• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.941-946
• /
• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• Journal of Mechanical Science and Technology
• /
• v.17 no.7
• /
• pp.966-977
• /
• 2003

This paper investigates how intentional mistuning of bladed disks reduces their sensitivity to unintentional random mistuning. The class of intentionally mistuned disks considered here is limited, for cost reasons, to arrangements of two types of blades (A and B, say). A two-step procedure is then described to optimize the arrangement of these blades around the disk to reduce the effects of unintentional random mistuning. First, a pure optimization effort is undertaken to obtain the pattern (s) of the A and B blades that yields small/the smallest value of the largest amplitude of response to a given excitation in the absence of unintentional random mistuning using Genetic Algorithm. Then, in the second step, a qualitative/quantitative estimate of the sensitivity for the optimized intentionally mistuned bladed disks with respect to unintentional random mistuning is performed by analyzing their amplification factor, probability density function and passband/stopband structures. Examples of application with simple bladed disk models demonstrate the significant benefits of using this class of intentionally mistuned disks.

• Journal of Korea Multimedia Society
• /
• v.3 no.6
• /
• pp.652-660
• /
• 2000

This paper proposes a new type of sampling Phase Detector (SPD) for NRZ random bit synchronization circuit. The proposed SPD calculates the mean value of phase difference between bit interval of input signal and period of local reference. Simulated and experimental results show that the proposed SPD is applicable to the phase detector for NRZ random signal. finally the Random NRZ bit synchronization circuit. is designed and implemented by using SPD.

• Korean Journal of Remote Sensing
• /
• v.38 no.4
• /
• pp.375-386
• /
• 2022

The city of Khartoum, the capital of Sudan, was heavily damaged by the flood of the Nile in 2020. Classification using satellite images can define the damaged area and help emergency response. As Synthetic Aperture Radar (SAR) uses microwave that can penetrate cloud, it is suitable to use in the flood study. In this study, Random Forest classifier, one of the supervised classification algorithms, was applied to the flood event in Khartoum with various sizes of the training dataset and number of images using Sentinel-1 SAR. To create a training dataset, we used unsupervised classification and visual inspection. Firstly, Random Forest was performed by reducing the size of each class of the training dataset, but no notable difference was found. Next, we performed Random Forest with various number of images. Accuracy became better as the number of images in creased, but converged to a maximum value when the dataset covers the duration from flood to the completion of drainage.

• Journal of the Korean Statistical Society
• /
• v.33 no.2
• /
• pp.245-254
• /
• 2004

This paper derives a distribution function of the terminal value and running maximum of two-dimensional Brownian motion {X($\tau$) = (X$_1$($\tau$), X$_2$ ($\tau$))', $\tau$ 〉0}. One random variable of the joint distribution is the terminal time value, X$_1$ (T). The other random variable is the maximum of the Brownian motion {X$_2$($\tau$), $\tau$〉} between time s and time t. With this distribution function, this paper also derives an explicit pricing formula for an outside barrier option whose monitoring period starts at an arbitrary date and ends at another arbitrary date before maturity.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.8 no.6
• /
• pp.33-41
• /
• 1971

This paper presents a theoretical calculation and measurements for the RCS(Radar Cross Scetion) value of a moving complex target, a small metal aircraft. The front view of aircraft on the drawing is divided in to several simple models to calculate its RCS value by the relative phase nlethod and the random phase method at the given frequency. The aircraft, cessna 305, inbounded from 170$^{\circ}$ to X international airport, is searched by radar with the wave length of 11cm to measure its miximum range which is necessary to determine the RCS value. The measured data are found to be similar to the theoretical values.

• Polymer(Korea)
• /
• v.37 no.3
• /
• pp.379-386
• /
• 2013

SAPO-11 was applied for the first time to the catalytic pyrolysis of miscanthus and random polypropylene (random PP). Thermogravimetric analysis confirmed that SAPO-11 promoted the dehydration of miscanthus while suppressing the formation of char. In the pyrolysis of random PP, the decomposition temperature and activation energy were reduced by using a catalyst. A large fraction of levoglucosan, which was the main oxygenate product from the non-catalytic pyrolysis of miscanthus, was converted to high value-added products, such as furans, phenolics and aromatics using SAPO-34. The catalytic pyrolysis of random PP produced gasoline- and diesel-range hydrocarbons.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.1
• /
• pp.85-93
• /
• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Journal of Korea Multimedia Society
• /
• v.10 no.5
• /
• pp.623-630
• /
• 2007

With the development in IT technology and with growing demands of users, a ubiquitous environment is being made. Because of individuals identification is important in ubiquitous environment, RFID, a technology used frequently. RFID, a technology that radio frequency identification, reader send signer, then tag provide user information. RFID has various strengths, such as high recognition rates, quick recognition speed, but Eavesdropping is possible and problem that user information is revealed happens. To solve this, study is proceeded with activity, but, because of low-cost passive tag is limited operation capability, usually used hash function and random number. Also updates value that is used to present session and uses in next session. Therefore, this scheme protects user privacy using random number. And this sheme can offer synchronization by creating variable value without updating value.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.6
• /
• pp.722-728
• /
• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.