• Journal of IKEEE
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• v.22 no.3
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• pp.651-657
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• 2018

IEEE 802.11 wireless LANs support 20, 40, 80 and 160MHz bandwidth transmission. In general, the data rate increases as the transmission bandwidth increases. However, the transmission power spectral density decreases, which may lead to increasing packet errors and retransmissions. In this paper, we derive a mathematical model of energy consumption with consideration of various factors such as transmission bandwidth, packet error rate and data size. Based on the model, we design a scheme to adapt a transmission bandwidth for each frame transmission. The scheme estimates packet error rates for different bandwidth cases, updates the table of energy consumption and selects the best bandwidth for the next transmission. The simulation study with VoIP traffic shows the energy consumption of the scheme under various environments.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.533-540
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• 2014

We propose an age estimation-based smart digital signage for the next-generation airport service. The proposed system can recognize the face of the customer so that it can display the selective information. Using a webcam, the system captures the face of the customer and estimates the age of the customer by calculating the wrinkle density of the face and applying bayesian classifier. The developed age estimation method is tested with a face database for the performance evaluation. We expect the new digital signage may improve the satisfaction of customers of the airport business.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1088-1097
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• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.63-76
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• 2014

Although most behavioral reaction times (RTs) for cognitive tasks exhibit positively skewed distributions, the majority of studies primarily rely on a measure of central tendency (e.g. mean) which can cause misinterpretations of data's underlying property. The purpose of current study is to introduce procedures for describing characteristics of RT distributions, thereby effectively examine the influence of experimental manipulations. On the basis of assumption that RT distribution can be represented as a convolution of Gaussian and exponential variables, we fitted the ex-Gaussian function under a maximum-likelihood method. The ex-Gaussian function provides quantitative parameters of distributional properties and the probability density functions. Here we exemplified distributional analysis by using empirical RT data from two conventional visual search tasks, and attempted theoretical interpretation for setsize effect leading proportional mean RT delays. We believe that distributional RT analysis with a mathematical function beyond the central tendency estimates could provide insights into various theoretical and individual difference studies.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.694-702
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• 2014

Since Greenhouse Gas Inventory & Research Center (GIR) of Korea was founded in 2010, the annual greenhouse gas inventory reports, one of the collections of GIR's major affairs, have been published from 2012. In the reports many items related to greenhouse gas emission quantities are included, but among them uncertainty values are replaced to basic values which IPCC guideline suggests. Even though IPCC guideline suggests the equations of each Tier level in details, the guideline recommends developing nation's own methodology on uncertainty which is closely related to statistical problems such as the estimation of a probability density function or Monte carlo methods. In the road transportation sector the emissions have been calculated by Tier 1 but the uncertainties have not been reported. This study introduce a bootstrap technique and Monte carlo method to estimates annual emission quantity and uncertainty, given activity data and emission factors such as annual traveled distances, fuel efficiencies and emission coefficients.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.5
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• pp.390-396
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• 2000

The dynamic elastic constants of the simulated weld HAZ (heat-affected zone) of SA 508 Class 3 reactor pressure vessel (RPV) steel were investigated by resonant ultrasound spectroscopy (RUS). The resonance frequencies of rectangular parallelepiped samples woe calculated from the initial estimates of elastic stiffness $c_{11},\;c_{12}\;and\;c_{44}$ with an assumption of isotropic property, dimension and density. Through the comparison of calculated resonant frequencies with the measured resonant frequencies by RUS, very accurate elastic constants of SA 508 Class 3 steel were determined by iteration and convergence processes. Clear differences of Youngs modulus and shear modulus were shown from samples with different thermal cycles and microstructures. Youngs modulus and shear modulus of samples with fine-grained bainite were higher than those with coarse-grained tempered martensite. This tendency was confirmed from other results such as micro-hardness test.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.93-102
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• 2014

Recently the interest in permanent magnet alternating motor using for electric compressor become great. Especially the research on Interior Permanent Magnet Motor has been doing actively for its advantages in the energy density and the efficiency. In order to control the output of motor to the desired value, the current control or speed control of motor are required. The accurate detection of rotor position and speed information are necessary for the control of motor. In general, the encoder, hall sensor, and resolver are used to obtain the information of motor position and speed and the speed detection algorithm, M/T method, is applied. However, the M/T method causes the error depending on rotor speed. Therefore, this M/T speed detection method is not perfect. In this paper, it is proposed that the PI control with a 1st transfer function and the integration element between velocity and position are composed in series and this feeds back to the reference value of position angle. The proposed algorithm is a function of the integral elements 2nd term, speed element, is used as an output. Thus, it is possible to detect the correct speed by configuring like the mechanical structure similarly. The proposed algorithm is verified by using PSIM DLL and is applied to the BLAC motor drive. And also it is confirmed that this system estimates the accurate speed regardless of rotor speed changes. As a example, the experimental results and simulations shows that the proposed method is very effective.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.385-389
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• 2019

Knowledge of abundance, or population size, is fundamental in wildlife conservation and management. Camera-trapping, in combination with capture-recapture methods, has been extensively applied to estimate abundance and density of individually identifiable animals due to the advantages of being non-invasive, effective to survey wide-ranging, elusive, or nocturnal species, operating in inhospitable environment, and taking low labor. We assessed the possibility of using coat patterns from images to identify an individual leopard cat (Prionailurus bengalensis), a Class II endangered species in South Korea. We analyzed leopard cat images taken from Digital Single-Lense Relfex camera (high resolution, 18Mpxl) and camera traps (low resolution, 3.1Mpxl) using HotSpotter, an image matching algorithm. HotSpotter accurately top-ranked an image of the same individual leopard cat with the reference leopard cat image 100% by matching facial and ventral parts. This confirms that facial and ventral fur patterns of the Amur leopard cat are good matching points to be used reliably to identify an individual. We anticipate that the study results will be useful to researchers interested in studying behavior or population parameter estimates of Amur leopard cats based on capture-recapture models.

• Journal of IKEEE
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• v.19 no.2
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• pp.225-231
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• 2015

The parameter K which decides how much to convert wind energy to electric energy in MPPT(maximum power point tracking) control of wind turbine system using torque controller is changed because blade shape and air density change. If the parameter K is not optimal value, power lose occur. The changed parameter K is important issue in wind turbine system. In this paper, to solve this problem, considering wind turbine system using back-to-back converter control and torque control, we propose the adaptive MPPT algorithm which performs fast control by using initial K, estimates mechanical power using Kalman filter method, uses the estimated mechanical power as input for MPPT algorithm again, and consequently performs optimal MPPT control.