• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.1 s.116
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• pp.62-75
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• 2007

This paper describes a shaped-beam antenna for increasing the antenna gain of a radiating element. The proposed antenna structure is composed of an exciting element and a multi-layered disk array structure(MDAS). The stack micro-strip patch elements were used as the exciter for effectively radiating the electromagnetic power to the MDAS over the broadband, and finite metallic disk array elements - which give the role of a director for shaping the antenna beam with the high gain - were finitely and periodically layered onto it. The efficient power coupling between the exciter and the MDAS should be carried out in such a way that the proposed antenna has a high gain characteristic. The design parameters of the exciter and the MDAS should be optimized together to meet the required specifications to meet the required specifications. In this study, a shaped-beam antenna with high gain was optimally designed under the operating conditions with a linear polarization and the frequency band of $9.6{\sim}10.4\;GHz$. Two methods constructed using thin dielectric film and dielectric foam materials respectively were also proposed in order to implement the MBAS of the antenna. In particular, through the computer simulation process, the electrical performance variations of the antenna with the MDAS realized by the thin dielectric film materials were shown according to the number of disk array elements in the stack layer. Two kinds of antenna breadboard with the MDAS realized with the thin dielectric film and dielectric foam materials were fabricated, but experimentation was conducted only on the antenna breadboard(Type 1) with the MDAS realized with the thin dielectric film materials according to the number of disk array elements in the stack layer in order to compare it with the electrical performance variations obtained during the simulation. The measured antenna gain performance was found to be in good agreement with the simulated one, and showed the periodicity of the antenna gain variations according to the stack layer number of the disk array elements. The electrical performance of the Type 1 antenna was measured at the center frequency of 10 GHz. As the disk away elements became the ten stacks, a maximum antenna gain of 15.65 dBi was obtained, and the measured return loss was not less than 11.4 dB within the operating band. Therefore, a 5 dB gain improvement of the Type 1 antenna can be obtained by the MDAS that is excited by the stack microstrip patch elements. As the disk array elements became the twelve stacks, the antenna gain of the Type 1 was measured to be 1.35 dB more than the antenna gain of the Type 2 by the outer dielectric ring effect, and the 3 dB beam widths measured from the two antenna breadboards were about $28^{\circ}$ and $36^{\circ}$ respectively.

• The Korean Journal of Nuclear Medicine
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• v.39 no.3
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• pp.174-181
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• 2005

Purpose: Reduction of respiratory motion artifacts in PET images was studied using respiratory-gated PET (RGPET) with moving phantom. Especially a method of generating simulated helical CT images from 4D-CT datasets was developed and applied to a respiratory specific RGPET images for more accurate attenuation correction. Materials and Methods: Using a motion phantom with periodicity of 6 seconds and linear motion amplitude of 26 mm, PET/CT (Discovery ST: GEMS) scans with and without respiratory gating were obtained for one syringe and two vials with each volume of 3, 10, and 30 ml respectively. RPM (Real-Time Position Management, Varian) was used for tracking motion during PET/CT scanning. Ten datasets of RGPET and 4D-CT corresponding to every 10% phase intervals were acquired. from the positions, sizes, and uptake values of each subject on the resultant phase specific PET and CT datasets, the correlations between motion artifacts in PET and CT images and the size of motion relative to the size of subject were analyzed. Results: The center positions of three vials in RGPET and 4D-CT agree well with the actual position within the estimated error. However, volumes of subjects in non-gated PET images increase proportional to relative motion size and were overestimated as much as 250% when the motion amplitude was increased two times larger than the size of the subject. On the contrary, the corresponding maximal uptake value was reduced to about 50%. Conclusion: RGPET is demonstrated to remove respiratory motion artifacts in PET imaging, and moreover, more precise image fusion and more accurate attenuation correction is possible by combining with 4D-CT.

• (The) Research of the performance art and culture
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• no.37
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• pp.391-435
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• 2018

This is the first study in Musicology that discusses the features of Kangwon Sangkangrye(the pre-lecture ritual in Buddhism). In this thesis, I reviewed and compared the similarity and uniqueness between Kangwon Sangkangrye in "Seokmunuibom" and the one being performed these days. The musical relation between the performance shown in the historical record and the one in contemporary ritual was illustrated here based on the findings derived from the anlaysis on its bell(小鐘) performance. The analysis made upon musical sources recorded on-site shows the characteristics of contemporary Kangwon Sangkangrye. Following is a brief summary of this study. The review and comparison between Kangwon Sangkangrae in "Seokmunuibom" and the one being performed these days showed that the second type, which was significantly different from the first type, was closer to that of the historical record. The performers at Unmunsa Temple and Chungamsa Temple seemed to be following the tradition bell(小鐘) performance style which was found in the text of the historical record. Through the analysis on Kangwon Sangkangrae, I found that it has musical characteristics as follows. The vocal range of type 1 and type 2 was mostly performed within Minor 7th and didn't exceed the perfect 8th. The melodic structure of type 1 starts with do'-la of naedeureum and ended with the melody which downscaled from do' and finalized from mi to la. Usually the mode was in menari-tori but at some lecture halls a few cases found to be upscaled from sol to la which differentiates it from the typical menari-tori of folk songs. Like the typical way of traditional rites, the singing was divided into two parts: the leading call and the following choral response. Most were sung to be one syllable on one or two tones or one syllable lasting for several tones and the musical forms were varied by musical pieces. Meantime, Sangkangrae at Haeinsa Temple was differed from that of the other temples in terms of ritual procedure and vocal style. It added Korean version of and the lead vocal skipped the first phrase of the Sasul. The melodic structure of Type 2 started with do'-la of naedeureum and was finalized as the same way of Type 1. The mode of was not the same as typical menari-tori but the Jeongrye(prostration) and Balweon(a great vow) were identical to the menari-tori of folk songs. The singing was done in two forms, solo and unison, and the lyric-attachment of Gesong was one syllable for one or two tones and that of Jeongrye and Balweon were one syllable for one or two tones + one syllable for several tones. The musical form of Jeongrye is A-B-C and A-C. Balweon didn't display a certain periodicity but still maintained sense of unity and formality through repetition of the finalizing melody.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.882-889
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• 2022

In this study, to understand the factors influencing the flow change the Tsushima Warm Current (TWC), the correlation between the volume transport the TWC, El Niño Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO) was analyzed. A calculation of the monthly volume transport of TWC for 25 years (1993-2018) revealed that the seasonal fluctuation cycle was the largest in summer and smallest in winter. Power spectrum analysis to determine the periodicity of the TWC volume transport, Oceanic Niño Undex (ONI), and PDO indicated that the TWC volume transport peaked at a one year cycle, but ONI and PDO showed no clear cycle. Further, to understand the correlation between the TWC transport volume and ONI and PDO, the coherence estimation method was used for analysis. The coherence of ONI and PDO had a high mutual contribution in long-period fluctuations of three years or more but had low mutual contribution in short-period fluctuations within one year. However, the coherence value between the two factors of the TWC volume transport and PDO was 0.7 in the 0.8-1.2 year cycle, which had a high mutual contribution. Meanwhile, the TWC volume transport and PDO have an inverse correlation between period I (1993-2002) and period III (2010-2018). When the TWC maximum transport volume (2.2 Sv or more) was high, the PDO index showed a negative value below -1.0, and the PDO index showed a positive value when the TWC maximum transport volume was (below 2.2 Sv). Therefore, using long-term PDO index data, changes in the TWC transport volume and water temperature in the East Sea coastal area could be predicted.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.