• Journal of the Korean earth science society
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• v.42 no.6
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• pp.717-733
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• 2021

This study is aimed to provide basic data to set the direction of polar literacy education and to raise awareness of the importance of polar research. Elementary, middle, and high school students' perception of the polar region was examined in terms of current status of polar information, impression regarding polar regions, and awareness of related issues. The study included 975 students from nine elementary, middle, and high schools, who responded to 16 questions, including close-ended and open-ended items. The results suggest that students had more experiences regarding the polar region on audiovisual media, but relatively limited learning experiences in school education. The impression they had of the polar region was confined to the monotonous image of a polar bear in crisis, following the melting of the glacier due to global warming. The students formed powerful images by combining scenes they saw in audiovisual media with emotions. In terms of recognizing problems in the polar region, the students were generally interested in creatures, natural environment, and climate change, but their interests varied depending on their school level and their own career path. The students highly valued the scientist's status as agents to address the problems facing the region, and gave priority to global citizenship values rather than practical standards. Based on the results, we suggest the following: introducing and systematizing content focusing on the polar region in the school curriculum, providing a differentiated learning experience through cooperation between scientists and educators, establishing polar literacy based on concepts that are relevant to various subjects, earth system-centered learning approach, setting the direction for follow-up studies and the need for science education that incorporates diverse values.

• Smart Media Journal
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• v.11 no.5
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• pp.17-25
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• 2022

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

• Smart Media Journal
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• v.12 no.10
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• pp.71-84
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• 2023

Paralichthys olivaceus accounts for a large proportion, accounting for more than half of Korea's aquaculture industry. However, about 25-30% of the total breeding volume throughout the year occurs due to diseases, which has a very bad impact on the economic feasibility of fish farms. For the economic growth of Paralichthys olivaceus farms, it is necessary to quickly and accurately diagnose disease symptoms by automating the diagnosis of Paralichthys olivaceus diseases. In this study, we create training data using innovative data collection methods, refining data algorithms, and techniques for partitioning dataset, and compare the Paralichthys olivaceus disease symptom detection performance of four object detection deep learning models(such as YOLOv8, Swin, Vitdet, MvitV2). The experimental findings indicate that the YOLOv8 model demonstrates superiority in terms of average detection rate (mAP) and Estimated Time of Arrival (ETA). If the performance of the AI model proposed in this study is verified, Paralichthys olivaceus farms can diagnose disease symptoms in real time, and it is expected that the productivity of the farm will be greatly improved by rapid preventive measures according to the diagnosis results.

• Smart Media Journal
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• v.12 no.8
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• pp.45-59
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• 2023

Users who want to experience the metaverse for tourism are exposed to strategic planning in space for the purpose of cultural content. In addition, users learn integrated cultural content in the process of proceeding according to the virtual environment. and Along with the meaning of time and space, users will experience space-telling. It is important to induce interest from the beginning of the experience to continue the experience. However, obstacles arise in this process. This is because developers should promote connections with new information to users who do not have sufficient prior knowledge and only have keywords of interest. Therefore, efficient design methods to enhance interest should be studied in advance. But so far, there has been no research on how to systematically design prior organizers to induce interest in virtual space. This study is an interest-inducing design method that occurs in the process of developing the meaning of virtual space and storytelling of cultural content, and can be seen as a basic study using conceptual guidance-based prior organizer education and learning techniques. First, virtual space elements and human behavior theories were considered. Subsequently, five representative examples of previous organizers currently used were explored, and redesigned and proposed based on a conceptual map for information access and delivery purposes. Through this research process, it was possible to confirm that spatial attributes and cognitive interest elements were effectively transmitted to meaningful learning leading to storytelling learning and elements of service design design method through conceptual guidance.

