• ALGAE
• /
• v.34 no.2
• /
• pp.111-126
• /
• 2019

The phototrophic dinoflagellate Biecheleriopsis adriatica is a small suessioid species characterized by a fragile thin wall. Although the morphology of this dinoflagellate is well established, there is currently little information available on its distribution and the environmental factors that influence this distribution. Thus, to investigate the spatial and seasonal distributions of the vegetative cells of B. adriatica in Korean waters, surface water samples were collected on a seasonal basis from 28 stations in the East, West, and South Sea of Korea and Jeju Island from April 2015 to October 2018, and abundances of the vegetative cells of B. adriatica were quantified using quantitative real-time polymerase chain reactions, for which we developed the species-specific primer and probe set. Simultaneously, major environmental parameters, including temperature, salinity, nutrient concentrations, and dissolved oxygen concentrations were measured. The vegetative cells of B. adriatica were detected at 20 of the 28 sampling stations: 19 stations in summer and 6 in autumn, although from no stations in either spring or winter. The ranges of water temperature and salinity at sites where this species was detected were $17.7-26.4^{\circ}C$ and 9.9-34.3, respectively, whereas those of nitrate and phosphate concentrations were not detectable-96.2 and $0.18-2.66{\mu}M$, respectively. Thus, the sites at which this species is found are characterized by a narrow range of temperature, but wide ranges of salinity and concentrations of nitrate and phosphate. The highest abundance of the vegetative cells of B. adriatica was $41.7cells\;mL^{-1}$, which was recorded in Jinhae Bay in July 2018. In Jinhae Bay, the abundance of vegetative cells was significantly positively correlated with the concentration of nitrate, but was negatively correlated with salinity. On the basis of these findings, it appears that the abundance of B. adriatica vegetative cells shows strong seasonality, and in Jinhae Bay, could be affected by the concentrations of nitrate.

• Journal of Digital Convergence
• /
• v.17 no.5
• /
• pp.137-143
• /
• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.

• The Journal of the Korea Contents Association
• /
• v.19 no.5
• /
• pp.381-388
• /
• 2019

In South Korea nowadays, Among the married immigrant women in Korea, the proportion of long-term residents living in Korea for more than 10 years is increasing continuously(48%), while the proportion of short-term residents who are under 5 years is decreasing(16%). However, Korean language education and related research in the Marriage and Immigration Women's Center are still focused on the initial immigrants. Therefore, we should classify married immigrant women according to their stay time in Korea, so that Korean language education and teaching materials need to be more diversified. This study focuses on married immigrant women with intermediate and advanced Korean proficiency and chooses a catalogue of Chinese characters idioms to explore the possibility and educational value of using Chinese characters Idioms in Korean education. According to the research results, Chinese characters idiom education can help married immigrant women in Korean language learning and information acquisition, interpersonal relationships and life attitudes, cultural understanding and social adaptation, child rearing and learning guidance. This is the important part of Korean language education that needs to be guided by married immigrant women. Based on this, 130 Chinese characters idioms in Korean language education and textbook development centered on married immigrant women were selected and catalogue edited in four stages. It is hoped that the results of this study will serve as a reference for Korean language education research and textbook development for married immigrant women in the future.

• Journal of the Korea Convergence Society
• /
• v.10 no.5
• /
• pp.203-211
• /
• 2019

This study is to examine the impact of spatial characteristics of cities on homicide based on spatial econometric model. It selects housing types, racial heterogeneity, residential instability, overcrowding, commercial area, rate of 15 to 29 ages, and rate of the elderly as variables for spatial characteristics of cities. This study employs spatial regression analysis applying the spatial error model to analyze the data from 229 locals collected from Korean Statistical Information Service and Statistical Year Book of local governments. As a result, it shows that homicide has close relationships with apartment and multi-housing as housing types, racial heterogeneity, residential instability, and overcrowding, but not with the commercial area, rate of 15 to 29 ages, and rate of the elderly. The study contributes to expanding understanding and explanation on the causes of homicide focusing on social-structure approach for criminology by analyzing a more advanced model in applying variables than one of existing literature. This study suggests follow-up research on homicide based on both social-behavior approach and social-structure approach in the near future for the development of criminological theory.

