• Title/Summary/Keyword: 인공지능알고리즘

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Artificial Intelligence Applications to Music Composition (인공지능 기반 작곡 프로그램 현황 및 제언)

  • Lee, Sunghoon
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.4
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    • pp.261-266
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    • 2018
  • This study aimed to provide an overview of artificial intelligence based music composition programs. The artificial intelligence-based composition program has shown remarkable growth as the development of deep neural network theory and the improvement of big data processing technology. Accordingly, artificial intelligence based composition programs for composing classical music and pop music have been proposed variously in academia and industry. But there are several limitations: devaluation in general populations, missing valuable materials, lack of relevant laws, technology-led industries exclusive to the arts, and so on. When effective measures are taken against these limitations, artificial intelligence based technology will play a significant role in fostering national competitiveness.

A proposed framework for UX evaluation of artificial intelligence services (인공지능 서비스 UX 평가를 위한 프레임워크)

  • Hur, Su-Jin;Youn, Joosang;Kim, Sung-Hee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.274-276
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    • 2021
  • As artificial intelligence develops rapidly, we can experience it in our everyday life such as with medical, education, and game applications. Traditional SW services were programmed explicitly by the intention of the programmer, and we have conducted evaluation on it. However, due to the uncertianty of AI services, risk follows to the products. Therefore, UX evaluations need to be different from traditional UX evaluations. Therefore, in this paper we suggest a AI-UX framework that consideres the task delegability, UX evaluations metrics, and individual differences.

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Proposal of AI-based Graffiti Robot for Children disconnected from Peers with COVID-19 (코로나19로 또래와 단절된 아동을 위한 인공지능 낙서 로봇 제안)

  • Song, Ju-Yeon;Lee, Kang-Hee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.07a
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    • pp.29-31
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    • 2020
  • 본 논문에서는 코로나19 사태로 인한 팬데믹(pandemic) 현상으로 인해 또래와 단절된 아동들의 정서발달을 위해 인공지능 낙서 로봇인 Doodle Robot을 제안한다. Doodle Robot은 또래 형제가 없는 아동에게 함께 그림을 그릴 수 있는 그림친구로서 아동의 정서적 발달에 기여한다. YOLO 알고리즘을 사용하여 객체검출기능을 구현하였고 낙서 Data는 Quick! Draw Dataset에서 추출하였다.

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The Improvement Plan for Personal Information Protection for Artificial Intelligence(AI) Service in South Korea (우리나라의 인공지능(AI)서비스를 위한 개인정보보호 개선방안)

  • Shin, Young-Jin
    • Journal of Convergence for Information Technology
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    • v.11 no.3
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    • pp.20-33
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    • 2021
  • This study is to suggest improvements of personal information protection in South Korea, according to requiring the safety of process and protection of personal information. Accordingly, based on data collection and analysis through literature research, this study derived the issues and suitable standards of personal information for major artificial intelligence services. In addition, this cases studies were reviewed, focusing on the legal compliance and porcessing compliance for personal information proection in major countries. And it suggested the improvement plan applied in South Korea. As the results, in legal compliance, it is required reorganization of related laws, responsibility and compliance to develop and provide AI, and operation of risk management for personal information protection laws in AI services. In terms of processing compliance, first, in pre-processing and refining, it is necessary to standardize data set reference models, control data set quality, and voluntarily label AI applications. Second, in development and utilization of algorithm, it is need to establish and apply a clear regulation of the algorithm. As such, South Korea should apply suitable improvement tasks for personal information protection of safe AI service.

Application of object detection algorithm for psychological analysis of children's drawing (아동 그림 심리분석을 위한 인공지능 기반 객체 탐지 알고리즘 응용)

  • Yim, Jiyeon;Lee, Seong-Oak;Kim, Kyoung-Pyo;Yu, Yonggyun
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.5
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    • pp.1-9
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    • 2021
  • Children's drawings are widely used in the diagnosis of children's psychology as a means of expressing inner feelings. This paper proposes a children's drawings-based object detection algorithm applicable to children's psychology analysis. First, the sketch area from the picture was extracted and the data labeling process was also performed. Then, we trained and evaluated a Faster R-CNN based object detection model using the labeled datasets. Based on the detection results, information about the drawing's area, position, or color histogram is calculated to analyze primitive information about the drawings quickly and easily. The results of this paper show that Artificial Intelligence-based object detection algorithms were helpful in terms of psychological analysis using children's drawings.

Development of Data Driven Flood Arrival Time and Water Level Estimation Simulator (데이터 기반 홍수 도달시간 및 수위예측 시뮬레이터 개발)

