• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.492-503
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• 2008

With the recent development and increasing importance of personal identification systems, biometric technologies with less risk of loss or unauthorized use are being popularized rapidly. In particular, because of their high identification rate and convenience, fingerprint identification systems are being used much more commonly than other biometric systems such as iris recognition, face recognition and vein pattern recognition. However, a fingerprint identification system has the problem that artificially forged finger-prints can be used as input data. Thus, in order to solve this problem, the present study proposed a method for detecting forged fingerprints by measuring the degree of attenuation when the light from an optical fingerprint sensor passes through the finger and analyzing changes in the transmission of light over stages at fixed intervals. In order to prove improvement in the performance of the proposed system, we conducted an experiment that compared the system with an existing multi-sensor recognition system that measures also the temperature of fingerprint. According to the results of the experiment, the proposed system improved the forged fingerprint detection rate by around 32.6% and this suggests the possibility of solving the security problem in fingerprint identification systems.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.501-512
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• 2018

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A two-stage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC $0.18{\mu}m$ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of $0.15^{\circ}C$/LSB and a temperature error of $-0.6/0.7^{\circ}C$ within the range from $-30^{\circ}C$ to $70^{\circ}C$. The proposed sensor tag achieves maximum communication distance of 11.8 m.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.272-284
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• 2013

In this paper, we propose a new framework for anomaly detection in medical wireless sensor networks, which are used for remote monitoring of patient vital signs. The proposed framework performs sequential data analysis on a mini gateway used as a base station to detect abnormal changes and to cope with unreliable measurements in collected data without prior knowledge of anomalous events or normal data patterns. The proposed approach is based on the Mahalanobis distance for spatial analysis, and a kernel density estimator for the identification of abnormal temporal patterns. Our main objective is to distinguish between faulty measurements and clinical emergencies in order to reduce false alarms triggered by faulty measurements or ill-behaved sensors. Our experimental results on both real and synthetic medical datasets show that the proposed approach can achieve good detection accuracy with a low false alarm rate (less than 5.5%).

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.63-69
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• 2016

Although the previous information technologies had been used for the quick and accurate processing of work, At present, however, as the combination with the Internet, the IOT(Internet-of-Things) era in which the diverse pieces of information are collected and handled through the sensor networks is in progress. Among these application fields of the IoT, the indoors position identification technology has been developing in the direction of providing the position information in the buildings of which the lengths and the interiors are complicated and in the direction of providing the various pieces of information and others of the like to the nearby customers. In this paper, we proposed an indoors position identification system that detects the patrol positions of the prison officers in the correctional facilities and in the prisons by using the ultrasonic waves, that transmits these to the control system and the data gateway, and that transmits the detected data. The Indoors Positioning identification System is organized with the tags for recognizing the positions that transmit the ultrasonic signal, ultrasonic receiver and data gateway. And the indoors position information data were transmitted to the management system through the data gateway. We evaluated the transmission error, by changing the distance of the proposed system for location recognition tag and the receiver, As a result, we found out that, when the transmission distance was 10 cm or less, the errors occurred in the form of the distortions. And when it was 110 cm or more, the transmission errors occurred due to the propagation diminutions of the ultrasonic wave signals. And when the transmission distance was from 10 cm to 100 cm, it was shown that the proposed system was possible without any errors.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.331-350
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• 2017

Based on the alternative stabilization diagram by varying the time lag parameter in the stochastic subspace identification analysis, this study aims to investigate the measurements from several cases of civil structures for extending the applicability of a recently noticed criterion to ensure stable identification results. Such a criterion demands the time lag parameter to be no less than a critical threshold determined by the ratio of the sampling rate to the fundamental system frequency and is firstly validated for its applications with single measurements from stay cables, bridge decks, and buildings. As for multiple measurements, it is found that the predicted threshold works well for the cases of stay cables and buildings, but makes an evident overestimation for the case of bridge decks. This discrepancy is further explained by the fact that the deck vibrations are induced by multiple excitations independently coming from the passing traffic. The cable vibration signals covering the sensor locations close to both the deck and pylon ends of a cable-stayed bridge provide convincing evidences to testify this important discovery.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.1038-1046
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• 2008

This study was carried out to develop a small-sized biosensor based on surface plasmon resonance (SPR) for the rapid identification of insecticide residues for food safety. The SPR biosensor module consists of a single 770 nm-light emitting diodes (LED) light source, several optical lenses for transferring light, a hemisphere sensor chip, photo detector, A/D converter, power source, and software for signal processing using a computer. Except for the computer, the size and weight of the sensor module are 150 (L)$\times$70 (W)$\times$120 (H) mm and 828 g, respectively. Validation and application procedures were designed to assess refractive index analysis, affinity properties, sensitivity, linearity, limits of detection, and robustness which includes an analysis of baseline stability and reproducibility of ligand immobilization using carbamate (carbofuran and carbaryl) and organophosphate (cadusafos, ethoprofos, and chlorpyrifos) insecticide residues. With direct binding analysis, insecticide residues were detected at less than the minimum 0.01 ppm and analyzed in less than 100 sec with a good linear relationship. Based on these results, we find that the binding interaction with active target groups in enzymes using the miniaturized SPR biosensor could detect low concentrations which satisfy the maximum residue limits for pesticide tolerance in Korea, Japan, and the USA.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.127-138
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• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.673-676
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• 1993

The field-oriented control of induction motor without speed sensor has been widely studied. This paper proposes the new design method of adaptive sliding observer for induction motor, which include the rotor speed identification together with the rotor flux estimation. The proposed adaptive observer has advantage of their global stability which is developed on some assumption. It is easy to analyse because the identifier is seperated from the controller. Finally, the chattering which is caused by switching is reduced by new control scheme, and the validaity of the adaptive algorithm is verified by simulation.