• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.504-514
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• 2013

Purpose: This study was to identify the educational effects of self directed learning applying basic nursing practice contents of e-learning on nursing students' knowledge, self-confidence, and learning satisfaction. Method: This study applied a quasi-experimental pre-test and post-test control group design with 63 freshman nursing students (31 experimental group, 32 control group) of G. university in Incheon, Korea as subjects. The e-learning content was about the application of topical medications, central line care, and blood transfusion. All were available at the web site in school. Self-directed e-learning was more than 120 min.(3 times a week, 2 weeks)during Sep-Nov in 2011. In both groups, there were no significant difference in general characteristics, self-directed learning readiness, knowledge, and self-confidence for the pre-homogeneity. Results: The experimental group showed a higher level of improvement in knowledge and learning satisfaction but not significantly. However, the self-confidence was significantly improved in the experimental group. Conclusion: When self-directed learning using e-learning contents added to the conventional practical class, it may be beneficial for the nursing students to learn skills effectively.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.729-735
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• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.141-174
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• 2021

In this study, by examining the actual usage data of the university library website before and after COVID-19 outbreak, the usage behavior of users was analyzed, and the data before and after the virus outbreak was compared, so that university libraries can provide more efficient information services in a pandemic situation. We would like to suggest ways to improve it. In this study, the user traffic made on the website of University C was 'using Google Analytics', from January 2018 to December 2018 before the oneself of the COVID-19 virus and from January 2020 to 2020 after the outbreak of the virus. A comparative analysis was conducted until December. Web traffic variables were analyzed by classifying them into three characteristics: 'User information', 'Path', and 'Site behavior' based on metrics such as session, user, number of pageviews, number of pages per session time, and bounce rate. To summarize the study results, first, when compared with data from January 1 to January 20 before the oneself of COVID-19, users, new visitors, and sessions all increased compared to the previous year, and the number of sessions per user, number of pageviews, and number of pages per session, which showed an upward trend before the virus outbreak in 2020, increased significantly. Second, as social distancing was upgraded to the second stage, there was also a change in the use of university library websites. In 2020 and 2018, when the number os students was the lowest, the number of page views increased by 100,000 more in 2020 compared to 2018, and the number of pages per session also recorded10.46, which was about 2 more pages compared to 2018. The bounce rate also recorded 14.38 in 2018 and 2019, but decreased by 1 percentage point to 13.05 in 2020, which led to more active use of the website at a time when social distancing was raised.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.3
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• pp.98-114
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• 2016

The this study aimed to expand urban heritage using Public Goods and to suggest the assemblage of urban heritage and urban spaces in order to improve landscape conservation and management scheme of urban heritage exposed to a rapidly changing urban environment. The results obtained in this study were summarized as follows: First, in order to improve understanding of the heritage in urban spaces, urban heritage were illustrated on a 1:1000 map with all the public facilities surrounding it using a cultural heritage conservation map listed on the Cultural Heritage Administration's web site, standards for changing present condition, and a topographic map. Second, the status and changes of urban heritage and surroundings were analyzed using the minutes of Historical Cultural Heritage Division Committee for 10 years from 2005 to 2014 to create a status map of urban heritage. Land uses surrounding the urban heritage were investigated the areas of conservation potential and the places that can enhance the to find out values of urban heritage. Also, a profile was created to examine the site characteristics surrounding urban heritage, and photos were taken at important heritage areas and public facilities in order to record the field. Third, analyzed were the relationship of the distance, location, function, and distribution between urban heritage and public facilities surrounding the heritage. using visual features and moving routes in order to identify their impacts on urban heritage and their functions as potential resources. In addition, the role of Public Goods in urban spaces and the plan for revitalizing surrounding areas asset were examined. Fourth, selections were made on Public Goods that have direct or indirect effects on urban heritage. The role of public asset was investigated through visual, areal, and linear elements. The results were summarized to suggest improvement landscape and management mauser on of urban heritage.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.25-35
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• 2022

