• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.4
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• pp.141-152
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• 1984

Nowadaty, To keep pace with the mass transportation carried out by vessels in the international trade, the Korean government is trying to make a rapid progress to be a higher ranked shipping country to the world through the shipping increase. For the effective management of international trade by vessels and the safe operation of vessels, it is indispensable for ships radio communication to be effective and smooth. Therefore, to enhance the efficiency of ships radio communication is one of the primary factors to be solved for the econimics of shipping management. The reserch area is not only limited to the ships radio communication on the North Pacific Ocean but limited to the ships radio communication which is one of the chiefest methods of communications. From the research for the efficient methods of ships radio communication, the following results are obtained. (1) The operator on ships radio communication should have the knowledge of specific know-how and wide experience in the operation of ships radio communications. (2) The operator should abopt the radio propagation prediction made by the Ministry of Communications to use the best ionosphere reflection in the short wave communications. (3) The increase the radio officer of 1 to 2 in order to contrive the safety at sea and to keep the ships radio communication fare low. (4) The owner should pay their attentions to the education and employment of radio officer. (5) The authorities concerned on the ships radio communication should estabilish the effective and consistent policy for the ships radio officers.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.388-394
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• 2010

In this paper the object recognition performance of a photon counting integral imaging system is quantitatively compared with that of a conventional gray scale imaging system. For 3D imaging of objects with a small number of photons, the elemental image set of a 3D scene is obtained using the integral imaging set up. We assume that the elemental image detection follows a Poisson distribution. Computational geometrical ray back propagation algorithm and parametric maximum likelihood estimator are applied to the photon counting elemental image set in order to reconstruct the original 3D scene. To evaluate the photon counting object recognition performance, the normalized correlation peaks between the reconstructed 3D scenes are calculated for the varied and fixed total number of photons in the reconstructed sectional image changing the total number of image channels in the integral imaging system. It is quantitatively illustrated that the recognition performance of the photon counting integral imaging system can be similar to that of a conventional gray scale imaging system as the number of image viewing channels in the photon counting integral imaging (PCII) system is increased up to the threshold point. Also, we present experiments to find the threshold point on the total number of image channels in the PCII system which can guarantee a comparable recognition performance with a gray scale imaging system. To the best of our knowledge, this is the first report on comparisons of object recognition performance with 3D photon counting & gray scale images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.698-702
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• 2005

As a rapidly progressing of globalization and real time Prcessing in market, Korea's IT is developing, which is aimming at world market. In addition, propagation of cultivation is forming natually by lead to CT in the Asia. Latest in '90's hallyu(korean culture wave) was generated from in the east-north China province and moved to the east south Asia. It is also spreading form TV drama, music to movie, game, food, fashion and so on. This paper analyzed the outcome related with hallyu and IT innovation in knowledge-based economic society. It also addressed some effective strategies for advancing world market incorporating hallyu waves into IT.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.759-760
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• 2006

In this paper proposed to Neural network PI self-tuning direct controller using Error back propagation algorithm. Proposed controller applies to speed controller and current controller. Also, this built up the interface environment to drive it simply and exactly in any kind of reference, environment fluent and parameter transaction of BLDC motor. Neural network PI self-tuning simulator using Visual C++ and Matlab Simulation is organized to construct this environment. Built-u-p interface has it's own purpose that even the user who don't have the accurate knowledge of neural network can embody operation characteristic rapidly and easily.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.4
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• pp.102-111
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• 1993

One of the most important design procedures for large sized structures is the evaluation of fracture strength against fatigue and brittle fractures threatening to occur in their steel members. In this paper, the safety assessment based upon the knowledge about the fracturing characteristics of such ship structures was discussed, which can be estimated from such phenomena as fatigue crack propagation and brittle fractures, as obtained by employing fracture mechanics at the basic design stage. Model tests with a partial structure specimen of full size was carried out to authenticate a question as to whether or not the fracturing characteristics of such sophisticated structures could be estimated with precision from ordinary scale specimen tests, It was shown that the behviour of fatigue crack growth of large sized structures in this study could be predicted from the results of ordinary scale specimen test.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1318-1327
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• 2008

Geotechnical sites in urban areas may have embedded structures such as utility lines and underground concrete structures, which cause difficulties in site investigation. This study is a preliminary research to establish knowledge base for developing an optimal technique for site investigation in urban areas. Surface-wave method and resistivity survey, which are frequently adopted for non-destructive site-investigation for geotechnical sites, were investigated to characterize effects of adjacent structures. In case of surface wave method, patterns of wave propagation were investigated for typical sets of multi-layered geotechnical profiles by numerical simulation based on forward modeling theory and field experiments for small-size model tests and real-scale tests in the field. In case of resistivity survey, 3-D finite element analyses and field tests were performed to investigate effects of adjacent concrete structures. These theoretical and experimental researches for surface-wave method and resistivity survey resulted in establishing physical criteria to cause interference of adjacent structures in site investigation at urban areas.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.705-709
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• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.195-200
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• 1998

Since the neural network was introduced, significant progress has been made on data handling and learning algorithms. Currently, the most popular learning algorithm in neural network training is feed forward error back-propagation (FFEBP) algorithm. Aside from the success of the FFEBP algorithm, polynomial neural networks (PNN) learning has been proposed as a new learning method. The PNN learning is a self-organizing process designed to determine an appropriate set of Ivakhnenko polynomials that allow the activation of many neurons to achieve a desired state of activation that mimics a given set of sampled patterns. These neurons are interconnected in such a way that the knowledge is stored in Ivakhnenko coefficients. In this paper, the PNN model has been developed using the plasma enhanced chemical vapor deposition (PECVD) experimental data. To characterize the PECVD process using PNN, SiO$_2$films deposited under varying conditions were analyzed using fractional factorial experimental design with three center points. Parameters varied in these experiments included substrate temperature, pressure, RF power, silane flow rate and nitrous oxide flow rate. Approximately five microns of SiO$_2$were deposited on (100) silicon wafers in a Plasma-Therm 700 series PECVD system at 13.56 MHz.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Journal of Korean Society of Rural Planning
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• v.20 no.4
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• pp.137-143
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• 2014

Car exhaust emissions are recognized as one of the key sources for climate change and electric vehicles have no emissions from tailpipe. However, the limited charging infrastructures could restrict the propagation of electric vehicles. The purpose of this study is to find the vulnerable districts limited to the charging station services after meeting the goal of Ministry of Knowledge Economy(12%). We assumed that the charging service can be provided by current gas stations. The range of the vulnerable grades was determined by the accessibility to current gas stations and the vulnerable regions were classified considering the optimal number of charging stations estimated by the efficiency function. We used 4,827 sub-municipal divisions and 11,677 gas station locations for this analysis. The results show that most of mountain areas are vulnerable and the fringe areas of large cities generally get a good grade for the charging infrastructure. The gangwon-do, jeollanam-do, gyeongsangbuk-do, and chungcheongnam-do include more than 40% vulnerable districts.