• Journal of the Semiconductor & Display Technology
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• v.4 no.3 s.12
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• pp.29-33
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• 2005

As the integrated devices become more and more sophistcated, the diameter of wafers increased up to 300 mm and strict level of cleaning is necessary to remove the particulates on the surface of wafer. Therefore we need a new type of wet-station which can reduce DI water and chemical in the cleaning process. Moreover, it is important to control the temperature and the concentration of chemical in the wet-station. In the conventional chemical supply system, it is difficult not only to fit the mixing rate of chemicals in cleaning process, but also to fit the quantity and temperature. Thus, we propose a new chemicals supply system, which overcomes above problems by the analysis of fluid and thermal transfer on chemical supply system.

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.355-365
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• 1998

The purposes of this study are to propose a network for the characterizing of the input data and to show how to design predictive neural net재가 expert system which doesn't need previous knowledge base. We derived this network from the radial basis function networks(RBFN), and named it as a statistical EBFN. The proposed network can replace the statistical methods for analyzing dynamic relations between target disease and other parameters in medical studies. We compared statistical RBFN with the probabilistic neural network(PNN) and fuzzy logic(FL). And we testified our method in the diabetes prediction and compared our method with the well-known multilayer perceptron(MLP) neural network one, and showed good performance of our network. At last, we developed the diabetes prediction expert system based on the proposed statistical RBFN without previous knowledge base. Not only the applicability of the characterizing of parameters related to diabetes and construction of the diabetes prediction expert system but also wide applicabilities has the proposed statistical RBFN to other similar problems.

• Journal of Microbiology and Biotechnology
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• v.12 no.4
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• pp.687-691
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• 2002

To enhance the production of flavonoids [baicalin, wogonin-7-Ο-glucuronic acid (GA)], which are secondary metabolites of Scutellaria baicalensis Georgi(G.) plant cells, a multilayer perceptron control system was applied to regulate the substrate feeding in a fed-batch cultivation. The optimal profile for the substrate feeding rate in a fed-batch culture of S. baicalensis G. was determined by simulating a kinetic model using a genetic algorithm. Process variable profiles were then prepared for the construction of a multilayer perceptron controller that included massive parallelism, trainability, and fault tolerance. An error back-propagation algorithm was applied to train the multiplayer perceptron. The experimental results showed that neurocontrol incorporated with a genetic algorithm improved the flavonoid production compared with a simple fuzzy logic control system. Furthermore, the specific production yield and flavonoid productivity also increased.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.1-6
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• 2003

The Delayed Feedback Control method (DFC) proposed by Pyragas applies an input based on the difference between the current state of the system, which is generating chaos orbits, and the $\tau$-time delayed state, and stabilizes the chaos orbit into a target. In DFC, the information about a position in the state space is unnecessary if the period of the unstable periodic orbit to stabilize is known. There exists the fault that DFC cannot stabilize the unstable periodic orbit when a linearlized system around the periodic point has an odd number property. There is the chaos control method using the prediction of the $\tau$-time future state (PDFC) proposed by Ushio et al. as the method to compensate this fault. Then, we propose a method such as improving the fault of the DFC. Namely, we combine DFC and PDFC with parameter W, which indicates the balance of both methods, not to lose each advantage. Therefore, we stabilize the state into the $\tau$ periodic orbit, and ask for the ranges of Wand gain K using Jury' method, and determine the quasi-optimum pair of (W, K) using a genetic algorithm. Finally, we apply the proposed method to a discrete-time chaotic system, and show the efficiency through some examples of numerical experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.37-43
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• 2003

