• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
• /
• pp.24.1-24
• /
• 1996

The development of future aircraft that involves the expanded flight envelop will place increased performance requirements on the design of the flight control system. Maneuvering areas are expanding into flight envelopes characterized by significantly larger levels of modeling uncertainty than encountered in present flight control designs. Conventional flight control techniques that ignore the effects of large parameter variations, modeling uncertainties and nonlinearities, will likely produce designs with poor performance and robustness. Recent advances in modern control theories called advanced control theories, most notably the H$\_$.inf./ synthesis technique, adaptive control and neural network application, offer the promise of a design technique that can produce both high performance and robust controllers for next generation aircraft. This special lecture will survey the recent development in advanced flight control and review the possible application of advanced control theories.

• International Journal of Internet, Broadcasting and Communication
• /
• 제12권3호
• /
• pp.32-38
• /
• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.1570-1575
• /
• 1991

The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권3호
• /
• pp.1333-1343
• /
• 2016

Spectrum sharing in centrally controlled cognitive radio (CR) networks has been widely studied, however, research on channel access for distributively controlled individual cognitive users has not been fully characterized. This paper conducts an analysis of random channel access of cognitive users controlled in a distributed manner in a CR network. Based on the proposed estimation method, each cognitive user can estimate the current channel condition by using its own Markov-chain model and can compute its own blocking probability, collision probability, and forced termination probability. Using the proposed scheme, CR with distributed control (CR-DC), CR devices can make self-controlled decisions based on the status estimations to adaptively control its system parameters to communicate better.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1991년도 학술발표회 논문집
• /
• pp.117-121
• /
• 1991

본 논문은 견인선(tow-ship)에서 발생하는 자체 잡음을 제거하여 수중 신호처리 시스템에서 표적 탐지(target detection)와 표적 식별(target identification) 등의 성능 향상을 위하여 표적 방향으로 형성된 빔의 출력을 원시 입력신호(primary input)로 사용하고 견인선 방향으로 형성된 빔의 출력을 참고 입력신호(reference input)로 사용한 적응 잡음 제거기(adaptive noise canceller)에 대해 연구하였다. 잡음 제거를 위해 사용되는 계수들은 LMS(Least Mean Square) 알고리듬을 이용하여 조정하였다. 컴퓨터 시뮬레이션을 통하여 TDL(Tapped-Delay Line) 구조와 LAT(LATtice) 구조를 갖는 적응 잡음 제거기 성능을 여러 가지 환경에서 비교, 관찰하였다. 두 알고리듬을 사용할 경우, 자체 잡음이 어떠한 형태로 나타나더라도 제거시킬 수 있음을 보여 주었으나 고유값 분포율(eigenvalue spread ratio)이 큰 경우에는 LMS-LAT가 LMS-TDL보다 수렴 속도뿐만 아니라 성능면에서도 우수함을 보였다.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 1998년도 춘계학술대회 논문집
• /
• pp.55-58
• /
• 1998

Recently, neural networks with self-adaptability like human brain have attracted much attention. It is desirable for the neuron-function to be implemented by exclusive hardware system on account of huge quantity in calculation. We have proposed a novel neuro-device composed of a MFSFET(ferroelectric gate FET) and oscillation circuit with CUJT(complimentary unijuction transistor) and PUT(programmable unijuction transistor). However, it is difficult to preserve ferroelectricity on Si due to existence of interfacial traps and/or interdiffusion of the constitutent elements, although there are a few reports on good MFS devices. In this paper, we have simulated CUJT and PUT devices instead of fabricating them and composed oscillation circuit. Finally, we have resented, as an approach to the MFSFET neuron circuit, adaptive learning function and characterized the elementary operation properties of the pulse oscillation circuit.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (B)
• /
• pp.535-537
• /
• 2005

최근 컴퓨팅 환경의 급격한 발전과 다양화는 소프트웨어 외부 환경의 복잡성과 변화를 야기시켰으며, 소프트웨어는 예상하지 못한 외부 환경 변화에 직면하였을 때, 지속적으로 서비스의 제공과 동시에 동적 변경에 대한 적응 능력을 필요로 하게 되었다. 본 논문에서는 외부 환경의 변화를 인식하고, 대안을 선택하기 위해 '어떻게' 적응하도록 할 것 인가에 대해 모델을 이용한 적응 매카니즘을 제안하며, 시스템이 고려해야 할 컨텍스트 정보들을 모델링을 통하여 소프트웨어가 행위를 변경할 때 이용할 수 있도록 모델링 기법과 모델 기반 자가 적응형 프로세스를 제안한다. 또한, 프로세스를 이용하여 동작하는 모델 기반 자가 적응 시스템의 일반적 모듈들을 제시하고. 그 유효성을 확인하기 위하여 원격 화상 회의 시스템에 적용하였다.

• 한국지능시스템학회논문지
• /
• 제12권3호
• /
• pp.261-268
• /
• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• 디지털산업정보학회논문지
• /
• 제14권2호
• /
• pp.11-17
• /
• 2018

IDS/IPS and networked computer systems are playing an increasingly important role in our society. They have been the targets of a malicious attacks that actually turn into intrusions. That is why computer security has become an important concern for network administrators. Recently, various Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems is useful for existing intrusion patterns on standard-only systems. Therefore, probe detection of private clouds using BlockChain has become a major security protection technology to detection potential attacks. In addition, BlockChain and Probe detection need to take into account the relationship between the various factors. We should develop a new probe detection technology that uses BlockChain to fine new pattern detection probes in cloud service security in the end. In this paper, we propose a probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) based on service security using BlockChain technology.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2009년도 춘계학술대회
• /
• pp.317-320
• /
• 2009

At the present day, the use of containers crisscrossing seven seas and intercontinental transport has significantly increased and bringing the change on the shape of the world economy which we cannot be neglected. Additionally, with the recent technological advances in wireless sensor network (WSN) technologies, has providing an economically feasible monitoring solution to diverse application that allow us to envision the intelligent containers represent the next evolutionary development step in order to increase the efficiency, productivity, utilities, security and safe of containerized cargo shipping. This paper we present a comprehensive containerized cargo monitoring system which has adaptively embedded WSN technology into cargo logistic technology. We share the basic requirement for an autonomous logistic network that could provide optimum performance and a suite of algorithms for self-organization and bi-directional communication of a scalable large number of sensor node apply on container regardless inland and maritime transportation.