• Journal of Digital Convergence
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• v.22 no.3
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• pp.1-7
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• 2024

This study provides an in-depth analysis of the impact of the deepening reform and opening-up policies announced at the 20th CPC Central Committee's Plenary Session, particularly focusing on the <Foreign Investment Law> and its effects on the tax decisions and organizational restructuring of Korean companies operating in China. Using a comprehensive literature review and policy analysis, the study compares the dual legal structure and tax differences before and after the implementation of the law, assessing how legal unification has influenced the organizational forms and tax strategies of Korean companies. The findings indicate that the <Foreign Investment Law> has played a crucial role in enhancing legal consistency and tax equity between foreign-invested enterprises and domestic enterprises, thereby enabling Korean companies to manage their operations in the Chinese market more stably and efficiently. Additionally, in the context of the ongoing U.S.-China trade conflict, the law's provision of national treatment and tax benefits has proven to be a significant factor in the survival strategy of Korean companies in China. Future research should focus on empirically examining the long-term effects of this law and its impact on actual corporate performance.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.87-118
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• 2024

Coastal ports play an essential role in developing a country and a city. Port efficiency is an important factor affecting port trade, and the importance of port efficiency for port performance has been recognized in previous literature. DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis) are widely used in this field of research. However, these two methods are limited in selecting input and output variables. In addition, the literature studies on Chinese coastal ports mainly focus on the study of port clusters in local areas, which lacks a holistic approach and generally lacks up-to-date data. Therefore, to fill the gap in this area of research, this paper introduces a model combining principal component analysis and data envelopment analysis to analyze the operational efficiency of the top 17 coastal ports in China in terms of throughput based on the most recent data available in 2021. This paper identifies container throughput as the output variable, and 13 second indicators are selected as input variables from four primary indicators: land, capital, labor, and infrastructure. Four principal components were selected from 13 second indicators using PCA.After that, DEA (BBC) and DEA (CCR) were used to analyze the 17 ports, among which five were Shanghai, Ningbo-Zhoushan, Guangzhou, Xiamen, and Dongguan, respectively, DEA efficient, and the remaining 12 ports were non-DEA efficient. Finally, improvement directions for each port are derived, and brief suggestions are made. This paper provides some reference value for developing and constructing coastal ports in China.

• Journal of Sensor Science and Technology
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• v.33 no.5
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• pp.318-325
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• 2024

In this study, we fabricated TiO₂-decorated SnO₂ nanorods (TSNRs) via glancing-angle deposition to achieve highly sensitive and selective CH₃COCH₃ detection. The gas-sensing properties of the TSNRs were systematically investigated, and the optimal sensing performance was achieved at 350℃ by 2-nm-thick TSNRs. When the sensors were exposed to 50 ppm of various gases (CH₃COCH₃, C₂H₅OH, C₅H₈, CH₄, and CO), the 2-nm-thick TSNRs demonstrated a 4.6-fold increase in response (R_a/R_g-1=134) to CH₃COCH₃ compared with bare SnO₂ nanorods (R_a/R_g-1=29.5) and exhibited excellent selectivity. In a high-humid environment (relative humidity = 80%), the 2-nm-thick TSNRs indicated a low theoretical detection limit of ≈5.31 ppb for CH₃COCH₃. These results suggest the significant potential of the proposed sensor for use in Internet-of-Things applications, particularly under extreme environmental conditions.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Journal of Agricultural Extension & Community Development
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• v.21 no.2
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• pp.1-28
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• 2014