• Journal of Convergence for Information Technology
• /
• v.9 no.5
• /
• pp.158-164
• /
• 2019

Recently many studies to reduce the noise of dental hand piece which generate inevitably mechanical sound to offend to the ear of a patient have been spotlighted. Generally, methods of adding a sound absorbing material inside the exhaust valve, air pump of machine or automobile are widely reported as optimal way to reduce the mechanical noise. In this paper we studied a new UV laser aided manufacturing of micro-porous structure of EPP substrate and applied dental hand piece to improve the efficiency of sound absorption. A lot of micro-sized pores were fabricated with UV laser processing on the surface of sliced EPP substrate. From fundamental experiments, more high-performance of micro-porous EPP substrate has finally demonstrated for sound-absorbing structure of the micro muffler inside dental hand piece, which actually has the excellent potential to apply a lot of potable machine.

• Korean Journal of Breeding Science
• /
• v.50 no.4
• /
• pp.364-377
• /
• 2018

Hexaploid wheat (common wheat/bread wheat) is one of the most important cereal crops in the world and a model for research of an allopolyploid plant with a large, highly repetitive genome. In the heritability of agronomic traits, variation in gene presence/absence plays an important role. However, there have been relatively few studies on the variation in gene presence/absence in crop species, including common wheat. Recently, a reference genome sequence of common wheat has been fully annotated and published. In addition, advanced next-generation sequencing (NGS) technology provides high quality genome sequences with continually decreasing NGS prices, thereby dawning full-scale wheat functional genomic studies in other crops as well as common wheat, in spite of their large and complex genomes. In this review, we provide information about the available tools and methodologies for wheat functional genomics research supported by NGS technology. The use of the NGS and functional genomics technology is expected to be a powerful strategy to select elite lines for a number of germplasms.

• Journal of Broadcast Engineering
• /
• v.26 no.5
• /
• pp.500-507
• /
• 2021

The virtual reality industry has an opportunity to take another leap forward with the surge in demand for non-face-to-face content and interest in the metaverse after Covid-19. Therefore, in order to popularize virtual reality content along with this trend, high-quality content production and storytelling research suitable for the characteristics of virtual reality should be continuously conducted. In order for content to which virtual reality characteristics are applied to be effectively produced through user feedback, a quantitative index that can evaluate the content is needed. In this study, the process of viewing virtual reality contents was analyzed and head movement was set as a quantitative indicator. Afterwards, the experimenter watched five animations and analyzed the correlation between recorded head movement information and immersion. As a result of the analysis, high immersion was shown when the head movement speed was relatively slow, and it was found that the head movement speed can be used significantly as an index indicating the degree of content immersion. The result derived in this way can be used as a quantitative indicator that can verify the validity of the storytelling method applied after the prototype is produced when the creator creates virtual reality content. This method can improve the quality of content by quickly identifying the problems of the proposed storytelling method and suggesting a better method. This study aims to contribute to the production of high-quality virtual reality content and the popularization of virtual reality content as a basic research to analyze immersion based on the quantitative indicator of head movement speed.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.531-540
• /
• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.3
• /
• pp.73-86
• /
• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• Journal of the Korea Convergence Society
• /
• v.11 no.12
• /
• pp.1-13
• /
• 2020

With the advent of an intelligent information society, research toward artificial intelligence education was conducted. In previous studies, the subject of research is biased, and studies that analyze attitudes toward artificial intelligence are insufficient. So, in this study developed a test tool to measure the artificial intelligence of high school students and analyze their attitudes toward artificial intelligence. To develop the test tool, 229 high school students completed a preliminary test, of which the results were analyzed via exploratory factor analysis. To analyze the students' attitudes toward artificial intelligence, the resulting test tool was applied to 481 high school students, and their test results were analyzed according to factors. From the study's results, there was no difference according to gender in the students' attitudes toward artificial intelligence, but there was a significant difference per grade. In addition, there was a significant difference in attitudes according to artificial intelligence-related experiences: the high school students who had direct and indirect experience with artificial intelligence, programming, and more frequently used it had more positive attitudes toward artificial intelligence than students without this experience. However, artificial intelligence education experience negatively influenced the students' attitudes toward artificial intelligence. Overall, the higher their interest in artificial intelligence, the more positive the high school students' attitudes toward artificial intelligence.