• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.79-82
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• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.603-609
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance procedures. Condition Monitoring System(CMS) can be used to aid plant owners in achieving these goals. Its aim is to provide operators with information regarding the health of their machines, which in turn, can help them improve operational efficiency. In this work, systematic design procedure for artificial neural network based normal behavior model which can be applied for fault detection of various devices is proposed. Furthermore, to verify the design method SCADA(Supervisor Control and Data Acquisition) data from 850KW wind turbine system installed in Beaung port were utilized.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.193-206
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• 2021

Artificial Intelligence (AI) has been inserted into people's lives through Intelligent Virtual Assistants (IVA), like Alexa. Moreover, intelligent systems have expanded to design studios. This research delves into designers' perspectives on developing AI-based practices and examines the challenges of adopting future intelligent design assistants. We surveyed UX/UI professionals in Brazil to understand how they use IVAs and AI design tools. We also explored a scenario featuring the use of Alexa Sensei, a hypothetical voice-controlled AI-based design assistant mixing Alexa and Adobe Sensei characteristics. The findings indicate respondents have had limited opportunities to work with AI, but they expect intelligent systems to improve the efficiency of the design process. Further, majority of the respondents predicted that they would be able to collaborate creatively with AI design systems. Although designers anticipated challenges in natural language interaction, those who already adopted IVAs were less resistant to the idea of working with Alexa Sensei as an AI design assistant.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.687-699
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• 2021

When a vulnerability occurs in a program, it is documented and published through CVE. However, some vulnerabilities do not disclose the details of the vulnerability and in many cases the source code is not published. In the absence of such information, in order to find a vulnerability, you must find the vulnerability at the binary level. This paper aims to find out-of-bounds read vulnerability that occur very frequently among vulnerability. In this paper, we design a memory area using memory access information appearing in binary code. Out-of-bounds Read vulnerability is detected through the designed memory structure. The proposed tool showed better in code coverage and detection efficiency than the existing tools.

• Journal of the Korea Computer Graphics Society
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• v.1 no.2
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• pp.279-283
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• 1995

21세기 정보화 시대에 효과적으로 대비하기 위해 세계 여러나라에서 추진하고 있는 정보화 사회를 구축하는데 필수적인 요소로 lnfrastructure인 초고속 정보 통신망을 구축하고 있다. 이에 따라 국내에서도 정부주도로 초고속망을 이용한 대국민 서비스 사업을 추진하고 있고, 이 사업의 일환으로 문화체육부에서도 국립중앙박물관을 중심으로 대국민 서비스용 문화정보망 구축을 추진하고 있다. 이러한 문화정보망 사업의 최종 목표는 종래의 개념을 넘어선 인간에게 가장 현실감을 줄 수 있는 "가상박물관"과 같이 문화재를 글, 그림 이외에 3차원 업체형상을 가진 문화재를 3차원적으로 표현하여 보이지 않는 부분을 볼 수 있도록 문화재를 이동, 회전 및 확대, 축소 표현이 가능한 3차원 형상정보 데이타베이스를 구축하여야 한다. 본 과제에서는 이러한 3차원 형상정보 데이타베이스 구축을 위해, 컴퓨터 그래픽스 기술과 인공지능 기술이 복합적으로 구현된 3차원 입체형상 자동 입력 시스템 및 모델링 시스템과 지원 도구 개발을 목표로 진행되고 있다. 이 시스템이 완성되면 문화재 형상의 영구보존, 문화재의 특성(크기,색,무늬,질감) 보존, 문화재 형상 복원 및 문화재의 시대적 상대평가를 용이하게 하는 효과를 얻을 뿐아니라, 컴퓨터 그래픽스 기술 및 정보처리 기술을 문화재 연구와 전시에 적용하여 문화정보망 사업의 구체적 효과를 가시화 할 수 있다.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.419-434
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• 2020

The purpose of the study is to design and propose metadata standard for building AI training dataset of landmark images. In order to achieve the purpose, we first examined and analyzed the state of art of the types of image retrieval systems and their indexing methods, comprehensively. We then investigated open training dataset and machine learning tools for image object recognition. Sequentially, we selected metadata elements optimized for the AI training dataset of landmark images and defined the input data for each element. We then concluded the study with implications and suggestions for the development of application services using the results of the study.

