• Journal of the Korean Geosynthetics Society
• /
• v.10 no.2
• /
• pp.29-34
• /
• 2011

The purpose of this study was to prevent spreading of contaminants from movement of underground water by creating a barrier using artificial freezing method on a soil contaminated by oils and various DNAPLs. Specimens with 80% and 90% degrees of saturation were prepared to form freezing barrier using artificial freezing method. As the results of freezing specimen within soil bin with artificial ground freezing system, artificial contaminated soil cut off wall formed the thinnest wall after 12 hours. It is judged that this cut off wall will control the second soil pollution by intercepting expansion and movement of pollutants and DNAPLs within artificial contaminated soil cut off wall by underground water, intercepting inflow or outflow of underground water. Cut off walls formed by artificial ground freezing system had each other freezing speed according to degree of saturation.

• Journal of The Korean Association of Information Education
• /
• v.26 no.5
• /
• pp.353-360
• /
• 2022

The purpose of this study is to verify the effect of artificial intelligence storytelling education program designed to help learning artificial intelligence based on storytelling, the most important element of human intelligence, on learning flow. To this end, a 16-hour artificial intelligence education program was designed and developed, and applied over 8 weeks to 19 gifted students in 5th and 6th grades of elementary school. Artificial intelligence storytelling education program was developed in the form of teaching and learning course plans for each class and storybooks. Artificial intelligence storytelling education program application results showed significant improvements in average scores in all 9 sub-factors of learning flow, including combination of challenges and abilities, integration of behavior and consciousness, clear goal, concrete feedback, focus on task, sense of control, loss of self-consciousness, Distortion of the sense of time, and self-purpose experience. In other words, it was confirmed that artificial intelligence storytelling education program was effective in improving learning flow.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.38 no.4
• /
• pp.482-494
• /
• 2014

This study researched TV makeup types with a focus on Korean aesthetics. First, natural beauty is expressed with a random form that excluded artificial techniques or decorations often shown in the form of incompletion and space through TV entertainment programs. Incompletion is what excludes artificial technique and denies the whole completion in expressing a face, it shows the intentional incompletion that leaves it as a bare face that has no type, no color, and no decoration. A pursuit for purity, as nature leads to realizing the internal world of concentrating on the essence of object. Space is what makes it empty without filling, it offers a mental space in the inner side so that diverse images can be imagined beyond external form. This trend is indicated similarly to the tendency that the recent global interest in naturalism yearns for purity in nature and wellbeing. The presentation of skin (preferably healthy looking skin) is given attention; consequently, the similarity was being shown between the TV makeup that focuses on expressing skin and recent trends.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.115.5-115
• /
• 2001

This paper suggests that the immune algorithm can effectively be used in tuning of a multivariable system. Then artificial immune network always has a new paraller decentralized processing mechanism for various situations, since antibodies communication to each other among different species of antibodies/B-cells through the simulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach ...

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.873-879
• /
• 2022

In the future, AI and the metaverse are becoming so powerful that their application areas and influences are swallowing up the world. The advertising field is no exception, and it is becoming more important to predict, analyze, and strategize these future changes. In order to study the future change of advertising according to the development of artificial intelligence and metaverse, literature research related to the development of artificial intelligence and metaverse technology and the resulting change in the advertising environment, in-depth interviews with future and advertising experts, and Delphi technique research method I want to study change. First, through this study, we would like to examine the opinions of experts through in-depth interviews on the development of artificial intelligence and metaverse technology and the changes in the advertising sector in the post-coronavirus era of civilizational transformation. In addition, the Delphi technique is used to determine how important the change is by future advertising technology area, future advertising media area, future advertising form area, future advertising effect area, future advertising application area, and future advertising process area, and at what point in the future it will change. In addition, we want to study how the future advertising form will change in detail. Also, based on this, we would like to propose a countermeasure for the advertising industry.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.26 no.2
• /
• pp.1-14
• /
• 2024

