• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.

• Journal of Distribution Science
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• v.14 no.8
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• pp.113-121
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• 2016

Purpose - This paper aims to examine the impact of buyer-supplier cooperation on suppliers' trust on buyers and the moderating role of buyers' governance mechanism between the sharing activities and trust. Research design, data, and methodology - An integrated research model is designed to materialize the research hypotheses. First, the impact of buyer-supplier cooperation is empirically analyzed by looking into how the sharing activities, in the field of information, resource, and knowledge, of buyer with supplier will affect the trust of supplier on buyer. Second, the moderating effect of contract-based governance mechanism of buyer is empirically analyzed. Third, the influence of trust on innovation performance of suppler is empirically analyzed. Results - Our findings provide supporting evidence for some of our hypotheses. First, all of the sharing activities are significantly influential, but in different degree, to trust of supplier. Second, contract-based governance mechanism of buyer have a moderating effect on the relationship between sharing activities and trust, positively in resource-sharing activities, negatively in information-sharing activities, not significant in knowledge-sharing activities. Third, supplier's trust on buyer positively affects supplier's own innovation performance. Conclusions - The strategies applied in supply chain management have become important as the competition among firms has shifted from competition between individual firms to competition between supply chains. A customer's sharing activities with its supplier may contribute to an increase in innovation performance. The supplier's information-sharing activity with its customer could affect its information-sharing activities with its main supplier. Cooperative activity with a partner in the supply chain is cultivated and amassed into relationship knowledge, and this study shows that the cooperative relational knowledge related to information-sharing activities enables firms to participate in sharing activities with their main suppliers. Increasing evidence shows that sharing various activities between buyer and supplier improves trust and performance outcomes, and enables firms to maintain competitive advantage. From the perspective of knowledge theory, external knowledge is becoming more important in firms' innovation activities, because innovative knowledge is acquired primarily through interaction with another organization. In addition, relationship learning could be an important tool in absorbing the supplier's core technology, information, expertise, and core competencies, increasing relational value.

• Korean Journal of Crystallography
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• v.2 no.2
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• pp.13-21
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• 1991

X-ray methods have been used to determine the chain conformation and packing of the thermotropic liquid crystalline copolyester prepared from 50% tarephthaloyl chloride(TPA) and 50% (1-phenylethyl) hydroquinone(PEHQ). The x-ray patterns of annealed melt-spun fibers contain a series of annealed melt-Pointing to a well ordered crystalline structure, despite the random sense(2 or 3-) of the 1-phenylethyl substiuttion on the TPA-hydroquinone backbone. The crystalline fiber is monoclinic with space group P2l and the unit cell has dimensions 11=12.77 A, b=10.17 A (upique axis), c=12.58 h (fiber axis). and β=90.1° and contains TPA-PEHO units of to or chains. The random substitution of 1-phenylethyl groups was modelled by placing these groups at both the 2and 3 positions and giving each a weight of one-hal(. T he structure has been refined by linked a rom least square methods(LALS) against 16 observed and 21 unobserved reflections. and had a final R value of 0.20. Packing of the side chains is effected by staggering adjacent chains along the b axis by approximately c/2, so that the side chains are interleaved. The phenyl-COO and COO-phenyl torsion angles are -6.1 and 65.6, respectively, such that the main chain phenyls are mutually inclined at 59.5 (the ester groups are assumed to be planar). These torsion angles compare very well with those for the model compounds, notably phenylbenzoate, and can be used in future analyses of the structures of more complex random sequence copolyesters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.1-10
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• 2014

The characteristics of internet traffic was dramatically changed recently. Especially, the ratio of video traffic in internet network is highly increased. Because the video traffic changes the traditional interactive traffic transport into one way contents delivery, internet network pricing structure is not efficient to reflect this changes. The fundamental reason for these is the discontinuity between the cost and revenue of the internet traffic. Although the internet traffic is forecasted to grow highly, the revenue of network provider is not expected to increase as such. The present paper investigates various alternatives to improve the present business model and to accommodate traffic growth. Then, the desirable options is proposed to invoke the innovation and to reflect the price signal according to some criteria.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.7
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• pp.157-164
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• 2020

As the consumption of fishery products continues to increase, aquaculture industry has emerged instead of fishing industry facing limitations of fish stock resources. Recently, smart fish farming industry has rapidly developed through convergence with 4th Industrial Revolution technology. Accordingly, it is important to derive a future model of smart fish farming platforms in order to secure the superiority of the aquaculture industry and the technology standard hegemony. In this study, the future direction of smart fish farm platform was derived through the analysis of environment related to politics, economy, society, and technology related to smart fish farming by applying PEST methodology of macro-environment analysis. It is expected that it will help the public and industrial circles in planning and implementing related projects by including the entire process of value chain of aquaculture industry of breeding, production, management and distribution, and by presenting advanced models based on artificial intelligence and digital twin.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.45-56
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• 2007

As the knowledge-based society has been constructed, the size of work process that has to be done grows bigger and the amount of the information that has to be analyzed increases. So each company is trying to construct more conformable process models in business model. This study helps to understand the interaction between Process data and structure which are collected on the profess by appling six Sigma as a process improving methodology. On Six Sigma, businesses tn practice Best Practice Process with the view of Value Chain To measure data for the process performing action, introducing Schedule management method makes it possible to collect and reflect accurate data of workers' ability. By this method, efficiency in production will be improved because workers we able to perform the process correctly and preliminary management for defects.

