• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.5
• /
• pp.175-182
• /
• 2010

The paper presents a novel algorithm for face and iris detection with the application for driver iris monitoring. The proposed algorithm consists of the following major steps: Skin-color segmentation, facial features segmentation, and iris positioning. For the skin-segmentation we applied a multi-layer perceptron to approximate the statistical probability of certain skin-colors, and filter out those with low probabilities. The next step segments the face region into the following categories: eye, mouth, eye brow, and remaining facial regions. For this purpose we propose a novel segmentation technique based on estimation of facial class probability density functions (PDF). Each facial class PDF is estimated on the basis of salient features extracted from a corresponding facial image region. Then pixels are classified according to the highest probability selected from four estimated PDFs. The final step applies the circular Hough transform to the detected eye regions to extract the position and radius of the iris. We tested our system on two data sets. The first one is obtained from the Web and contains faces under different illuminations. The second dataset was collected by us. It contains images obtained from video sequences recorded by a CCD camera while a driver was driving a car. The experimental results are presented, showing high detection rates.

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.97-105
• /
• 2020

A thermal imaging sensor receives the radiating energy from the target and the background, so it has been widely used for detection, tracking, and classification of targets at night for military purpose. In recognizing the target automatically using thermal images, if the correct edges of object are used then it can generate the classification results with high accuracy. However since the thermal images have lower spatial resolution and more blurred edges than color images, the accuracy of the classification using thermal images can be decreased. In this paper, to overcome this problem, a new hierarchical classifier using both shape and local features based on the segmentation reliabilities, and the class/pose updating method for vehicle classification are proposed. The proposed classification method was validated using thermal video sequences of more than 20,000 images which include four types of military vehicles - main battle tank, armored personnel carrier, military truck, and estate car. The experiment results showed that the proposed method outperformed the state-of-the-arts methods in classification accuracy.

• Journal of Broadcast Engineering
• /
• v.27 no.6
• /
• pp.885-896
• /
• 2022

Motor failure in manufacturing plays an important role in future A/S and reliability. Motor failure is detected by measuring sound, current, and vibration. For the data used in this paper, the sound of the car's side mirror motor gear box was used. Motor sound consists of three classes. Sound data is input to the network model through a conversion process through MelSpectrogram. In this paper, various methods were applied, such as data augmentation to improve the performance of classifying fault motors and various methods according to class imbalance were applied resampling, reweighting adjustment, change of loss function and representation learning and classification into two stages. In addition, the curriculum learning method and self-space learning method were compared through a total of five network models such as Bidirectional LSTM Attention, Convolutional Recurrent Neural Network, Multi-Head Attention, Bidirectional Temporal Convolution Network, and Convolution Neural Network, and the optimal configuration was found for motor sound classification.

• Journal of Advanced Marine Engineering and Technology
• /
• v.25 no.3
• /
• pp.595-604
• /
• 2001

As an improvement in the standard of living and economic growth, the demand for air conditioning equipment is increasing rapidly. Nowadays, air conditioning equipments are being used for industry, large building, house and car. There equipments were concentrated on improving heat efficiency of economic aspects while thy design heat exchanger for cooling and heating. These air conditioning equipments using heat exchanger cause a discomfort to user due to generating mist at the beginning of operating. Therefore, the user demand air of high class and quality. In this experimental study, to acquire elementary data for development of heat exchanger which be able to supply air of high quality, that is to say, possess a restraint effect of mist generation. We estimate an effect on cooling plate quality, supply air velocity, supply air temperature, cooled plate temperature and supply air relative humidity which have an influence on outlet air condition of heat exchanger.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.14 no.6
• /
• pp.98-103
• /
• 2015

Swing reducers are widely used in special vehicles that have swing motions. Generally, compact swing reducers were constituted by a worm gear pair. Worm gears are one of the most important technical devices for transmitting torque between spatially crossed axes. Due to their high transmission ratio and compact structure, they are widely used in power transmission applications where high reduction is required. This paper presented approaches to improve the transmission efficiency and assembling performance of 3.5 ton class worm gear swing reducers. Worm wheel and the case of swing reducers were optimized and certified by a finite element method. Finally, an actual swing reducer was processed and assembled to test the performance.

• Journal of Energy Engineering
• /
• v.11 no.3
• /
• pp.254-261
• /
• 2002

The fabrication method for the main components of the polymer electrolyte membrane fuel cell stack such as electrodes, membrane-electrode assemblies, and bipolar plates was established for the effective electrode area of 240 ㎠. A counter-flow type 100-cell stack was fabricated by using the above components and then a maximum power of 7.44 kW for H$_2$/O$_2$ and 5.56 kW for H$_2$/air could be obtained at 70$\^{C}$ and 1 atm. It was seen that the distribution of the OCV for unit cells in the stack was uniform but the voltage deviation increased as the load increased due to the IR drop and the electrode polarization. The stack was applied to the power source of the fuel cell/battery hybrid electric golf car. It produced about 1 kW at a room temperature operation during the test run, which occupied about 43% of the total power required by the 2.3 kW motor.

• International Journal of Highway Engineering
• /
• v.12 no.4
• /
• pp.47-51
• /
• 2010

A vehicle classification data is essential for traffic road planning and pavement. In this study, the vehicle height, vehicle criteria for classification applied to measure the height of the car driving has devised a way to install equipment. It is capable of measuring the vehicle height was confirmed to field experiments, the measurement system is obtained to the vehicle length and height data. In this experiment, results showed the accuracy of 88.6% compared to classification data using the discriminant function obtained from video replaying. The height of vehicle applying the classification criteria can be utilized to determine the vehicle class.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.8 no.6
• /
• pp.142-155
• /
• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.22 no.1
• /
• pp.46-51
• /
• 2014

2,097 deaths out of 5,229 by traffic accident occurred by vehicle to vehicle crash and 855 deaths out of 2,097 occurred at side crash in 2011. Korean government adopted New Car Assessment Program to reduce the wounded and deaths at traffic accident in 1999 and side impact test has been added in 2003. 43 out of 53 vehicles tested in NCAP side impact rated 4 and 5 stars means the highest occupant protection. In this study three small class vehicles have been tested according to Insurance Institute for Highway Safety's side crashworthiness test protocol. IIHS test protocol uses 1,500kg moving barrier rather than NCAP's 950kg and the occupant protection rated Good, Acceptable, Marginal and Poor based on injury measure, structural integrity and head protection.

• Communications for Statistical Applications and Methods
• /
• v.25 no.2
• /
• pp.217-234
• /
• 2018

Copulas are a tool for constructing multivariate distributions and formalizing the dependence structure between random variables. From copula literature review, there are a few asymmetric copulas available so far while data collected from the real world often exhibit asymmetric nature. This necessitates developing asymmetric copulas. In this study, we discuss a method to construct a new class of bivariate asymmetric copulas based on products of symmetric (sometimes asymmetric) copulas with powered arguments in order to determine if the proposed construction can offer an added value for modeling asymmetric bivariate data. With these newly constructed copulas, we investigate dependence properties and measure of association between random variables. In addition, the test of symmetry of data and the estimation of hyper-parameters by the maximum likelihood method are discussed. With two real example such as car rental data and economic indicators data, we perform the goodness-of-fit test of our proposed asymmetric copulas. For these data, some of the proposed models turned out to be successful whereas the existing copulas were mostly unsuccessful. The method of presented here can be useful in fields such as finance, climate and social science.