• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.4
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• pp.36-44
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• 1997

An efficient context-free multiple-object segmentation using attention operator based on modified generalized symmetry transform is proposed and implemented by modifying a radial basis function network. By using the difference of intensity gradient, instead of te intensity gradient itself, in generalized symmetry tranform so as to make the attention operator to preserve the edges of the objects shape, an efficient context-free multiple-object segementation is proposed in which no a priori shape informtion on the objects is requried. The attention operator is implemented by using a modified radial basis function network which can reflect symmetry, and by using te edge pyramid of the input image, both of the local and the global symmetry of the objects are reflected simultaneously to make the multiple-object with different sizes be segmented with a singel fixed-size $n\timesm$ can be done with O(n) complexity. The simulaton results show that the proposed algorithm can efficiently be used in context-free multiple-object segmentation even for the low contrast IR images as well as for the images from the camera.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.474-480
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• 2007

This paper presents an application of intelligent modeling method to manual control system with human operator. Human operator as a part of controller is difficult to be modeled because of changes in individual characteristics and operation environment. So in these situation, a fuzzy model developed relying on the expert's experiences or trial and error may not be acceptable. To supplement the fuzzy model block, a neural network based modeling error compensator is incorporated. The feasibility of the present fuzzy-neural modeling scheme has been investigated for the real human based target tracking system.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.759-762
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• 2005

Recently, Intelligent Transportation System(ITS) has been applied to satisfy increasing traffic demand every year and to solve many traffic problems. Especially, Advanced Traveller Information System(ATIS) is a transportation system to optimize the trip of each other vehicle. It is important to provide the driver with quick and comfortable path from source to destination. However, it is difficult to provide a shortest path in a road network with dynamic cost. Because the existing research has a static cost. Therefore, in this paper we propose an operator for searching traffic dependent shortest path. The proposed operator finds the shortest path from source to destination using a current time cost and a difference cost of past time cost. Such a method can be applied to the road status with time. Also, we can expect a predicted arrival time as well as the shortest path from source to destination. It can be applied to efficiently application service as ITS and have the advantages of using the road efficiently, reducing the distribution cost, preparing an emergency quickly, reducing the trip time, and reducing an environmental pollution owing to the saving the fuel.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.167-179
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• 2020

Recently, the increasing importance of artificial intelligence (AI) technology has led to its increased use in various fields in the shipbuilding and marine industries. For example, typical scenarios for AI include production management, analyses of ships on a voyage, and motion prediction. Therefore, this study was conducted to predict a response amplitude operator (RAO) through AI technology. It used a neural network based on one of the types of AI methods. The data used in the neural network consisted of the properties of the vessel and RAO values, based on simulating the in-house code. The learning model consisted of an input layer, hidden layer, and output layer. The input layer comprised eight neurons, the hidden layer comprised the variables, and the output layer comprised 20 neurons. The RAO predicted with the neural network and an RAO created with the in-house code were compared. The accuracy was assessed and reviewed based on the root mean square error (RMSE), standard deviation (SD), random number change, correlation coefficient, and scatter plot. Finally, the optimal model was selected, and the conclusion was drawn. The ultimate goals of this study were to reduce the difficulty in the modeling work required to obtain the RAO, to reduce the difficulty in using commercial tools, and to enable an assessment of the stability of medium/small vessels in waves.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.69-87
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• 2000

Models and Strategies for Network Operator's B2B Ecommerce The B2B ecommerce market is one of the fastest growing areas in the telecom industry. However network operators have been slow to enter the arena, Network operator have been held back by their general unsurety about the Internet business. Network operators'core business(the supply of connectivity and transport service) is becoming unprofitable. As a result they are looking to diversify into areas where margins are higher. B2B ecommerce offers them a major way to achieve this. It is possible to identify various business models for offering ecommerce services to end user, ranging from the provision of complete packaged applications to the implementation and management of customized ecommerce solution. In this study the three main approaches available to network operators are the traditional IT outsourcing model, the ASP model and the community builder model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2925-2948
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• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.709-716
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• 2005

As a way to build more efficient and intelligent container cranes for todays hub ports, communication networks are used to interconnect numerous sensors, actuators, controllers, and operator switches and consoles that are spatially distributed over a crane. Various signals such as sensor values and operator's commands are digitized and broadcast on the network instead of using separate wiring cables. This not only makes the design and manufacturing of a crane more efficient, but also easier implementation of intelligent control algorithms. This paper presents the performance evaluation of CAN(Controller Area Network), TTP(Time Triggered Protocol) and Byteflight that can be used for cranes. Through discrete event simulation, several important quantitative performance factors such as the probability of a transmission failure, average system delay (data latency) and maximum system delay have been evaluated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2101-2106
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• 2009

The power system state estimation and prediction are very important for operation. Because that accidents of the Power system are the cause that many devices and etc are damaged. Currently, almost every power systems have 2nd,3rd back-upsystem for prevention of accident. But prevention of accident by miss-operation, due to operator or miss data, has not acounter plan. Because, we need to estimate the power system for correcting miss data and preventing miss operation by operator. We suggest algorithm for integrity of power system network data.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.111-126
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• 2013

As the gaps become narrower in interconnection fee and volume rate, the MNOs began to introduce flat pricing for unlimited voice traffic competitively in Korea wireless telecommunication market : 'unlimited talks within intra-network' by the 1st operator, followed by the 3rd operator's 'unlimited talks over all networks'. As a result, subscribers tip in toward the third ranked operator and could bring a substantial change to steadfast market structure over the last decade in Korea. This paper aims to develop a simple economic model to analyze competition with flat pricing for unlimited voice traffic, and to check whether the pricing can be appropriate for the MNOs. The results show that MNOs already step in the necessary conditions to launch flat pricing for voice traffic. It also predicts that the MNOs compete with unlimited talk over all networks and set a single fee in an equilibrium. At present, the MNOs run virtually identical pricing for unlimited talk over all networks, considering their differentiation with respect to service quality, coverage and brand preference.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1631-1638
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• 2015

This paper describes the design methodology of the operator training simulator for power monitor and control system in the railway system. In power system, the purpose of energy management system was to monitor, control, and analyze the performance of generation and transmission system based on H/W and S/W. Network analysis applications provide a clear picture of power system characteristics using state estimation, power flow and short circuit analysis. In this respect, the operator training system in the railway system should be equipped with the methodology of these systems. First, the proposed database structure in the railway system was introduced. Then the overall structure of operator training system based on railway analysis applications was proposed. Finally, a methodology to verify the performance of the developed applications was described.