  • Lee, Ho Hyun;Lee, Dong Hun;Hong, Sung Taek;Kim, Sung Hoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.104-104
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    • 2022
  • 임진강 수계는 북측 지역이 다수를 차지하는 유역 특성으로 예고 없는 상류 급방류, 강우 등으로 인해 댐 운영에 근본적 어려움이 있으며, 이에 따라 홍수조절지 및 댐 하류 계측 가능 지역의 취득 자료를 고려한 하천 수위 변화에 대한 사전 예측을 필요로 하고 있다. 홍수기 하천 도달시간 및 수위예측 기법으로는 물리 기반 및 데이터 기반 모델들이 다양하게 연구되어 왔으며, 일부 연구성과들은 현업에 활용하고 있다. 물리기반 모델은 하천 지형 변화에 대한 자료 취득 및 분석에 많은 시간을 요하는 단점은 있으나, 설명 가능한 모델을 구현할 수 있을 것으로 사료 된다. 반면, 데이터 기반 인공지능 모델은 짧은 시간 및 비용으로 모델을 개발할 수 있으나, 복잡한 알고리즘구현 시 설명이 불가하여 일관성을 의심 받을 수 있다. 본 논문에서는 홍수 도달시간과 하류 수위 상승에 대하여 설명 가능한 인공지능 알고리즘 및 시뮬레이션 프로그램을 개발하고자 하였다. 홍수 도달시간 예측은 기존 조견표 방식에서 고려하지 않았던 홍수파의 영향을 추가 변수화 하고, 데이터의 전후처리를 통하여 도달시간을 예측하였다. 실시간 하류 수위 예측은 댐 방류량, 주변 강우, 조위 등을 고려하여 도달시간 후 수위를 예측할 수 있도록 구현하였으며, 자료 동화 기술을 일부 적용하였다. 미래 방류조건에 대한 시뮬레이션을 위해서는 미래 방류량, 예상 강우 입력 시 하천 지점별 수위 상승을 예측할 수 있도록 알고리즘 및 프로그램을 개발하였다. 이를 구현하기 위하여 다양한 인공지능 알고리즘을 이용한 학습, 유전자 알고리즘을 이용한 가중치 학습 제한 조건내 최적화, 수위파와 조위파의 중첩의 정리 등을 이용하여 예측 정확도 및 신뢰성을 제고 하였다. 인공지능 분석결과의 현업활용성 제고를 위하여 시뮬레이터 프로그램을 개발하여 현업에 적용하였다.

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Distributed Autonomous Robotic System based on Artificial Immune system and Distributed Genetic Algorithm (인공 면역 시스템과 분산 유전자 알고리즘에 기반한 자율 분산 로봇 시스템)

  • Sim, Kwee-Bo;Hwang, Chul-Min
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.164-170
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    • 2004
  • This paper proposes a Distributed Autonomous Robotic System(AIS) based on Artificial Immune System(AIS) and Distributed Genetic Algorithm(DGA). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: dispersion and aggregation. AIS decides one among above two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the DGA in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

Artificial Intelligence-based Leak Prediction using Pipeline Data (관망자료를 이용한 인공지능 기반의 누수 예측)

  • Lee, Hohyun;Hong, Sungtaek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.963-971
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    • 2022
  • Water pipeline network in local and metropolitan area is buried underground, by which it is hard to know the degree of pipe aging and leakage. In this study, assuming various sensor combinations installed in the water pipeline network, the optimal algorithm was derived by predicting the water flow rate and pressure through artificial intelligence algorithms such as linear regression and neuro fuzzy analysis to examine the possibility of detecting pipe leakage according to the data combination. In the case of leakage detection through water supply pressure prediction, Neuro fuzzy algorithm was superior to linear regression analysis. In case of leakage detection through water supply flow prediction, flow rate prediction using neuro fuzzy algorithm should be considered first. If flow meter for prediction don't exists, linear regression algorithm should be considered instead for pressure estimation.

기업부도예측을 위한 통합알고리즘

  • Bae Jae-Gwon;Kim Jin-Hwa
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2006.06a
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    • pp.195-202
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    • 2006
  • 본 연구에서는 보다 효과적인 기업부도예측을 위하여, 동계적 방법과 인공지능 방법을 결합한 통합모형을 제시하였다. 이를 위하여 통계적인 모형 중에서 가장 널리 활용되고 있는 다변량 판별분석, 로지스틱 회귀분석과 인공 지능적인 방법으로서 최근 널리 사용되고 있는 인공신경망, 규칙유도기법, 베이지안 망의 5가지 방법론을 통합한 Voting with Performance & Weights from ANN(WP-ANN) 통합모형을 제시하였다. 실험결과, 본 연구에서 제안한 WP-ANN 통합모형은 다변량 판별분석, 로지스탁 회귀분석, 인공신경망, 규칙유도기법, 베이지안 망 등의 단일모형과 비교한 결과 가장 예측정확성이 유수한 것으로 나타났다. 따라서 본 연구를 통해 기업부도예측에 있어서 WP-ANN 통합모형이 기존의 모형들에 비해 우수한 예측정확성을 나타냄을 알 수 있었다.

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Study on Development of Graphic User Interface for TensorFlow Based on Artificial Intelligence (인공지능 기반의 TensorFlow 그래픽 사용자 인터페이스 개발에 관한 연구)

  • Song, Sang Gun;Kang, Sung Hong;Choi, Youn Hee;Sim, Eun Kyung;Lee, Jeong- Wook;Park, Jong-Ho;Jung, Yeong In;Choi, Byung Kwan
    • Journal of Digital Convergence
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    • v.16 no.5
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    • pp.221-229
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    • 2018
  • Machine learning and artificial intelligence are core technologies for the 4th industrial revolution. However, it is difficult for the general public to get familiar with those technologies because most people lack programming ability. Thus, we developed a Graphic User Interface(GUI) to overcome this obstacle. We adopted TensorFlow and used .Net of Microsoft for the develop. With this new GUI, users can manage data, apply algorithms, and run machine learning without coding ability. We hope that this development will be used as a basis for developing artificial intelligence in various fields.