인공신경망 알고리즘을 이용한 손상된 RC교량의 유지관리시스템 개발

손용우 ( Yong-woo Son ),이경동 ( Gyeong-dong Lee ),한상호 ( Sang-ho Han ) 한국환경기술학회 2005 한국환경기술학회지 Vol.6 No.3

현재 교량 바닥판손상의 증가에 따라 본 연구의 적정유지관리 전문가 시스템 모델을 이용함으로써 보다 효율적인 교량 바닥판의 보수·보강 판정뿐 만 아니라 생애주기비용에 대한 보수비용 예측을 수행할 수 있으며, 보수·보강비용 예측평가모델은 실제 개축비용 자료를 바탕으로 회귀분석방법에 의해 개발되었기 때문에 교량 바닥판의 유지관리 대책에 필요한 보수·보강을 위한 우선순위 결정에 실용적으로 활용될 수 있다고 사료된다. 보수·보강 공법의 선정문제는 보다 높은 신뢰성을 얻기 위하여 많은 자료와 전문지식과 경험을 수집하여 계속적인 보완이 필요하고, 나아가 교량구조물 전체에 대한 전문가 시스템의 구성을 위해 지속적인 연구노력이 필요하다. The purpose of this study makes a retrofit and rehabilitation practice through the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for RC deck slabs were analyzed. Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing reinforced concrete bridge decks from damage cause, damage type, and integrity assessment at the initial stage is need. The training and testing of the network were based on a database of 36. Four different network models were used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterns were minimized. This generally occurred after about 5,000 cycles of training.

스트리밍 서비스의 품질 보장을 위한 전송률 제어 기법

김동칠(Dongchil Kim),정광수(Kwangsue Chung) 한국정보과학회 2012 정보과학회 컴퓨팅의 실제 논문지 Vol.18 No.11

무선 네트워크는 불안정한 채널 특성과 제한된 대역폭으로 인해 멀티미디어 스트리밍 서비스의 품질을 보장하지 못한다. 본 논문에서는 광대역 무선 네트워크에서 스트리밍 서비스의 품질 보장을 위한 적응적 전송률 제어기법인 N-RC(Network-aware Rate Control)를 제안한다. N-RC 기법은 기지국에 접속한 단말의 수와 무선 채널 상태를 고려하여 적응적으로 전송률을 조절한다. 또한, 측정된 가용 대역폭을 기반으로 비디오 품질을 조절한다. 실험 결과를 통해 제안하는 기법이 무선 네트워크 환경에서 전송률 향상과 패킷 손실률을 최소화하여 비디오의 재생 품질을 보장할 수 있음을 확인하였다. Due to the characteristics of unreliable channel and limited bandwidth, wireless networks do not guarantee the quality for multimedia streaming services. In this paper, N-RC (Network-aware Rate Control) scheme is proposed to improve the media quality for streaming services in broadband wireless networks. N-RC scheme adjusts transmission rates according to the number of devices accessed to BS (Base Station) and wireless network status. It also controls the video quality based on estimated network bandwidth. The simulation results show that the proposed scheme can guarantee the video playback quality by reducing packet loss ratio and improving transmission rates in wireless networks.

센서네트워크의 보안 오버헤드를 줄이기 위한 신뢰와 RBAC 기반의 타원곡선암호

김효진 ( Hyo Jin Kim ),박호 ( Ho Hyun Park ) 한국정보처리학회 2013 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.2 No.11

배터리를 사용하는 센서 네트워크에서는 불필요한 오버헤드를 줄이는 것이 중요하다. 또한 보안의 필요성으로 인해 암호화 역시 중요하다. 하지만 암호화의 경우 어쩔 수 없는 오버헤드가 발생하는 데 보안과 오버헤드는 트레이드오프 관계에 있다. 본 논문에서는 암호화시 추가되는 오버헤드를 줄이기 위하여 신뢰값(Trust)라는 개념을 암호화에 사용하고 신뢰도가 높은 경로와 신뢰도가 낮은 경로 이용시 암호화에 사용되는 키 크기의 조절을 통해 보안 수준은 유지하면서 오버헤드는 줄이는 방법을 시도하였다. 시뮬레이션을 통해 일반적인 암호화와 신뢰값을 고려한 암호화를 비교하였고 그 결과 신뢰값을 고려하는 경우가 총 실행시간도 적고 오버헤드도 적었다. 실제 네트워크에서 구성 목적이나 환경 조건을 고려하여 보안 수준을 충족하는 신뢰값 기준을 정한다면 센서 네트워크에서 제한된 리소스를 효율적으로 사용할 수 있을 것이다. It is important to reduce unnecessary overhead in sensor network using battery. In addition encryption is important because of necessity of security. Since unavoidable overhead occurs in case of encryption, security and overhead are in trade-off condition. In this paper, we use a concept called trust to reduce the encryption overhead. We reduce overhead by controlling encryption key sizes while maintaining the security level where high and low trust nodes are mixed. We simulated and compared normal encryption and trust value based encryption. As a result, the latter has lower execution time and overhead. If we define a standard of trust levels considering purpose and circumstances of real network, we can use constrained resources efficiently in sensor network.

