• Journal of IKEEE
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• v.23 no.4
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• pp.1166-1174
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• 2019

This paper propose and experiment advanced PersonNet, a human identification model, with advanced performance. We apply the inception layer to extract feature points, and increase the existing 32 feature points to 154. Also, we modify the CND method used by PersonNet to mitigate asymmetry, and apply weights to the feature map of pedestrian images in three parts, thereby making the features more distinct. Three databases were used for performance evaluation : CUHK01, CUHK03 and Market-1501. The experiment results showed 27-31% improvement in performance.

• Journal of Haehwa Medicine
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• v.19 no.2
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• pp.35-42
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• 2011

The purpose of this study is to evaluate the difference about pathogenesis of skin type. the theory that explains each individual react to certain stress is generally accepted in traditional oriental medicine. The aim of this experiment is to find out relationship between the effect of facial condition and the vital conditions of traditional Oriental medicine. We recognized that pattern identification of fluid-humor could be divided into 4 different groups. The reason is that the fluid-humor could be interpreted as Qi & Blood, furthermore Qi & Blood were categorized into deficiency and excess groups. Korean female volunteers in good health participated in this experiment. Three doctors of Oriental medicine classified them into 4 groups based on qi-blood and deficiency-excess concept(qi-deficiency; qi-excess:qi-stagnation; blood-deficiency; blood-excess:static-blood). Volunteers were assessed with non-invasive skin measuring devices. And we analyzed the correlation of skin physiological parameters with vital conditions; moisture, sebum and elasticity. Measurement moisture and sebum of facial skin tended to deacease only in static blood group.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.169-174
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• 2005

The AIS(Automatic Identification System) is the useful equipment in order to promote the maritime safety and real time monitoring at the sea. In this study, the plan to construct the ubiquitous Aids to navigation is proposed. In order to verify the construction of ubiquitous Aids to navigation, the experiment on the sea was carried out and analyzed.

• Smart Structures and Systems
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• v.16 no.1
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• pp.47-65
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• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.79-88
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• 2017

One of the important applications of activity sensing in the home is energy monitoring. Many previous methodologies for detecting and recognizing household appliances have been proposed. This paper presents an approach that uses an energy metering circuit (EMC) to classify and identify the various electrical devices in home based on root-mean-square (RMS) consumed current value. EMC gathers the RMS current values created by appliance state transition (e.g., on to off) and apparatus operating process. In this paper, an identification algorithm is proposed to detect a change in current levels using the standard deviation of current signals and their average values. In addition, characteristic of the appliance is extracted concerning four feature parameters concerning the number of current levels, the minimum level, the maximum level, and signal-to-noise ratio (SNR) of them. Experiment results validate the reliable performance of the proposed identification method for 11 representative appliances.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.317-324
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• 1995

A need exists for the accurate identification of time series models having time varying parameters, as is important in the case of real time identification of nonstationary EMG signal. Thls paper describes real time identification and muscle fatigue monitoring method of nonstationary EMG signal. The method is composed of the efficient identifier which estimates the autoregressive parameters of nonstationary EMG signal model, and its real time implementation by using T805 parallel processing computer. The method is verified through experiment with real EMG signals which are obtained from surface electrode. As a result, the proposed method provides a new approach for real time Implementation of muscle fatigue monitoring and the execution time is 0.894ms/sample for 1024Hz EMG signal.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.435-447
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• 2018

Fingerprint-based biometric identification is one of the most interesting automatic systems for identifying individuals. Owing to the poor sensing environment and poor quality of skin, biometrics remains a challenging problem. The main contribution of this paper is to propose a new approach to recognizing a person's fingerprint using the fingerprint's local characteristics. The proposed approach introduces the barycenter notion applied to triangles formed by the Delaunay triangulation once the extraction of minutiae is achieved. This ensures the exact location of similar triangles generated by the Delaunay triangulation in the recognition process. The results of an experiment conducted on a challenging public database (i.e., FVC2004) show significant improvement with regard to fingerprint identification compared to simple Delaunay triangulation, and the obtained results are very encouraging.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1189-1196
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• 2010

This paper provides an identification method for three-parameter models i.e. first order with dead time models and second order with dead time models. The proposed identification method is based on step response and can be easily implemented using digital microprocessors. The proposed method first identifies the order of the plant i.e. first order or second order from the behavior of the plant with constant input. After the order of the plant is determined, a test step input is applied to the system and the three parameters of the plant are obtained from the corresponding response of the plant. The output of the plant need not to be zero when the test signal is applied. The efficacy of proposed algorithms is verified through simulation and experiment.

• Journal of KSNVE
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• v.6 no.6
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• pp.835-842
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• 1996

To identify the locations and strengths of acoustic sources, one may use a microphone line array. Apparent advantage of the source identification method utilizing a line array is that it requires less measurement points than intensity method and holography. This method is based on the information of magnitude and phase difference between pressure signals at each microphone. Since those differences are dependent on the source model, we have to assume them such as plane, monopole, etc. In this paper the conventional source identification methods such as beamforming method and MUSIC method are briefly reviewed by modeling a source as plane and spherical wave, then a modified method is introduced. This can be applied to sound field which may by either coherent or incoherent. Typical simulations and experiment are performed to confirm this identification method.