• 대한전자공학회논문지
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• 제9권5호
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• pp.6-11
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• 1972

임의의 안정한 전달함수를 실현하는 일반적인 능동 RC회로합성방법에 대하여 논의하였다. 회로요소는 R, C, 및 연산증폭기 뿐이며, 회로구성은 박막 RC전로와 IC연산증폭기를 적용하는데 적합하다. 극과 전송령은 서로 독립식으로 조정될 수 있으며, 이들은 회로요소들의 변화에 민감하지 않다.

• Computers and Concrete
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• 제3권6호
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• pp.439-454
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• 2006

This paper develops an artificial neural network (ANN) model for uniformly loaded restrained reinforced concrete (RC) slabs incorporating membrane action. The development of membrane action in RC slabs restrained against lateral displacements at the edges in buildings and bridge structures significantly increases their load carrying capacity. The benefits of compressive membrane action are usually not taken into account in currently available design methods based on yield-line theory. By extending the existing knowledge of compressive membrane action, it is possible to design slabs in building and bridge decks economically with less than normal reinforcement. The processes involved in the development of ANN model such as the creation of a database of test results from previous research studies, the selection of architecture of the network from extensive trial and error procedure, and the training and performance validation of the model are presented. The ANN model was found to predict accurately the ultimate strength of fully restrained RC slabs. The model also was able to incorporate strength enhancement of RC slabs due to membrane action as confirmed from a comparative study of experimental and yield line-based predictions. Practical applications of the developed ANN model in the design process of RC slabs are also highlighted.

• Computers and Concrete
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• 제30권3호
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• pp.209-224
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• 2022

In this paper, the artificial neural network (ANN) is employed to predict the flexural behavior of reinforced concrete (RC) beams retrofitted with carbon fiber/epoxy composites modified by carbon nanotubes (CNTs). Multiple techniques are used to improve the accuracy of the ANN prediction, as the data represents a multivalued function. These techniques include static ANN modeling, ANN modeling with load history, and ANN modeling with double load history. The developed ANN models are used to predict the load-displacement profiles of beams retrofitted with either CFRP or CNTs modified CFRP, flexural capacity, and maximum displacement of the beams. The results demonstrate that the ANN is able to predict the flexural behavior of the retrofitted RC beams as well as the effect of each parameter including the type of the used epoxy and the presence of the CNTs.

• Structural Engineering and Mechanics
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• 제12권5호
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• pp.527-540
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• 2001

A new sort of learning algorithm named whole learning algorithm is proposed to simulate the nonlinear and dynamic behavior of RC members for the estimation of structural integrity. A mathematical technique to solve the multi-objective optimization problem is applied for the learning of the feedforward neural network, which is formulated so as to minimize the Euclidean norm of the error vector defined as the difference between the outputs and the target values for all the learning data sets. The change of the outputs is approximated in the first-order with respect to the amount of weight modification of the network. The governing equation for weight modification to make the error vector null is constituted with the consideration of the approximated outputs for all the learning data sets. The solution is neatly determined by means of the Moore-Penrose generalized inverse after summarization of the governing equation into the linear simultaneous equations with a rectangular matrix of coefficients. The learning efficiency of the proposed algorithm from the viewpoint of computational cost is verified in three types of problems to learn the truth table for exclusive or, the stress-strain relationship described by the Ramberg-Osgood model and the nonlinear and dynamic behavior of RC members observed under an earthquake.

• 전기의세계
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• 제24권4호
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• pp.80-82
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• 1975

This paper presents a synthesis procedure of multi-channel active filters, which realizes an arbitrary N*N matrix of real rational functions in the complex variable s as a voltage transfer matrix. The resultant network reveals a transformerless grounded active RC(2N+1)-terminal network. The active network is consisted of six 2N-port RC networks with 2N single-ended operational amplifiers.

• 대한전자공학회논문지
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• 제7권1호
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• pp.9-17
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• 1970

부임피던스 변환기를 사용한 능동 RC 여파기의 RC 회로망의 극의 최적치 선정방법과 안정도 개선책을 논했다. 아울러 실제예로 차단주파수 3.4KC, 모듈라각 55°인 2차연린 Chebyshev 특성을 갖는 저주파 능동 RC 여파기를 설계하여 실험한 결과 이론치와 잘 일치했으며 동작 또한 안정했다.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.164-168
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• 2023

As our community has become increasingly dependent on technology, security has become a bigger concern, which makes it more important and challenging than ever. security can be enhanced with encryption as described in this paper by combining RC6 symmetric cryptographic algorithms with RSA asymmetric algorithms, as well as the Vigenère cipher, to help manage weaknesses of RC6 algorithms by utilizing the speed, security, and effectiveness of asymmetric algorithms with the effectiveness of symmetric algorithm items as well as introducing classical algorithms, which add additional confusion to the decryption process. An analysis of the proposed encryption speed and throughput has been conducted in comparison to a variety of well-known algorithms to demonstrate the effectiveness of each algorithm.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.168-174
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• 2021

The Cognitive radio (CR) is evolving technology for managing the spectrum bandwidth in wireless network. The security plays a vital role in wireless network where the secondary users are trying to access the primary user's bandwidth. During the allocation the any malicious user either he pretends to be primary user or secondary user to access the vital information's such as credentials, hacking the key, network jam, user overlapping etc. This research paper discusses on various types of attack and to prevent the attack in cognitive radio network. In this research, secondary users are identified by the primary user to access the primary network by the secondary users. The secondary users are given authorization to access the primary network. If any secondary user fails to provide the authorization, then that user will be treated as the malicious user. In this paper two approaches are suggested one by applying elliptic curve cryptography and the other method by using priority-based service access.

• 한국전자파학회논문지
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• 제21권12호
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• pp.1460-1466
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• 2010

본 논문은 바이스태틱 RCS와 모노스태틱 RCS를 이용하여 각각 표적 구분 실험을 수행하고 그 성능을 비교 분석하였다. 모노스태틱 및 바이스태틱 RCS로부터 특성을 추출하기 위하여 시간-주파수 영역 해석법인 STFT와 CWT를 이용하였으며, 다중 퍼셉트론 신경망을 구분기로 이용하였다. 실험 결과, 모노스태틱과 바이스태틱 RCS 모두 CWT가 STFT보다 더 나은 구분 성능을 보여주었다. 또한, STFT에서는 바이스태틱 RCS를 이용했을 때, CWT에서는 모노스태틱 RCS를 이용하였을 때 대체적으로 더 좋은 성능을 나타내었다. 결과적으로 본 논문을 통하여 바이스태틱 RCS도 모노스태틱 RCS처럼 표적 구분에 똑같이 적용할 수 있다는 것을 알 수 있었다.

• Structural Engineering and Mechanics
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• 제87권6호
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• pp.517-527
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• 2023

The severe deterioration of structures has led to extensive research on the development of structural repair techniques using composite materials. Consequently, previous researchers have devised various analytical methods to predict the interface performance of bonded repairs. However, these analytical solutions are highly complex mathematically and necessitate numerous calculations with a large number of iterations to obtain the output parameters. In this paper, an artificial neural network prediction models is used to calculate the interfacial stress distribution in RC beams strengthened with FRP sheet. The R2value for the training data is evaluated as 0.99, and for the testing data, it is 0.92. Closed-form solutions are derived for RC beams strengthened with composite sheets simply supported at both ends and verified through direct comparisons with existing results. A comparative study of peak interfacial shear and normal stresses with the literature gives the usefulness and effectiveness of ANN proposed. A parametrical study is carried out to show the effects of some design variables, e.g., thickness of adhesive layer and FRP sheet.