• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.10
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• pp.791-798
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• 1991

In this paper, microstrip array antenna with the phase lock are designed to consist of main lobe and sidelobe with difference 21.97dB for sharp beam pattern using Tchebyscheff polynominals. Microstrip array antenna with phase lock of 0$^{\circ}$, 45$^{\circ}$, 90$^{\circ}$ are designed, to scan beam for 0$^{\circ}$, 6$^{\circ}$, 12$^{\circ}$ to be 1:2:2:1 for the relative current distribution. The designed microstrip array antenna with phase lock is measured in terms of various characteristics such as return loss, resonant frequency, radiation pattern, bandwidth, beamwidth, and the measurement value and theoretical value agreed with each other. Also, the patch array antenna with the relative current distribution is presented phase shift for beam scanning.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.555-559
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• 1998

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis have been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, We proposed an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted four morphological features parameters such as centromeric index (C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.). These Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results shown that the chromosome classification error was reduced much more than that of the other classification methods.

• Journal of Mechanical Science and Technology
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• v.19 no.7
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• pp.1517-1525
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• 2005

Liquid sloshing displays the highly nonlinear free surface fluctuation when either the external excitation is of large amplitude or its frequency approaches natural sloshing frequencies. Naturally, the accurate tracking of time-varying free surface configuration becomes a key task for the reliable prediction of the sloshing time-history response. However, the numerical instability and dissipation may occur in the nonlinear sloshing analysis, particularly in the long-time beating simulation, when two simulation parameters, the relative time-increment parameter a and the fluid mesh pattern, are not elaborately chosen. This paper intends to examine the effects of these two parameters on the potential-based nonlinear finite element method introduced for the large amplitude sloshing flow.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.395-407
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• 2012

The aim of this study is to investigate the pattern of inbound and outbound tourism and their receipts and expenditures in Korea, and wishes to suggest a policy implication. The finding in this research indicates that inbound tourism is mainly influenced by a relative income, while the receipts are effected not only by a scale of tourism, relative price, relative income, but also by the exchange rate. Outbound tourism and the expenditures are tentatively determined by a set of information which is synthetically made up by an economic factors. To this end, it could be concluded that tourism policy should be elaborately established to take of the inbound tourism, and appropriately designed information networking system for tourism would be helpful to assist the outbound tourism.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.505-510
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• 2000

Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.104-108
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• 2014

This paper represents the effect analysis results of surface-Icing on the UHF-band antenna for Space Launch Vehicle. In order to obtain structural model of the surface-icing, Relative Permittivity of ice at $-180^{\circ}C$ was extracted. Using this surface-Icing model, UHF-band antenna simulation and comparative analysis about the antenna parameters such as resonance frequency, reflection loss and radiation pattern were performed for each case of with or without surface-icing. Simulation results show that resonance frequency is shifted out of operation frequency due to the additional ice permittivity. This resonance frequency changes cause severe affect to the antenna performance and its radiation pattern.

• Asian review of World Histories
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• v.2 no.2
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• pp.147-167
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• 2014

The urban modernity that became an irresistible model for elites in Asia in the decades before and after 1900 was far from being gender-neutral. It represented an exceptional peak of patriarchy in its exclusion of respectable middle class women from the work force, from ownership and control of property and from politics. Marriage was indissoluble and the wife's role in the male-headed nuclear family was to care for and educate the abundant children she produced. Puritan religious values underlined the perils for women of falling outside this pattern of dependence on the male. Though upheld as modern and civilized, this ideal was in particularly striking contrast with the pre-colonial Southeast Asian pattern of economic autonomy and balance between women and men, and the relative ease of female-initiated divorce. Although attractive to many western-educated Southeast Asian men, including religious reformers determined to 'save' and domesticate women, urban respectability of this type was a poor fit for women accustomed to dominant roles in commerce and marketing, and at least equal ones in production. Southeast Asian relative failure in the high colonial era to adapt to the modern market economy may also have a gendered explanation. We should not be surprised that patriarchy and puritanism became more important in Southeast Asia as it urbanized in the late 20th Century, since this was echoing the European experience a century earlier. The question remains how far Southeast Asia could retain its relatively balanced gender pattern in face of its eventual rapid urbanization and commercial development.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.290-294
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• 1997

Chromosomes, as the genetic vehicles, provide the basic material for a large proportion of genetic investigations. The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, we propose an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We are employed three morphological feature parameters ; centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.), as input in neural network by preprocessing twenty human chromosome images. The results of our experiments show that our TMANN classifier is much more useful in neural network learning and successful in chromosome classification than the other classification methods.

• Journal of the Korean Ceramic Society
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• v.56 no.4
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• pp.354-359
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• 2019

Information security films that can ensure personal privacy by reducing the viewing angle of display screens were fabricated by microlouver patterning and a ZnO nano-ink filling process. Optical simulation results demonstrated that all the microlouver films showed good security performances. Security performances were evaluated as calculated relative luminance ratios compared between the side and front. Based on the simulation results, microlouver films were fabricated by UV imprint lithography and nano-ink bar coating. However, distortion of the microlouver pattern occurred with the use of high-viscosity nano-inks such as ZrO₂ and TiO₂, and the CuO-filled microlouver film suffered from very low optical transmittance. Accordingly, the effects of ZnO filling height on security performance were intensively investigated through simulation and experimental measurements. The fabricated microlouver film with a 75-㎛-high ZnO filling exhibited a good relative luminance ratio of 0.75 at a 60° side angle and a transmittance of 44% at a wavelength of 550 nm.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.133-136
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• 1997

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room or improving the accuracy of chromosome classification. In this paper, We propose an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of multi-step multi-layer neural network(MMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted three morphological features parameters such as centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.). This Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results show that the chromosome classification error is reduced much more than that of the other classification methods.