• 농촌지도와개발
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• 제8권1호
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• pp.107-119
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• 2001

As the information gap between rural and urban area, and between men and women has been widening, the Rural Development Administration(RDA) has initiated the women farmers information project from 2000. The aims of this project are; 1) to facilitate women farmers' computer and information application in agriculture and income generating activities, and 2) to make them to be leaders to popularize computer application in rural area and agricultural sector. For these, RDA has provided not only PC, software, computer training but also the post support of extension educator to target group. This paper focused on evaluating the effect of the project, clarifying the related variables with the effect, and providing suggestions to enhance the effect. The data were gathered from 310 target women farmers and 166 extension educators in charge of the project all over the country by mailing survey with questionnaire. The main findings of this study were as follows; 1) The level of computer application of the target group was improved drastically, 2) As their self-assessment, they could improve psychological fear on the computer, recognition about information, and attitude to seek information, 3) This project was helpful for them in terms of information gathering and farm(or income generating activities) management, 4) They tried to disseminate the benefit of computer application to neighbors, so that the neighbors' interest in computer and attendance of computer training were improved, 5) Variables such as the computer training hours, the number of interaction with extension educator, formal schooling and farming history were significantly related to the project's effect. To enhance the project's effect the following strategies should be carried out; 1) The period of the computer training course should be standardized and the subjects should attend to the computer training course for the standardized period. 2) Through continuous interaction with the subjects, the extension educator should support them to use computer well and to overcome some difficulties as a beginner. 3) In selecting the subjects, the priority should be given to the person who graduated high school at least. 4) The subjects should focus on using management software, gathering useful information for their business, and selling their products directly to the consumer. 5) So as to enhance the abilities mentioned above, RDA should strengthen learning opportunities through on-line training and providing educational software, besides of existing off-line training.

• 한국IT서비스학회지
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• 제11권1호
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.65-70
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• 2021

According to the trend of increasingly sophisticated cyber threats, the need for technology research that can be applied to cyber security personnel management and training systems is constantly being raised not only overseas but also in Korea. Previously, the US and UK have already recognized the need and have been steadily conducting related research from the past. In the United States, by encouraging applications based on related research (NICE Cybersecurity Workforce Framework) and disclosing successful use cases to the outside, it is laying the groundwork for profiling cyber security experts. However in Korea, research on cyber security expert training and profiling is insufficient compared to other countries. Therefore, in this study, in order to create a system suitable for the domestic situation, research and analysis of cases in the United States and the United Kingdom were conducted over the past few years, and based on this, a prototype was produced for the study of profiling technology for domestic cyber security experts.

• 컴퓨터교육학회논문지
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• 제22권3호
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• pp.113-121
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• 2019

본 연구에서는 교사들의 소프트웨어 교육 및 정보 교육 수업 전문성 함양을 위하여 백워드 설계를 기반으로 TPACK-P 교육 프로그램에 백워드 설계의 이해에 대한 내용을 포함하여 설계하였다. 이를 비정보과 교사를 대상으로 32시간의 교사 연수를 실시한 결과, 교사들은 SW교육 교수 효능감 측정도구(SE-TEBI)의 사후 검사 결과가 사전 검사에 비해 SE-TE 전체 값(t=-3.541, p<.01) 및 하위 범주인 개인효능(t=-3.559, p<.01), 결과기대(t=-2.258, p<.05)가 모두 통계적으로 유의하게 상승하였음을 확인하였다. 따라서 본 연구에서 개발한 백워드 설계 기반 TPACK-P 교육 프로그램은 교사들의 소프트웨어 교육 및 정보 교육에 대한 수업 전문성을 높이는데 도움이 된다고 해석할 수 있다. 하지만 검사 결과 전반적으로 교사들의 개인효능(PSETE)이 결과기대(SEOE)보다 낮은 경향을 보이는데, 이는 수업에 대한 자신감의 부족으로 해석된다. 따라서 추후 연구에서는 교사들의 수업 자신감을 촉진할 수 있는 교사 교육 프로그램의 개발이 요구된다.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.214-224
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• 2017

