• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.225-231
• /
• 2006

The purpose of this study is to develop a promising hybrid structural health monitoring system for structural joints. For this propose, the combined use of vibration-based techniques and electro-mechanical impedance technique is employed. For the verification of the proposed health monitoring scheme, a series of damage scenarios are designed to simulate various situations at which the connection joints can experience during their service life. The obtained experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the connecting states and the target damage locations. From the analysis. it is shown that the proposed hybrid health monitoring system is successful for acquiring global and local damage information on the structural joints.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.669-674
• /
• 2007

To develop a promising hybrid structural health monitoring (SHM) system, a combined use of structural vibration and electro-mechanical (EM) impedance is proposed. The hybrid SHM system is designed to use vibration characteristics as global index and EM impedance as local index. The proposed health monitoring scheme is implemented into prestressed concrete (PSC) girder bridges for which a series of damage scenarios are designed to simulate various prestress-loss situations at which the target bridges car experience during their service life. The measured experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the occurrence of damage and furthermore to indicate its location.

• Convergence Security Journal
• /
• v.1 no.1
• /
• pp.57-68
• /
• 2001

Computer security is considered important because of the side effect generated from the expansion of computer network and rapid increase of the use of computer. Intrusion Detection System(IDS) has been an active research area to reduce the risk from intruders. In this paper, the Hybrid Intrusion Detection System(HIDS) based biometric immuntiy collects and filters audit data by misuse detection is innate immune, and anomaly detection is acquirement immune in multi-hosts. Since, collect and detect audit data from one the system in molt-hosts, it is design and implement of the intrusion detection system which has the immuntiy the detection intrusion in one host possibly can detect in multi-hosts and in the method of misuses detection subsequently.

• Journal of Korean Institute of Industrial Engineers
• /
• v.20 no.4
• /
• pp.113-134
• /
• 1994

A radial basis hybrid neural network (RHNN) is presented for an on-line detection of machine condition change. Two-phase modeling by RHNN is designed for describing a machine condition process and for predicting future signal. A moving block procedure is also designed for detecting a process change. A fast on-line learning algorithm, the recursive least square estimation, is introduced. Experimental results showed the RHNN could be utilized efficiently for on-line machine condition monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.1
• /
• pp.42-48
• /
• 2006

In this paper a joint detection method for other cell interference cancellation is proposed in the next generation hybrid TD-CDMA mobile communication systems. A joint detection technique, a most characteristic feature of hybrid TD-CDMA mobile communication systems. retrieves users' data in the same time slot simultaneously with the elimination of multiple user interference. Previously a two stage joint detection method was proposed to cancel other cell interference as well as multiple user interference in the target cell. However the previous scheme does not have concrete ways to recognize other cell users who give major interference to the target cell. Thus all users in neighbor other cells has to be jointly detected and it causes huge complexity of the two stage joint detection. In this paper a method is proposed to perform two stage joint detection according to users' interference with the target cell. Performances of the proposed scheme are investigated through simulations and compared to the previous method the proposed method has no performance degradation and also lower the complexity of two stage joint detection significantly.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.3B
• /
• pp.472-486
• /
• 2000

This paper analysis the performance of joint receiving structure consisting of the decorrelating multiuser detection and beamfromenr-RAKE receive for DS-CDMA communication systems. In asynchronous transmission as the number of simultaneous users increase. the capacity of CDMA system becomes severly reduced due to the nonideal orthogonality between user-assigned PN sequences and improper power control. Accordingly, the CDMA receiving system becomes vulnerable to the multiple access interferences and the near-far problem under multipath fading channel environment. To withstand these undesired performance degradations, this paper proposes the new type of multiuser detection which has a form of the hybrid structure of concatenating beamformer-RAKE receiver and decorrelating multiuser detection. the beam former-RAKE receiver performs temporal and spatial diversity combining with alleviating fading effect and suppressing undesired interferences, and the multiuser detection plays a role of making the receiver robust to the near-far problem. Regarding the individual merit on the usage of either multiuser detection or beamformer-RAKE receiver, the hybrid one is expected to produce the enhanced performance in multipath fading CDMA channel. However major drawback of using decorrelating multiuser detection for practical deployment is arised from its computational complexity , which is exponentially increased as more number of users and transmitted symbols involve. To diminish the computational complexity, this paper exploits an efficient block Toeplitz inversion technique using matrix Levinson polynomial will be introduced. And this paper provided the mathematical analysis to show the efficiency of the proposed joint structure under the multipath propagation environment. And results of a series of exhaustive computer simulations are presented in order to demonstrate the overall performance of the proposed hybrid structure in multipath fading CDMA channel.

• The KIPS Transactions:PartC
• /
• v.10C no.6
• /
• pp.727-738
• /
• 2003

Much research efforts are being exerted for the study of intrusion detection system(IDS). However little work has been for the communication medels and performance eveluation of the IDS. Here we present a communication framework for doing hybrid intrusion detection in which agents are used for local intrusion detections with a centralized data anaysis componenta for a global intrusion detection at multiple domains environment. We also assume the combination of host-based and network-based intrusion detection systems in the oberall framework. From the local domain, a set of information such as alert, and / or log data are reported to the upper level. At the root of the hierarchy, there is a global manager where data coalescing is performed. The global manager delivers a security policy to its lower levels as the result of aggregation and correlation of intrusion detection alerts. In this paper, we model the communication mechanisms for the hybrid IDS and develop a simular using OPNET modeller for the performance evaluation of transmission capabillities for the delivery of data and policy. We present and compare simulation results based on several scenarios focuding on communication delay.

• ETRI Journal
• /
• v.40 no.2
• /
• pp.218-226
• /
• 2018

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

• Journal of Korea Multimedia Society
• /
• v.18 no.3
• /
• pp.359-367
• /
• 2015

In this paper, we propose intelligent fire learning and detection system using hybrid visual attention mechanism of human. Proposed fire learning system generates leaned data by learning process of fire and smoke images. The features used as learning feature are selected among many features which are extracted based on bottom-up visual attention mechanism of human, and these features are modified as learned data by calculating average and standard variation of them. Proposed fire detection system uses learned data which is generated in fire learning system and features of input image to detect fire.

• Journal of Information Processing Systems
• /
• v.18 no.1
• /
• pp.146-158
• /
• 2022

With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.