Digital transformation has been actively evolving through the use of digital platforms. The fashion industry also utilizes digital platforms and significant changes have become particularly evident in fashion shows. Therefore it is essential to research digital fashion shows. The purpose of this study is to analyze the evolution of digital fashion shows in terms of their form and characteristics in response to changes in digital platforms. The research method consisted of literature research and case analysis. In this study, the development stages of digital platforms were divided into four stages: Internet platforms, SNS platforms, Metaverse platforms, and Artificial Intelligence platforms. Results were derived by analyzing digital fashion shows published on digital platforms at each stage. Internet digital fashion shows were used as an ancillary implement for fashion shows. SNS digital fashion shows expanded the fashion presentation method by experimenting with various fashion show formats. The Metaverse Digital Fashion Show offers a unique experience by integrating Virtual Reality and digital technology to create visual effects customized for the virtual environment. The Artificial Intelligence digital fashion show used virtual graphics created using Artificial Intelligence. Digital fashion shows will continue to evolve and become a significant digital strategy for fashion content and brands. The change in the format of digital fashion shows clearly showcases the characteristics of each stage, but the formats appear to merge during the development process.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06a
• /
• pp.119-124
• /
• 1999

This paper proposes an evolutionary model for automatically generating artificial creatures of various shapes and colors according to insect ecology. This model offers a novel way to naturally evolve the shapes and colors of artificial creatures. The evolutionary model used in our research is based on Genetic Algorithms (GA). In this paper, artificial Computer Graphics(CG) creatures develop into various shapes and colors according to the evolutionary model. Later, they can be used as CG animated characters. This model also solves the problem of reducing the time and labor cost for mass production of various characters. It could be used in such areas as the cavalry battle scene in Disney's animation, “Mulan”. Our approach has two steps. At first, artificial creatures move according to information gathered form the five senses. This information is also used for generating the shapes of the five sense organs[1]. Then, based on the GA, evolutionary mode[2], we prepare prototype creatures, which evolve into various shapes and different colors in alternating generations. Finally, our evolutionary model successfully generates various character shapes and colors automatically.

• Proceedings of the Korean Society for Rock Mechanics Conference
• /
• 2008.10a
• /
• pp.43-51
• /
• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

• Korean Journal of Artificial Intelligence
• /
• v.10 no.2
• /
• pp.7-11
• /
• 2022

OLED displays cannot be used permanently due to burn-in or generation of dark spots due to degradation. Therefore, the time when the display can operate normally is very important. It is close to impossible to physically measure the time when the display operates normally. Therefore, the time that works normally should be predicted in a way other than a physical way. Therefore, if you do computer simulations based on artificial intelligence, you can increase the accuracy of prediction by saving time and continuous learning. Therefore, if we do computer simulations based on artificial intelligence, we can increase the accuracy of prediction by saving time and continuous learning. In this paper, a dataset in the form of development from generation to diffusion of dark spots, which is one of the causes related to the life of OLED, was generated by applying the finite element method. The dark spots were generated in nine conditions, such as 0.1 to 2.0 ㎛ with the size of pinholes, the number was 10 to 100, and 50% with water content. The learning data created in this way may be a criterion for generating an artificial intelligence-based dataset.

• Nuclear Engineering and Technology
• /
• v.54 no.4
• /
• pp.1271-1287
• /
• 2022

When abnormal operating conditions occur in nuclear power plants, operators must identify the occurrence cause and implement the necessary mitigation measures. Accordingly, the operator must rapidly and accurately analyze the symptom requirements of more than 200 abnormal scenarios from the trends of many variables to perform diagnostic tasks and implement mitigation actions rapidly. However, the probability of human error increases owing to the characteristics of the diagnostic tasks performed by the operator. Researches regarding diagnostic tasks based on Artificial Intelligence (AI) have been conducted recently to reduce the likelihood of human errors; however, reliability issues due to the black box characteristics of AI have been pointed out. Hence, the application of eXplainable Artificial Intelligence (XAI), which can provide AI diagnostic evidence for operators, is considered. In conclusion, the XAI to solve the reliability problem of AI is included in the AI-based diagnostic algorithm. A reliable intelligent diagnostic assistant based on a merged diagnostic algorithm, in the form of an operator support system, is developed, and includes an interface to efficiently inform operators.