本文运用文献计量分析的可视化软件 CiteSpace 对 CNKI 数据库平台上收录的我国高校工程管理人才培养研究相关文献进行分析, 了解我国高校工程管理人才培养研究现状以及研究的发展轨迹。 研究结果显示: 我国高校工程管理人才培养研究持续活跃, 文献数量呈稳步上升趋势, 载文期刊分布广泛, 研究者多, 但各研究机构之间合作少; 研究热点主要集中在应用型工程管理人才培养,实践教学改革和课程体系改革等方面。 为此, 我国高校工程管理人才培养相关研究可加强学术团体间的合作, 拓展研究对象的范围, 丰富研究视角, 并进一步探讨 "新工科" 发展下的工程管理人才培养。

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• ETRI Journal
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• 제30권6호
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• pp.865-867
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• 2008

A conventional environment adaptation for robust speech recognition is usually conducted using transform-based techniques. Here, we present a discriminative adaptation strategy based on a multi-condition-trained model, and propose a new method to provide universal application to a new environment using the environment's specific conditions. Experimental results show that a speech recognition system adapted using the proposed method works successfully for other conditions as well as for those of the new environment.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.1051-1054
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• 2017

이 논문에서는 인공지능 기반의 드럼 연습 시스템을 설명하고 있다. 먼저 사용자의 드럼 신로를 MIDI 파일로 변환하고, 이를 DB에 저장되어있던 추천곡의 MIDI 파일과 비교하여 가장 유사한 것을 추천해준다. 또한 실시간으로 사용자의 드럼 연습을 도와주는 전문가 시스템역할을 함으로써 연주의 숙련도를 높여준다.

• 한국항행학회논문지
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• 제24권5호
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• pp.343-347
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• 2020

본 논문에서는 수중에서의 물체위치추적 소프트웨어와 수중선저 입체지도 생성 소프트웨어를 개발하였다. 선저청소로봇을 위한 소프트웨어로써 선저 청소로봇의 위치를 추적하고 음파통신의 음영지역을 발견함으로써 센서의 정위 구현을 목표로 하였다. 수중에서 로봇의 위치를 추적하기 위하여 개발된 소프트웨어는 수중의 초음파통신에 변수로 작용하는 파도의 고저와 세기를 적용하였다. 선(lines)들을 이용하여 그려진 선박의 도면을 스캔하여 OpenGL을 이용하여 입체지도를 형성하는 소프트웨어를 개발하였다. 이는 청소로봇이 비가시적인 수중 선저에서의 위치파악이 용이하며, 선저의 굴곡으로 인한 초음파통신 음영지역을 쉽게 발견함으로써 그에 따른 센서의 정위를 구현하여 원활한 통신 상태를 유지하는데 활용될 수 있다.

• 항공우주시스템공학회지
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• 제16권1호
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• pp.40-48
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• 2022

최근 AR기술을 접목한 UAV 기반 재난구조 시스템이 연구되고 있다. 일반적으로 실제 재난 현장과 유사한 환경에서 재난 구조 훈련을 진행하는 것은 높은 비용과 사고 위험이 야기된다. 본 논문에서는 AR 기술을 접목한 UAV 기반 재난구조 시스템의 운용을 구조요원이 저렴하고 안전하게 훈련할 수 있도록 VR 기술을 이용한 훈련 시뮬레이션 소프트웨어를 제안한다. 기존 시스템의 분석을 통하여 훈련을 가상화하기 위한 요구사항을 도출하고 Unreal Engine 및 Airsim API를 이용하여 제안하는 시뮬레이션 소프트웨어를 개발한다. 모의실험은 제안하는 시뮬레이션 소프트웨어가 기존 재난구조 플랫폼의 동작을 효과적으로 모의할 수 있음을 보여준다.