• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.740-743
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• 1998

This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.459-462
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• 2000

In this paper, we propose the initial optimized structure of the Radial Basis Function Network which is more simple in the part of the structure and converges more faster than Neural Network with the analysis method using Time-Frequency Localization. When we construct the hidden node with the Radial Basis Function whose localization is similar with an approximation target function in the plane of the Time and Frequency, we make a good decision of the initial structure having an ability of approximation.

• Convergence Security Journal
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• v.1 no.1
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• pp.37-45
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• 2001

In this paper, separated and optimized pattern database model is proposed. In order to improve efficiency of Network-based IDS, pattern database is classified by proper basis. Classification basis is decided by the specific Intrusions validity on specific target. Using this model, IDS searches only valid patterns in pattern database on each captured packets. In result, IDS can reduce system resources for searching pattern database. So, IDS can analyze more packets on the network. In this paper, proper classification basis is proposed and pattern database classified by that basis is formed. And its performance is verified by experimental results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.173-174
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• 2008

In this paper, we study IEEE 802.16 network for IP subnet aspects and propose optimized subnet model in accordance with IEEE 802.16 network in the point of mobility.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1568-1569
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• 2005

This paper presents a method to optimize train radio communication network for train control(CBTC) or multimedia services. To determine the optimized distance between wayside radio stations in a radio communication network constructed along railway, radio frequency allocation and hand-over capability is studied in terms of radio communication cell coverage and roaming feasibility.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.612-618
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• 1998

The success of a fuzzy logic control system solving any given problem critically depends on the architecture of th network. Various attempts have been made in optimizing its structure its structure using genetic algorithm automated designs. In a regular genetic algorithm , a difficulty exists which lies in the encoding of the problem by highly fit gene combinations of a fixed-length. This paper presents a new approach to structurally optimized designs of a fuzzy model. We use a messy genetic algorithm, whose main characteristics is the variable length of chromosomes. A messy genetic algorithms used to obtain structurally optimized fuzzy models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the exampled of a cart-pole balancing.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.41-50
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• 1997

In this paper, we describe the design, implementation and evaluation for a multimedia conferencing system with intramedia and intermedia synchronization support between audio and video. The synchronization mechanism proposed here is capable of dynamically adapting to various network conditions thus providing an optimized QoS. In realizing the system based on this mechanism, NeVoT on Mbone is used for audio and VIC for video. Furthermore a synchromization controller is designed and realized with a unique process in supporting intermedia synchronization. Each media agents handling its media stream are modified with intramedia synchronization function. And a communicative function between media agents and synchronization controller is added as well for intermedia synchronization function. Each media agents function reports its buffering status to the synchronization control process which in turn send out optimized buffering delay value thus supporting intermedia synchronization. The realized system is configured and tested on Ethernet and ATM network where performance measurements were performed and its effective synchronization support has been assured.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.519-521
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• 1998

Fuzzy inference systems have found many applications in recent years. The fuzzy inference system design procedure is related to an expert or a skilled human operator in many fields. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. The messy genetic algorithm is used to obtain structurally optimized fuzzy neural network models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the problem of a time series estimation.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.129-142
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• 2003

The SCM is that Supply Chain Network is Promptly and Voluntarily Optimized in Unstable Market Change Environment. The Cash flow Efficiency of Hole Supply Chain Network is Improved by Changing the Information and Changing the Foundation of Business Processes. The Role of WMS has been Changing Importantly with the Introduction of SCM. WMS Needed to Change to the Information Center in Order to Change Information in Real Time and the WMS of Information Storing in Order to Support an Idea Decision. This Development was Defined about the Importance of WMS in SCM Environment. The Criterion of Valuation is Normally Measured Time between Taking a Order Receive and Bringing the Items to Customer. The Decreasing Move Time of Order Picker in Warehouse is Directly Influence to the Job Execution. So, this Research is Defined about the Optimized Route of Order Picker and Suggests Algorithm. To do this, Past Algorithm is Studied. It's Easy to Introduce and this Study is Looking for Method about the Noticing of Order Picker. The Algorithm will Improve to be Adapt to Standard Process System.