• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.52-56
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• 2004

Unmanned Aerial Vehicles (UAVs) are remotely piloted or self-piloted aircraft by inputted program in advance or artificial intelligence. In this study Aileron and Elevator are used to control the movement of airplane for horizontal and vertical flights about its longitudinal and lateral axis. In an introduction, the drone was linearly modeled by extracting aerodynamic parameter through flight test and simulation, lift and drag coefficient corresponding to angle of attack, changes of pitching moment coefficient. In the main subject, the flight simulation was performed after constructing hardware using TMS320F2812 from TI company and PID with lateral and longitudinal controller for horizontal and vertical flights. Flying characteristics of two system were estimated and compared through real flight test with hardware equipped algorithm and adaptive algorithm that was applied to consider external factors such as turbulence. In conclusion the control performance of the controller with proposed algorithm was streamlined at lateral and longitudinal controller respectively, we will discuss guidance command to pass way point.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.201-207
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• 2003

인터넷의 사용이 보편화됨에 따라 인터넷을 통한 정보 제공 서비스가 확대되고 있다. 이에 따라 빠르게 변화하는 사용자의 요구를 만족시킴과 동시에 편리하고 유용한 서비스를 제공하기 위하여 사용자와 자연스럽게 의사소통할 수 있는 대화형 에이전트의 연구가 활발히 진행되고 있다. 더불어 시스템의 효율적인 설계 또한 중요한 문제가 아닐 수 없다. 본 논문에서는 패턴매칭 기법과 베이지안 네트워크를 이용해 사용자 질의에 대한 적절한 답변을 생성하고, 스크립트 인터페이스를 통한 자동 스크립트 설계로 보다 효율적인 시스템 구축 방안을 제안해 보고자 한다. 실제 의류 사이트를 위한 안내 도우미 에이전트를 구현해 봄으로써 그 기능성을 평가해 본다.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.160-165
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• 2018

This paper designed and developed the image processing system of integrating feature extraction and matching by using convolutional neural network (CNN), rather than relying on the simple method of processing feature extraction and matching separately in the image processing of conventional image recognition system. To implement it, the proposed system enables CNN to operate and analyze the performance of conventional image processing system. This system extracts the features of an image using CNN and then learns them by the neural network. The proposed system showed 84% accuracy of recognition. The proposed system is a model of recognizing learned images by deep learning. Therefore, it can run in batch and work easily under any platform (including embedded platform) that can read all kinds of files anytime. Also, it does not require the implementing of feature extraction algorithm and matching algorithm therefore it can save time and it is efficient. As a result, it can be widely used as an image recognition program.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.6
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• pp.187-196
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• 2001

In this study, by using the natural language processing of the field of artificial intelligence, automated index was performed. And then, the Natural Language Processing Interface for knowledge representation(NALPI) has been developed. Furthermore, the DEsign KnOwledge DataBase(DEKODB) has been also developed, which is designed to interlock the knowledge base. The DEKODB processes both the documented design-data, like a concrete standard specification, and the design knowledge from an expert. The DEKODB is also simulates the design space of structures accordance with the production rule, and thus it is determined that DEKODB can be used as a engine to retrieve new knowledge and to implement knowledge base that is necessary to the development of automatic design system. The application field of the system, which has been developed in this study, can be expanded by supplement of the design knowledge at DEKODB and developing dictionaries for foreign languages. Furthermore, the perfect automation at the data accumulation and development of the automatic rule generator should benefit the unified design automation.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.38-44
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• 1996

The CAD system for design and drawing of limit gauges was constructed and developed. This system was made by Visual Basic program. Using this system, drawings together with concerned data for the manufacturing of limit gauges are generated on the screen, file and printer. The data base was constructed by referring handbooks, textbooks, relevant standards and regulations. This system was proved a powerful tool for design and drawing of limit gauges by actual applications. The output drawings from this system are in good agreement with the drawings and data of the concerned standards and regulations.

• Journal of Energy Engineering
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• v.26 no.3
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• pp.11-29
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• 2017

In recent years, the use of artificial intelligence technology such as deep neural net machine learning(deep learning) is becoming an effective and practical option in industrial manufacturing process. This study focuses on recent deep learning development environments and their applications in the manufacturing field.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.285-286
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• 2016

본 연구는 가상현실시스템을 이용한 훈련이 뇌졸중 환자의 균형과 낙상효능감에 미치는 영향을 알아보기 위해 실시하였다. 연구 대상자는 뇌졸중 환자 20명으로 실험군 10명 대조군 10명씩 각각 배정하였다. 실험군과 대조군 모두 일반적인 주 5회의 물리치료와 작업치료를 받았다. 실험군은 추가적으로 가상현실 프로그램을 이용하여 8주간 1일 20분 주 3회 시행하였다. 본 연구의 측정은 균형수행 능력검사, 낙상효능감 척도검사를 사용하였다. 두 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 또한 각 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 따라서 가상현실 프로그램 병행한 훈련이 뇌졸중 환자의 균형과 낙상효능감을 향상시키는데 긍적적인 도움을 주어 유용한 뇌졸중 환자의 치료 프로그램으로 사용될 수 있을 것으로 보여 진다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.1
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• pp.16-21
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• 1990

A Knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. Expert system has the potential to solve a wide range of problems which require knowledge about the problem rather than a purely analytical approach. This papaer presents the application of knowledge based expert system to power system fault diagnosis. The contents of expert system develpped in this paper is judgement of fault section from a given alarm sets and production of all possible hypothesis for the single fault. Both relay failures and circuit breaker failures are considered simultaneously. Although many types of relay are used in actual system, experts recognize ones as several typical signals corresponding to the fault types. Therefore relays are classified into several types. The expert system is written in an artificial intelligence language "PROLOG" . Best-first search method is used for problem solving. Both forward chaining and backward chaining schemes are used in reasoning process. The application to a part of actual power system proves the availability of the developed expert system.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.35-44
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• 2021

The Myanmar rice cycle's existing system is still relying on a third party to manage every rice data information from several organizations. It is inconvenient to supervise simultaneously due to the unreliability of information provided by organizations. Thus, the rice cycle's original data is challenging to be utterly trusted since irresponsible parties can manipulate the current state of information. Moreover, the applied system does not preserve a proper incentive for the involved parties. In this paper, we leverage the Ethereum blockchain to be adopted to tackle the aforementioned issues. The main objective is to build trust between parties in the Myanmar rice cycle system. Our proposed scheme allows customers to check and trace information about the rice cycle information without worrying about the integrity of the data. Furthermore, the authorized parties are also rewarded by the government through Ethereum smart contract features. Eventually, our scheme achieves traceability in the rice chain system and leads to the complete digitization and automation of the rice cycle information.