• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.137-144
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• 2019

The purpose of this study was to provide basic data for the development of a prototype of a garment that allows middle aged men to look idealized by examining the type of perception of middle aged men based on their subjective evaluation and their characteristics. This study used the Q methodology, which is a subjective research method that finds correlations among middle aged men across subjective attributes. The types of perception of body shape of middle aged men were analyzed as three types: leaning forward shape with bird legs, developed upper body shape with thick legs, protruding abdomen obesity body shape. The leaning forward shape with bird legs was recognized as the lowest in the BMI index, and the shoulder and chest were sagging, legs were thinner than the body and leaned forward. And that the hip were protruding and had a flat rectangular shape. Developed upper body shape with thick legs was the second overweight type of BMI index. It was recognized that the ankle and calf thighs were thick and the upper abdomen protruded upper body development body. Protruding abdomen obesity body shape was the most obese type with BMI index. In this type, the height was the smallest, and the upper abdomen came out and the abdomen protruded, and the abdomen was more exuded than the chest, and the neck was thick and the hips were recognized as the big body. The middle aged men's recognitive body shape was classified as a similar to actual body shape. However, in the recognition type, the frontal and side body types were mixed and classified. It is necessary to study the ergonomic pattern considering the features of each body type. This suggests that psychological effects can be obtained that allow the body shape that changes with age to be accepted more positively.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.825-833
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• 2018

We examined the relationship between the order of signs and the order of vote within parties in electing local district councilors during the 7th nationwide local election held on June 13th, 2018. We analyzed election data for respective cases that include two, three, four candidates within the same party. In most cases, the candidate with sign 'Ga' gained more than other candidates in the same party, showing a need for provisional measures. In addition, a difference in voting tendency was found between in-house voting and early outside voting when there were two candidates in the Democratic Party of Korea as well as for when there were two candidates in the Liberty Korea Party.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.15-22
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• 2019

Recent technological advances in three-dimensional (3D) sensing devices and machine learning such as deep leaning has enabled data-driven 3D applications. Research on artificial intelligence has developed for the past few years and 3D deep learning has been introduced. This is the result of the availability of high-quality big data, increases in computing power, and development of new algorithms; before the introduction of 3D deep leaning, the main targets for deep learning were one-dimensional (1D) audio files and two-dimensional (2D) images. The research field of deep leaning has extended from discriminative models such as classification/segmentation/reconstruction models to generative models such as those including style transfer and generation of non-existing data. Unlike 2D learning, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become increasingly popular owing to advances in 3D vision technology, the generation/acquisition of 3D data is still very difficult. Even if 3D data can be acquired, post-processing remains a significant problem. Moreover, it is not easy to directly apply existing network models such as convolution networks owing to the various ways in which 3D data is represented. In this paper, we summarize technological trends in AI-based 3D content generation.

• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.449-460
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• 2019

Today, the fashion business environment of the 4.0 generation is changing based on fashion technology combined with advanced digital technologies such as AI (Artificial Intelligence), big data and IoT (Internet of Things). "Digital Transformation" means a fundamental change and innovation in a digital paradigm including corporate strategy, organization, communication, and business model, based on the utilization of digital technology. Thus, this study examines digital transformation strategies through the fashion brand Burberry. The study contents are as follows. First, it examines the theoretical concept of digital transformation and its utilization status. Second, it analyzes the characteristics of Burberry's digital transformation based on its strategies. For the research methodology, a literature review was performed on books and papers, aligning with case studies through websites, social media, and news articles. The result showed that first, Burberry has reset their main target to Millennials who actively use mobile and social media, and continues to communicate with them by utilizing digital strategy in the entire management. Second, Burberry is quickly delivering consistent brand identity to consumers by internally creating and providing social media-friendly content. Third, they have started real-time product sales and services by using IT to enhance access to brands and to lead consumers towards more active participation. In this study, Burberry's case shows that digital transformation can contribute to increased brand value and sales, keeping up with the changes in the digital paradigm. Therefore, the study suggests that digital transformation will serve as an important business strategy for fashion brands in the future.

