• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.256-258
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• 2005

올리고뉴크레오타이드 서열의 디자인은 일반 분자 생물학 뿐만 아니라 DNA 컴퓨팅 분야에서도 중요한 문제이다. DNA나 RNA와 같은 생체 물질간의 화학반응을 이용하여 계산을 수행하는데 사용되는 염기 서열의 품질은 계산의 정확도에 큰 영향을 미치기 때문에, 문제의 특성에 따른 요구 조건에 안는 염기 서열을 디자인 하기위한 방법에 대해 여러 가지 연구가 있어왔다. 기존의 DNA 컴퓨팅을 위한 염기서열 디자인은 주어진 녹는점의 범위에서 단순히 서로 독립적인 염기서열들의 집합을 디자인 하거나, 분자생물학 실험에 사용되는 올리고 프로브나 프라이머 셋을 디자인 하는 것을 중심으로 이루어졌다. 반면, 본 논문에서는 세포에서 추출된 DNA/RNA 분자가 섞여있는 환경에서 어느 DNA/RNA 분자와도 흔성화 반응물 하지않는 범용 올리고뉴클레오타이드 태그를 디자인하는 간단한 유전 알고리즘을 제시하며, 이를 이용해서 디자인된 염기서열 결과를 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.15-20
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• 2018

Currently the mobile augmented reality does not require supplemental hardware, such as markers like specific images or depth cameras, in order to acquire 3D environment information. This allows for increased accessibility and usability for the general user, and also broadened scope of development. The market research enterprise Counterpoint Research predicted that the growth of the augmented reality market will reach 70 trillion Korean Won by 2021. Application developments are also progressing. Wargaming, the developer of the global game World of Tanks, has launched an application that uses AR core at the GDC 2018. Thus, we must prepare for the impending augmented reality market and acquire top class augmented reality technology using 3D environment. This paper outlines the development of a game using AR CORE SDK to acquire 3D environment and Unity 3D game engine to combine camera images and 3D graphics, which all comes together to construct a natural augmented reality.

• The Journal of Information Systems
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• v.32 no.4
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.615-618
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• 2023

최근 computer vision 기술 발달이 가속화되고 있으나, 특정 산업의 경우 산업 적용의 어려움과 데이터적 특성으로 인하여 기술 발전의 속도를 따라가지 못하고 있다. 특히, CCTV 는 대부분 실외 환경에 운영되어 다양한 환경의 변화 및 데이터 고유 특성상 노이즈가 많기 때문에 데이터 산포가 커서 기술의 현장 적용에 어려움이 있다. 본 논문에서는 CCTV 데이터의 특성을 고려하여 CCTV 운용 환경에 강건한 객체탐지(object detector) 학습을 위한 데이터 설계 방안을 제안한다. 제안 기법은 대용량의 CCTV 영상에서 객체탐지에 효과적인 샘플링을 유도하는 방안과 소수의 CCTV 레이블 데이터 외 MS COCO 등 다수 오픈 레이블 데이터를 혼합학습 하여 일반화 성능을 높이는 방안을 제안한다. 다수의 실험을 통해 제안 기법의 우수성을 입증하였으며, 특히 mAP 기준 13.39%의 성능 향상을 꾀할 수 있음을 선보였다.

• Advances in Computational Design
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• v.7 no.1
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• pp.1-17
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• 2022

In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.

• Journal of KIBIM
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• v.11 no.2
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• pp.54-59
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• 2021

In the process of designing a building, the process of expressing the designer's ideas through images is essential. However, it is expensive and time consuming for a designer to analyze every individual case image to generate a hypothetical design. This study aims to visualize the basic design draft sketch made by the designer as a real image using the Generative Adversarial Network (GAN) based on the continuously accumulated architectural case images. Through this, we proposed a method to build an automated visualization environment using artificial intelligence and to visualize the architectural idea conceived by the designer in the architectural planning stage faster and cheaper than in the past. This study was conducted using approximately 20,000 images. In our study, the GAN algorithm allowed us to represent primary materials and shades within 2 seconds, but lacked accuracy in material and shading representation. We plan to add image data in the future to address this in a follow-up study.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.141-158
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• 2023

In the field of animation, as technology advances, production technology, production methods, and production culture are also steadily developing. The demand for content is increasing rapidly around the OTT platform, and the demand for animation content and diversity is increasing. With these market changes, animation creation ability is becoming a more important animation education goal. There is also a need to innovate educational methods to provide students with the skills and knowledge required in the modern animation business. This paper investigated the composition of the educational curriculum of domestic and foreign animation universities education. It examines artificial intelligence (AI) technology that can be used in animation creation and explores the design and direction of the university animation curriculum using it. AI technology has already proven its potential in various areas, and it is integrated into the animation curriculum to present various development potentials. Using AI technology, students can focus on practical and essential animation education by preventing technical difficulties in animation creation, increase their experience in animation production, and experiment with planning and producing various contents. It is proposed to design an educational curriculum that further strengthens animation creation and production capabilities by forming smart animation classes to foster talents who can lead the future animation industry in a new direction.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Fourth Industrial Review
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• v.2 no.1
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• pp.19-32
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• 2022

Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.