• Journal of Microbiology and Biotechnology
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• v.30 no.4
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• pp.533-539
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• 2020

A quantitative real-time polymerase chain reaction (QPCR) was applied to estimate biokinetic coefficients of Clostridium cadaveris and Clostridium sporogenes, which utilize protein as carbon source. Experimental data on changes in peptone concentration and 16S rRNA gene copy numbers of C. cadaveris and C. sporogenes were fitted to model. The fourth-order Runge-Kutta approximation with non-linear least squares analysis was employed to solve the ordinary differential equations to estimate biokinetic coefficients. The maximum specific growth rate (μ_max), half-saturation concentration (K_s), growth yield (Y), and decay coefficient (K_d) of C. cadaveris and C.sporogenes were 0.73 ± 0.05 and 1.35 ± 0.32 h^-1, 6.07 ± 1.52 and 5.67 ± 1.53 g/l, 2.25 ± 0.75 × 10¹⁰ and 7.92 ± 3.71 × 10⁹ copies/g, 0.002 ± 0.003 and 0.002 ± 0.001 h^-1, respectively. The theoretical specific growth rate of C. sporogenes always exceeded that of C. cadaveris at peptone concentration higher than 3.62 g/l. When the influent peptone concentration was 5.0 g/l, the concentration of C.cadaveris gradually decreased to the steady value of 2.9 × 10¹⁰ copies/ml at 4 h Hydraulic retention time (HRT), which indicates a 67.1% reduction of the initial population, but the wash out occurred at HRTs of 1.9 and 3.2 h. The 16S rRNA gene copy numbers of C. sporogenes gradually decreased to steady values ranging from 1.1 × 10¹⁰ to 2.9 × 10¹⁰ copies/ml. C. sporogenes species was predicted to wash out at an HRT of 1.6 h.

• Journal of Nutrition and Health
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• v.21 no.3
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• pp.173-181
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• 1988

Various types of evidence suggest that some changes in cellular in cellular calcium may well signal the initiation of a chain of events leading to the physiological effects of the bone resorbing agents. The effects of 1,25-dihydorxycholecalciferol, $1.25\textrm{(OH)}_2\textrm{D}_3$, Ca ionophore A23187 and calcium antagonist, diltiazem on bone resprption and the cellular transport of Ca were investigated. Bone $^{45}\textrm{Ca}$ desaturation experiment was realized in isolated heterogenous rat bone cells after equilibrating the cells with $^{45}\textrm{Ca}$. Results of $^{45}\textrm{Ca}$ desaturation experiments were analysed by fitting the $^{45}\textrm{Ca}$ desaturation curve to a model of 2 exponential terms which indicated the presence of 2 exchangeable cellular calcium pools. $1.25\textrm{(OH)}_2\textrm{D}_3$ (0.5ng/$m\ell$) induced significantly bone resorption which was decreased by the physiological dose of diltiazeme(above 5nmol/$m\ell$) although it was ineffective alone. Ionophore A23187 (0.2$\mu\textrm{g}$/$m\ell$) decreased Ca release from bone but no additivity of effect with diltiazem(20nmol/$m\ell$) was observed. $1.25\textrm{(OH)}_2\textrm{D}_3$ (0.5ng/$10^{6}$ cells) had a moderate effect on the two kinetic phases of $^{45}\textrm{Ca}$ desaturation curve and these values were normalized when diltiazeme (20nmol/$10^{6}$ cells) was added along with $1.25\textrm{(OH)}_2\textrm{D}_3$. Ionophore($0.05\mu\textrm{g}$/$10^{6}$ cells) alone increased specifically the value of the slow turnover rate which was not affected by addition of diltiazem. The hypothesis concerning the involvement of calcium in bone resorption seems in fact to be verified in case of $1.25\textrm{(OH)}_2\textrm{D}_3$ but more unsettled for Ca inophore A23187.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.319-332
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• 2014

Insertion loss is used as the character to express the efficiency of EMI filter. In this paper, we studied the better method that can measure the insertion loss of EMI filter exactly than the original method. For the achievement of this, the method measuring both common mode(CM) and differential mode(DM) insertion loss with arbitrary input/output impedance is accomplished using a 4-ports S-parameters system for consideration of unbalanced factor. Using this method, when input/output used in specific system is known, CM/DM insertion loss of EMI filter inserted in the system can be calculated. Finally, we applied 4-ports modeling method to 'X/Y capacitor part' and suggested the algorithm for selecting suitable the value of Y-capacitor using mixed mode S-parameters and mixed mode chain S-parameters.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.789-792
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• 2004

In various fields as web mining, bioinformatics, statistical data analysis, and so forth, very diversely missing values are found. These values make training data to be sparse. Largely, the missing values are replaced by predicted values using mean and mode. We can used the advanced missing value imputation methods as conditional mean, tree method, and Markov Chain Monte Carlo algorithm. But general imputation models have the property that their predictive accuracy is decreased according to increase the ratio of missing in training data. Moreover the number of available imputations is limited by increasing missing ratio. To settle this problem, we proposed statistical learning theory to preprocess for missing values. Our statistical learning theory is the support vector regression by Vapnik. The proposed method can be applied to sparsely training data. We verified the performance of our model using the data sets from UCI machine learning repository.