• Education of Primary School Mathematics
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• v.27 no.1
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• pp.19-38
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• 2024

This study aims to analyze the characteristics of students' understanding of artificial intelligence and mathematical concepts by developing and applying an artificial intelligence education program for mathematics convergence using robots. To this end, we analyzed the content standards of elementary artificial intelligence education to extract conceptual elements of artificial intelligence and identified mathematics achievement standards that can effectively integrate them. In particular, a five-session (15 classes in total) program was developed by selecting the units 'angle' and 'quadrilateral' suitable for utilizing the robot's movement and reorganizing the lesson to integrate the mathematics achievement standard with the artificial intelligence content elements. As a result of applying this to 22 fourth grade elementary school students over five months and analyzing the students' understanding revealed by topic of artificial intelligence content, the artificial intelligence education program for mathematics convergence using robots was helpful in students' understanding artificial intelligence principles and mathematical concepts. In addition, the use of robots was confirmed to improve students' understanding of artificial intelligence and mathematics as well as their participation in class by making them visually check a series of performing procedures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.74-75
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• 2013

Pseudolite is a contraction of the term "pseudo-satellite," used to refer to something that is not a satellite which performs a function commonly in the domain of satellites. Pseudolite are most often small transceivers that are used to create a local, ground-based GPS alternative. This paper proposes a clock synchronization scheme for pseudolite.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.846-848
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• 2018

최근 4차 산업혁명이 이슈가 되면서 빅 데이터나 인공지능에 대한 연구가 활발해지고, 이를 통해 자동화 및 자율화가 제조 공정이나 차량 운행 등에서 활용되고 있다. 또한 이를 위해서 데이터를 분석하고 정제하며 시각화를 효과적으로 하는 방법에 대한 관심도 같이 늘어나고 있다. 본 논문에서는 자동화 공장의 제품을 관리함에 있어 데이터를 쉽게 이해할 수 있도록 시각화하는 방법에 대한 연구를 수행했다. 이를 위해 D3 자바스크립트 라이브러리를 통해 웹기반으로 구현한 제품과 장애를 효과적으로 관리할 수 있는 시스템을 개발했다. 제안하는 관리 시스템은 자동화 공장의 제조 공정 중 제품이나 장애 상황에 대한 이해를 빠르게 하도록 하여 의사결정 하는데 기여할 것이다.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2001.10a
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• pp.66-67
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• 2001

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2001.05a
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• pp.40-41
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• 2001

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.233-242
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• 2021

In this paper, as a liberal arts course for non-majors, we proposed a supervised learning artificial neural network parameter optimization method and a basic education method for activation function to design a basic artificial neural network subject curriculum. For this, a method of finding a parameter optimization solution in a spreadsheet without programming was applied. Through this training method, you can focus on the basic principles of artificial neural network operation and implementation. And, it is possible to increase the interest and educational effect of non-majors through the visualized data of the spreadsheet. The proposed contents consisted of artificial neurons with sigmoid and ReLU activation functions, supervised learning data generation, supervised learning artificial neural network configuration and parameter optimization, supervised learning artificial neural network implementation and performance analysis using spreadsheets, and education satisfaction analysis. In this paper, considering the optimization of negative parameters for the sigmoid neural network and the ReLU neuron artificial neural network, we propose a training method for the four performance analysis results on the parameter optimization of the artificial neural network, and conduct a training satisfaction analysis.

• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.340-361
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• 2019

This study analyzes the technological structure of artificial intelligence (AI) and technological capabilities of AI companies based on patent information. 2589 AI patents registered in USPTO from 2007 to 2017 were collected and analyzed by the Latent Dirichlet Allocation (LDA) to derive 20 AI technology topics. Analysis of technology development trends by AI technology reveals that visual understanding, data analysis, motion control, and machine learning are growing, while language understanding and speech technology are sluggish. In addition, we also investigated leading companies in each sub-field of AI as well as core competencies of global IT companies. The findings of this study are expected to be fruitfully used for formulation and implementation of technology strategy of AI companies.

• Bulletin of the Korean Space Science Society
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• 2004.04a
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• pp.65-65
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• 2004

국가지정연구실 사업인 “인공위성 및 지구접근천체 감시연구(NEOPAT)”에서는 인공위성에 대한 거리 정보를 광학 관측으로부터 결정하기위하여 2개의 관측소에서 동일한 시각에 동일한 위성에 대한 관측을 진행하는 스테레오 관측 연구를 진행하였다. 이를 위해서 대전에 위치한 한국천문연구원의 60cm 광시야 망원경과 천안 연세대 관측소의 50cm 광시야 망원경 그리고 200mm NIKON 렌즈에 2K CCD로 구성된 소형 위성관측 시스템(KASAT) 2기를 사용하여 2003년부터 2004년까지 고도별 위성들에 따른 동시 관측을 시도하였다. (중략)

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.698-701
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• 2024

인공지능 기술이 발전함에 따라 인공지능은 인간이 하는 업무들을 대체하고 있다. 현재 인공지능 기술은 시각, 청각 분야로 초점이 맞춰져 있으나 최근 후각 분야에 관련된 연구도 활발히 진행 중이다. 후각 AI는 식품, 의료, 보안, 안전 등에 활용될 전망이며 본 논문에서는 우리 사회의 안전불감증 문제를 언급하고 오작동 비율이 높은 화재경보기에 후각 AI를 대입하여 화재경보기의 오작동 비율을 줄이고 화재경보기에 대한 인식을 해결되는 것을 기대한다.

• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.409-414
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• 2000

A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.