Whole learning algorithm of the neural network for modeling nonlinear and dynamic behavior of RC members

Satoh, Kayo,Yoshikawa, Nobuhiro,Nakano, Yoshiaki,Yang, Won-Jik Techno-Press 2001 Structural Engineering and Mechanics, An Int'l Jou Vol.12 No.5

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.

Evaluation of Encryption Method of SNEP for Implementing Security in Wireless Sensor Network using SPINS Framework

Vartika Shah,Sanjiv Sharma 보안공학연구지원센터 2014 International Journal of Grid and Distributed Comp Vol.7 No.5

Wireless sensor network (WSN) is a collection of densely deployed sensor nodes. These nodes are prone to attack and also resource constrained. Resource accountability is also required for Security implementation in WSN. Some researchers proposed different methods, algorithms and frameworks for WSN security implementation. SPINS is a framework for implementing overall security in WSN using SNEP (Sensor Network Encryption Protocol) and μTESLA (the “micro” version of the Timed, Efficient, Streaming, Loss-tolerant Authentication Protocol) protocol. Existing research works reveal that SNEP employed RC5 encryption algorithm for WSN. This paper analyzed efficient encryption algorithm XTEA for SNEP & evaluate that it is better as compare to RC5 in terms of energy, storage and time.

Bond strength prediction of steel bars in low strength concrete by using ANN

Sohaib Ahmad,Kypros Pilakoutas,Muhammad M. Rafi,Qaiser U. Zaman 사단법인 한국계산역학회 2018 Computers and Concrete, An International Journal Vol.22 No.2

This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi- Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.

Active Notch Uniformly Distributed RC Circuit and Their Application

Nipont Tangthong,Virote Pirajnanchai,Kanok Janchitrapongvej 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

Many application of the RC parallel-T network, only two performance characteristics are considered important the frequency and depth of the attenuation notch. In this paper the design presented, active notch distributed RC network (U RC) circuit from design values. The proposed circuit configuration consists of U RC , one external resistor (Rn) or capacitor (Cn) and single gain amplifier. The parameters of the proposed circuit can be adjusted to improve the magnitude response with notch tunable frequency. This structure reduces an amount of circuit complexity and is simple to use for application. The experiments and computer simulation showed good agreement with theoretical values. The active notch U RC can application to experiments high frequency active band-pass filter, sinusoidal wave oscillator and frequency discriminator

Neural-based prediction of structural failure of multistoried RC buildings

Sirshendu Hore,Sankhadeep Chatterjee,Sarbartha Sarkar,Nilanjan Dey,Amira S. Ashour,Dana Bălas-Timar,Valentina E. Balas 국제구조공학회 2016 Structural Engineering and Mechanics, An Int'l Jou Vol.58 No.3

Various vague and unstructured problems encountered the civil engineering/ designers that persuaded by their experiences. One of these problems is the structural failure of the reinforced concrete (RC) building determination. Typically, using the traditional Limit state method is time consuming and complex in designing structures that are optimized in terms of one/many parameters. Recent research has revealed the Artificial Neural Networks potentiality in solving various real life problems. Thus, the current work employed the Multilayer Perceptron Feed-Forward Network (MLP-FFN) classifier to tackle the problem of predicting structural failure of multistoried reinforced concrete buildings via detecting the failure possibility of the multistoried RC building structure in the future. In order to evaluate the proposed method performance, a database of 257 multistoried buildings RC structures has been constructed by professional engineers, from which 150 RC structures were used. From the structural design, fifteen features have been extracted, where nine features of them have been selected to perform the classification process. Various performance measures have been calculated to evaluate the proposed model. The experimental results established satisfactory performance of the proposed model.

