• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.73-79
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• 2013

Cloud computing is a form which provides IT resources through network and pays the cost as much as you used. And it has advantages that it doesn't need to construct infrastructure and can be offered a variety of environments. The main core of these computing is virtualization technology. Security mechanism about attacks using vulnerabilities of virtualization technology isn't provided right and existing security tools can't be applied as it is. In this paper, we proposed honeyVM structure that can cope actively by collecting the information about attacks using virtualization vulnerability. Mamdani fuzzy inference is used to adjust dynamically the number of formed honeyVM depending on the load of system. Security structure to protect actual virtual machine from attacks and threats is proposed. The performance of the proposed structure in this paper measured occurred attack detection rate and resource utilization rate.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.79-85
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• 2009

This research study and design, implement the digital multi-media description technique of Mashup Web which will be evolved into visible visual structure in form of cooperation studying. This technique is study user connect location information and service using pattern, then this information description technique of Mashup pre-operate inference data by tracking user service data.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.547-557
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• 2019

To extract the depth map from a single image, a number of CNN-based deep learning methods have been performed in recent research. In this study, the GAN structure of Pix2Pix is maintained. this model allows to converge well, because it has the structure of the generator and the discriminator. But the convolution in this model takes a long time to compute. So we change the convolution form in the generator to a depthwise convolution to improve the speed while preserving the result. Thus, the seven down-sizing convolutional hidden layers in the generator U-Net are changed to depthwise convolution. This type of convolution decreases the number of parameters, and also speeds up computation time. The proposed model shows similar depth map prediction results as in the case of the existing structure, and the computation time in case of a inference is decreased by 64%.

• Ocean Systems Engineering
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• v.9 no.2
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• pp.179-190
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• 2019

This paper deals with the problem of the global stabilization for a class of ocean structure systems. It is well known that, in general, the global asymptotic stability of the ocean structure subsystems does not imply the global asymptotic stability of the composite closed-loop system. The classical fuzzy inference methods cannot work to their full potential in such circumstances because given knowledge does not cover the entire problem domain. However, requirements of fuzzy systems may change over time and therefore, the use of a static rule base may affect the effectiveness of fuzzy rule interpolation due to the absence of the most concurrent (dynamic) rules. Designing a dynamic rule base yet needs additional information. In this paper, we demonstrate this proposed methodology is a flexible and general approach, with no theoretical restriction over the employment of any particular interpolation in performing interpolation nor in the computational mechanisms to implement fitness evaluation and rule promotion.

• Trans-
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• v.14
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• pp.65-92
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• 2023

The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.235-238
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• 2000

대용량의 데이터베이스에서 효율적인 의사결정을 하기 위해서는 불필요한 지식을 제거한 지식베이스의 구축이 필요하다. 사용자의 언어적인 질의에 대해 대용량의 데이터베이스에서 불필요한 규칙을 제거한 최소지식베이스를 구축한다. 또한 불완전한 데이터베이스로부터 규칙들을 일반화한 근사함수에 기반하여 규칙 추출의 중요도를 나타낸다. 그리고 앞에서 생성된 최소지식베이스를 통해 언어적 변수에 대한 퍼지 연산을 수행하여 추론값을 도출할 수 있는 모델을 제안한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.579-584
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• 1998

In this work, we present a method to deal with the interval valued decision making systems. First, we propose a new type of equality measure based on the Ordered Weighted Averaging (OWA) operator. The proposed equality measure has a structure to render the extreme values of the measure by choosing a suitable weighting vector of the OWA operator. From this property, we derive a bidirectional fuzzy inference network which can be applied for the decisionmaking systems requiring the inverval valued decisions.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.196-197
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• 2004

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.412-416
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• 1993

In this paper, fuzzy-neural network is proposed to identify the Activated Sludge Process(A.S.P) in sewage treatment such as "IF-THEN" type fuzzy rules and using various learning methods and improved complex method, the performance index of the identified model is improved. The proposed FNN has the neural network structure of which the connection weights have particular meanings for obtaining fuzzy inference rules and for tuning membership functions. And based on the identified model, graphic simulator which can analize nonlinear characteristics of A.S.P and generate control strategy for A.S.P is being developed.developed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.359-362
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• 1996

Our unicycle robot has simple mechanical structure. But unicycle's dynamical system is a very sensitive unstable system. Equation of motion of this simple unicycle robot was derived using Lagrange's method. In this paper a human inference control mechanism was established throughout an inquiry into hyman riding a unicycle, and we developed a hybrid controller to control our unicycle robot. Our controller is consisted with the PD and fuzzy controller containing fuzzy gain scheduling technique. Computer simulation shows good results.