• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.14 no.1
• /
• pp.84-92
• /
• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion skewness, kurtosis) about each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.

• Korean Institute of Interior Design Journal
• /
• v.22 no.5
• /
• pp.152-161
• /
• 2013

This study is about the visual appreciation by sex with the analysis of time range of observing data which was got through observation experiment with the space of lobby in hospitals. The observation data of the subjects who observed the space include the frequency and time, through which the process of visual appreciation could be evaluated with the definition of the frequency and the time of observation. First, the fact that men had higher frequency of observation than women means the former had more movement than the latter, and another fact of their fewer times can be understood as the time of their staying was shorter. That is, even though the men had more movements of sight, they showed the feature of staying shorter. Second, the rate high and low of observation frequency and times made it possible for observation characteristics to be defined as 'intensive search' 'active search' 'fixed concentration' and 'search wandering.' The definition of understanding this process of visual appreciation can be available for a frame of effective analysis of observation characteristics according to the passage of time. Third, the intense search is the case of 'high frequency' having the feature of high visual appreciation owing to the active visual actions for acquiring information. Men were found to have more intense search which decreased gradually as time passed, while women showed the feature of many times of intense search. Fourth, it was found that with many observation data in a certain range of time the subjects had fixed concentration, where women were found to have repetitive fixed concentration along with the change of observation time while men were seen to have more observation tendency for fixed concentration. Fifth, at the cross tabulation of frequency and times, men had the feature of dispersed visual appreciation while women had more distinction between fixation and movement, which revealed that there is surely the difference between men and women in the process of visual appreciation.

• The Journal of Bigdata
• /
• v.1 no.1
• /
• pp.61-66
• /
• 2016

With big data analysis, companies use the customized marketing strategy based on customer's information. However, because of the concerns about privacy issue and identity theft, people start erasing their personal information or changing the privacy settings on social network site. Facebook, the most used social networking site, has the feature called 'Likes' which can be used as a tool to predict user's demographic profiles, such as sex and age range. To make accurate analysis model for the study, 'Likes' data has been processed by using Gaussian RBF and nFactors for dimensionality reduction. With random Forest and 5-fold cross-validation, the result shows that sex has 75% and age has 97.85% accuracy rate. From this study, we expect to provide an useful guideline for companies and marketers who are suffering to collect customers' data.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.254-259
• /
• 2015

In this paper, The wireless robot control system was proposed using Brain-computer interface(BCI) systems based on the steady-state visual evoked potential(SSVEP). Cross Power Spectral Density(CPSD) was used for analysis of electroencephalogram(EEG) and extraction of feature data. And Linear Discriminant Analysis(LDA) and Support Vector Machine(SVM) was used for patterns classification. We obtained the average classification rates of about 70% of each subject. Robot control was implemented using the results of classification of EEG and commanded using bluetooth communication for robot moving.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.53 no.2
• /
• pp.65-69
• /
• 2004

This paper calculates and gives the analysis of electron swarm transport coefficients as described electric conductive characteristics of pure Ar, pure $SiH_4$, Ar-$SiH_4$ mixture gases($SiH_4$-0.5%, 2.5%, 5%) over the range of E/N = 0.01~300[Td], P = 0.1, 1, 5.0 [Torr] by Monte Carlo the backward prolongation method of the Boltzmann equation using computer simulation without using expensive equipment. The results have been obtained by using the electron collision cross sections by TOF, PT, SST sampling, compared with the experimental data determined by the other author. It also proved the reliability of the electron collision cross sections and shows the practical values of computer simulation. Electron swann parameters in argon were drastically changed by adding a small amount of mono-silane. The electron drift velocity in these mixtures showed unusual behaviour against E/N. It had negative slope in the medium range of E/N, yet the slope was not smooth but contained a small hump. The longitudinal diffusion coefficient also showed a corresponding feature in its dependence on E/N. A two-tenn approximation of the Boltzmann equation analysis and Monte Carlo simulation have been used to study electron transport coefficients.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.3 s.35
• /
• pp.173-182
• /
• 2005

