• Proceedings of The KACE
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• 2018.01a
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• pp.93-95
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• 2018

음성인식 기술이 인공지능의 핵심 연구 분야로 떠오르면서 음성인식 기술은 인공지능(AI)과 결합하여 음성비서, 자율 주행차, 실시간 음성검색, 음성 통역 등 다양한 분야에서 활용될 것으로 기대되고 있다. 문자가 아닌 음성으로 검색하는 새로운 검색 시장이 확대되면서 '음성이용자인터페이스(VUI: Voice User Interface)' 인 음성비서 서비스 기능을 가진 인공지능(AI) 스피커 시장 경쟁이 시간이 갈수록 가열되고 있다. 이에 인공지능 스피커의 등장배경부터 현재 국내외 음성인식 기기 소개 그리고 앞으로의 교육의 방향에 맞는 음성인식 기기의 교육적 활용 방안에 대해서 알아보고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.673-674
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• 2020

의식주 중에서 자신을 표현하고 외부와의 교류를 할 수 있는 분야는 패션분야로서 인간 생활과 밀접한 관계를 가지고 있으며 사람들의 개인화된 성향 변화 및 인터넷 환경의 개선으로 트렌드는 빠르게 변화하고 있다. 인공지능 기술의 발전은 단순히 객체의 검출 및 분류에서 벗어나 패션 아이템의 분석 및 세부적인 속성을 분석할 수 있는 수준에 다다랐으며 인공지능 기술을 활용하여 사용자에게 추천할 수 있는 서비스가 출시되고 있다. 패션 트렌드의 빠른 변화 및 인공지능 기술의 발전으로 이를 활용한 플랫폼에 기반을 두어 디자이너에게는 디자인 기술을 향상시킬 수 있으며 사용자에게는 개인화된 제품을 구매할 수 있는 플랫폼 개발이 요구되고 있다. 본 논문에서는 인공지능 기술 기반 패션 분석 기술 개발을 위하여 패션 검출 모듈, 패션 검색 모듈, 패션 검색을 위한 벡터 검색 모듈, 상하의 분리를 위한 세그먼테이션 모듈, 패션 복종 분류 모듈을 개발하여 통합하였으며 패션 검색 정확도는 Top-5 기준 75.28%, 벡터 검색 속도는 벡터당 0.002m sec 이하, 세그먼테이션 추출 정확도 87.6%이상, 패션 검출 결과 IoU 0.5 환경에서 96.2%, 복종분석 90.54%의 성능을 보였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.63-66
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• 2022

본 논문에서는 분자의 특성을 정확하게 예측하기 위해 효과적인 사전학습(pretraining) 전략과 트랜스포머(Transformer) 모델을 활용한 방법을 제시한다. 딥러닝을 활용한 분자의 성능을 예측하는 연구는 그동안 레이블이 부족한 분자데이터의 특성에 의해 학습 때 사용된 데이터이외의 분자데이터에 대해 일반화 능력이 떨어지는 어려움을 겪었다. 이 논문에서 제시한 모델은 사전학습(pretraining)을 수행할 때 자기지도학습(self-supervised training)을 사용하여 부족한 레이블에 의한 문제점을 피할 수 있다. 대규모 분자 데이터셋으로부터 학습된 이 모델은 4가지 다운스트림 데이터셋에 대해 모두 우수한 성능을 보여주어 일반화 성능이 뛰어나며 효과적인 분자표현을 얻을 수 있음을 보인다.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.33-35
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• 2022

빅데이터·인공지능 등 4차 산업혁명 기술은 교통·의료·환경 등 다양한 분야에서 기술개발을 추진하고 이미 많은 기술이 실제 활용되고 있다. 특히, 철도관제와 항공 관제분야에서도 인공지능 기반 시스템이 접목되어 운영되고 있으나 선박교통관제 분야는 현장에 접목되어 활용되는 기술은 극히 드물다. 선박교통관제사가 관제구역 내에서 적게는 수척, 많게는 수십척의 선박을 동시에 관제하며 발생할 수 있는 인적 과실을 줄이기 위한 인프라 구축은 선박의 안전확보를 위해 필수요소이다. 본 연구는 해양경찰청 선박교통관제기술개발단에서 자체 개발한 음주운항 자동탐지 시스템과 닻 끌림 자동탐지 시스템에 활용한 기술을 소개하고 향후 고도화 및 활용방안을 제시하고자 한다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.149-157
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• 2021

Ahead of the introduction of artificial intelligence education into the revised curriculum in 2022, various class cases based on artificial intelligence should be developed. In this study, we designed an artificial intelligence education program based on explainable artificial intelligence using design-based research. Artificial intelligence, which covers three areas of basic, utilization, and ethics of artificial intelligence and can be easily connected to real-life cases, is set as a key topic. In general design-based studies, more than three repetitive processes are performed, but the results of this study are based on the results of the primary design, application, and evaluation. We plan to design a program on artificial intelligence that is more complete based on the third modification and supplementation by applying it to the school later. This research will help the development of artificial intelligence education introduced at school.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.199-204
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• 2021

Along with the development of technology in the fourth industrial revolution, the fields that can apply artificial intelligence technology are rapidly increasing. In order to improve computational thinking, overseas countries such as the U.S. and the U.K. are already using various AI education platforms to provide artificial intelligence education. Therefore, there is an increasing need for elementary school pre-service teachers in Korea to strengthen their AI education capabilities along with the existing software education. However, it may be difficult for learners with low levels of programming experience and AI education experience to choose an AI education platform that can sustain their learning motivation. Therefore, in this study, the factors related to learning motivation in the AI education platform were explored using the ARCS model. Through this, we present the factors required by the AI education platform for motivation and sustain of learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.167-177
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• 2022

Unlike previous studies on AI chatbot preference that focused mostly on satisfaction, this study considered both satisfaction and dissatisfaction. This study established that (1) AI chatbot preference is driven by attractive, must-be, and one-dimensional qualities, (2) AI chatbot need to develop service strategies by taking into account users' satisfaction and dissatisfaction in accordance with preference drivers, and (3) users view interaction as a requisite and thus, if they are not satisfied with services of a AI chatbot, they don't tend to appeal their opinion and leave the service with AI chatbot. This study emphasizes that a AI chatbot that desires to be a dominant market player must provide differentiated services according to the preference drivers and must continuously encourage user participation in order to improve service quality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.201-208
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• 2023

As the demand for AI education increases, AI education is actively conducted in the educational field, but it is difficult to internalize AI education due to securing time, difficulty in organizing class contents, and lack of curriculum. As a way to solve this problem, there is a school autonomous course. The school autonomous course allows schools to have autonomy and discretion throughout the curriculum, such as adjusting the number of hours in the subject group and restructuring the use of achievement standards. In this study, in order to enhance AI education, the effect was analyzed by developing and applying an AI education immersion course using a school autonomous curriculum. In the AI education immersion course, students continuously experience AI education in a dense manner within a limited time, so substantial AI education can be achieved. After the AI curriculum, it was found that students' overall AI literacy and self-determination learning motivation improved. It is expected that this study will be able to present a direction to internalize AI education using school autonomous curriculum.