• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.436-439
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• 1995

In this paper we present a method to construct fuzzy model with multi-dimension input membership function, which can construct fuzzy inference system on one node of the network directly. This method comes from a common framework called Universal Learning Network (ULN). The fuzzy model under the framework of ULN is called Universal Learning Network-based Fuzzy Inference System (ULNFIS), which possesses certain advantages over other networks such as neural network. We also introduce how to imitate a real system with ULN and a control scheme using ULNFIS.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.138-144
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• 1994

An inference network is proposed as a tool for bidirectional approximate reasoning. The inference network can be designed directly from the given fuzzy data(knowledge). If a fuzzy input is given for the inference netwok, then the network renders a reasonable fuzzy output after performing approximate reasoning based on an equality measure. Conversely, due to the bidirectional structure, the network can yield its corresponding reasonable fuzzy input for a given fuzzy output. This property makes it possible to perform forward and backward reasoning in the knowledge base system.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.258-260
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• 2006

In this paper, we designed a embedded system that will perform a primary role of Tangible Space implementation. This hardware includes function of image capture through camera interface, image process and sending off image information by LAN (local area network) or WLAN(wireless local area network). We define this hardware as a network based Visual Agent Platform for Tangible Space

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.172-174
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• 2007

In this paper, we designed a embedded system that will perform a primary role of Tangible Space implementation. This hardware includes function of image capture through camera interface, image process and sending off image information by LAN(local area network) or WLAN(wireless local area network). We define this hardware as a network based Visual Agent Platform for Tangible Space, This Visual Agent Platform includes the software that is RTLinux and CORBA

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.138-139
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• 2021

This work introduces neural network based simulation for Poisson Boltzmann equation. First, samples are generated via a finite element method, whose pairs are used to train neural network. We report the performance of the neural network.

• Structural Engineering and Mechanics
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• v.73 no.3
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• pp.339-351
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• 2020

Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.68-74
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• 2001

This paper mentions a centralized approach based on SNMP protocol and distributed approach based on mobile agent in network management s system. And it presents a few Quantitative models for systematically evaluating those two different approaches. To do this, we propose model m that is applicable under a uniform network environment, and compare network execution times of each paradigms based on parameters from s simulation. The model is then refined to take into account non-uniform networks. We show that it can reduce overall network execution times b by determining the best interaction patterns to perfo$\pi$n network management operations from this model. We believe that the model proposed h here should help us to decide appropriate paradigms and interaction patterns for developing network management applications.

• Journal of Industrial Technology
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• v.41 no.1
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• pp.1-6
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• 2021

Fly ash and silica fume belong to industry by-products that can be used to produce concrete. This study shows the model of a neural network to evaluate the strength development of blended concrete containing fly ash and silica fume. The neural network model has four input parameters, such as fly ash replacement content, silica fume replacement content, water/binder ratio, and ages. Strength is the output variable of neural network. Based on the backpropagation algorithm, the values of elements in the hidden layer of neural network are determined. The number of neurons in the hidden layer is confirmed based on trial calculations. We find (1) neural network can give a reasonable evaluation of the strength development of composite concrete. Neural network can reflect the improvement of strength due to silica fume additions and can consider the reductions of strength as water/binder increases. (2) When the number of neurons in the hidden layer is five, the prediction results show more accuracy than four neurons in the hidden layer. Moreover, five neurons in the hidden layer can reproduce the strength crossover between fly ash concrete and plain concrete. Summarily, the neural network-based model is valuable for design sustainable composite concrete containing silica fume and fly ash.

• Smart Structures and Systems
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• v.30 no.6
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Journal of the Korean Society of Systems Engineering
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• v.4 no.2
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• pp.45-54
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• 2008

This paper describes an operational concept of the network based future airborne force power using a systems engineering approach. The battlefield is changing to new system of systems that command and control by the network based BM/C4ISR. Also, it is composed of various sensors and shooters in an single theater. Future threats may be characterized as unmanned moving bodies that the strategic effect is great such as UAVs, cruise missile and tactical ballistic missiles. New threats such as low altitude stealth cruise missile may also appear. The implementation of future airborne force power network systems against these future threats is required to complex and integrated approach based on systems engineering. This work developed the operational concepts of the future airborne network system, and then derived the requirements for performing missions effectively. In addition, the scheme of future airborne force power network systems is presented.