• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.51-61
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• 2021

In the era of the 4th industrial revolution symbolized by the Internet of Things, big data and artificial intelligence, various embedded devices are increasing exponentially. These devices have communication functions despite their low specifications, so the possibility of personal information leakage is increasing, and security threats are also increasing. Embedded devices can have security issues at most levels, from hardware to services over the network. In addition, it is difficult to apply general security techniques because it has characteristics of resource constraints such as low specifications and low power, and the related technology has not been standardized. In this study, we present vulnerabilities and possible problems and considerations in applying SDN to embedded devices in consideration of structural characteristics and real-world discovered cases. This study presents vulnerabilities and possible problems and considerations when applying SDN to embedded devices. From a hardware perspective, we consider the problems of Wi-Fi chips and Bluetooth, the problems of open flow implementation, SDN controllers, and examples of structural properties. SDN separates the data plane and the control plane, and provides a standardized interface between the two, enabling efficient communication control. It can respond to the security limitations of existing network technologies that are difficult to respond to rapid changes.

• Phonetics and Speech Sciences
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• v.12 no.4
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• pp.63-71
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• 2020

Speech recognition is one of the areas actively commercialized using deep learning and machine learning techniques. However, the majority of speech recognition systems on the market are developed on data with limited diversity of speakers and tend to perform well on typical adult speakers only. This is because most of the speech recognition models are generally learned using a speech database obtained from adult males and females. This tends to cause problems in recognizing the speech of the elderly, children and people with dialects well. To solve these problems, it may be necessary to retain big database or to collect a data for applying a speaker adaptation. However, this paper proposes that a new end-to-end speech recognition method consists of an acoustic augmented recurrent encoder and a transformer decoder with linguistic prediction. The proposed method can bring about the reliable performance of acoustic and language models in limited data conditions. The proposed method was evaluated to recognize Korean elderly and children speech with limited amount of training data and showed the better performance compared of a conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.873-879
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• 2020

The importance of data as a core resource of the 4th industrial revolution is emerging, and companies illegally collect and use personal data. In the financial sector, active research is conducted to safely manage personal data and provide better services using blockchain, big data, and AI technology. In this paper, we propose a system that can safely manage personal data by using blockchain technology, which can be used without changing the existing system. The composition of this system consists of a blockchain, blockchain linkages, a service provider, and a user (i.e., an app). Blockchain can be used regardless of its type and form, and services are provided by classifying blockchains and services in the blockchain linkages. Service providers can access personal data only after requesting and receiving delegated permission from users. Existent MyData services store all data in a user's mobile phone, so information may get leaked due to jailbreaks or rooting. But in the proposed system, personal data are stored in blockchain so information leakage can be prevented. In the future, we will study ways to provide customized services using personal data stored in blockchain.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.47-53
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• 2021

With increasing interest in the 4th industrial revolution, data-driven scientific methodologies have developed. However, there are limitations of data collection in the real estate field of research. In addition, as the public becomes more knowledgeable about the real estate market, the qualitative sentiment comes to play a bigger role in the real estate market. Therefore, we propose a method to collect quantitative data that reflects sentiment using text mining and k-means algorithms, rather than the existing source data, and to predict the direction of housing index through artificial neural network learning based on the collected data. Data from 2012 to 2019 is set as the training period and 2020 as the prediction period. It is expected that this study will contribute to the utilization of scientific methods such as artificial neural networks rather than the use of the classical methodology for real estate market participants in their decision making process.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.744-757
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• 2021

This study aims to develop a bodice and a jacket in 3D of the late 19th to early 20th based on the pattern drafting book of Gordon S. S., which contains body measurement method and pattern drafting system. The findings of this research are as follows. First, female tops of the late 19th to early 20th century are categorized as outer, jacket, vest, and bodice. Of these, this study highlights the jacket, which can be divided into 4 types: 4 kinds of basic jacket, 2 kinds of riding jacket, bolero jacket, and newmarket jacket. Second, by referring to Gordon's pattern drafting system and book, a bodice was developed in 3D format based on the adherence to the following steps: analysis of the pattern drafting system, pattern drafting, 3D virtual simulation, 3D virtual fitting analysis, and the pattern correction. A bodice pattern corrected by 3D virtual clothing simulation results was proposed. Last, a basic sleeve and collar pattern for a basic jacket was drafted, which was followed by the correction and transformation of the bodice pattern. The jacket developed shows great fit except for the issues at the armhole line and shoulder, which were caused by the unique shape of the sleeves(big sleeve head) of the time. The study attempted to develop the past costumes in 3D, providing the basis for interdisciplinary research in the field of fashion history field and suggesting a new approach for the virtual restoration of costumes. Future studies should target to 3D virtual simulation in accordance to the 3D avatar pose in the developed virtual costume.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.653-658
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• 2021

Convergence of ICT technology and various industry have been proliferated. It makes human life affluent pulling existing industry paradigm down while they do not realize. Also, it impacts on personal life and becomes a driving force which strengthen the state level and its competitiveness. Complexity is increasing, knowledge is expanding and ICT technology is evolving in the present industrial society. Thus, new business model is being created, established business without competitiveness is eliminated and new ecosystem is constructed for industry change or creation. The new business and its competitive order driving in current convergence environment is apt to be exposed to uncertainty risk. These changes promote the collapse of existing industry or create new business models. There are digital transformation and ICT convergence in the center of the changes. The change of society and industry caused by this phenomenon will be analyzed. Also, development direction, strategy and execution method for securing industry competitiveness of ICT convergence will be researched.

• Food Science and Industry
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• v.54 no.4
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• pp.293-300
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• 2021

Food safety accidents have been increasing by 2% over 5,000 cases every year since 2009. Most people know that the best method to prevent food safety accidents is a quick inspection, but there is a lack of inspection technology that can be used at the non-analytic level to food production and distribution sites. Among the recent on-site diagnostic technologies, the methods for testing gene-based food poisoning bacteria were introduced with the STA technology, which can range from sample to detection. If food safety information can be generated without forgery by directly inspecting food hazard factors by remote, unmanned, not human, pollution sources can be managed by predicting risks more accurately from current big-data and artificial intelligence technology. Since this information processing can be used on smartphones using the current cloud technology, it is judged that it can be used for food safety to small food businesses or catering services.

• Journal of KIBIM
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• v.11 no.4
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• pp.31-41
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• 2021

Digital twins between "BIM Digital Model-Physical Prototype Model" will be built for Noise Barrier tunnel(NBT) that meet the definition of N.G smart city facilities derived from previous studies to build a data flow that connects data at each stage of design, construction, and operation. In this process, BIM design automation tools are created and utilized, and consistent transmission of member and attribute data is performed by converting them into IFC format. Through this, the purpose is to improve the labor-intensive environment required from the design stage of the NBT and to consistently maintain the information required for subsequent production and construction. This includes achieving changes in the construction industry based on digital transformation by unifying various data formats used differently for each industry from design to operation. In addition, it demonstrates that information exchange in the maintenance and management stages is possible based on the data exchange of the established digital twin and aims to improve the existing labor-intensive environment and expand operability between digital and physical information. As suggested in previous studies, the implementation of digital twins in these N.G smart city facilities includes the possibility of building an environment that adds to the possibility of high value-added product platforms as well as the function of big data platforms targeting existing smart cities.