Private consulting firms that are currently participating in rural area development projects with a bottom-up approach are involved in nearly all areas of rural area development, and the policy environment that emphasizes the bottom-up approach will further expand their participation. Reviews of private consulting firms, which started out with high expectations in the beginning, are now becoming rather negative. Expertise is the key issue in the controversy over private consulting firms, and the analysis tends to limit the causes of the problems within firms. This study was conducted on the premise that the fixation on cause and structure results in policy issues in the promotion process. That is because the government authorities are responsible for managing and supervising the implementation of policies, not developing the policies. The current issues with consulting firms emerged because of the hasty implementation of private consulting through the government policy trend without sufficient consideration, as well as the policy environment that demanded short-term outcomes even though the purpose of bottom-up rural area development lies in the ideology of endogenous development focused on the changes in residents' perceptions. Research was conducted to determine how the problems of private consulting firms that emerged and were addressed in this context influenced the consulting market, using current data and based on the firms' business performance. In analyzing the types, firms were divided into three groups: top performers including market leaders (9), excellent performers (36), and average performers (34). An analysis of the correlation between the business performance of each type and managerial resources such as each firm's expertise revealed that there was only a correlation between human resources and regional development in excellent performers, and none was found with the other types. These results imply that external factors other than a firm's capabilities (e.g., expertise) play a significant role in the standards of selecting private consulting firms. Thus, government authorities must reflect on their error of hastily adopting private consulting firms without sufficient consideration and must urgently establish response measures.

• Journal of Life Science
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• v.18 no.8
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• pp.1132-1139
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• 2008

A CpG island is a short stretch of DNA in which the frequency of the CG dinucleotide is higher than other regions. CpG islands are present in the promoters and exonic regions of approximately $30{\sim}60$% of mammalian genes so they are useful markers for genes in organisms containing 5-methylcytosine in their genomes. Recent evidence supports the notion that the hypermethylation of CpG island, by silencing tumor suppressor genes, plays a major causal role in cancer, which has been described in almost every tumor types. In this respect, CpG island search by computational methods is very helpful for cancer research and computational promoter and gene predictions. I therefore developed a window program (called CpGi) on the basis of CpG island criteria defined by D. Takai and P. A. Jones. The program 'CpGi' was implemented in Visual C++ 6.0 and can determine the locations of CpG islands using diverse parameters (%GC, Obs (CpG)/Exp (CpG), window size, step size, gap value, # of CpG, length) specified by user. The analysis result of CpGi provides a graphical map of CpG islands and G+C% plot, where more detailed information on CpG island can be obtained through pop-up window. Two human contigs, i.e. AP00524 (from chromosome 22) and NT_029490.3 (from chromosome 21), were used to compare the performance of CpGi and two other public programs for the accuracy of search results. The two other programs used in the performance comparison are Emboss-CpGPlot and CpG Island Searcher that are web-based public CpG island search programs. The comparison result showed that CpGi is on a level with or outperforms Emboss-CpGPlot and CpG Island Searcher. Having a simple and easy-to-use user interface, CpGi would be a very useful tool for genome analysis and CpG island research. To obtain a copy of CpGi for academic use only, contact corresponding author.

• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.1-25
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• 2016

The present study investigated the effect size of attention and consciousness on change detection. We confirmed the effect size of consciousness by comparing the condition which combined attention and consciousness and the condition of attention without consciousness. Then, we confirmed the effect size of attention by comparing the condition of attention without consciousness and the control condition which excluded attention and consciousness. For this purpose, change detection task and continuous flash suppression (CFS) were used. CFS renders a highly visible image invisible. In CFS, one eye is presented with a static stimulus, while the other eye is presented with a series of rapidly changing stimuli, such as mondrian patterns. The result is that the static stimulus becomes suppressed from conscious awareness by the stimuli presented in the other eye. We used a customized device with smartphone and google cardboard instead of stereoscope to trigger CFS. In Experiment 1-1, we reenacted some study to validate our experimental setup. Our experimental setup produced the duration of stimulus suppression that were similar to those of preceding research. In Experiment 1-2, we reenacted a study for attention without consciousness using an customized device. The results showed that attention without consciousness more strongly work as a cue. We think that it is reasonable to use CFS treatment employing smartphone and google cardboard for a follow-up study. In Experiment 2, when performing the change detection task, we measured the effect size of consciousness and attention by manipulating the consciousness level of cue. We used the method in which everything but the variable of interest kept being fixed. That way, the difference this independent variable makes to the action of the entire system can be isolated. We found that there was significant difference of correct response rate on change detection performance among different consciousness level of cue. In this study, we investigated that not only the role of attention and consciousness were different also we were able to estimated the effect size.

