• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.14-20
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• 2021

Most accidents caused by road icing in winter lead to major accidents. Because it is difficult for the driver to detect the road icing in advance. In this work, we study how to accurately detect road traffic emerging risk using AutoML and CNN's ensemble model that use both structured and unstructured data. We train CNN-based road traffic emerging risk classification model using images that are unstructured data and AutoML-based road traffic emerging risk classification model using weather data that is structured data, respectively. After that the ensemble model is designed to complement the CNN-based classification model by inputting probability values derived from of each models. Through this, improves road traffic emerging risk classification performance and alerts drivers more accurately and quickly to enable safe driving.

• Parasites, Hosts and Diseases
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• v.51 no.6
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• pp.645-650
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• 2013

A simple, rapid, and high-throughput method for detection and identification of Wuchereria bancrofti, Brugia malayi, Brugia pahangi, and Dirofilaria immitis in mosquito vectors and blood samples was developed using a real-time PCR combined with high-resolution melting (HRM) analysis. Amplicons of the 4 filarial species were generated from 5S rRNA and spliced leader sequences by the real-time PCR and their melting temperatures were determined by the HRM method. Melting of amplicons from W. bancrofti, B. malayi, D. immitis, and B. pahangi peaked at $81.5{\pm}0.2^{\circ}C$, $79.0{\pm}0.3^{\circ}C$, $76.8{\pm}0.1^{\circ}C$, and $79.9{\pm}0.1^{\circ}C$, respectively. This assay is relatively cheap since it does not require synthesis of hybridization probes. Its sensitivity and specificity were 100%. It is a rapid and technically simple approach, and an important tool for population surveys as well as molecular xenomonitoring of parasites in vectors.

• Parasites, Hosts and Diseases
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• v.51 no.6
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• pp.689-694
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• 2013

Opisthorchis viverrini and Clonorchis sinensis are parasites known to be carcinogenic and causative agents of cholangiocarcinoma in Asia. The standard method for diagnosis for those parasite infections is stool examination to detect parasite eggs. However, the method has low sensitivity, and eggs of O. viverrini and C. sinensis are difficult to distinguish from each other and from those of some other trematodes. Here, we report a multiplex real-time PCR coupled with high resolution melting (HRM) analysis for the differentiation of O. viverrini and C. sinensis eggs in fecal samples. Using 2 pairs of species-specific primers, DNA sequences from a portion of the mitochondrial NADH dehydrogenase subunit 2 (nad 2) gene, were amplified to generate 209 and 165 bp products for O. viverrini and C. sinensis, respectively. The distinct characteristics of HRM patterns were analyzed, and the melting temperatures peaked at $82.4{\pm}0.09^{\circ}C$ and $85.9{\pm}0.08^{\circ}C$ for O. viverrini and C. sinensis, respectively. This technique was able to detect as few as 1 egg of O. viverrini and 2 eggs of C. sinensis in a 150 mg fecal sample, which is equivalent to 7 and 14 eggs per gram of feces, respectively. The method is species-specific, rapid, simple, and does not require fluorescent probes or post-PCR processing for discrimination of eggs of the 2 species. It offers a new tool for differentiation and detection of Asian liver fluke infections in stool specimens.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.108-126
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• 2013

Recently, it becomes essential for firms or nations to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage. Particularly, the mobile communications industry is characterized by rapid advance and wide application of its technology and thus identifying emerging technologies is more important in the industry than in others. Nevertheless, few attempts have been made to explore its emerging technologies. Therefore, this research aims to develop a methodology to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies for 2020 in the industry. For this purpose, firstly, we focused the key issues in the future targeting 2020 and identified user needs relating to them. Then, candidates of emerging technologies were defined from a set of technologies to meet the needs, for which technological and economic feasibility is assessed to determine their priorities. Finally, the top ten most important technologies were selected and verified. This research is distinct from the previous studies in that it takes a market-pull approach instead of a technology-push approach. The research results are expected to provide valuable information to support strategy- and policy-makings in the mobile communications industry.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Proceedings of the Korean Magnestics Society Conference
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• 2014.05a
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• pp.148-148
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• 2014

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.298-302
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• 2006

Driver electronics for emerging display technologies are presented for OLED's, microdisplays, electrophoretic displays & bi-stable LCD's. Key factors for commercialization of these technologies are derived from the experience of the LCD's, including driver IC designs, wafer and assembly processes & applications.

• Proceedings of the Korean Magnestics Society Conference
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• 2017.05a
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• pp.46-47
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• 2017

• Proceedings of the Korean Magnestics Society Conference
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• 2014.11a
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• pp.50-50
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• 2014

• Proceedings of the Korean Magnestics Society Conference
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• 2014.11a
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• pp.55-55
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• 2014