Current Internet system of the entrance exam information to the university that is depending on searching key to solve the overloaded problem in the network and DB server or other tools to support HTML edit, haven't satisfied user's wants by supplying uniformed searching system. So this thesis will establish EEIS(Entrance Examination Information System) to prevent database overload phenomena when many users request a great amount of data at the same time and improve the decrease of speed and overload problem in DB server. EEIS playa role of bridge between outside client and DB server by placing VVS(Virtual View Server) between web server and DB server. By that method this system give users several usefulness in convenience and variety by supplying realtime data searching function to user. EEIS also give inner system manager more efficiency and speed in control the management system by solving those problem. This system is design and implementation to satisfy user's desire and give them more convenience and bring up the confidence of university that adopt this system at the end.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.295-304
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• 2014

Communication infrastructure supports wide variety of mobile services such as photo and file sharing, location tracking, social network services and instant messaging. However, instances like power-loss and natural disasters disrupt these communication infrastructures unable to render support to these mobile services. Delay-tolerant networks (DTNs) offer a solution to these problems at hand. By utilizing mobility and opportunistic contacts among mobile devices, a plausible communication network can be establish and enable support to mobile applications. This paper presents an energy-efficient, reliable message delivery routing scheme with message prioritization rules for DTN. It uses the context information of nodes (mobile devices) such as the contact history (location and time of contact), speed/velocity, moving direction to determine the best forwarders among nodes in the network. The remaining energy of the nodes is also used to determine the message types a node can deliver successfully. The simulation results show that proposed approach outperforms Epidemic and Prophet routing schemes in terms of delivery ratio, overhead ratio, delivered messages per types and remaining energy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.288-294
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• 2014

Understanding a ship's present position has been one of the most important tasks during a ship's voyage, in both ancient and modern times. Particularly, a ship's dead reckoning (DR) has been used for predicting traffic situations and collision avoidance actions. However, the current system that uses the traditional method of calculating DR employs the received position and speed data only. Therefore, it is not applicable for predicting navigation within the harbor limits, owing to the frequent changes in the ship's course and speed in this region. In this study, planned routes were applied for improving the reliability of the proposed system and predicting the traffic patterns in advance. The proposed method of determining the dead reckoning position (DRP) uses not only the ships' received data but also the navigational patterns and tracking data in harbor limits. The Mercator sailing formulas were used for calculating the ships' DRPs and planned routes. The data on the traffic patterns were collected from the automatic identification system and analyzed using MATLAB. Two randomly chosen ships were analyzed for simulating their tracks and comparing the DR method during the timeframes of the ships' movement. The proposed method of calculating DR, combined with the information on planned routes and DRPs, is expected to contribute towards improving the decision-making abilities of operators.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.157-163
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• 2014

This paper demonstrates the benefit of using MOOS-IvP in the development of control system for Unmanned Underwater Vehicles(UUV). The demand for autonomy in UUVs has significantly increased due to the complexity in missions to be performed. Furthermore, the increased number of sensors and actuators that are interconnected through a network has introduced a need for a middleware platform for UUVs. In this context, MOOS-IvP, which is an open source software architecture, has been developed by several researchers from MIT, Oxford University, and NUWC. The MOOS software is a communication middleware based on the publish-subscribe architecture allowing each application to communicate through a MOOS database. The IvP Helm, which is one of the MOOS modules, publishes vehicle commands using multi-objective optimization in order to implement autonomous decision making. This paper explores the benefit of MOOS-IvP in the development of control software for UUVs by using a case study with an auto depth control system based on self-organizing fuzzy logic control. The simulation results show that the design and verification of UUV control software based on MOOS-IvP can be carried out quickly and efficiently thanks to the reuse of source codes, modular-based architecture, and the high level of scalability.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.67-72
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• 2002

In order to offer a service of highly qualified information, software of good quality should be designed and developed. We need the united estimation method because the existing approaches for the quality measurements measure the attributes at the different viewpoint individually. Therefor, this paper Propose the model that handles many methods of measurements. Our model selects the ratio scales and calculates the relative significance of them by using the rough logic. As a next step, the proposed method integrates the significance of scales and the measured value of them based upon the fuzzy integral. Finally, the correlations are analyzed between the existing scales with our measurements and our model is validated through statistical technique.