• Journal of Distribution Research
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• v.15 no.2
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• pp.71-99
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• 2010

Most of studies on patriotism in the marketing area have focused on ethnocentric tendencies observed in consumption behaviors. On the contrary, there have been few empirical studies on how patriotism in the general sense, indicating affection for, attachment to, and pride in the country, influences consumers' evaluation of domestic and foreign products. Given the current situation that marketing activities appealing to people's patriotism is increasing, this is somewhat surprising. Thus, this study examined empirically how patriotism influences people's evaluation of domestic and foreign products. In addition, we tested whether consumer ethnocentrism works as an intervening variable in the relation between patriotism and product evaluation. The empirical analysis was conducted through a questionnaire survey of undergraduate and graduate students at universities in Seoul. The survey asked about the respondents' patriotism, consumer ethnocentrism, domestic product evaluation, foreign product evaluation, and demographical characteristics. In foreign product evaluation, the respondents were requested to evaluate Chinese and Japanese products. Email was used to send and recover the questionnaires, and 135 replies were used in the analysis. Major findings from the empirical analysis are as follows. First, a significant relationship was observed between patriotism and domestic product evaluation. That is, patriotic participants evaluated domestic products more favorably. On the other hand, no significant relationship was observed between patriotism and foreign product evaluation(See Table 1-1 and 1-2). Next, the effect of patriotism on domestic product evaluation was mediated by consumer ethnocentrism. However, whether the effect of patriotism on domestic product evaluation is mediated by consumer ethnocentrism partially or fully was different according to product(See Table 2-1 and 2-2). Lastly, we tried to analyze the relation between consumer ethnocentrism and product evaluation and comparing the results with findings of previous researches. According to the results, a significant relationship was observed between consumer ethnocentrism and domestic product evaluation but not between consumer ethnocentrism and foreign product evaluation. The meanings of this study are as follows. First, there have been few marketing studies that investigated the relation between patriotism and product evaluation. Thus, this study is meaningful in that it supplemented the limitation of previous research. Second, consumer ethnocentrism was found to mediate the relation between patriotism and domestic product evaluation. Considering the absence of previous research that examined the role of consumer ethnocentrism as an intervening variable, this study is significant in that it expanded the scope of research on consumer ethnocentrism. Third, from the practical aspect, the results of this study suggest that marketing appealing to patriotism is effective in stimulating consumers' purchase and consumption of domestic products. Accordingly, such a marketing strategy is expected to be effective in protecting domestic markets from imported goods and overseas brands and to increase demands for domestic products and brands. However, there is the question of whether the effect of patriotism based marketing strategies in promoting demand for domestic products would persist. That is, this study could not find a significant relation between patriotism and foreign product evaluation, and this means that the increase in patriotism for the home country does not damage people's view to the quality of foreign products negatively. Accordingly, without change in people's perception of foreign products, it is highly likely that the increase in demand for domestic products or brands induced by patriotism elevated at a specific time or situation may not last long. Fourth, the results of this study suggest that the patriotism level may influence consumers' choice behavior toward retailers strongly connected to a specific country or region. That is, consumers with high level patriotism may hesitate or avoid using a retailer associated with some foreign country. Fifth, according to the results of this study, when people's patriotism is stimulated by a specific social situation or event, it can be an opportunity for domestic franchise brands to increase their market performance such as sales and market share and, at the same time, for foreign franchise brands to experience adversities. Therefore, during a period like the Olympic Games or the World Cup when people's sense of belonging or attachment to their country is heightened, domestic franchise brands need to make marketing activities that may lead market opportunities to substantial results and foreign franchise brands to cope with such adversities. Sixth, consumers' brand choice is often made in retail stores. It has been demonstrated by numerous studies that in store stimuli such as point of purchase display can affect consumers' behavior. Considering this, domestic brands facing competition with foreign brands should make continuous efforts to enhance the market performance of their products through developing in store stimuli that can stimulate consumers' patriotism. Finally, based on the major findings of this study, both academic and practical issues were discussed. Suggestions for future studies were provided.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.