• Journal of Marine Bioscience and Biotechnology
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• v.11 no.1
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• pp.14-22
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• 2019

Omega-3 fatty acids and carotenoids, which are known as representative high-value substances derived from microalgae, are being studied from various diatoms. Most of the diatoms contain fucoxanthin and omega-3 fatty acid. Fucoxanthin produced by diatom has been reported as bioactive compounds exhibiting strong antioxidant, anticancer and anti-inflammatory activities. However, the low growth rate and fucoxanthin content of diatoms are one of the big obstacles to the industrial application. In this study, indigenous marine diatom Achnanthidium sp. BS-001 was isolated for a candidate of fucoxanthin producer. Light intensity and temperature for the culture of Achnanthidium sp. BS-001 were optimized on PhotoBiobox. Optimization of silicate concentration for increasing BS-001 biomass productivity was confirmed in F/2 medium with various concentration of sodium silicate. As a result, condition of light intensity, temperature, and silicate concentration for optimal cultivation were $150{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, $18^{\circ}C$ and 0.106 mM, respectively. Maximum biomass productivity reaches to $154.3mg{\cdot}L^{-1}{\cdot}day^{-1}$, and then the content of omega-3 fatty acids and fucoxanthin were $19.4mg{\cdot}g^{-1}$, $9.05mg{\cdot}g^{-1}$, respectively. These results indicate that Achnanthidium sp. BS-001 has the potential to be used as a source of omega-3 fatty acids and fucoxanthin.

• Journal of Korean Society of Rural Planning
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• v.25 no.2
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.249-254
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• 2019

The concept of 'Edu-Tech', which is rapidly reorganized around e-Learning, has been spreading along with the development of intelligent information technology according to the fourth industrial revolution such as Artificial Intelligence (AI), Internet of Things (IoT), BigData. Currently, leading companies are conducting online education services, but real-time two-way communication is difficult. In addition, in the case of off-line class, there are many students, and not only the time is limited, but also they often miss the opportunities to ask questions. In order to solve these problems, this paper develops a real - time interactive question and answer management system that can freely questions both on - line and off - line by combining the benefits of offline instant answers and the advantages of online openness. The developed system is a real-time personalized education system that enables the respondent to check the situation of the questioner in real time and provide a customized answer according to the inquirer's request. In addition, by measuring and managing the system usage time in seconds, the questioner and the respondent can efficiently utilize the system.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.7-13
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• 2019

Role-based access or attribute-based access control in cloud environment or big data environment need requires a suitable mathematical structure to represent a hierarchical model. This paper define the notion of multipliers and simple multipliers of lattice implication algebras that can implement a hierarchical model of role-based or attribute-based access control, and prove every multiplier is simple multiplier. Also we research the relationship between multipliers and homomorphisms of a lattice implication algebra L, and prove that the lattice [0, u] is isomorphic to a lattice $[u^{\prime},1]$ for each $u{\in}L$ and that L is isomorphic to $[u,1]{\times}[u^{\prime},1]$ as lattice implication algebras for each $u{\in}L$ satisfying $u{\vee}u^{\prime}=1$.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.54.2-54.2
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• 2019

Removing noise which occurs inevitably when taking image data has been a big concern. There is a way to raise signal-to-noise ratio and it is regarded as the only way, image stacking. Image stacking is averaging or just adding all pixel values of multiple pictures taken of a specific area. Its performance and reliability are unquestioned, but its weaknesses are also evident. Object with fast proper motion can be vanished, and most of all, it takes too long time. So if we can handle single shot image well and achieve similar performance, we can overcome those weaknesses. Recent developments in deep learning have enabled things that were not possible with former algorithm-based programming. One of the things is generating data with more information from data with less information. As a part of that, we reproduced stacked image from single shot image using a kind of deep learning, conditional generative adversarial network (cGAN). r-band camcol2 south data were used from SDSS Stripe 82 data. From all fields, image data which is stacked with only 22 individual images and, as a pair of stacked image, single pass data which were included in all stacked image were used. All used fields are cut in $128{\times}128$ pixel size, so total number of image is 17930. 14234 pairs of all images were used for training cGAN and 3696 pairs were used for verify the result. As a result, RMS error of pixel values between generated data from the best condition and target data were $7.67{\times}10^{-4}$ compared to original input data, $1.24{\times}10^{-3}$. We also applied to a few test galaxy images and generated images were similar to stacked images qualitatively compared to other de-noising methods. In addition, with photometry, The number count of stacked-cGAN matched sources is larger than that of single pass-stacked one, especially for fainter objects. Also, magnitude completeness became better in fainter objects. With this work, it is possible to observe reliably 1 magnitude fainter object.