• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.89-94
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• 2021

Recently, the boundaries between people who produce and consume digital contents disappears due to the massive developments in information and communications technology (ICT) and the rapidly increasing spread of smartphones unlike in the traditional mass media (e.g., newspapers, radios, and TVs). Through the open service platform, the problem perception for each individual remains the same, but the problem solving methods varies as the service types have been diversified. The creation of added value through the growth of the new media platform industry is expected to enrich our lives, but it can also cause severe social side effects. For example, communication problems between social classes due to the information gap have led to generational conflict, and if such problems persist, it can cause national and social losses. Therefore, this paper analyzes the policy efforts to resolve the information gap and the necessity of the legalization of multimedia literary education to maximize the synergy effect through psychological model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.374-376
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• 2021

For the diagnosis of cancer-related diseases in clinical practice, pathological examination using biopsy is essential after basic diagnosis using imaging equipment. In order to proceed with such a biopsy, the assistance of an oncologist, clinical pathologist, etc. with specialized knowledge and the minimum required time are essential for confirmation. In recent years, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, previous studies show limitations in the type and accuracy of cells based on a limited algorithm. In this study, we propose a method to identify a total of 4 cancer cells through a convolutional neural network, a kind of deep learning. The optical images obtained through cell culture were learned through EfficientNet after performing pre-processing such as identification of the location of cells and image segmentation using OpenCV. The model used various hyper parameters based on EfficientNet, and trained InceptionV3 to compare and analyze the performance. As a result, cells were classified with a high accuracy of 96.8%, and this analysis method is expected to be helpful in confirming cancer.

• Knowledge Management Research
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• v.24 no.2
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• pp.117-135
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• 2023

With the spread of COVID-19 and the preference for untact services, kiosks, which is one of self-service technologies, have been expanding into various service fields. Kiosks have some advantages of reducing labor costs and increasing work efficiency, but they often cause difficulties in the process of using kiosks. In this vein, this study examines the key antecedents affecting consumer's continuance intention toward kiosks by integrating technology anxiety and innovativeness into the expanded expectation-confirmation model. The research model was verified for the MZ generation to examine the perceptions of MZ generation about Kiosks. This is because if the MZ generation feels technical anxiety or difficualty about using kiosks, customers of other generations can expect to feel even more uncomfortable. As a result of the analysis of this study, it was confirmed that technical anxiety has a significantly negative effect on consumer's continuance intention toward kiosks. However, among the characteristic factors of customers, innovativeness did not significantly consumer's continuance intention toward kiosks. Based on our findings, it is expected that service companies will be able to understand the mechanism of forming consumer's continuance intention toward kiosks and pursuit several management activities for successfully adopting kiosks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.104-109
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• 2017

The flooding and deterioration of water quality caused by urbanization and climate change are becoming more serious. In order to respond to this, studies on low impact development (LID) technology, which is designed to restore the hydrological system of the urban basin to its natural state, have been actively pursued all over the world, The announcement of the low carbon green growth law, hydrophilic area special law, etc., highlights the importance of technology such as the LID method. However, whereas various developments have been made in relation to the current LID element technology, there has been little research designed to verify its effectiveness. In this study, we analyzed the optimum spatial distribution of pitcher fire pitcher packing in parking lots using the K - LIDM model to verify the effectiveness of the low impact development (LID) method in the early stages. Using the eight package scenario and the three rain intensity scenarios, it was found that the lower 40% pitcher packaging results in an approximately 90% spill reduction effect, as in the case of the whole pitcher's package. The confirmation of these analyses and experimental verification is expected to ensure that the actual pitcher packaging will be used as a basis for arranging LID facilities such as urban planning and housing development in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.