as the weight. Then, it is possible to analyze the domestic market size of 125 ISIC codes in the manufacturing industry and to forecast the market size in the near future by using the model. Although the model has some limitations such as the difficulty in analysis on more subdivided items than ISIC items, the impossibility of the analysis on items in industries except for manufacturing, errors in the shipment due to some missing data, this study has significance in the sense that it provided the analysis method of domestic market size by using the most objective, reliable and sustainably useful data.

• Journal of Service Research and Studies
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• v.8 no.1
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• pp.89-102
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• 2018

The Industrial Classification is a systematic taxonomy of industrial activities and the Standard Industrial Classification is used in all country by their own a consistent classification method. Therefore, it is employed to analyze current status of industry affairs using statistical investigations in terms industrial activities for making industrial policies and to compare industrial activity among countries. Since the Second Industrial Revolution, the need for the homogenous standard of industrial classification among countries emerged as the economic and industrial exchanges between the countries have became more active. In 1940, Colin Clark who british economist divided the industry into the first (primitive), second (processed), and third (service) industries. Based on this, the United Nations Office for Statistics (UNSD) established International Standard Industry Classification (ISIC) in 1948, which most countries invoke it. ISIC(International Standard Industry Classification) and the standard industry classifications of countries have reached the present after several revisions since the enactment of the Act. In the 2000s, the standard industry classification is amended to reflect the emergence of new industries and changes in industrial structure, mainly featuring the creation and segmentation of sections in the tertiary industry domains. It also shows that primary and secondary sectors are shifting to tertiary industry. In this study, the causes of these common phenomena are systematically identified and the problems present classification systems have been analyzed. Also proposed is the direction of formation of the industrial classification system from a service economy point of view and the conceptual model of the new classification system. In the future, it is necessary to validate the proposed model through this study and to carry out various new classification system studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.60-79
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• 2022

The U-Net architecture-based segmentation models attained remarkable performance in numerous medical image segmentation missions like skin lesion segmentation. Nevertheless, the resolution gradually decreases and the loss of spatial information increases with deeper network. The fusion of adjacent layers is not enough to make up for the lost spatial information, thus resulting in errors of segmentation boundary so as to decline the accuracy of segmentation. To tackle the issue, we propose a new deep learning-based segmentation model. In the decoding stage, the feature channels of each decoding unit are concatenated with all the feature channels of the upper coding unit. Which is done in order to ensure the segmentation effect by integrating spatial and semantic information, and promotes the robustness and generalization of our model by combining the atrous spatial pyramid pooling (ASPP) module and channel attention module (CAM). Extensive experiments on ISIC2016 and ISIC2017 common datasets proved that our model implements well and outperforms compared segmentation models for skin lesion segmentation.

• International Journal of Railway
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• v.2 no.1
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• pp.37-42
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• 2009

Information management of products and services in every industries is gaining importance for resource planning and maintenance. In this paper, we analyzed the information classification systems for railway industry. International and domestic classification systems, such as HS, UNSPSC, eCl@ss and ISIC, are reviewed; as a result this paper presents the findings and the various issues. We proposed to-be images in adopting and utilizing the classification systems. Using the integrative information classification systems could make efficient electronic procurement, supply chain management and e-Business of railway services.

• Journal of Korea Trade
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• v.25 no.6
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• pp.126-142
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• 2021

Purpose - This study discusses the effects of human capital in the formation of GVC linkages. We also investigate GVC intensity between Korea and ASEAN. Design/methodology - To solve the doubling-counting problem in evaluating comparative advantage, RCA has been re-computed using domestic value-added (henceforth RCA_VA) at the country-sector level instead of value of trade. The impact of human capital on GVC intensity was empirically analyzed by establishing a panel data set with four industries (ISIC Rev. 4) in eight ASEAN countries from 2005 to 2015 from OECD-TiVA and WDI. Findings - The empirical results show that human capital has a negative effect on GVC intensity in the agriculture and manufacture industries, while it has a positive effect in the service and information industries. The results do not mean that low human capital is a barrier and inefficient to GVC linkages. Low Value-added activities may be more profitable to some emerging countries. These findings suggest that it is important to accurately identify the competitive elements to increase gains from trade under the GVC. Also, it shows that comparative advantages can be misled by an RCA index evaluated in trade volume under the GVC. Originality/value - This study highlights the importance of human capital as a factor for the efficient formation of Global Value Chain (GVC). This study has different from the literature in analyzing the role of human capital in formation of linkage of the GVC. And we clarify the changing patterns of trade by removing the double-counting problem under the GVC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2458-2482
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• 2023

Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, MultiHead Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.

• Journal of Korea Trade
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• v.25 no.2
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• pp.75-94
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• 2021

Purpose - This article will take the Korean manufacturing industry as an example to estimate Korea's global value chain status from the perspective of overall and sub-industry, hoping to provide a theoretical reference for Korean manufacturing to climb the global value chain. Design/methodology - Based on the WIOD data. The data is calculated by using MATLAB (2014a) coding. The data for 6 sectors are classified according to the International Standard Industrial Classification revision 3 (ISIC Rev. 3), the WIOD data are used to calculate and compare the position, participation and dynamics of the Korea, China and USA' manufacturing industry in the 1995-2016. Findings - The empirical results supported conclusions of the theoretical model. In the Korean GVC of electrical and optical sector, while stronger forward linkages than backward linkages to GVC are advantageous for an average advanced country, the benefits of downstream tasks are pronounced for non-advanced countries. And proved the correlation for an index to capture a country's upstream position or downstream position, it makes sense to compare that Korea's exports of intermediates in the same sector that are used by China and USA. Originality/value - The first is to re-examine the characteristics of South Korea's participation in global value chains under a more systematic and accurate theoretical framework, which provides a new empirical reference for related research; the second is to content covers of the manufacturing 6 sectors, so as to more completely describe the characteristics of Korean manufacturing's participation in global value chains; The value of this paper is providing empirical evidence of the effect of Korea's the GVC of manufacturing sectors. In the GVC of 6 sectors, first three have a higher position in the value chain and are in the upper middle and upper reaches of the GVC. The latter two have a low GVC position index, which has become the main sector that pulls down the overall position of Korea's manufacturing industry.

• Information Systems Review
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• v.19 no.4
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• pp.111-134
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• 2017

This study compares the linkage effects and competitive advantage between ICT and automobile industry in Korea from 1996 to 2011 using input-output tables. The ICT industry is classified according to the International Standard Industry Classification. Results show that (1) the ICT industry exhibits linkage effects similar to those of automobile industry. (2) Both ICT and automobile manufacturing sectors exert significant effects on the demand and supply. Additionally, (3) ICT service and automobile sectors show linkage effects on demand and supply, respectively. The present results present the classification criteria of the ICT industry discussed to date and suggest economic effects and policy implications.