• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.213-219
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• 2015

Real-time energy monitoring systems is a demand-response system which is reported to be effective in saving energy up to 12%. Real-time energy monitoring system is commonly composed of smart-plugs which sense how much electrical power is consumed and IHD(In-Home Display device) which displays power consumption patterns. Even though the monitoring system is effective, users should themselves match which smart plus is connected to which appliance. In order to make the matching work to be automatic, the monitoring system need to have appliance identification algorithm, and some works have made under the name of NILM(Non-Intrusive Load Monitoring). This paper proposed an algorithm which utilizes multiple classifiers to improve accuracy of appliance identification. The algorithm proposes to understand each classifiers performance, that is, when a classifier make a result how much the result is reliable, and utilize it in choosing the final result among result candidates from many classifiers. By using the proposed algorithm this paper make 4.5% of improved accuracy with respect to using single best classifier, and 2.9% of improved accuracy with respect to other method using multiple classifiers, so called CDM(Commitee Decision Mechanism) method.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.39-46
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• 1998

In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.229-235
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• 2019

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.82-89
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• 2006

Palmprint-based personal identification system, as a new member in the biometrics system family, has become an active research topic in recent years. Although lots of methods have been made, how to represent palmprint for effective classification is still an open problem and conducting researches. In this paper, the palmprint classification and recognition method based on PCA (Principal Components Analysis) using the dimension reduction of singular vector is proposed. And the 135dpi palmprint image which is obtained by the palmprint acquisition device is used for the effectual palmprint recognition system. The proposed system is consists of the palmprint acquisition device, DB generation algorithm and the palmprint recognition algorithm. The palmprint recognition step is limited 2 times. As a results GAR and FAR are 98.5% and 0.036%.

• Smart Structures and Systems
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• v.10 no.1
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• pp.47-65
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• 2012

The presence of crack-like defects in mechanical and structural elements produces failures during their service life that in some cases can be catastrophic. So, the early detection of the fatigue cracks is particularly important because they grow rapidly, with a propagation velocity that increases exponentially, and may lead to long out-of-service periods, heavy damages of machines and severe economic consequences. In this work, a non-destructive method for the detection and identification of elliptical cracks in shafts based on stress wave propagation is proposed. The propagation of a stress wave in a cracked shaft has been numerically analyzed and numerical results have been used to detect and identify the crack through the genetic algorithm optimization method. The results obtained in this work allow the development of an on-line method for damage detection and identification for cracked shaft-like components using an easy and portable dynamic testing device.

• Electrical & Electronic Materials
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• v.8 no.1
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• pp.48-55
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• 1995

A surface acoustic wave (SAW) sensor for the detection of odorants has been constructed by depositing various phospholipids and fatty acids onto the surface of the SAW device. The characteristics of a SAW device operating at 310 MHz deposited with silicon monoxide were analyzed. Menthone, amylacetate, acetoin, and other organic gases show different affinities to the coated lipids. An explanation is given for different odorant affinities based on the monolayer properties of phospholipids. The identification of odorants depending on the tkpe of lipid used for coating is discussed in terms of the similarity of their normalized resonant frequency shift patterns. Using a number of different lipid-coated SAW devices, odorants can be identified by a computerized pattern recognition algorithm.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.95-101
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• 2012

In this paper, we introduce the automatic speaker identification system 'SPO(Supreme Prosecutors Office) Verifier'. SPO Verifier is a GMM(Gaussian mixture model)-UBM(universal background model) based automatic speaker recognition system and has been developed using Korean speakers' utterances. This system uses a channel compensation algorithm to compensate recording device characteristics. The system can give the users the ability to manage reference models with utterances from various environments to get more accurate recognition results. To evaluate the performance of SPO Verifier on Korean speakers, we compared this system with one of the most widely used commercial systems in the forensic field. The results showed that SPO Verifier shows lower EER(equal error rate) than that of the commercial system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3997-4015
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• 2014

Radio frequency identification (RFID) is an emerging wireless communication technology which allows objects to be identified automatically. The tag anti-collision is a significant issue for fast identifying tags due to the shared wireless channel between tags and the reader during communication. The EPCglobal Class-1 Generation-2 which uses Q algorithm for the anti-collision is widely used in many applications such as consumer electronic device and supply chain. However, the increasing application of EPCglobal Class-1 Generation-2 which requires the dynamic environment makes the efficiency decrease critically. Furthermore, its frame length (size) determination and frame termination lead to the suboptimal efficiency. A new anti-collision algorithm is proposed to deal with the two problems for large-scale RFID systems. The algorithm has higher performance than the Q algorithm in the dynamic environment. Some simulations are given to illustrate the performance.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1994.05a
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• pp.90-93
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• 1994

A surface acoustic wave(SAW) sensor for the detection of odorants has been constructed by depositing various phospholipids and fatty acids onto the surface of the SAW device. Applying the Langmuir-Blodgett technique. it was possible to deposit the optimal number of layer which was found to be between 10 and 20. The characteristics of a SAW device operating at 310 MHz deposited with phosphatidyl choline were analysed. Menthone, amylacetate, acetion, and other organic gases sho7\\\\`ed different affinities to the coated lipids. An explanation is given for differant odorant affinities based on the monolayer properties of phospholipids. The identification of odorants depending on the type of lipid used for coating is discussed in terms of a comparison of their normalized resonant frequency chi It pat terns. Using a number of different lipid-coated SAW devices. odorants can be identified by a computerized pattern recognition algorithm.

• Smart Structures and Systems
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• v.20 no.5
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• pp.619-636
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• 2017

Magnetorheological (MR) damper is a type of controllable device widely used in vibration mitigation. This device is highly nonlinear, and exhibits strongly hysteretic behavior that is dependent on both the motion imposed on the device and the strength of the surrounding electromagnetic field. An accurate model for understanding and predicting the nonlinear damping force of the MR damper is crucial for its control applications. The MR damper models are often identified off-line by conducting regression analysis using data collected under constant voltage. In this study, a MR damper model is integrated with a model for the power supply unit (PSU) to consider the dynamic behavior of the PSU, and then a real-time nonlinear model updating technique is proposed to accurately identify this integrated MR damper model with the efficiency that cannot be offered by off-line methods. The unscented Kalman filter is implemented as the updating algorithm on a cyber-physical model updating platform. Using this platform, the experimental study is conducted to identify MR damper models in real-time, under in-service conditions with time-varying current levels. For comparison purposes, both off-line and real-time updating methods are applied in the experimental study. The results demonstrate that all the updated models can provide good identification accuracy, but the error comparison shows the real-time updated models yield smaller relative errors than the off-line updated model. In addition, the real-time state estimates obtained during the model updating can be used as feedback for potential nonlinear control design for MR dampers.