• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.817-825
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• 2013

The UHDTV system, which provides realistic service with ultra-high definite video and multi-channel audio, has been studied as a next generation broadcasting service. Since the conventional digital terrestrial transmission system is not capable to cover the increased transmission data rate of the UHDTV service, there are great necessity of researches about increase of data rate. Accordingly, the researches has been studied to increase the transmission data rate of the DVB-T2 system using dual-polarized MIMO technique and high order modulation. In order to optimize the MIMO DVB-T2 system where irregular LDPC codes are used, it is necessary to study the design of the bit mapper that matches the LDPC code and QAM symbols in MIMO channel. However, the research related to the design of the bit mapper has been limited to the SISO system. Therefore, this paper defines a new parameter that indicates the VND distribution of MIMO DVB-T2 system and performs the performance analysis according to the parameter which will be helpful for designing a MIMO bit mapper.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.

• Journal of Service Research and Studies
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• v.6 no.3
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• pp.29-40
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• 2016

Since the late 20th century, there has been much effort to improve the market value of media contents which are commercialized in a digital format, by fusing digital data of video, audio, numerals, characters with IT technology together. Then by what criteria and methodologies could the market value for the drama "Sons of the Sun" or the animated film 'Frozen', often referred to in the meida, be estimated? In the circumstances there has been little or no research on the valuation framework of media contents and the status of their valuation system development to date, we propose a practical valuation models for various purposes such as contents trading, review of investment adequacy, etc., by formalizing and presenting a contents valuation framework for the four types of media of movies, online games, and broadcasting commercials, and animations. Therefore, we develope computational methods of cash flows which includes production cost by media content types, provide reference databases associated with key variables of valuation (economic life cycle, discount rates, contents contribution and royalty rates), and finally propose the valuation framework of media contents based on both income approach and relief-from-royalty method which has been applied to valuation of intangible assets so far.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.2
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• pp.69-87
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• 2019

As the discussions on sharing research data prevail by the chance of the inauguration of the International Open Data Charter, research support organizations in the United States, the United Kingdom, and Japan are encouraging researchers to deposit their findings in a credible repository. Humanities and social sciences field, in which research data sharing culture and storage infrastructure are immature compared to life science and natural science, also needs to establish and operate a reliable storage infrastructure to guarantee the continuous access and utilization of data. This study analyzed the overall operational status of 305 subject repositories registered in re3data for the humanities and social sciences and clustered them according to the operational level using 5 indicators. As a result, 70% of the population were identified as universal clusters, and 20% of the excellent cluster was found to have the largest number of linguistic fields and the German-operated. In addition, this study confirmed through correspondence analysis that there is a relation between the sub-theme fields of humanities and social sciences and the types of data to be archived. The history and art domians are related to images, and social studies are related to statistical data. Linguistics has also been analyzed to be related to audio, plain text, and code.

• The Korean Journal of Archival Studies
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• no.30
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• pp.89-123
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• 2011

Archival materials in film archives is a memories and archival documents of human which is generated from cultural activities of human being, and provided long-term relevant information. However, it is different general public audio-visual records because main purpose of representing culture to create the contents of private sector rather than evidence of the factual information of public service activities. Therefore, should determine the description principle and rule in order to reflect specific physical, intellectual characteristics. So as to control the description, that is need in the textual standards to base the specific purposes and rules thus analyzed the international description standards as Dublin Core, ISAD(G), FIAF Cataloguing Rules For Film Archives. As a result, more effectively to describe archival materials in film archives required significant modifications in the organizations of the areas and the elements. This study argues that first, to divide existence the concept and the reality (work/item) of archival materials in film archives. Second, to need understanding and indicating their content, context, structure. Third, to establish of the areas and the elements including a characteristic of it. The final suggestion organizes separately to 6th and 8th areas, 22th and 25th elements in two parts. This conclusion does not prepare to refer the status and/or policy of a particular film arhicve, can be set accordingly to a specific elements or sub-elements by the film archives.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.473-481
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• 2020

Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.18-25
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• 2017

In computer science, an encoding is a standardization of converting information to one format for audio, video or text. Therefore, the encoding information of the data should be known to open and read it and there are algorithms detecting encoder of the data. However, some informations of data could be disappeared by packet loss when transmitted on network, especially, if the data is snatched by packet sniffing or eavesdropping from wireless communications. In this paper, we improve the performance of encoding detection algorithm of 'uchardet' program for multi-byte encoded data with errors based on bit-shift algorithm. To simulate the performance, we generated Korean and Japanese text data with errors that is removed some random bits at random positions. Then the detection algorithm are tested using the data and 'uchardet-bitshift' showed better performance than 'uchardet'. When Korean texts are used, 'uchardet' could detect perfectly with ≤0.005% errors but it showed 0% detection rate with ≥1% errors while 'uchardet-bitshift' detected perfectly with ≤0.05% errors and it showed correct detection cases with ≥1% errors. Japanese texts with errors tend to report falsely as Chinese encoding because Japanese texts include lots of Chinese characters. As a results, we improved encoding detection algorithms by applying bit shift operation.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.1
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• pp.23-38
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• 2009

The purpose of this study was to suggest the collection codes and simplification of call numbers for children's easy access to the children's materials. The classification schemes, author tables, expansion of classification schemes, collections codes, classification numbers used in domestic and foreign children's libraries were surveyed through questionnaires and interviewing with librarians. As a result, in foreign children's libraries, it was common practice to shelve children's materials separately into various collections and sub-collections, to mark the spine with collection code and the lead characters of the author's last name, and not to stick with their classification scheme when it comes to highly circulated children's materials such as fiction, picture book, biographies and so on. Also, in domestic children's libraries, it was found that a collection code was used a few and each call number was almost assigned by KDC number. Therefore, it was suggested that the types and codes of collection and sub-collection were divided as non-fiction, fiction, fiction/mystery, fiction/science fiction, picture book, cartoon, language, folks and fairy tales, biographies, legend, concept book, holiday, award, dinosaur, insect, DIY, transportation, tall book, pop-up, story book, board book, reference, magazine, series, new book, video, and audio and were easily expanded by combining age tables or fiction genre. Also, new simplifying methods of building call numbers with collection codes were suggested.