• Annual Conference of KIPS
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• 2019.05a
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• pp.346-347
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• 2019

의료영상은 환자의 질병을 진단하고 치료방침을 결정하는데 중요한 도구로 자리매김하고 있다. 최근 의료영상을 인공지능 연구가 국내외에서 활발하게 진행되고 있다. 특히 대규모의 의료영상들을 학습시켜 질병과 상태를 정밀 진단할 뿐만 아니라 예측하는 소프트웨어를 개발 하는 상황이다. 그러나 의료영상은 DICOM 표준에 따르고 있지만 태그정보의 사용은 의료기기와 의료기관마다 상이하다. 따라서 의료영상에 대한 메타 데이터의 표준화에 어려움이 있다. 본 논문은 이러한 의료영상 데이터를 표준화 할 수 있는 방법을 제안한다. 그리고 제안한 표준화 데이터로 변환할 수 있는 ETL 소프트웨어의 수행결과를 보이고, 조건에 따라 머신러닝 학습 데이터셋을 생성하는 결과를 제공한다. 향후 제안한 의료영상 표준화와 ETL 소프트웨어는 다양한 수요자 중심의 표준화된 데이터셋을 제공할 수 있는 플랫폼의 주요기능으로 활용 될 것으로 기대한다.

• Annual Conference of KIPS
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• 2021.11a
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• pp.602-605
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• 2021

최근 인공지능 연구가 활발히 진행되고 있는 가운데 국내외에서 오픈 데이터셋을 제공하고 있어 기술개발이 가속화되고 있다. 데이터셋은 지도학습을 위한 학습데이터로 라벨링 데이터를 포함하고 있어 다양한 라벨링 기능이 적용된 도구 개발이 필요하다. 본 논문에서는 의료영상의 라벨링 데이터를 정교하고 빠르게 생성하기 위한 라벨링 웹 애플리케이션에 대해서 기술한다. 이를 구현하기 위해서 Back Projection, Grabcut 기법을 이용한 반자동 방식과 기계학습 모델을 통해서 예측한 자동 방식의 라벨링 기능을 구현하였다. 이와 관련하여 라벨링 기능별 수행 결과를 근감소증 진단을 위한 영상 라벨링 수행결과와 정량분석 결과를 보였다.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.83-90
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• 2020

Disasters are causing significant damage to the lives and property of our society and are recognized as social problems that need to be solved nationally and globally. The 4th industrial revolution technologies affecting society as a whole such as the Internet of Things(IoT), Artificial Intelligence(AI), Drones(Unmanned Aerial Vehicles), and Big Data are continuously absorbed into the disaster and safety industries as scientific and technological tools for solving social problems. Very soon, twenty-nine domestic UAV-related organizations/companies will complete the construction of a multicopter type small UAV integrated system ('17~'20) that can be operated at disaster and security sites. The current work considers and proposes the mid-to-long term R&D direction of disaster UAV as a strategic asset of the national disaster response system. First, the trends of disaster and safety industry and policy are analyzed. Subsequently, the development status and future plans of small UAV, securing shortage technology, and strengthening competitiveness are analyzed. Finally, step-by-step R&D direction of disaster UAV in terms of development strategy, specialized mission, platform, communication, and control and operation is proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1693-1699
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• 2019

The recent software education in middle schools is focused on physical computing, unplugged learning and pilot training. However, they are struggling in many ways, including cost, inducement of interest, motivation, and concentration. Also, the lack of systematic classroom design could make negative effect to students' understanding of classes or academic performance. In this paper, we intend to study the method of algorithm education using Chatbot system, which will increase efficiency of software education, with less burdensome in terms of cost, and also could be able to used as an assist tool in various classes. In class scenarios that require the understanding of coding mechanisms such as function application, algorithm design, and program coding, students can learn by themselves through the Chatbot system, which has a positive effect on student learning.