In this paper, we propose a landmark recognition method which is irrelevant to the camera viewpoint on the navigation for localization. Features in previous research is variable to camera viewpoint, therefore due to the wealth of information, extraction of visual landmarks for positioning is not an easy task. The proposed method in this paper, has the three following stages; first, extraction of features, second, learning and recognition, third, matching. In the feature extraction stage, we set the interest areas of the image. where we extract the corner points. And then, we extract features more accurate and resistant to noise through statistical analysis of a small eigenvalue. In learning and recognition stage, we form robust feature models by testing whether the feature model consisted of five corner points is an invariant feature irrelevant to viewpoint. In the matching stage, we reduce time complexity and find correspondence accurately by matching method using similarity evaluation function and Graham search method. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed methods.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.5
• /
• pp.1001-1009
• /
• 2015

In Smart Grid, smart meter sends our electric signal data to the main server of power supply in real-time. However, the more efficient the management of power loads become, the more likely the user's pattern of usage leaks. This paper points out the threat of privacy and the need of security measures in smart device environment by showing that it's possible to identify the appliances and the specific usage patterns of users from the smart meter's data. Learning algorithm PCA is used to reduce the dimension of the feature space and k-NN Classifier to infer appliances and states of them. Accuracy is validated with 10-fold Cross Validation.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.26 no.1
• /
• pp.133-140
• /
• 2002

This article presents an application of a large-scale structural mixing model(Broadwell et at. 1984) to the blowout of turbulent reacting cross flow jets. Experimental observations, therefore, aim to identify the existence of large-scale vortical structure exerting an important effect upon the flame stabilization. In the analysis of common stability curve, it is seen that the phenomenon of blowout are only related to the mixing time scale of the two flows. The most notable observation is that the blowout distance is traced at a fixed positions according to the velocity ratio at all times. Measurements of the lower blowout limits in the liftable flame are qualitatively in agreement with the blowout parameter $\xi$, proposed by Broadwell et al. Good agrement between the results calculated by a modified blowout parameter $\xi$'and the present experimental results confirms the important effect of large-scale structure in the stabilization feature of blowout.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.6
• /
• pp.1098-1115
• /
• 2010

An inseparable challenge associated with every random access network is the design of an efficient Collision Resolution Algorithm (CRA), since collisions cannot be completely avoided in such network. To maximize the collision resolution efficiency of a popular CRA, namely Binary Exponential Backoff (BEB), we propose a reactive backoff algorithm. The proposed backoff algorithm is reactive in the sense that it updates the contention window based on the previously selected backoff value in the failed contention stage to avoid a typical type of collision, referred as cross-collision. Cross-collision would occur if the contention slot pointed by the currently selected backoff value appeared to be present in the overlapped portion of the adjacent (the previous and the current) windows. The proposed reactive algorithm contributes to significant performance improvements in the network since it offers a supplementary feature of Cross Collision Exclusion (XCE) and also retains the legacy collision mitigation features. We formulate a Markovian model to emulate the characteristics of the proposed algorithm. Based on the solution of the model, we then estimate the throughput and delay performances of WLAN following the signaling mechanisms of the Distributed Coordination Function (DCF) considering IEEE 802.11b system parameters. We validate the accuracy of the analytical performance estimation framework by comparing the analytically obtained results with the results that we obtain from the simulation experiments performed in ns-2. Through the rigorous analysis, based on the validated model, we show that the proposed reactive cross collision exclusionary backoff algorithm significantly enhances the throughput and reduces the average packet delay in the network.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.2
• /
• pp.359-365
• /
• 2020

Sasang Constitution data that were classified by the QSCCII (Questionnaire for the Sasang Constitution Classification II) and artery pulse waves of Chon, Guan, and Chuck data measured using an electronic manometer, were obtained from 732 subjects who visited an oriental hospital. The pulse width, peak height, and number of peaks were extracted from the pulse waves as feature variables. Validity and reliability analyses were performed to obtain the feature variables. The feature variables with high validity and reliability were selected as the discriminant variables. The pulse wave data were divided into training and predicting samples by applying a fivefold cross-validation technique. Discriminant analysis was performed for the training sample, and discriminant functions were obtained. The discriminant functions were applied to the predicting sample and the Sasang Constitution was predicted. The accuracy of prediction was estimated by comparing the predicted Sasang Constitution and that obtained by QSCCII. The accuracy of the predicted Sasang Constitution before (after) age and sex calibration was 73.6 % (70.4 %), 68.4 % (84.2 %), and 74.2 % (67.7 %) for Taeumin, Soumin, and Soyangin, respectively, and 72.5 % (73.8 %) in total.