• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.94-99
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• 2024

Recently, wind power has been gaining attention as a highly efficient renewable energy source, leading to various technological developments worldwide. Typically, wind power is operated in the form of large wind farms with many wind turbines installed in areas rich in wind resources. However, in developing countries or regions isolated from the power grid, off-grid small wind power systems are emerging as an efficient solution. To efficiently operate and expand off-grid small-scale power systems, the development of real-time monitoring systems is required. For the efficient operation of small wind power systems, it is essential to develop real-time monitoring systems that can actively respond to excessive wind speeds and various environmental factors, as well as ensure the stable supply of produced power to small areas or facilities through an Energy Storage System (ESS). The implemented system monitors turbine RPM, power generation, brake operation, and more to create an optimal operating environment. The developed small wind power system can be utilized in remote road lighting, marine leisure facilities, mobile communication base stations, and other applications, contributing to the development of the RE100 industry ecosystem.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.19-24
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• 2024

Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems

• Information Systems Review
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• v.26 no.2
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• pp.155-167
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• 2024

This study recognized the importance of joint research in the field of artificial intelligence and analyzed the characteristics of the industry-academic-research technological cooperation ecosystem focusing on patents from the perspective of the Techno-Economic Segment (TES). To this end, economic entities such as companies, universities, and research institutes within the ecosystem were identified for 7,062 joint research projects out of 113,289 artificial intelligence patents over the past 10 years filed in IP5 countries since 2012. Next, this study identified the topics of technological cooperation and the characteristics of cooperation. As a result of the analysis, technological cooperation is increasing, and the frequency of all types of cooperation was high in industry-to-industry (40%) and industry-to-university (25.2%) relationships. Here, this study confirmed that the role of universities is being strengthened, with an increase in the ratio of companies with strengths in funding and analytical data, industry and universities with excellent research personnel (9.8%), and cooperation between universities (1.9%). In addition, as a result of identifying collaborative patent research areas of interest and collaborative relationships through topic modeling and network analysis, overall similar research interests were derived regardless of the type of cooperation, and applications such as autonomous driving, edge computing, cloud, marketing, and consumer behavior analysis were derived. It was confirmed that the scope of research was expanding, collaborating entities were becoming more diverse, and a large-scale network including Chinese-centered universities was emerging.

• Applied Chemistry for Engineering
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• v.35 no.5
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• pp.423-428
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• 2024

Microneedles with micron-sized needle arrays are an emerging technology for the transdermal administration of active pharmaceutical ingredients with minimally invasive pain. Over the past decade, although various additive manufacturing technologies have been employed for precise fabrication of microneedles, these methods are often limited by material compatibility and bioavailability, in addition to being time-consuming and costly. In here, we compare the resolution of Polyjet and DLP-SLA 3D printing methods for the precise fabrication of biodegradable PCLDA/PEGDA microneedles. To enhance the structural accuracy of the microneedles from both printing methods, we evaluate the 3D printing conditions, including 3D printing angle and needle height and diameter. Molds for microneedles are fabricated using optimized 3D printing methods, and subsequent replica molding processes are employed to fabricate the polymeric microneedles with sharp need tips. Finally, we use photocurable PCLDA and PEGDA for biodegradable and biocompatible microneedles, and their mechanical properties as PCLDA concentrations are analyzed to assess the strength required for skin insertion. This study has demonstrated the efficient and low-cost fabrication of high-resolution microneedles for transdermal drug delivery.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.3
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• pp.208-222
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• 2024

Jeju Haenyeo is in danger of extinction, and the issue of labor force reproduction is emerging as an important agenda. The traditional method of labor force reproduction based on matrilineal succession is gradually disappearing, and part of its role is being taken over by vocational training institutions such as Jeju Haenyeo School. In order to maintain the social, economic, and cultural sustainability of Jeju Haenyeo, sustainable labor reproduction is an essential prerequisite, so multidimensional study on the labor reproduction issue of Jeju Haenyeo has important academic and policy implications. Accordingly, we analyzed previous studies directly and indirectly related to the reproduction of Jeju Haenyeo's labor force and the role of vocational training institutions in labor force reproduction. Based on this, we presented three issues that should be addressed. First, a detailed analysis of the role of Jeju Haenyeo School as a key platform for reproducing the Jeju Haenyeo's labor is required. Second, it is important to pay attention to the role of social capital in the reproduction of the Jeju Haenyeo labor. Third, a qualitative analysis process is needed to understand the meaning of the experiences in order to measure the organic relationships centered on the haenyeo community.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.3
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• pp.174-191
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• 2024

