• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.713-714
• /
• 2023

본 논문에서는 사전학습모델을 활용한 수학학습 도구 자동 생성 시스템을 제안한다. 본 시스템은 사전학습모델을 활용하여 수학학습 도구를 교과과정 및 단원, 유형별로 다각화하여 자동 생성하고 사전학습모델을 자체 구축한 Dataset을 이용해 Fine-tuning하여 학생들에게 적절한 학습 도구와 적절치 않은 학습 도구를 분류하여 학습 도구의 품질을 높이었다. 본 시스템을 활용하여 학생들에게 양질의 수학학습 도구를 많은 양으로 제공해 줄 수 있는 초석을 다지었으며, 추후 AI 교과서와의 융합연구의 가능성도 열게 되었다.

• Journal of Sensor Science and Technology
• /
• v.33 no.2
• /
• pp.78-85
• /
• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.

• International Journal of Contents
• /
• v.15 no.4
• /
• pp.1-7
• /
• 2019

As the recent developments of artificial intelligence, particularly machine-learning, impact every aspect of society, they are also increasingly influencing creative fields manifested as new artistic tools and inspirational sources. However, as more artists integrate the technology into their creative works, the issues of diversity and fairness are also emerging in the AI-based creative practice. The data dependency of machine-learning algorithms can amplify the social injustice existing in the real world. In this paper, we present an interactive visualization system for raising the awareness of the diversity and fairness issues. Rather than resorting to education, campaign, or laws on those issues, we have developed a web & ML-based interactive data visualization system. By providing the interactive visual experience on the issues in interesting ways as the form of web content which anyone can access from anywhere, we strive to raise the public awareness of the issues and alleviate the important ethical problems. In this paper, we present the process of developing the ML-based interactive visualization system and discuss the results of this project. The proposed approach can be applied to other areas requiring attention to the issues.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2006.04a
• /
• pp.74-75
• /
• 2006

We have investigated dielectric properties depending on temperature in organic light-emitting diodes using 8-hydroxyquinoline aluminum ($Alq_3$) as an electron transport and emissive material. We analyzed the dielectric properties of organic light-emitting diodes using characteristics of impedance. he Impedance characteristics was measured complex impedance Z and phase $\theta$ in the temperature range of 10 K to 300 K. We obtained complex electrical conductivity, dielectric constant and loss tangent ($tan{\delta}$) of the device at room temperature. From these analyses, we are able to interpret a conduction mechanism and dielectric properties contributed by an interfacial and orientational polarization.

• Annual Conference of KIPS
• /
• 2019.10a
• /
• pp.931-934
• /
• 2019

Research using artificial intelligence to generate captions for an image has been studied extensively. However, these systems are unable to create creative stories that include more than one sentence based on image content. A story is a better way that humans use to foster social cooperation and develop social norms. This paper proposes a framework that can generate a relatively short story to describe based on the context of an image. The main contributions of this paper are (1) An unsupervised framework which uses recurrent neural network structure and encoder-decoder model to construct a short story for an image. (2) A huge English novel dataset, including horror and romantic themes that are manually collected and validated. By investigating the short stories, the proposed model proves that it can generate more creative contents compared to existing intelligent systems which can produce only one concise sentence. Therefore, the framework demonstrated in this work will trigger the research of a more robust AI story writer and encourages the application of the proposed model in helping story writer find a new idea.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.17-18
• /
• 2019

최근 4차 산업혁명의 핵심 분야 중 하나인 인공지능에 대한 많은 연구가 이루어지고 있다. 많은 기업들이 인공지능 스피커와 같은 제품을 출시하고 있으나 대부분 비서 역할만을 할 수 있도록 구성된 제품이 대부분이다. 그러나 학교와 같이 많은 사람이 존재하는 경우 시끄러운 환경에서 사용되고 있는 인공지능 스피커는 명령 인식이 제대로 되지 않아 실용도가 저하되는 단점을 가지고 있으며, 현재 인공지능 스피커는 단순한 질의응답 수준의 응대만 가능하여 다소 부족한 부분이 있다. 또한 인공지능의 급속한 발전으로 인공지능 스피커가 아닌 전자제품에 인공지능 비서 기능이 탑재된 제품도 새롭게 출시되어 인공지능 스피커가 필요 없을 수도 있기에, 본 논문에서는 학교와 같은 주변의 소음이 많이 발생하는 교육 환경에서도 소통이 가능한 인공지능 마이크를 활용할 수 있는 모델을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1213-1220
• /
• 2022

This study was conducted to understand how to derive educational methods to efficiently improve class satisfaction for 130 college students who experienced non-face-to-face classes during the last Covid-19. The appropriateness of class time, improvement of learning effect, continuity of non-face-to-face classes, and use of educational media were set as items corresponding to class satisfaction. Research was attempted to derive an educational method for efficient class satisfaction improvement by grasping the difference and relationship between variables.

• Steel and Composite Structures
• /
• v.42 no.6
• /
• pp.733-745
• /
• 2022

This study proposed a robust artificial intelligence (AI) model based on the social behaviour of the imperialist competitive algorithm (ICA) and artificial neural network (ANN) for modelling the deflection of reinforced concrete beams, abbreviated as ICA-ANN model. Accordingly, the ICA was used to adjust and optimize the parameters of an ANN model (i.e., weights and biases) aiming to improve the accuracy of the ANN model in modelling the deflection reinforced concrete beams. A total of 120 experimental datasets of reinforced concrete beams were employed for this aim. Therein, applied load, tensile reinforcement strength and the reinforcement percentage were used to simulate the deflection of reinforced concrete beams. Besides, five other AI models, such as ANN, SVM (support vector machine), GLMNET (lasso and elastic-net regularized generalized linear models), CART (classification and regression tree) and KNN (k-nearest neighbours), were also used for the comprehensive assessment of the proposed model (i.e., ICA-ANN). The comparison of the derived results with the experimental findings demonstrates that among the developed models the ICA-ANN model is that can approximate the reinforced concrete beams deflection in a more reliable and robust manner.

• Electronics and Telecommunications Trends
• /
• v.37 no.4
• /
• pp.36-45
• /
• 2022

As the interest in achieving an intelligent society grows with the fourth industrial revolution's development, information and communications technologies technologies like artificial intelligence (AI), Internet of Things, virtual reality, information security, and blockchain technology are being actively employed in different fields for achieving an intelligent society. With these modifications, the information security paradigm in industrial and public institutions, like personal sensitive data, is quickly changing, and it is exposed to different cyber threats and breaches. Furthermore, as the number of cyber threats and breaches grows, so does the need for rapid detection and response. This demand can be satisfied by establishing cyber training programs and fostering experts that can improve cyber security abilities. In this study, we explored the domestic and international technology trends in cyber security education and training facilities for developing experts in information security. Additionally, the AI technology application in the cyber training ground, which can be established to respond to and deter cyber threats that are becoming more intelligent, was examined.

• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.132-138
• /
• 2022

Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob.