• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.362-370
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• 2013

In this paper, we propose a novel optical implementation of a 3DES algorithm based on dual XOR logic operations for a cryptographic system. In the schematic architecture, the optical 3DES system consists of dual XOR logic operations, where XOR logic operation is implemented by using a free-space interconnected optical logic gate method. The main point in the proposed 3DES method is to make a higher secure cryptosystem, which is acquired by encrypting an individual private key separately, and this encrypted private key is used to decrypt the plain text from the cipher text. Schematically, the proposed optical configuration of this cryptosystem can be used for the decryption process as well. The major advantage of this optical method is that vast 2-D data can be processed in parallel very quickly regardless of data size. The proposed scheme can be applied to watermark authentication and can also be applied to the OTP encryption if every different private key is created and used for encryption only once. When a security key has data of $512{\times}256$ pixels in size, our proposed method performs 2,048 DES blocks or 1,024 3DES blocks cipher in this paper. Besides, because the key length is equal to $512{\times}256$ bits, $2^{512{\times}256}$ attempts are required to find the correct key. Numerical simulations show the results to be carried out encryption and decryption successfully with the proposed 3DES algorithm.

• Journal of Information Management
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• v.41 no.4
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• pp.69-91
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• 2010

Libraries are encountering hostile conditions around journal licensing such as limited budget, the high price of packages, and vendor-led negotiation. They need to collect and analyze usage data of electronic journals to develop electronic journal collection appropriate for their own circumstances. The purpose of this study is to suggest an practical guideline for librarians' analysis of electronic journal usage statistics. For this, the study reviewed related previous studies and examined current state on usage statistics provided from COUNTER release 3 compliant vendors. Finally this study proposed five core statistics including full-text article request per journal, journal using rate, price per full-text article request, most use group, and low use group, and further discussed how to use them effectively for the electronic journal management.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.13-18
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• 2019

In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.171-176
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• 2022

With the recent development of deep learning technology, the areas of recommendation systems have also diversified. This paper studied algorithms to improve the learning rate and studied the significance results according to words through comparison with the performance characteristics of the Word2Vec model. The problem recommendation algorithm was implemented with the values expressed through the reflection of meaning and similarity test between texts, which are characteristics of the Word2Vec model. Through Word2Vec's learning results, problem recommendations were conducted using text similarity values, and problems with high similarity can be recommended. In the experimental process, it was seen that the accuracy decreased with the quantitative amount of data, and it was confirmed that the larger the amount of data in the data set, the higher the accuracy.

• Journal of Korea Trade
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• v.25 no.2
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• pp.22-45
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• 2021

Purpose - This study aims to identify new attributes by analyzing reviews conducted by global automaker customers and to examine the influence of these attributes on satisfaction ratings in the U.S. automobile sales market. The present study used J.D. Power for customer responses, which is the largest online review site in the USA. Design/methodology - Automobile customer reviews are valid data available to analyze the brand personality of the automaker. This study collected 2,998 survey responses from automobile companies in the U.S. automobile sales market. Keyword analysis, topic modeling, and the multiple regression analysis were used to analyze the data. Findings - Using topic modeling, the author analyzed 2,998 responses of the U.S. automobile brands. As a result, Topic 1 (Competence), Topic 5 (Sincerity), and Topic 6 (Prestige) attributes had positive effects, and Topic 2 (Sophistication) had a negative effect on overall customer responses. Topic 4 (Conspicuousness) did not have any statistical effect on this research. Topic 1, Topic 5, and Topic 6 factors also show the importance of buying factors. This present study has contributed to identifying a new attribute, personality. These findings will help global automakers better understand the impacts of Topic 1, Topic 5, and Topic 6 on purchasing a car. Originality/value - Contrary to a traditional approach to brand analysis using questionnaire survey methods, this study analyzed customer reviews using text mining. This study is timely research since a big data analysis is employed in order to identify direct responses to customers in the future.

