• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.608-627
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• 2016

Wireless mesh networks (WMNs) based on IEEE 802.11s have emerged as one of the prominent technologies in multi-hop communications. However, the deployment of WMNs suffers from serious interference problem which severely limits the system capacity. Using multiple radios for each mesh router over multiple channels, the interference can be reduced and improve system capacity. Nevertheless, interference cannot be completely eliminated due to the limited number of available channels. An effective approach to mitigate interference is to apply dynamic channel switching (DCS) in WMNs. Conventional DCS schemes trigger channel switching if interference is detected or exceeds a predefined threshold which might cause unnecessary channel switching and long protocol overheads. In this paper, a P-learning based dynamic switching algorithm known as learning automaton (LA)-based DCS algorithm is proposed. Initially, an optimal channel for communicating node pairs is determined through the learning process. Then, a novel switching metric is introduced in our LA-based DCS algorithm to avoid unnecessary initialization of channel switching. Hence, the proposed LA-based DCS algorithm enables each pair of communicating mesh nodes to communicate over the least loaded channels and consequently improve network performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.65-68
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• 2001

RBFN has some problem that because the basis function isnt orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested in this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.256-263
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• 1998

Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.157-164
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• 2011

This paper presents a fast and scalable re-routing algorithm that adapts to dynamically changing networks. The proposed algorithm integrates Dijkstra's shortest path algorithm with the genetic algorithm. Dijkstra's algorithm is used to define the predecessor array that facilitates the initialization process of the genetic algorithm. After that, the genetic algorithm re-searches the optimal path through appropriate genetic operators under dynamic traffic situations. Experimental results demonstrate that the proposed algorithm produces routes with less traveling time and computational overhead than pure genetic algorithm-based approaches as well as the standard Dijkstra's algorithm for large-scale networks.

• KSCI Review
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• v.2 no.1
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• pp.121-129
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• 1995

Fault simulation of logic circuits is an important part of the test-generation process. It is used for the propose of generation fault dictionaries or for the verification of the adequacy of tests. In this paper, a backtrace fault simulation is proposed to test generation. This is consists of 3 part ; initialization phase for given circuit, backtrace fault simulation phase to find fault list and reevaluation phase to list event. The main idea of this algorithm is to retain a minimum fault list by cutting uncontrollable lines of path when a logic event occurs in backward tracing phases. And the simulator is revaluates a fault list associated with the output of an element only if logic event occurs at any of its inputs when a list event occurs at one of its primary inputs. It reguires a O(n) memory space complexity. where n is a number of signal lines for the given circuits. Several examples are given to illustrate the power of this algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.335-352
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• 2023

When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.61-73
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• 2024

Quantum information technology is driving innovative computing, communication, and sensing advancements. High-performance tunable lasers have become essential tools for precisely controlling and manipulating qubits. These lasers provide high stability and accuracy at specific wavelengths, enabling efficient control of various types of qubit systems, such as ions, neutral atoms, and defects. High-performance tunable lasers allow the initialization of qubit states, execution of quantum gate operations, and minimization of errors during the readout process. In addition, tunable lasers are critical in precisely regulating the interactions between multiple qubits to optimize quantum entanglement and correlation. This study explores the existing and state-of-the-art technologies related to the design and implementation of high-performance tunable lasers in the visible and near-infrared wavelength ranges that are crucial for key material systems used in quantum technology. Based on this investigation, we present new methodologies for maximizing the scalability of qubit control. These laser technologies are expected to contribute to the commercialization and performance enhancement of quantum information technology, a common foundational technology.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.709-716
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• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.107-115
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• 2013

Recently, the RFID technology is combined with a u-healthcare services is an emerging trend in the field of medical services. u-healthcare service, as covering the field of personal health information beyond the level of simple health screening and treatment of life are closely related. Considering security, invasion of privacy, as well as life may be threatened even if your personal health information to be exposed or exploited illegally u-Healthcare services certification is essential. In 2012, Jeong proposed J-L patient authentication protocol that Initialization process, and patients using RFID technology separates the certification process. Jeong, such as the claim that the proposed protocol for reuse attacks, spoofing attacks, prevent information disclosure and traceability fire safety, but raises issues of security and operations efficiency. Therefore, in this paper, Jeong, such as the security of the proposed protocol and to prove the computational efficiency issues, and to enhance the safety and efficiency of RFID technology based on practical u-Healthcare services authentication protocol is proposed.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.163-170
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• 2009

There is a request from the client, we almost apply dynamic memory allocating method using Accept() of looping method; thus, there could be process of connecting synchronously lots of client in most of On-line gaming server engine. However, this kind of method causes on-line gaming server which need to support and process the clients, longer loading and bottle necking. Therefore we propose the object pooling scheme to minimize the memory fragmentation and the load of the initialization to the client using an AcceptEx() and static allocating method for an efficient gaming server of the On-line in this paper. We design and implement the gaming server applying to our proposed scheme. Also, we show efficiency of our proposed scheme by performance analysis in this paper.