• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.367-369
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• 1997

In signal system such as MAGLEV, the transmission channel that has wireless transmission line between on-board and ground-site is susceptible to have interference and may introduce data error on transmission. In this paper, by applying inductive wireless and FSK(frequency shift keying) modulation using widely in railway signal system, we intend to analyze the data transmission characteristics. In this case, noise may have effect on transmission channel. Therefore transmission channel should be lessened the data error from random noise. Considering the transmission medium, the objective of this study is to analyze the transmission characteristics between on-board and ground-site and to obtain transmission performance.

• Korean Journal of Computational Design and Engineering
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• v.11 no.6
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• pp.422-428
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• 2006

In this paper, an NC data optimization approach for enhancing 5-axis machining speed is presented. It is usual to use expensive commercial CAD/CAM programs for NC data of 5-axis machining, since it needs very large calculations for optimal tool positioning and orientation, tool path planning, and collision-free tool path generation. Since commercial CAD/CAM systems have similar functions and efficiency based on common algorithms of reliable theories, they do not have their own unique features for machining speed and efficiency. In other words, most commercial CAD/CAM systems consider only the characteristics of part geometry to be machined, which means that they generate almost the same NC data if the part to be machined is the same, even though different machines are used for the pin. A new approach is proposed for optimizing NC data of 5-axis machining, which is based on the characteristics of the machine to be operated. As a result, the speed of 5-axis machining can increase without losing machining accuracy and surface quality.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1695-1699
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• 2009

This paper analyzed the characteristics of the demand of electric power in Jeju by year, day. For this analysis, this research used the correlation between the changes in the temperature and the demand of electric power in summer, and cleaned the data of the characteristics of the temperatures, using the coefficient of correlation as the standard. And it proposed the algorithm of forecasting the short-term electric power demand in Jeju, Therefore, in the case of summer, the data by each cleaned temperature section were used. Based on the data, this paper forecasted the short-term electric power demand in the exponential smoothing method. Through the forecast of the electric power demand, this paper verified the excellence of the proposed technique by comparing with the monthly report of Jeju power system operation result made by Korea Power Exchange-Jeju.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.13-19
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• 2003

Discriminant method using seismic signal was studied for discrimination of surface explosion. By means of the seismic spectral characteristics, multi-variate discriminant analysis was performed. Four single discriminant techniques - Pg/Lg, Lg1/Lg2, Pg1/Pg2, and Rg/Lg - based on seismic source theory were applied to explosion and earthquake training data sets. The Pg/Lg discriminant technique was most effective among the four techniques. Nevertheless, it could not perfectly discriminate the samples of the training data sets. In this study, a compound linear discriminant analysis was defined by using common characteristics of the training data sets for the single discriminants. The compound linear discriminant analysis was used for the single discriminant as an independent variable. From this analysis, all the samples of the training data sets were correctly discriminated, and the probability of misclassification was lowered to 0.7％.

• Journal of Power System Engineering
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• v.13 no.2
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• pp.63-70
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• 2009

This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.3
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• pp.560-569
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• 2002

The segmentation has been performed to the data of good quality in most cases, so the adoption of previous segmentation theory to the measured data with a laser scanner does not produce good result because of the characteristics of the data with noise component. A new approach to perform the segmentation on the scanned data is introduced to deal with problems during reverse engineering process. A triangular net is generated from measured point data, and the segmentation on it is classified as plane, smooth and rough segment. The segmentation result in each segment depends on the user-defined criteria. And the difference of the segmentation between the data of good quality and the data with noise is described and analyzed with several real models. The segment boundaries selected are used to maintain the characteristics of the parts during modeling process, thus they contribute to the automation of the reverse engineering.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.269-281
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• 2016

The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.335-335
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• 2007

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.545-551
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.