• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.252-264
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• 2023

This paper proposes a design of a dual-band band-pass filter that integrates a λg/2 open SIR structure, a transmission line, and a fork-type structure with symmetric and asymmetric open stubs. To obtain the dual-band effect, the proposed filter uses the SIR structure and adjusts the impedance ratio of the SIR structure. Therefore, the position of the harmonics of the filter is shifted through the adjustment of the impedance ratio, and this can obtain a double-band effect. In order to obtain the dual-band characteristics, the dual-band effect is obtained by inserting a open stub between the SIR structures with the SIR structure divided in half. In addition, the second frequency response is obtained by adjusting the length of the open symmetrical stub in the fork-shaped structure. The asymmetrical open stub in the fork form achieves optimum bandwidth by adjusting the length. Therefore, the first center frequency of the proposed band-pass filter is 5.896 GHz and the bandwidth is 13.6 %. At this time, the measurement results are 0.13 dB and 33.6 dB. The second center frequency is 5.906 GHz and the bandwidth is 13.6 %. At this time, the measurement results are 0.15 dB and 19.8 dB. The reason is that when the impedance ratio (Δ) is higher than 1, the position of the harmonic is shifted to a lower frequency band. However, if the impedance ratio (Δ) is lowered by one step, the position of harmonics will move to a higher frequency band. The function of the filter designed using these characteristics can be obtained from the measurement result. The proposed band-pass filter has no coupling loss and no via energy concentration loss because there is no coupling structure of input/output and no via hole. Therefore, system integration is possible due to its excellent performance, and it is expected that dedicated short-range communication (DSRC) system applications used in traffic communication systems will be possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.579-586
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• 2018

Short-term prediction of travel speed has been widely studied using data-driven non-parametric techniques. There is, however, a lack of research on the prediction aimed at urban areas due to their complex dynamics stemming from traffic signals and intersections. The purpose of this study is to develop a hybrid approach combining ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting urban travel speed. The EEMD decomposes the time-series data of travel speed into intrinsic mode functions (IMFs) and residue. The decomposed IMFs represent local characteristics of time-scale components and they are predicted using an ANN, respectively. The IMFs can be predicted more accurately than their original travel speed since they mitigate the complexity of the original data such as non-linearity, non-stationarity, and oscillation. The predicted IMFs are summed up to represent the predicted travel speed. To evaluate the proposed method, the travel speed data from the dedicated short range communication (DSRC) in Daegu City are used. Performance evaluations are conducted targeting on the links that are particularly hard to predict. The results show the developed model has the mean absolute error rate of 10.41% in the normal condition and 25.35% in the break down for the 15-min-ahead prediction, respectively, and it outperforms the simple ANN model. The developed model contributes to the provision of the reliable traffic information in urban transportation management systems.