• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.584-585
• /
• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.3
• /
• pp.85-92
• /
• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• Industry Promotion Research
• /
• v.8 no.3
• /
• pp.125-136
• /
• 2023

This study tried to establish a system of service paradigm by re-examining the Korean play culture through the people who play in the era of King Jeongjo and revealing the integration of modern service culture. The results of this study are as follows. First, King Jeongjo inspired the autonomy and creativity of the participants through the patronage of Changdeokgung Palace and led the renaissance era of Joseon as a creative play. The creative play of the service industry is reborn as a place of innovation that realizes development through a communicative intellectual network. Second, the 60th birthday Jin Chan-yeon and the aesthetics of slowness that evoke artistic play are the language of innovation that transcends language and culture. Artistic play becomes a channel of communication to share happiness with people around the world based on absolute beauty and aesthetic sensibility. Third, Jeongjo was a humanist in Joseon. This humanistic ideology leads to humanistic religion. K-service, which uses religious play as a medium, has a turning point towards healing and happiness as all participants in the service experience sacredness. There is an implication in that it pioneered a service culture by presenting a new paradigm by combining play and service, and laid the groundwork for building a unique area in global business.

• Convergence Security Journal
• /
• v.22 no.5
• /
• pp.21-35
• /
• 2022

The use of digital information according to the development of information and communication technology and the 4th industrial revolution is continuously increasing and diversifying, and in proportion to this, crimes using digital information are also increasing. However, there are few cases of establishing an environment for processing and analysis of digital evidence in Korea. The budget allocated for each organization is different and the digital forensics laboratory built without solving the chronic problem of securing space has a problem in that there is no standard that can be referenced from the initial configuration stage. Based on this awareness of the problem, this thesis conducted an exploratory study focusing on tools and equipment necessary for building a digital forensics laboratory. As a research method, focus group interviews were conducted with 15 experts with extensive practical experience in the digital forensic laboratory or digital forensics field and experts' opinions were collected on the following 9 areas: network configuration, analyst computer, personal tools·equipment, imaging devices, dedicated software, open source software, common tools/equipment, accessories, and other considerations. As a result, a list of tools and equipment for digital forensic laboratories was derived.

• The Journal of Bigdata
• /
• v.7 no.2
• /
• pp.113-128
• /
• 2022

After COVID-19, interest in "sustainable tourism" increased, and the number of tourists who wanted to experience "sustainable tourism" also increased. However, there is a problem that the programs and methods for 'sustainable tourism' are not specific and diverse. In addition, since most of the interests of "sustainable tourism" focus on "environment" and "carbon neutrality," there are not many programs or government policies that can contribute to the community. Therefore, in this study, news data and review data were analyzed to suggest a method for promoting 'sustainable tourism'. First, in this study, major themes of sustainable travel were derived through news big data analysis. Through this analysis, policy themes and events of 'sustainable tourism' were derived. By analyzing news big data related to "sustainable tourism," we would like to analyze the reasons why sustainable travel has not been activated in Korea. Finally, in order to promote sustainable travel in Jeju island, we analyzed user review data of Jeju local currency, and propose a idea to coexist with the local community.

• Nutrition Research and Practice
• /
• v.17 no.4
• /
• pp.682-697
• /
• 2023

BACKGROUND/OBJECTIVES: Tibetan tea is a kind of dark tea, due to the inherent complexity of natural products, the chemical composition and beneficial effects of Tibetan tea are not fully understood. The objective of this study was to unravel the composition of Tibetan tea using knowledge-guided multilayer network (KGMN) techniques and explore its potential antioxidant and hypolipidemic mechanisms in mice. MATERIALS/METHODS: The C57BL/6J mice were continuously gavaged with Tibetan tea extract (T group), green tea extract (G group) and ddH2O (H group) for 15 days. The activity of total antioxidant capacity (T-AOC) and superoxide dismutase (SOD) in mice was detected. Transcriptome sequencing technology was used to investigate the molecular mechanisms underlying the antioxidant and lipid-lowering effects of Tibetan tea in mice. Furthermore, the expression levels of liver antioxidant and lipid metabolism related genes in various groups were detected by the real-time quantitative polymerase chain reaction (qPCR) method. RESULTS: The results showed that a total of 42 flavonoids are provisionally annotated in Tibetan tea using KGMN strategies. Tibetan tea significantly reduced body weight gain and increased T-AOC and SOD activities in mice compared with the H group. Based on the results of transcriptome and qPCR, it was confirmed that Tibetan tea could play a key role in antioxidant and lipid lowering by regulating oxidative stress and lipid metabolism related pathways such as insulin resistance, P53 signaling pathway, insulin signaling pathway, fatty acid elongation and fatty acid metabolism. CONCLUSIONS: This study was the first to use computational tools to deeply explore the composition of Tibetan tea and revealed its potential antioxidant and hypolipidemic mechanisms, and it provides new insights into the composition and bioactivity of Tibetan tea.

• Journal of Korea Water Resources Association
• /
• v.56 no.2
• /
• pp.91-101
• /
• 2023

In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R²), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R²: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.

• Journal of Service Research and Studies
• /
• v.11 no.1
• /
• pp.59-79
• /
• 2021

Service-related research in accordance with the transition to the service economy era has been conducted in a wide variety of ways, but the development of a service-related scale suitable for the present time is still insignificant. The purpose of this study is to define the nature of services and to develop measurement items for them. First, four categories of service nature were adopted in the previous study. The four categories are 'relationship', 'interactivity', 'horizontality', and 'harmony'. In this study, sub-factors and specific items of each of these four service essences were extracted and developed as measurable items. As a qualitative study, the four categories of sub-factors were extracted, and a mixed study was adopted to prove the reliability and validity of the extracted factors through quantitative studies. The scale items were identified through literature study, free response method, and Delphi technique, and the measurement items were refined through a second questionnaire of 30 Delphi panels composed of experts. As a result of the study, 15 out of 52 questions for relationship, 11 out of 45 questions for bilateral direction, 9 out of 33 questions for horizontality, and 17 out of 61 questions for harmonization were derived after secondary refining. Through this study, it was possible to uncover new essential items suitable for the service economy era. SNS, network, synergy, platform, system, real name, and breakthrough are concepts that have not been obtained in previous studies, and can be seen as contributions of this study. However, due to various limitations, this study did not cover all aspects of the service, but mainly dealt with people-centered services, which are part of the service. In the future, it is necessary to study the development of service essence measurement items for the overall aspect of services developed according to the evolution of the service economy era.

• Smart Media Journal
• /
• v.12 no.1
• /
• pp.9-16
• /
• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.1
• /
• pp.79-89
• /
• 2023

The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.