• Journal of Elementary Mathematics Education in Korea
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• v.21 no.1
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• pp.73-92
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• 2017

A table as an effective arrangement tool of a set of data has not been focused on as a single research subject despite of the fact that the table has been clearly one of learning and teaching elements of national math curriculum for a long time. I hope this article gets to be a starting point for future studies of tables. For this, the Finland elementary mathematics textbooks which use tables so often for many various purpose are chosen and analysed. As a result, it confirms that tables can be practical tools for developing different mathematical ideas in mathematics textbooks. Its applicable area is not limited on statistics but numbers and operations, geometry, measurement, ratio and rate. In addition, some ideas of the outlook, the size and dimension of tables, and the context of datum and etc are induced from the Finland elementary mathematics textbooks.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• Cross-Cultural Studies
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• v.27
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• pp.415-434
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• 2012

The Hanja used in Korean are traditional Chinese characters, but what Chinese people use now is simplified characters. So, there are differences in pronunciation and meaning between the characters used by Korean and Chinese. More than 70% of the Korean language vocabulary derived from or were influenced by hanja. For the inheritance and development of traditional culture,and for the communication among countries of the Chinese characters cultural circle in Northeast Asia, should we build up an authentic Chinese education system. But the government hasn't pay much attention to this work, and the government's policy can't implement the efficient education. Consequently, in these days, there are more and more Korean people who are functionally illiterate in Chinese. Recently, proficiency tests of Chinese characters are expected to promote the development of Chinese education. But, most Koreans' motives for Chinese study are usually to pass the college entrance exam or to compete for jobs. However, after passing the test, the motive for studying gradually fade away. It is the basic problem faced by Korean Chinese character education. Since the 1950s, various character education methods have been studied in China, the research results were appliedin their textbooks and other materials. Therefore, a well-organized and efficient learning-by-step education system was built up. At present, China's literacy education in the textbooks utilizes a range of methods including revisional centralized and distributed. Unfortunately, there is still one shortcoming worthy of concerns: how to solve the problems due to the simplification of traditional Chinese characters? Is it possible to revive traditional Chinese characters? Before adopting the results of research on China's literacy education and applying them to our character education, we should consider our specific situation carefully. Adopting the research results with cautious review and objective criticism should have a positive impact on Korean Chinese character education.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.531-539
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• 2019

This paper proposes the training features for malware family analysis and analyzes the multi-classification performance of ensemble models. We construct training data by extracting API and DLL information from malware executables and use Random Forest and XGBoost algorithms which are based on decision tree. API, API-DLL, and DLL-CM features for malware detection and family classification are proposed by analyzing frequently used API and DLL information from malware and converting high-dimensional features to low-dimensional features. The proposed feature selection method provides the advantages of data dimension reduction and fast learning. In performance comparison, the malware detection rate is 93.0% for Random Forest, the accuracy of malware family dataset is 92.0% for XGBoost, and the false positive rate of malware family dataset including benign is about 3.5% for Random Forest and XGBoost.

• Journal of Platform Technology
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• v.9 no.3
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• pp.63-69
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• 2021

Limited materials to make coins for countries and designs suitable for hand-carry make the shape, size, and color of coins similar. This similarity makes that it is difficult for visitors to identify each country's coins. To solve this problem, we propose the coin classification method using CNN effective to image processing. In our coin identification method, we collect the training data by using web crawling and use OpenCV for preprocessing. After preprocessing, we extract features from an image by using three CNN layers and classify coins by using two fully connected network layers. To show that our model designed in this paper is effective for coin classification, we evaluate our model using eight different coin types. From our experimental results, the accuracy for coin classification is about 99.5%.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.239-245
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• 2021

Due to the fourth industrial revolution and the Corona19, the availability of digital devices such as kiosks is a matter directly related to survival for older adults with digital divide. This paper analyzes the problems of existing information service education for older adults and proposes an IT education strategy tailored to aging and life cycle of older adults. The proposed in this study is an educational application-based IT training method that supports repetitive learning regardless of time and place, developing kiosk function as a functional game-type educational application and experimenting with post-training effectiveness. The research method proposed UI usability evaluation frame for older adults, and developed educational applications based on proposed evaluation frame, and conducted kiosk education. As a result of the experiment, the mission success rate after using the IT application was 80.6%, which is a 55.1%P improvement compared to the pre-use(25.5%). This study confirmed that the proposed education for older adults is a way to overcome the limitations of existing IT education in the current situation.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.4
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• pp.7-34
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• 2021

The purpose of the study was to explore the uses and gratification of social media among first-year student groups at a satellite campus of a public university in Ghana. The study employed a descriptive survey design. The study involved all 1061 first-year university students in six academic departments of the College. A total of 680 (64%) participants returned validly completed copies of the questionnaire. Descriptive statistics and thematic analysis were employed for data analysis. The findings indicate that WhatsApp was the most popular application for social media groups, while a need for information-sharing, peer-tutoring and learning, and finding and keeping friends were the primary motivations for joining social media groups. First-year students are involved mainly in reactive activities, as most engage when solving an academic assignment through group discussions. Though challenges persist, such as posting of unwanted images, inadequate participation, and ineffective and irrelevant communication, most are willing to continue their social media groups' membership in the long term. This study provides valuable insight into transitioning students' lived experiences on social media from the group perspective. These insights are valuable conceptually and practically to academic counsellors, librarians and student affairs officers who are expected to provide on-going education on (social) media literacy to first-year students to enhance the adjustment process. The study is the first of its kind in Ghana that investigates social media group participants' exit intentions.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.328-342
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• 2022

The Internet of Things (IoT) is a technology that offers lucrative services in various industries to facilitate human communities. Important information on people and their surroundings has been gathered to ensure the availability of these services. This data is vulnerable to cybersecurity since it is sent over the internet and kept in third-party databases. Implementation of data encryption is an integral approach for IoT device designers to protect IoT data. For a variety of reasons, IoT device designers have been unable to discover appropriate encryption to use. The static support provided by research and concerned organizations to assist designers in picking appropriate encryption costs a significant amount of time and effort. IoTES is a web app that uses machine language to address a lack of support from researchers and organizations, as ML has been shown to improve data-driven human decision-making. IoTES still has some weaknesses, which are highlighted in this research. To improve the support, these shortcomings must be addressed. This study proposes the "IoTES with Security" model by adding support for the security level provided by the encryption algorithm to the traditional IoTES model. We evaluated our technique for encryption algorithms with available security levels and compared the accuracy of our model with traditional IoTES. Our model improves IoTES by helping users make security-oriented decisions while choosing the appropriate algorithm for their IoT data.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.91-97
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• 2021

This paper uses a data extension technique originally designed for the rule refinement problem to handling incomplete data. This technique is characterized in that each event can have a weight indicating importance, and each variable can be expressed as a probability value. Since the key problem in this paper is to find the probability that is closest to the missing value and replace the missing value with the probability, three different algorithms are used to find the probability for the missing value and then store it in this data structure format. And, after learning to classify each information area with the SVM classification algorithm for evaluation of each probability structure, it compares with the original information and measures how much they match each other. The three algorithms for the imputation probability of the missing value use the same data structure, but have different characteristics in the approach method, so it is expected that it can be used for various purposes depending on the application field.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.221-229
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• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.