Improving QoS using Cellular-IP/PRC in Hospital Wireless Network

Sung hong Kim 한국전자통신학회 2006 한국전자통신학회 논문지 Vol.1 No.2

병원 무선망에서 호 수락 방식과 보다 적은 범위 셀 환경에서 QoS를 보장하기 위해 통합된 페이징과 루프 정보 관리 캐시를 사용하는 Cellular IP 특성을 가진 Cellular-IP/PRC 네트워크를 제안한다. 제안한 호 수락 방식은, 이동 노드의 홈 기지국 용량이 충분하고, 인접 셀 이동 노드가 홈 기지국에서 호가 수락되었다고 가정할 경우 받을 간섭의 증가량을 고려해 통화 품질이 보장될 때, 홈 기지국은 새로운 호를 이동 노드의 송신 전력 예측에 기반을 둔 호 수락 방식이다. 병원 무선망 내의 페이징과 라우터를 관리하기 위해 사용되었던 PC(Paging Cache)와 RC(Routing Cache)를 하나의 PRC(Paging Router Cache)로 통합 관리하고, 모든 노드 내에 구성하여 운용토록 하고, 이동 노드의 핸드오프 및 로밍 상태를 효율적으로 관리 할 수 있도록 이동 노드에 핸드오프 상태 머신을 추가하며, 노드에서 관련 기능을 수행하도록 연구한다. 시스템 환경에서 통화량에 영향을 주는 인자를 분석하고 각 링크 통화권 및 불균형 정도를 예측하여, 하향링크에 의해 통화권이 제한되었는지를 판단하여 호를 수락 또는 차단하는 알고리즘 이용 총 송수신 전력을 기반으로 제안한 알고리즘을 응용해서 QoS에서 가장 밀접하고 중요한 호 차단 확률과 호 탈락 확률, GoS(Grade of Service), 셀 용량의 효율을 예측 처리하여 QoS 성능 개선을 나타낸다. In this paper, we propose for improving QoS in hospital wireless network using Cellular-IP/PRC(Paging Route Cache) with Paging Cache and Route Cache in Cellular-IP. Although the Cellular-IP/PRC technology is devised for mobile internet communication, it has its vulnerability in frequent handoff environment. This handoff state machine using differentiated handoff improves quality of services in Cellular-IP/PRC. Suggested algorithm shows better performance than existing technology in wireless mobile internet communication environment. When speech quality is secured considering increment of interference to receive in case of suppose that proposed acceptance method grooves base radio station capacity of transfer node is plenty, and most of contiguity cell transfer node was accepted at groove base radio station with a blow, groove base radio station new trench lake acceptance method based on transmission of a message electric power estimate of transfer node be. Do it so that may apply composing PC(Paging Cache) and RC(Routing Cache) that was used to manage paging and router in radio Internet network in integral management and all nodes as one PRC(Paging Router Cache), and add hand off state machine in transfer node so that can manage hand off of transfer node and Roaming state efficiently, and studies so that achieve connection function at node. Analyze benevolent person who influence on telephone traffic in system environment and forecasts each link currency rank and imbalance degree, forecast most close and important lake interception probability and lake falling off probability, GoS(Grade of Service), efficiency of cell capacity in QoS because applies algorithm proposing based on algorithm use gun send-receive electric power that judge by looking downward link whether currency book was limited and accepts or intercept lake and handles and displays QoS performance improvement.

Realizable Reduction of RC Networks with Current Sources for Dynamic IR-Drop Analysis of Power Networks of SoCs

CHE, Hong Bo,PARK, Hyoun Soo,KIM, Jin Wook,KIM, Young Hwan The Institute of Electronics, Information and Comm 2009 IEICE transactions on fundamentals of electronics, Vol.92 No.2

<P>The authors present R<SUP>2</SUP>Power, an effective approach to the realizable reduction of RC networks with independent current sources. The proposed approach is based on the entrywise perturbation theory for diagonally dominant M-matrices. The accuracy of the node voltages of the reduced network, as compared to those of the original network, is maintained on the order of the entrywise perturbation performed during reduction. R<SUP>2</SUP>Power can be used to reduce the size of RC networks used to model the power networks of SoCs, for efficient IR-drop analysis. Experiments showed that R<SUP>2</SUP>Power reduced the size of industrial examples by more than 95%, with maximum relative node voltage errors of less than 0.012%.</P>