• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.478-487
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• 2004

We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.23-28
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• 2021

In this paper, we analyze the tracking errors of monopulse radar according to the JSR of retrodirective cross-eye and radar skin return signals. The cross-eye jammer gain(G_c) is used to calculate the radar tracking errors, and the relationship between the jammer gain and the JSR is represented mathematically. We analyze the radar tracking errors by varying the tracking angle and JSR. Analysis results of the phase difference(ϕ) and amplitude ratio(a) between the two jammer signals and the changing JSR show that the closer the phase difference of the two jammer signals is to 180, the greater the tracking error and it shows that if the JSR is above 20dB, the tracking errors no longer increase. This work presents an effective utilization of retrodirective cross-eye jammers through various tracking error analyses based on the JSR, tracking angles, two-jammer phase differences and amplitude ratios of two-jammer signals.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.97-103
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• 2023

Since most of the information is transmitted through the network, eavesdropping and interception by a third party may occur. Appropriate measures are required for effective, secure and confidential communication in the network. Steganography is a technology that prevents third parties from detecting that confidential information is hidden in other media. Due to structural vulnerabilities, information protected by encryption and steganography techniques can be easily exposed to illegitimate groups. In order to improve the limitations of LSB where the simplicity and predictability of the hiding method exist, I propose a technique to improve the security of the message to be hidden based on PRNG and recursive function. To enhance security and confusion, XOR operation was performed on the result of selecting a random bit from the upper bits of the selected channel and the information transformed by the RS-box. PSNR and SSIM were used to confirm the performance of the proposed method. Compared to the reference values, the SSIM and PSNR of the proposed method were 0.9999 and 51.366, respectively, confirming that they were appropriate for hiding information.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.921-929
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• 2015

Road conditions which obstruct the driver from seeing road markings, such as in the evening or in the rain, due to the lack of a light source gives way to increasing the risk of traffic accidents. In order to increase road safety, the Korea Expressway Corporation set up a pilot project which used high-quality materials along a section of the Gyeongbu Expressway between Daejeon and Pangyo. There is little research on high-quality materials in the field of pavement marking. This study introduces high-quality materials used in pavement materials, presents the results of a survey conducted to examine the effect of the pilot project and analyzes traffic accident data from before and after the implementation of the pilot project. The survey results show that 87% of the respondents were highly satisfied with the pilot project. With the goal of evaluating the effect of the pilot project, this study used traffic accident data provided by the Korea Expressway Corporation accident data and performed a before-after study of the number of traffic. The results of data analysis show that there were 62 and 48 traffic accidents before and after the implementation of the pilot project. In addition, the result of Emperical Bayes Method indicates that there is an 41.7% decrease in the number of traffic accidents as an effect of High-quality Pavement Marking Materials.

• Journal of agriculture & life science
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• v.44 no.5
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• pp.55-64
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• 2010

This study was conducted to estimate genetic parameters for reproductive traits using multivariate animal models in Yorkshire breed. For the study, 4,989 records for litter traits collected between the year 2001 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as farrowing year, parity, weaning to estrus interval (WEI), and suckling period were statistically significant (p<0.05), but farrowing season was not significant, for reproductive traits. The estimates genetic correlations and phenotypic correlations in total number of born and number of suckling, was shown to highly correlated. The genetic correlations were higher than phenotypic correlation. The estimates of heritabilities for reproductive traits, considering permanent environment effects (PE) were much lower than those obtained when permanent environment effects were not considered (NPE) in the model. The estimates of heritabilities were 0.240 and 0.076 for total number of born and 0.187 and 0.096 for number of suckling in NPE, and PE, respectively. These results itivcate that PE should be considered in the statistical mode to estimate more acco ate breeding values.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.105-116
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• 2020