• Child Health Nursing Research
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• v.29 no.3
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• pp.182-194
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• 2023

Purpose: This study analyzed research trends in infant and toddler rearing behavior among family caregivers over a 10-year period (2010-2021). Methods: Text network analysis and topic modeling were employed on data collected from relevant papers, following the extraction and refinement of semantic morphemes. A semantic-centered network was constructed by extracting words from 2,613 English-language abstracts. Data analysis was performed using NetMiner 4.5.0. Results: Frequency analysis, degree centrality, and eigenvector centrality all revealed the terms ''scale," ''program," and ''education" among the top 10 keywords associated with infant and toddler rearing behaviors among family caregivers. The keywords extracted from the analysis were divided into two clusters through cohesion analysis. Additionally, they were classified into two topic groups using topic modeling: "program and evaluation" (64.37%) and "caregivers' role and competency in child development" (35.63%). Conclusion: The roles and competencies of family caregivers are essential for the development of infants and toddlers. Intervention programs and evaluations are necessary to improve rearing behaviors. Future research should determine the role of nurses in supporting family caregivers. Additionally, it should facilitate the development of nursing strategies and intervention programs to promote positive rearing practices.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.331-339
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• 2008

This paper presents the development of certain highly efficient and accurate system for producing animation key data for 3D lip-synch animation. The system developed herein extracts korean phonemes from sound and text data automatically and then computes animation key data using the segmented phonemes. This animation key data is used for 3D lip-synch animation system developed herein as well as commercial 3D facial animation system. The conventional 3D lip-synch animation system segments the sound data into the phonemes based on English phonemic system and produces the lip-synch animation key data using the segmented phoneme. A drawback to this method is that it produces the unnatural animation for Korean contents. Another problem is that this method needs the manual supplementary work. In this paper, we propose the 3D lip-synch animation system that can segment the sound and text data into the phonemes automatically based on Korean phonemic system and produce the natural lip-synch animation using the segmented phonemes.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1145-1161
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• 2004

The purpose of this research is to establish a method for the construction of a multimedia electronic dictionary system by integrating the media data available from linguistic resources on the Internet. As the result of this study, existing text-oriented electronic dictionary systems can be developed into multimedia lexical systems with greater efficiency and effectiveness. A method is proposed to integrate the media data of linguistic resources on the Internet by a web browser. In the proposed method, a web browser carries out all the work related to integration of media data, and it does not need a dedicated server system. The system constructed by our web browser environment integrates text, image, and voice sources, and also can produce moving pictures. Each media is associated with the meaning of data so that the data integration and movement may be specified in the associations. SMIL documents are generated by analyzing the meaning of each data unit and they are executed in a web browser. The proposed system can be operated without a dedicated server system. And also, the system saves storage space by sharing the each media data distributed on the Internet, and makes it easier to update data.

• Journal of The Korean Association For Science Education
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• v.22 no.3
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• pp.595-603
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• 2002

The influences of the characteristics of anomalous data on cognitive conflict and conceptual change in learning density were investigated. The subjects were 416 seventh graders. First, the Group Assessment of Logical Thinking and a preconception test were administered. A questionnaire on the responses to anomalous data was then administered. In the questionnaire, four types of anomalous data varying presentation type (movie/text) and authority level (high/low) were randomly presented. After a computer-assisted instruction on density, a conception test was administered. The results indicated that anomalous data presented in movie type significantly induced more cognitive conflict than that in text type. Students presented with anomalous data of high authority scored higher in the conception test than those of low authority. There were no significant interactions between the characteristics of anomalous data and students' logical thinking ability in the scores of both the cognitive conflict and the conception test.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.257-264
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• 2019

Recently, deep neural network based approaches have shown a good performance for various fields of natural language processing. A huge amount of training data is essential for building a deep neural network model. However, collecting a large size of training data is a costly and time-consuming job. A data augmentation is one of the solutions to this problem. The data augmentation of text data is more difficult than that of image data because texts consist of tokens with discrete values. Generative adversarial networks (GANs) are widely used for image generation. In this work, we generate sentimental texts by using one of the GANs, CS-GAN model that has a discriminator as well as a classifier. We evaluate the usefulness of generated sentimental texts according to various measurements. CS-GAN model not only can generate texts with more diversity but also can improve the performance of its classifier.