• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.299-302
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• 2014

Due to the convergence between digital devices and the development of wireless communication technology, bit-signal sensor miniaturization, building an Electronic Medical Record (EMR) which is a digital version of a paper chart that contains all of a patient's medical history and the information of Electronic Health Record (EHR), Ubiquitous healthcare (u-Healthcare) that can monitor their health status and provide personal healthcare service anytime and anywhere. Also, the appearance of cloud computing technology is one of the factors that accelerate the development of u-healthcare service. However, if the individual information to be used maliciously during the u-healthcare service utilization, leads to serious problems directly related to the individual's life because if it goes beyond the level of simple health screening and treatment, it may not provide accurate and reliable healthcare services. For this reason, we analyzed a variety of security issues related to u-healthcare service in cloud computing environment and described about directions of secure health information sharing system construction. In addition, we suggest the future developmental direction for th activation of u-healthcare industry.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.347-352
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• 2019

We analyzed the correlation among fruit bearing branch (FBB) and shoot and fruit characteristics in order to select the length of FBB suitable for producing high-quality fruits of 'Soomee', a peach tree developed in Korea. The length and diameter of FBB were 26.1 cm and 6.1 mm, respectively, shoot and leaf number per FBB were 3.2 and 38.6, respectively. Of these, the coefficient of variation was very high in the shoots and leaf number. The average weight and soluble solid content (SSC) of fruit were 298.6 g and 12.2 Brix, respectively, and coefficient of variation of the fruit weight was 18.0 %, which was higher than that of SSC. As the FBB of 10-20 cm and 20-30 cm length per tree were 27.1 % and 25.4 %, respectively, the sum of short and middle FBB frequency per tree was more than 50 %. Fruits of 250-350 g and 11.0-13.0 Brix per tree were distributed in 68.6 % and 74.0 %, respectively. As a result of correlation analysis, fruit weight and shoot number were affected by the length of FBB. In particular, length of FBB showed the relation of fruit weight with $y=-0.0482x^2+2.4512x+277.36$. As a result, the length of FBB that can maximize fruit weight was analyzed as 25.4 cm. Therefore, in the filed, the suitable FBB for producing 'Soomee' peach is estimated to be about 20-30 cm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.135-144
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• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.

• Science of Emotion and Sensibility
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• v.26 no.2
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• pp.129-140
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• 2023

Following ISO 20471, in this study, first, two sets of safety clothes and safety vests were made by designing and attaching animal and bird patterns preferred by children to retroreflective films and black fabrics on those fluorescent fabrics and retroreflective materials prescribed by international standards. Second, by mounting a smart photonic device on the safety clothing so that the body can be recognized from a distance even without an ambient light source at night, children can emit three types of light depending on the situation with just one-touch of the button. From a result of comparison with visibility a day and night by dressing a mannequin in the made smart safety clothing, the difference in visibility was evident at night, it was confirmed that we can see the figure of a person even at a distance of approximately 70 m. Therefore, it is expected to contribute to the prevention of traffic and other accidents on the road, as the drivers driving at night or in bad weather can recognize a person from a distance. Third, in case of the energy is exhausted and cannot maintain the stability of the light-emitting function of the optical faber, we can use energy harvesting device, and the light-emitting time will be extended. As a result it comes up to emit light stably for a long time. And this prove that smart photonic safety clothing can also be used for night workers. Therefore, optical fiber safety clothing is expected to be highly wearable not only in real life but also in dark industrial sites due to stable charging by applying the energy harvesting provided by solar cells.

• Knowledge Management Research
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• v.24 no.1
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• pp.1-29
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• 2023

The COVID-19 pandemic has accelerated digital transformation across all industries and daily life. Edutech is spreading in the education field, also bringing changes in university education. Non-face-to-face online-only classes at universities have spread after the COVID-19 pandemic physical distancing started. Online-only or real-time online classes showed diverse educational imitations. 'Metaverse' started to attract attention as a learning space and community activity support platform that may solve the limitations of online education and communication. It is time to prepare an introduction strategy for the actual application of education using metaverse. This study, first, by examining previous studies and cases of metaverse application, and second, establishing a metaverse introduction framework based on the technology lifecycle model and the innovation diffusion theory. Finally, we provide an introduction strategy in steps, a specialized introduction plan according to the main users is established and presented as a scenario. We expect that this study will provide the theoretical background of the new technology introduction and the spread of metaverse research. Also, we present an efficient introduction strategy, the basis for a service model, and a practical basis for the university's value-added strategy.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.461-470
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• 2023

This paper analyzes the spatial representations constructed by reality, filming, and narrative in the works of Hong Kong film director Wong Kar-wai, and how these spaces influence Hong Kong's urban culture, perception, and interpersonal relationships. To analyze Wong Kar-wai's films, Charles Sanders Peirce's semiotics concepts and Paul Virilio's spatial concepts were applied. Through this, we examined how the meaning embedded in the spatial representations of Wong Kar-wai's films could become a crucial factor in their success. Wong Kar-wai focused on the values of human relationships formed by society in his subject expression, directly representing the human inner world and prompting audiences to think about it. In this paper, we categorized the spaces depicted in Wong Kar-wai's films as public, private, and connective spaces, and analyzed them as a means to show the living environment and emotions of Hong Kong's youth. Through this, we determined that the spatial representations in Wong Kar-wai's films effectively demonstrate the cultural interpretation function of Hong Kong's citizen consciousness at the junction of Eastern and Western cultures and social connections. In conclusion, Wong Kar-wai's works provide a rich understanding of contemporary people's lives, emotions, and urban spaces, offering valuable insights into Hong Kong's film industry and cultural values.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.17-23
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• 2023

This study purports to explore the landscape of welfare attitudes of young generation of Korea in their 20s and 30s focusing upon potential differences from those of older generations. Korea has recently been in the significant debate on pension reform and the disadvantages of relatively young generations has been on of the most crucial issues during the reform. Survey data from 17th Korean Welfare Panel are analyzed and such variable as attitudes toward government expenditure on public pension, health care, old age support, poverty, family and child care and so on. In addition, welfare-related variables such as universalism vs selectivism, tax increase for welfare expenditure, and political orientation are to be analyzed. The results show several findings. First of all, correspondence analysis shows that young generation in Korea are strongly associated with higher education and full time employment compared to older generations. Secondly, the most interested welfare issues of young generations are housing and child support. Moreover, young generations' attitudes toward government expenditure increase differ from those of older generations on the issues of public pension, housing, and family and child support. Lastly, political orientation of those young generation tend to be progressive and they support universalism in welfare policy, but they do not support tax increase for welfare purpose, which, I would say, is inconsistent.