The purpose of this study is to progress the limitations and disadvantages of existing safety clothing by applying high technology to current safety clothing that is produced and distributed only with fluorescent fabrics and retroreflective materials. Therefore, the industrial suspender-type safety belt and engineering technology are introduced, designed, and fabricated to help save a life in an emergency. First, the suspender-type safety belt to be developed is designed to emit light by LED attached to the film, and the body of the belt-wearer is recognized from a distance through retroreflection from the flashing LED. It aims to support people's safety by preventing accidents during roadside work, rescue activities, and sports activities at night. Second, with the development of advanced devices when the user is in an unconscious state due to distress or falls into an unconscious state due to distress or accident, the tilt sensor of the control unit attached to the belt automatically detects the angle of the human body and generates light and sound. It is intended to further enhance the utilization by mounting a sensing and signaling device that generates a distress signal and shaping it in the form of a belt attached to a vest that can be easily detached from the outside of the garment. When the wearer falls due to an accident, the tilt sensor of this belt detects the angle change and then the controller generates a high-frequency sound and repeated LED blinking signals at the same time. In the case of conventional safety vests, it is almost impossible to detect that the person is wearing a vest when there is no ambient light, but in case of the safety belts in this study, the sound and light signals of the safety belt enable us to find the wearer within 100 meters even when there is no ambient light.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.188-198
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• 2013

Maximally flat (MAXFLAT) half-band filters usually have wider transition band than other filters. This is due to the fact that the maximum possible number of zeros at $z={\pm}1$ is imposed, which leaves no degree of freedom, and thus no independent parameters for direct control of the frequency response. This paper describes a novel method for the design of FIR halfband filters with an explicit control of the transition-band width. The proposed method is based on a generalized Lagrange halfband polynomial (g-LHBP) with coefficients parametizing a 0-th coefficient $h_0$, and allows the frequency response of this filter type to be controllable by adjusting $h_0$. Then, $h_0$ is modeled as a steepness parameter of the transition band and this is accomplished through theoretically analyzing a polynomial recurrence relation of the g-LHBP. This method also provides explicit formulas for direct computation of design parameters related to choosing a desired filter characteristic (by trade-off between the transition-band sharpness and passband & stopband flatness). The examples are shown to provide a complete and accurate solution for the design of such filters with relatively sharper transition-band steepness than MAXFLAT half-band filters.

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.157-164
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• 2012

This study was conducted to investigate the effect of different farrowing space, narrow and wide, on the sow performances and piglet growth performances. The $1.5m^2$ of narrow farrowing space was determined as the size of farrowing crate. The $3.0m^2$ of wide space for farrowing sow was the same of farrowing pen to allow the behavior freedom of sow. Baby piglets in the wide farrowing space was protected from crushing of sow by installation of safety bar. The pregnant sows used in this study were stall-housed during gestation and moved to each farrowing spaces on 8 d before parturition. Feed intake, backfat thickness and body condition score of sow were not affected by both farrowing spaces. However, the changes in backfat thickness and body condition score between farrowing and weaning in wide farrowing space were lower (p<0.05) than in narrow farrowing space. The return to estrus of sow was remarkably decreased in wide farrowing space compared to sows in narrow farrowing space. The lower number of stillbirth and higher mortality of piglets were observed in wide farrowing space. From the results, although wide farrowing space could be practically acceptable in terms of sow performances, possible cause of mortality of piglets should be scrutinized through observation of piglet and sow behaviors.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.103-114
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• 2005

The transit fare resulted from the renovation of public transit system in Seoul is basically determined based on the distance-based fare policy (DFP). In DFP, the total fare a passenger has to pay for is calculated by the basic-transfer-premium fare decision rule. The fixed amount of the basic fare is first imposed when a passenger get on a mode and it lasts within the basic travel distance. The transfer fare is additionally imposed when a passenger switches from one mode to another and the fare of the latter mode is higher than the former. The premium fare is also another and the fare of the latter begins to exceed the basic travel distance and increases at the proportion of the premium fare distance. The purpose of this study is to propose an algorithm for finding K number of paths, paths that are sequentially sorted based on total amount of transit fare, under DFP of the idstance-based fare policy. For this purpose, the link mode expansion technique is proposed in order to save notations associated with the travel modes. Thus the existing K shortest path algorithms adaptable for uni-modal network analysis are applicable to the analysis for inter-modal transportation networks. An optimality condition for finding the K shortest fare routes is derived and a corresponding algorithms is developed. The case studies demonstrate that the proposed algorithm may play an important role to provide diverse public transit information considering fare, travel distance, travel time, and number of transfer.