This study analyzed the spatiotemporal evolution of Korean multinational corporations' (MNCs') foreign direct investment (FDI) networks from 1978 to 2023, focusing on Samsung Electronics and LG Electronics. Using data on the consolidated overseas subsidiaries of these two companies, a two-mode network was constructed to examine the status of host countries through the betweenness centrality index and to identify types of countries with similar value chain arrangements by investigating their linkage structures. The main findings are as follows. First, during the early phase of Korean electronics MNCs' overseas expansion in the 1980s, they primarily established sales bases in developed consumer markets. However, over time, they gradually expanded into other business areas, including manufacturing, producer services, and R&D, increasing complexity in their FDI networks as cross-border mergers and acquisitions (M&As) became more frequent. Second, the United States has remained central to these MNCs' FDI networks since the 1980s, but more recently, China has emerged as a significant hub, challenging the U.S. in global value chains. Third, emerging Asian economies, including India, Vietnam, and Indonesia, have strengthened their positions due to the diversification of MNCs' investment objectives from manufacturing bases to a broader range of business areas. Finally, since the 2010s, the convergence of the electronics industry with the automotive electronics sector and new industries has led to a diversification of the value chain arrangements of Korean electronics MNCs.

• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Clinical and Experimental Pediatrics
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• v.50 no.1
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• pp.56-64
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• 2007

Purpose : This study was performed to identify the etiologic agents and antimicrobial susceptibility patterns of organisms responsible for bloodstream infections in pediatric cancer patients for guidance in empiric antimicrobial therapy. Methods : One hundred and ninety-seven episodes of bloodstream infections that developed in 128 pediatric cancer patients were analyzed, which were identified at the Seoul National University Children's Hospital during a 4 year-period from 2002 to 2005. Results : A total of 214 pathogens was isolated, of which 64.0 percent were gram-negative, 31.3 percent were gram-positive bacteria, and 4.7 percent were fungi. The most common pathogens were Klebsiella spp. (21 percent) and Escherichia coli (16.8 percent), and coagulase-negative staphylococci (CNS, 7.9 percent) and viridans streptococci (7.5 percent) emerged as important pathogens. Neutropenic patients were more often associated with gram-negative bacteria than non-neutropenic patients (67.5 percent vs. 51.1%, P=0.018) and patients with central venous catheters were more often associated with CNS and viridans streptococci than those without. Resistance rates of gram-positive bacteria to penicillin, oxacillin and vancomycin were 83.3 percent, 48.5 percent and 0.5 percent, respectively, and those of gram-negative bacteria to cefotaxime, piperacillin/tazobactam, imipenem, gentamicin and amikacin were 24.1 percent, 17.2 percent, 6.6 percent, 21.6 percent, and 14.2 percent, respectively. Gram-negative bacteremias were more often associated with intensive care than gram-positive bacteremias (26.5 percent vs. 10.3 percent, P=0.016), and patients with catheters were more often associated with intensive care (34.4 percent vs. 10.8 percent, P<0.001) and higher fatality rate (16.7 percent vs. 4.8 percent, P=0.012) than those without. Conclusion : This study revealed that gram-negative bacteria are still a dominant organism in bloodstream infections, especially in neutropenic patients, and confirmed that gram-positive bacteria are emerging as important etiological agents in bloodstream infections of pediatric hemato-oncologic patients.

• Journal of Life Science
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• v.19 no.4
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• pp.423-428
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• 2009

Selenium was investigated using human origin preadipocytes to see whether it possesses preventive or therapeutic effects for obesity. Unveiling the potential of selenium in the reduction of adipogenesis can help predict the therapeutic capabilities of selenium in obesity. In the present study, the molecular mechanism of the inhibition of adipogenesis by selenium was explored to unravel the involvement of the AMP-activated protein kinase. There is emerging evidence that AMPK, a sensor of cellular energy status, is a possible molecular target of controlling adipocyte differentiation on the basis of discovery that AMPK is responsible for the major metabolic responses to exercise, and integration of nutritional and hormonal signals to modulate feeding behavior or energy expenditure in the hypothalamus. Treatment of selenium resulted in inhibition of the adipocyte differentiation process and induction of mature apoptosis in 3T3-L1 adipocytes. We hypothesized that selenium may exert anti-adipogenic potential though modulating AMPK. We have found that selenium significantly activated AMPK and phosphorylated its substrate acetyl-CoA carboxylase ($ACC-serine^{79}$) during the inhibitory process of adipocytes. Also, the inhibition process of adipocyte differentiation by selenium was comparable to either reveratrol or a synthetic AMPK activator, AICAR (5-aminoimidazole-4-carboxamide-1-${\beta}$-D-ribofuranoside). To evaluate the involvement of AMPK in anti-lipogensis, we applied AICAR and Compound C, an AMPK inhibitor, to 3T3-L1-adipocytes and found that AMPK is required for the adipocyte differentiation blocking process. These results suggest that selenium has a potential to control adipogenesis and that this effect is mediated by AMPK, an essential kinase for both inhibition of adipocyte differentiation and apoptosis of mature adipocytes.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.