• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1327-1334
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• 2011

subway has became citizen's feet which can transport over 24 million people since the era of high oil price started. Because the request of passengers for more comfortable thermal comfort is drastically increasing, the importance of comfortable environment in the passenger car is more stressed. This paper suggests an indicator whether railroad car is fitted with suitable cooling and heating equipment by applying the international climatic testing method, UIC 553, 553-1. Specified ambient temperature, humidity, solar irradiation condition, as well as extreme outside condition, can be achieved by using an environmental chamber. The change temperature and humidity in the passenger space can be monitored to judge if the passenger room is nicely air-conditioned.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.171-176
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• 2013

X-ray cross-sectional image-based inspection technique is one of the most useful methods to inspect the brazing joints of heat exchanger. Through X-ray cross-sectional image acquisition, image processing, and defect inspection, the defects of brazing joints can be detected. This paper presents a method to judge the type of detected defects automatically, and to display them three-dimensionally. The defect type is classified as unconnected defect, void, and so on, based on location, size, and shape information of defect. Three-dimensional display which is realized using OpenGL (Open Graphics Library) will be helpful to understand the overall situation including location, size, shape of the defects in a test object.

• Structural Engineering and Mechanics
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• v.16 no.5
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• pp.581-595
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• 2003

Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.418-430
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• 2014

In this paper, a modelling technique for simulating self-propelled ships in waves is presented. The flow is modelled using a RANS solver coupled with an actuator disk model for the propeller. The motion of the ship is taken into consideration in the definition of the actuator disk region as well as the advance ratio of the propeller. The RPM of the propeller is controlled using a PID-controller with constraints added on the maximum permissible RPM increase rate. Results are presented for a freely surging model in regular waves with different constraints put on the PID-controller. The described method shows promising results and allows for the studying of several factors relating to self-propulsion. However, more validation data is needed to judge the accuracy of the model.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.67-78
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• 2015

This study investigated whether people experience a correspondence between color hue-tone and the main characters' emotions in the 2012 British musical drama film, Les $Mis\grave{e}rables$ through three practical experiments. Six screen images, which represent the characters' different emotions (Parrot's six primary types including love, joy, surprise, anger, sadness, and fear) were selected. For each screen image, participants were asked to judge the degree of the character's dominant emotions evoked from 17 varied screen images, which consisted of original chromatic and achromatized images as well as 15 color-filtered images (5 hues X 3 tones of the IRI color system). These tasks revealed that a chromatic color scheme is more effective to deliver the characters' positive emotions (i.e. love and joy) than an achromatic one. In addition, they proved that the hue and tone dimensions partially influence the relationships between the character emotions and colors.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.1-9
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• 2014

This paper discusses the problem of estimation of finite population mean in double sampling for stratification. In fact, ratio and product type exponential estimators of population mean are proposed in double sampling for stratification. The biases and mean squared errors of proposed estimators are obtained upto the first degree of approximation. The proposed estimators have been compared with usual unbiased estimator, ratio and product estimators in double sampling for stratification. To judge the performance of the proposed estimators an empirical study has been carried out.

• ETRI Journal
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• v.18 no.1
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• pp.29-41
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• 1996

This paper describes a method to select a suitable feature for speech recognition using information theoretic measure. Conventional speech recognition systems heuristically choose a portion of frequency components, cepstrum, mel-cepstrum, energy, and their time differences of speech waveforms as their speech features. However, these systems never have good performance if the selected features are not suitable for speech recognition. Since the recognition rate is the only performance measure of speech recognition system, it is hard to judge how suitable the selected feature is. To solve this problem, it is essential to analyze the feature itself, and measure how good the feature itself is. Good speech features should contain all of the class-related information and as small amount of the class-irrelevant variation as possible. In this paper, we suggest a method to measure the class-related information and the amount of the class-irrelevant variation based on the Shannon's information theory. Using this method, we compare the mel-scaled FFT, cepstrum, mel-cepstrum, and wavelet features of the TIMIT speech data. The result shows that, among these features, the mel-scaled FFT is the best feature for speech recognition based on the proposed measure.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.161-164
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• 2001

This paper partially presents a Hierachical neural network architecture for providing the intelligent control of complex Automatic Transmission(A/T) system which is usually nonlinear and hard to model mathematically. It consists of the module to apply or release an engine brake at the slope and that to judge the intention of the driver. The HNN architecture simplifies the structure of the overall system and is efficient for the learning time. This paper describes how the sub-neural networks of each module have been constructed and will compare the result of the intelligent A/T control to that of the conventional shift pattern.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.108-115
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• 2020

Blended learning is a teaching method utilizing all the advantages in 'on and off-line' learning circumstances in order to enhance the learning effect and efficiency, more than the simple use of online factors in the classroom education. In this paper, we present the realization and simulation of algorithm for the realtime evaluation of low-grade and high-grade subjects in order to implement smart e-learning system, considering a lecture intelligibility. In order to grasp the levels of student's intelligibility, we simulated a function that automatically summarizes the study contents of class given by a lecturer. Especially, in administrator mode of smart e-learning system, we suggested and simulated a system in order to help the lecturer to easily manage the student's grades, and we have provided software to tell the student's intelligibility of lecture, analyzed the rate of incorrect answers, automatic judgment of lecture intelligibility and judge the weakest subject.