• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.818-821
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• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.

• 인터넷정보학회논문지
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• 제20권6호
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• pp.167-177
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• 2019

미래사회에서의 국가 경쟁력 강화는 뛰어난 SW융합영재 발굴과 양성이다. 이러한 SW융합영재를 양성하기 위해서는 담당교원의 역량 강화가 선결되어야 할 것이다. 이를 위하여 본 논문에서는 SW융합영재 담당교원의 역량 강화를 위한 4차 산업혁명 시대의 핵심기술 중에 하나인 인공지능 교육 콘텐츠를 개발하였다. 인공지능 교육 콘텐츠의 방향을 설정 후, 인공지능 중에서도 중등 SW융합영재 교육에 적합한 교육 콘텐츠를 구성하여 상세 설계 및 개발하였다. 인공지능 교육 콘텐츠의 구성은 머신러닝과 텐서플로우의 이해, 수치 예측을 위한 선형 회귀 머신러닝 구현, 다중 선형 회귀 기반의 가격 예측 머신러닝 구현으로 이루어져 있다. 개발한 인공지능 교육 콘텐츠는 전문가에게 질적인 측면의 검증을 실시하였다. 향후 본 논문에서 제안한 인공지능 교육 콘텐츠는 SW융합영재 담당교원의 역량 강화에 도움을 줄 것으로 기대한다.

• 한국융합학회논문지
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• 제12권10호
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• pp.203-210
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• 2021

이 연구는 초등학생들이 인공지능 학습원리에 대해 직관적으로 쉽게 이해할 수 있도록 입력 데이터(온도, 습도 등)와 출력 데이터(채소, 과일 등) 모두 생활 속에서 쉽게 접할 수 있는 형태의 스마트팜을 이용한 융합교육 프로그램을 개발하기 위해 수행하였다. 이를 위해 초등학교의 2015 교육과정에 따른 실과교과의 원예·sw·로봇 단원에 대한 내용 분석과 인공지능교육 내용 체계에 관한 선행연구 분석을 통해 스마트팜 적용이 쉬우며 인공지능 학습원리를 쉽게 설명해 줄 수 있는 구성 요소 13개와 성취 기준 16개를 선정하여 4회기(8차시) 분량의 인공지능교육 프로그램과 스마트팜 기능이 들어있는 비닐하우스 교구를 개발하였다. 이 연구에서 개발한 융합교육 프로그램은 추후 초등학생을 대상으로 하는 인공지능교육에 대한 다양한 교수학습자료 개발 시 참고자료로 활용할 수 있다.

• 한국인공지능학회지
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• 제11권1호
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• pp.9-15
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• 2023

As mobile devices such as smartphones, tablets, and kiosks become increasingly prevalent, there is growing interest in developing alternative input systems in addition to traditional tools such as keyboards and mouses. Many people use their own bodies as a pointer to enter simple information on a mobile device. However, methods using the body have limitations due to psychological factors that make the contact method unstable, especially during a pandemic, and the risk of shoulder surfing attacks. To overcome these limitations, we propose a simple information input system that utilizes gaze-tracking technology to input passwords and control web surfing using only non-contact gaze. Our proposed system is designed to recognize information input when the user stares at a specific location on the screen in real-time, using intelligent gaze-tracking technology. We present an analysis of the relationship between the gaze input box, gaze time, and average input time, and report experimental results on the effects of varying the size of the gaze input box and gaze time required to achieve 100% accuracy in inputting information. Through this paper, we demonstrate the effectiveness of our system in mitigating the challenges of contact-based input methods, and providing a non-contact alternative that is both secure and convenient.

• 한국인공지능학회지
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• 제11권1호
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.113-120
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• 2019

Recently, the artificial intelligence(AI) is used in various environments in life, and research on this is being actively conducted in education. In this paper, we designed a Design-Based Research(DBR)-based AI programming education program and analyzed the application of the program for the improvement of understanding of AI in elementary school. In the artificial intelligence education program in elementary school, we should considerthat itshould be used in conjunction with software education through programming activities, rather than creating interest through simple AI experiences. The designed education program reflects the collaborative problem-solving procedures following the DBR process of analysis - design - execution - redesign, allowing the real-world problem-solving activities using AI experiences and block-type programming language. This paper also examined the examples of education programs to improve understanding of AI by using Machine Learning for Kids and to draw implications for developing and operating such a program.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.352-359
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• 2021

The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

• 정보화정책
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• 제23권4호
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• pp.24-37
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• 2016

지능정보사회는 정보가 중심이 되는 정보사회를 한 단계 넘어선 지능형 초연결사회를 의미한다. 인공지능이 구체적으로 논의되는 지금, 인공지능이 핵심적인 역할을 하는 지능정보사회의 대응을 위한 법 제도에 대한 논의를 시작해야할 때이다. 어느 순간 특이점을 넘어설 때는 너무 늦은 대응이 될 수 있기 때문이다. 물론, 인공지능이 우리 사회를 어떻게 변화시킬 지는 예측하기가 쉽지 않다. 다만, 고민스러운 것은 알고리즘이 세상을 지배하거나 적어도 의사결정의 지원을 하게될 지능정보사회에서 인간은 인공지능과 어떤 관계를 모색할 것인지 여부이다. 한 가지 분명한 것은 인공지능을 지배하거나, 또는 인공지능을 배제하는 것은 해결방안이 되기는 어렵다는 점이다. 인공지능이 중심에 서는 지능정보사회를 대응하기 위한 법제도적인 논의는 사람을 전제하는 현행 법제도를 인공지능으로 대체하는 수준까지 이뤄질 필요가 있다. 지능정보사회로의 패러다임 전환에 따른 법제 정비는 인공지능과 로봇, 그리고 사물이라는 새로운 객체의 출현과 그 객체의 주체화까지도 가정할 수 있기 때문이다.

• 소성∙가공
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• 제30권4호
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• pp.186-194
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• 2021

Finite element simulation is a widely applied method for practical purpose in various metal forming process. However, in the simulation of elasto-plastic behavior of porous material or in crystal plasticity coupled multi-scale simulation, it requires much calculation time, which is a limitation in its application in practical situations. A machine learning model that directly outputs the constitutive equation without iterative calculations would greatly reduce the calculation time of the simulation. In this study, we examined the possibility of artificial intelligence based constitutive equation with the input of existing state variables and current velocity filed. To introduce the methodology, we described the process of obtaining the training data, machine learning process and the coupling of machine learning model with commercial software DEFROM^TM, as a preliminary study, via rigid plastic finite element simulation.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.