• Information Systems Review
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• v.24 no.1
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• pp.157-181
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• 2022

As competition in the airline industry intensifies, effective airline service quality evaluation has become one of the main challenges. In particular, as big data analytics has been touted as a new research paradigm, new research on service quality measurement using online review analysis has been attempted. However, these studies do not use review titles for analysis, relyon supervised learning that requires a lot of human intervention in learning, and do not consider airline characteristics in classifying service quality dimensions.To overcome the limitations of existing studies, this study attempts to measure airlines service quality and to classify it into the AIRQUAL service quality dimension using online review text as well as title based on self-trainingand sentiment analysis. The results show the way of effective extracting service quality dimensions of AIRQUAL from online reviews, and find that each service quality dimension have a significant effect on service satisfaction. Furthermore, the effect of review title on service satisfaction is also found to be significant. This study sheds new light on service quality measurement in airline industry by using an advanced analytical approach to analyze effects of service quality on customer satisfaction. This study also helps managers who want to improve customer satisfaction by providing high quality service in airline industry.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.73-81
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• 2010

The main purpose of this study was to examine the effects of meta-cognition, learning flow and problem solving ability of the college engineering students on academic achievement. For this purpose, a total of 396 college engineering freshmen of the six different departments was chosen to conduct a survey. A hypothetical model was proposed, which was composed of meta-cognition, problem solving ability and learning flow as the prediction variables, and academic achievement as the outcome variables. The results of this study through multiple regression analysis showed that meta-cognition, learning flow and problem solving ability significantly influenced on the college engineering studnets' academic achievement. In addition, learning flow was used as a significant mediated variable in the relationships among meta-cognition, problem solving ability and academic achievement. Based on these study results, the above variables investigated in this study should be considered in the design and development of the college engineering courses that enable students to facilitate their problem-solving attitude and improve academic achievement.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.383-394
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• 2018

In this paper, we investigate image and video compression techniques based on deep learning which are actively studied recently. The deep learning based image compression technique inputs an image to be compressed in the deep neural network and extracts the latent vector recurrently or all at once and encodes it. In order to increase the image compression efficiency, the neural network is learned so that the encoded latent vector can be expressed with fewer bits while the quality of the reconstructed image is enhanced. These techniques can produce images of superior quality, especially at low bit rates compared to conventional image compression techniques. On the other hand, deep learning based video compression technology takes an approach to improve performance of the coding tools employed for existing video codecs rather than directly input and process the video to be compressed. The deep neural network technologies introduced in this paper replace the in-loop filter of the latest video codec or are used as an additional post-processing filter to improve the compression efficiency by improving the quality of the reconstructed image. Likewise, deep neural network techniques applied to intra prediction and encoding are used together with the existing intra prediction tool to improve the compression efficiency by increasing the prediction accuracy or adding a new intra coding process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.187-196
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• 2020

This is a single group pre-post study conducted to confirm the effectiveness of HIV/AIDS education for nursing students, imparted via video-learning methods. Study participants enrolled were 93 students in the 4th grade of the Department of Nursing at J-City V University. Data were collected from May 26 to June 16, 2020, and were analyzed using descriptive statistics, paired t-test, independent t-test, ANOVA, and Pearson's correlation coefficient using the SPSS WIN 23.0 program. Results of this study confirm improvements in HIV/AIDS knowledge and attitude after attending video-learning modules. However, when assessing the details of attitude, insufficient data was obtained for difference in attitude toward social stigma recognition. Therefore, numerous attempts are required for imparting educational contents and methods that will positively alter social stigma recognition. The results of this study prove that video lectures are a useful teaching and learning method to transform the knowledge and attitude of nursing students towards HIV/AIDS. We believe that results obtained are meaningful, and provide a basis for imparting education by utilizing different media, such as a video-learning module.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.22-33
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• 2010

The main purpose of this study was to develope a reflective journal and examine its effects on student's academic achievement and self-regulated learning strategies. For this study, 'a structured reflective journal' was designed through the steps of systems approach with the purpose of enhancing student's academic achievement and self-regulated learning strategies, especially meta-cognition and critical thinking. The reflective journal used in this study contained the constructive elements of (1) self-evaluation with 5 likert scale, (2) learning essay, (3) dialogue with peers, and (4) dialogue with professor. A total of 94 freshmen enrolled in one of two sections of the engineering courses(theory-based class and experiment and practice-based class) participated in the study for 8 weeks. A pre-test-post-test design was used to examine the effects of the application of reflective journal on student's achievement and self-regulated learning strategies. For the result, analysis of covariance was conducted to determine whether there were any academic achievement differences and self-regulated learning strategy differences. The results suggested that students were taking advantages of the reflective journal, and there were statistically significant differences in academic achievement in the experiment and practice-based class and self-regulated learning strategies in both classes.