Covid-19, of which the first patient in Korea occurred in January 2020, has affected various fields. Of these, the tourism sector might havebeen hit the hardest. In particular, since tourism-based industrial structure forms the basis of the region, Gangwon-province, and the tourism industry is the main source of income for small businesses and small enterprises, the damage is great. To check the situation and extent of such damage, targeting the Chuncheon region, where public access is the most convenient among the Gangwon regions, one-day tours are possible using public transportation from Seoul and the metropolitan area, with a general image that low expense tourism is recognized as possible, this study conducted empirical analysis through data analysis. For this, the general status of the region was checked based on the visitor data of Chuncheon city provided by the tourist information system, and to check the levels ofinterest in 2019, before Covid-19, and in 2020, after Covid-19, by comparing keywords collected from the web service sometrend of Vibe Company Inc., a company specializing in keyword collection, with SK Telecom's T-map search site data, which in parallel provides in-vehicle navigation service and communication service, this study analyzed the general regional image of Chuncheon-city. In addition, by comparing data from two years by developing a tourism popularity index applying keywords and T-map search site data, this study examined how much the Covid-19 situation affected the level of interest of visitors to the Chuncheon area leading to actual visits using a data analysis approach. According to the results of big data analysis applying the tourism popularity index after designing the data mart, this study confirmed that the effect of the Covid-19 situation on tourism popularity in Chuncheon-city, Gangwon-provincewas not significant, and confirmed the image of tourist destinations based on the regional characteristics of the region. It is hoped that the results of this research and analysis can be used as useful reference data for tourism economic policy making.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.366-374
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• 2012

Recently pathogenic E. coli is one of the main foodborne pathogens resulting in many patients in Korea. To understand the characteristics of pathogenic E. coli outbreaks in Korea, the epidemiological investigation reports of pathogenic E. coli outbreak in 2009 (41 reports) and in 2010 (27 reports) were collected in the web site of the Korea Centers for Disease Control and Prevention, reviewed and analysed in this study. The main places of the pathogenic E. coli outbreaks were food catering service area (64.8%) and restaurants (25.0%). The main type of the pathogens were EPEC (44.7%) and ETEC (34.2%). EAEC and EHEC was responsible for 10.5 and 9.2%, respectively. Eight of 68 outbreak cases were caused by more than 2 types of pathogenic E. coli which implicates the complicated contamination pathways of pathogenic E. coli. The incidence rate of pathogenic E. coli was $33.6{\pm}30.5%$ and the main symptoms were diarrhea, stomach ache, nausea, vomiting, and fever etc. The two identified food sources were identified as frozen hamburger pattie and squid-vegetable mixture. To improve the food source identification by epidemiological investigation, food poisoning notification to the agency should not be delayed, whole food items attributed the outbreak should be collected and detection method of the various pathogenic E. coli in food has to be improved. In conclusion, the characteristics between the EHEC outbreaks in the western countries and the EPEC or ETEC outbreaks in Korea needs to be distinguished to prepare food safety management plan. In addition, the development of the trace back system to find the contamination pathway with the improved detection method in food and systemic and cooperative support by the related agencies are necessary.

• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.39-50
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• 2024

In ecosystems within limited resources, interspecific competition is inevitable, often leading to the competitive exclusion of inferior species. This study aims to provide foundational information for the conservation and restoration management of Microphysogobio rapidus by evaluating species' ecological response to biological factors within its habitat. To understand this relationship, we collected food web organisms from site where M. rapidus coexist with Microphysogobio yaluensis, a specie ecologically similar to M. rapidus, and evaluated the trophic levels (TL), isotopic niche space (INS), and the overlap of INS among fishes within the habitat using stable isotope analysis. Our analysis revealed that the M. rapidus exhibited a higher TL than M. yaluensis, with TL of 2.6 and 2.4, respectively. M. yaluensis exhibited a broad INS, significantly influencing the feeding characteristics of most fish. Conversely, M. rapidus showed a narrow INS and asymmetric feeding relationships with other species, in habitats with high competition levels. This feeding characteristics of M. rapidus indicate that the increase in competitors sharing the similar resources lead to a decrease in available resources and, consequently, is expected to result in a decrease in their density.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.