• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.297-300
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• 2004

In cellular communication, subscriber authentication is an essential technique. The mobile station should operate in conjunction with the base station to authenticate the identity. In CDMA system, authentication is the process by which information is exchanged between a mobile station and base station for the purpose of confirming the mobile station. A successful authentication process means that the mobile station and base station process identical sets of shared secret data(SSD). SSD can be generated by authentication algorithms. The cryptographic hash function is a practical way of authentication algorithms. In this paper, we propose and implement MD5 and SHA-1 with modified structure.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.200-209
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• 2006

Load building is an important step to make the delivery supply chain efficient. We present a family of load makeup algorithms using market based control strategy, named LoadMarket, in order to build efficient loads where each load consists of a certain number of finished products having destinations. LoadMarket adopts Clark-Wright algorithm for generating initial endowment for Load Traders who cooperate to minimize either total travel distance or the variance with respect to the travel distances of loads by means of the spot market or double-sided auction market mechanism. The efficiency of the LoadMarket algorithms is illustrated using simulation based experiments.

• Computers and Concrete
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• v.13 no.3
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• pp.389-409
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• 2014

Precast hollow core slabs (HCS) are technically advanced products in the precast concrete industry, widely used in the last years due to their versatility, their multipurpose potential and their low cost. Using three dimensional FEM (Finite Element Method) elements, this study focuses on the stresses induced by the prestressing of steel. In particular the investigation of the spalling crack formation that takes place during prestressing is carried out, since it is important to assure the appropriate necessary margins concerning such stresses. In fact, spalling cracks may spread rapidly towards the web, leading to the detachment of the lower part of the slab. A parametric study takes place, capable of evaluating the influence of the tendon position and of the web width on the spalling stress. Consequently, after an extensive literature review on the topic of soft computing, an optimization of the HCS is performed by means of Genetic Algorithms coupled with 3-D FEM models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.162-164
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• 2010

Terrestrial trunked radio (TETRA) standard specifies shortened Reed-Muller (RM) codes as forward error correction means for control signals. In this paper, we compare decoding algorithms for RM codes in TETRA, in terms of performance and complexity trade-off. Belief propagation and majority logic decoding algorithms are selected for comparison.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1851-1852
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• 2008

Type-2 퍼지 논리 집합은 언어적인 불확실성을 다루기 위하여 고안된 Type-1 퍼지 논리 집합의 확장한 것이다. Type-2 퍼지 논리 시스템은 외부 노이즈를 효율적으로 다룰 수 있다. 본 논문에서는 불확실성을 표현하기 위해서 전.후반부 멤버쉽 함수로 삼각형 형태의 Type-2 퍼지 집합을 사용한다. 전반부 멤버쉽 함수의 정점을 결정하는데 유전자 알고리즘(Genetic Algorithms)으로 멤버쉽 함수의 정점을 결정한다. 제안된 모델은 모델 평가에 주로 사용되는 가스로 시계열 데이터를 적용하고, 테스트 데이터로 노이즈에 영향 받은 데이터를 사용하여 수치적인 예를 보인다.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.362-373
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• 2004

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.833-842
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• 2017

In this study, the design methodology of radial basis function neural networks based on incremental K-means clustering is introduced for learning and processing the big data. If there is a lot of dataset to be trained, general clustering may not learn dataset due to the lack of memory capacity. However, the on-line processing of big data could be effectively realized through the parameters operation of recursive least square estimation as well as the sequential operation of incremental clustering algorithm. Radial basis function neural networks consist of condition part, conclusion part and aggregation part. In the condition part, incremental K-means clustering algorithms is used tweights of the conclusion part are given as linear function and parameters are calculated using recursive least squareo get the center points of data and find the fitness using gaussian function as the activation function. Connection s estimation. In the aggregation part, a final output is obtained by center of gravity method. Using machine learning data, performance index are shown and compared with other models. Also, the performance of the incremental K-means clustering based-RBFNNs is carried out by using PSO. This study demonstrates that the proposed model shows the superiority of algorithmic design from the viewpoint of on-line processing for big data.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.261-266
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• 2019

Differential evolution (DE) is an uncomplicated and serviceable developmental algorithm. Nevertheless, its execution depends on strategies and regulating structures. The combination of several strategies between subpopulations helps to stabilize the probing on DE. In this paper, we propose a unique k-mean soft island model DE(KSDE) algorithm which maintains population diversity through soft island model (SIM). A combination of various approaches, called KSDE, intended for migrating the subpopulation information through SIM is developed in this study. First, the population is divided into k subpopulations using the k-means clustering algorithm. Second, the mutation pattern is singled randomly from a strategy pool. Third, the subpopulation information is migrated using SIM. The performance of KSDE was analyzed using 13 benchmark indices and compared with those of high-technology DE variants. The results demonstrate the efficiency and suitability of the KSDE system, and confirm that KSDE is a cost-effective algorithm compared with four other DE algorithms.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.700-702
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. In fuzzy controller which has been widely applied and used. in order to construct the best fuzzy rules that include adjustment of fuzzy sets, a highly skilled techniques using trial and error are required. To deal with such a problem, first, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller from each control output in steady state and transient state. Second, a auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller, utilizing the simplified reasoning method and genetic algorithms. In addition, to obtain scaling factors and PID Parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The HFCs are applied to the first-order second-order process with time-delay and DC motor Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed from performance indices.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.529-534
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• 2009

One of the characteristics of the hearing impaired is that their frequency selectivity is poorer than that of the normal hearing. To compensate this, formant enhancement algorithms and spectral contrast enhancement algorithms have been developed. However in some cases, these algorithms fail to improve the frequency selectivity of the hearing impaired. One of the reasons is the acoustic masking among enhanced formants. In this study, we tried to enhance the formants based on the individual masking characteristic of each subject. The masking characteristic used in this study was minimum level difference (MLD) between the first formant to the second formant while acoustic masking was occurred. If the level difference between the two formants in each frame is larger than the MLD, the gain of the first formant was decreased to reduce the acoustic masking that occurred among formants. As a result of the speech discrimination test, using formant enhanced speeches, speech discrimination score (SDS) of the speeches having differently enhanced formants was significantly superior to SDS of the speeches having equally enhanced formants. It means that suppression of the acoustic masking among formants improve frequency selectivity of the hearing impaired.