• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• Special Issue of the Society of Naval Architects of Korea
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• 2009.09a
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• pp.40-46
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• 2009

The GSCAD (Global Shipbuilding CAD) System used in Samsung Heavy Industries is based on the Relation and Rule. The design area where excellence of these Relation & Rule can be used fully is pipe support modeling. That's because, many rules are required to place a pipe support and it's supported by hull structural object. Samsung Heavy Industries has been customizing the Relation and Rule supported by SmarMarine3d(R) to model pipe support easily and satisfies standard. Also, the pipe support fabrication drawing program was developed to generate a drawing for the pipe support customized. This paper reviews the characteristics of pipe support modeling on GSCAD and the Rules customized also, fabrication drawing program will be introduced.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.352-359
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• 2002

A neuro-fuzzy controller has some problems that he difficulty of tuning up the membership function and fuzzy rules, long time of inferencing and defuzzifying compare to PID. Also, the fuzzy controller's own defect as a PD controller has. In this study, it is proposed two methods to solve these problems. The first method is that inner fuzzy rules are tuned up automatically by the back propagation learning according to error patterns. And the second method is a new type defuzzification method that shorten the calculation time of an inferencing and a defuzzifying. In this study, it is designed the new type neuro-fuzzy controller that improves the fast response and the stability of a system by using the proposed methods. And, the designed controller is named EPLNFC(Error pattern Learning Neuro-Fuzzy Controller). To evaluate the fast response and the stability of EPLNFC designed in this study, EPLNFC is applied to a speed control of a DC motor and AC motor.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.59-68
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• 2010

This study addresses the issue of whether Korean(L1)-English(L2) non-proficient bilinguals are affected by the native coda-neutralization process when recognizing words in English continuous speech. Korean phonological rules require that if liaison occurs between 'words', then coda-neutralization process must come before the liaison process, which results in liaison-consonants being coda-neutralized ones such as /b/, /d/, or /g/, rather than non-neutralized ones like /p/, /t/, /k/, /$t{\int}$/, /$d_{\Im}$/, or /s/. Consequently, if Korean listeners apply their native coda-neutralization rules to English speech input, word detection will be easier when coda-neutralized consonants precede target words than when non-neutralized ones do. Word-spotting and word-monitoring tasks were used in Experiment 1 and 2, respectively. In both experiments, listeners detected words faster and more accurately when vowel-initial target words were preceded by coda-neutralized consonants than when preceded by coda non-neutralized ones. The results show that Korean listeners exploit their native phonological process when processing English, irrespective of whether the native process is appropriate or not.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.147-151
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• 2013

On retrieving high frequency keywords in information retrieval system, mismatchings to user's request are problems because of the various meanings of keywords in the existing ontology configuration. In this paper, it is to construct personnel selection ontology and rules in personnel management which are composed of various concepts and knowledges based on semantic web technology and suggest selection procedures to support these rules and knowledge retrieval system to verify suitability of selection results. This system utilizes a method of extraction of speech features by using non-parametric correlation coefficient. This proposed method has been validated by showing that the result average SNR of the experiment evaluation of the proposed techniques was shown to be decreased by .752dB.

• Nuclear Engineering and Technology
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• v.14 no.1
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• pp.22-40
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• 1982

The nuclear LS-energy matrix elements have been calculated with the harmonic oscillator shell model wave functions for the configurations ( $l_{i}$ $l_{i+1}$｜ $l_{i}$ $l_{i+1}$) where 1$_1$= $l_{s}$ , $l_2$=lp, $l_3$=ld, 2s, $l_4$=1f, 2p, $l_{5}$ =1g, 2d, 3s. The resulting matrix elements are expressed in terms of both Talmi integrals $I_1$ and Slater integrals $F^{k}$ . In addition to this various sum rules are derived and applied to check the results of the calculations.ons.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.273-280
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• 2022

Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2388-2398
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• 2017

In this study, we propose a robust face recognition system to pose variations based on automatic pose estimation. Radial basis function neural network is applied as one of the functional components of the overall face recognition system. The proposed system consists of preprocessing and recognition modules to provide a solution to pose variation and high-dimensional pattern recognition problems. In the preprocessing part, principal component analysis (PCA) and 2-dimensional 2-directional PCA ($(2D)^2$ PCA) are applied. These functional modules are useful in reducing dimensionality of the feature space. The proposed RBFNNs architecture consists of three functional modules such as condition, conclusion and inference phase realized in terms of fuzzy "if-then" rules. In the condition phase of fuzzy rules, the input space is partitioned with the use of fuzzy clustering realized by the Fuzzy C-Means (FCM) algorithm. In conclusion phase of rules, the connections (weights) are realized through four types of polynomials such as constant, linear, quadratic and modified quadratic. The coefficients of the RBFNNs model are obtained by fuzzy inference method constituting the inference phase of fuzzy rules. The essential design parameters (such as the number of nodes, and fuzzification coefficient) of the networks are optimized with the aid of Particle Swarm Optimization (PSO). Experimental results completed on standard face database -Honda/UCSD, Cambridge Head pose, and IC&CI databases demonstrate the effectiveness and efficiency of face recognition system compared with other studies.

• Korean Journal of Human Ecology
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• v.3 no.1
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• pp.1-14
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• 2000

This paper is on the Kasaya that reveals conspicuously the religious meaning among the Korean Buddhist costumes. The Kasaya has the most special meaning among Korean costume culture. It has the most important historical value, for Buddhism is the oldest religion that begins at 4th century A.D.. It has the most unordinary shape that we could not find any other costume culture. It has very important meaning to study on the Kasaya in the religious and cultural history of Korean costume. We have to study Korean Kasaya from surveying Indian Buddhist Kasaya diachronicaly. Buddha establishes himself the rules of weaving, coloring and wearing Kasaya. Bunso costume(분소의)is the first shape of Kasaya that he has worn during his ascetic practice. Bunso costume was a kind of shari. It is made with diapers those clean ordure of baby It symbolizes the life of ascetic practice. However Buddha could not stick to it as the only costume of monks. From his age Buddhist devotees have thought Buddha and monks as sacred beings. So they eagerly want to Provide the sacred beings with foods. clothes and other things that samgha(승가) need to live and accomplish their duties. At that time there are many kings, aristocracies and rich merchants among the devotees. They often offered them the luxurious silk Kasaya. that the ascetic monks could not wear. to express their deep faith. So the rules of the samgha has been distorted. The samgha has enlarged day by day as a great huge religious association. There are many different shapes of Kasaya. The Buddhist samgha need to establish a minute and rigid rules of Kasaya to order living of monks and to teach the moral and educational life to ordinary people. That book of rule is Vinaya pitaka(율장) . There are many kinds of Vinaya pitaka. This paper surveys the rules of Kasaya from Southern Vinaya pitaka(남전율장). This study will be the basic ground to research the Korean Buddhist Kasaya.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.4
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• pp.1-7
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• 1994

As a subsequent work presented in Ref.[1] which deals with the global dynamic wave loads in the classification rules, further studies on such as the dynamic pressures above load waterline, motions and accelerations and other local design loads were carried out. Frequency domain 2D linear strip theory is employed and statistical analyses for the concerned ship responses were carried out for the 17 existing ships to derive simple and descriptive formula which can be used as a guidelines at preliminary design stage as well as a part of classification rules. The calculated results and thereby proposed formula are compared with those of other available data, and will be incorporated in the rules for steel ships of Korean Register of Shipping.