• Investigative Magnetic Resonance Imaging
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• v.7 no.1
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• pp.12-21
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• 2003

Purpose : In order to overcome limitations in the existing conventional spectrometer, a new spectrometer with advanced functionalities is designed and implemented. Materials and Methods : We designed a spectrometer using the TMS320C6701 DSP capable of 1 giga floating point operations per second (GFLOPS). The spectrometer can generate continuously varying complicate gradient waveforms by real-time calculation, and select image plane interactively. The designed spectrometer is composed of two parts: one is DSP-based digital control part, and the other is analog part generating gradient and RF waveforms, and performing demodulation of the received RF signal. Each recover board can measure 4 channel FID signals simultaneously for parallel imaging, and provides fast reconstruction using the high speed DSP. Results : The developed spectrometer was installed on a 1.5 Tesla whole body MRI system, and performance was tested by various methods. The accurate phase control required in digital modulation and demodulation was tested, and multi-channel acquisition was examined with phase-array coil imaging. Superior image quality is obtained by the developed spectrometer compared to existing commercial spectrometer especially in the fast spin echo images. Conclusion : Interactive control of the selection planes and real-time generation of gradient waveforms are important functions required for advanced imaging such as spiral scan cardiac imaging. Multi-channel acquisition is also highly demanding for parallel imaging. In this paper a spectrometer having such functionalities is designed and developed using the TMS320C6701 DSP having 1 GFLOPS computational power. Accurate phase control was achieved by the digital modulation and demodulation techniques. Superior image qualities are obtained by the developed spectrometer for various imaging techniques including FSE, GE, and angiography compared to those obtained by the existing commercial spectrometer.

• Journal of fish pathology
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• v.19 no.2
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• pp.155-164
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• 2006

Tissue distribution and residue depletion of oxytetracycline (OTC) and tetracycline (TC) following dipping administration were evaluated in olive flounder (Paralichthys olivaceus), rockfish (Sebastes schlegeli), and red sea bream (Pagrus major) under field conditions. Fishes were held in floating cages placed in sea water and fed a commercial diet for 15 days to acclimate to a new surrounding. Fishes were dipped in OTC 50 g/ton water for 30min and TC 18 g/ton water for 5 hours. Blood and muscle were sampled from fishes on 0th, 1th, 2th, 3th, and 5th day after administration. After solid-phase extraction, OTC and TC analyses were carried out by HPLC. The recovery rate of OTC in serum and muscle samples was 71-77% and 78-84%, respectively. Also, the recovery rate of TC in serum and muscle samples was 70-79% and 73-78%, respectively. The results of recovery rate were similar to previous studies reported. At the termination of dipping administration of OTC and TC, residue concentration in muscle samples of rockfish was significantly higher than those of olive flounder and red sea bream. At day 5, residue concentrations of all samples were believed to decrease to lower than 0.05 mg/kg, the detection limit. The present study showed that residue concentrations of OTC and TC decreased to below 0.05 mg/kg after treatment 5th day, faster than the established withdrawal period. The tissue reside depletion time of dipping administration of OTC and TC seems to be shorter than those of oral or parenteral administration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1847-1855
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• 2012

A 1V 1.6-GS/s 6-bit flash analog-to-digital converter (ADC) with a clock calibration circuit is proposed. A single track/hold circuit with a bootstrapped analog switch is used as an input stage with a supply voltage of 1V for the high speed operation. Two preamplifier-arrays and each comparator composed of two-stage are implemented for the reduction of analog noises and high speed operation. The clock calibration circuit in the proposed flash ADC improves the dynamic performance of the entire flash ADC by optimizing the duty cycle and phase of the clock. It adjusts the reset and evaluation time of the clock for the comparator by controlling the duty cycle of the clock. The proposed 1.6-GS/s 6-bit flash ADC is fabricated in a 1V 90nm 1-poly 9-metal CMOS process. The measured SNDR is 32.8 dB for a 800 MHz analog input signal. The measured DNL and INL are +0.38/-0.37 LSB, +0.64/-0.64 LSB, respectively. The power consumption and chip area are $800{\times}500{\mu}m2$ and 193.02mW.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.613-622
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• 2009

The modal spilt of highway has been increased and the one of railway has been decreased from 17.2%(1990) to 6.3%(2006). In this context, it is meaningful to examine the competitiveness of the railroad of Korea. The objective of this study is to analyze the competitiveness of railroad with the highway so that countermeasures improving the competitiveness of railroad could be suggested. For this, firs of all, indicators representing the competitiveness of the railroad transport are determined. The main influencing factors for mode choice include transport time, transport cost and level of service. Three types of commodity, container, cement and steel are the target for the analysis. It was found that the overall competitiveness of railroad transport is weaker compared with highway even for the main freight origin-destination pairs. It means that the freight transport system is focused on road rather than railroad. Therefore, we need to remeasure the competitiveness of railroad transport related to methods for freight railroad competitiveness improvement.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.3
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• pp.243-254
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• 2014

It is essential to predict the coil temperature under over load and over speed conditions for reliability in high speed low torque surface mounted PM synchronous motors(SPM). In the present study, the losses and coil temperature are measured under rated condition and calculated under over speed and over load conditions in the three different motors with 35PN440, 25PN250 and 15HTH1000. The heat transfer modeling has been performed based on acquired losses and temperature. The difference of coil temperature between heat transfer modeling and experiment is less than 6.4% under no load, over speed and over load conditions. Subsequently, the coil temperature of the motor with 15HTH1000 is 84.4% of the coil temperature of the motor with 35PN440 when speed is 0.9 and load is 3.0. The output of motor with 15HTH1000 is 85.2% greater than the output of the motor with 35PN440 when the dimensionless coil temperature is 1.0.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.139-148
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• 2015

By increasing the vertical stiffness of the rail fastening system, the dynamic wheel load of the vehicle can be increased on the ballast track, though this increases the cost of track maintenance. On the other hand, the resistance acting on the wheel is decreased, which lowers the cost of the electric power to run the train. For this reason, the determination of the optimal fastener stiffness is important when attempting to minimize the economic costs associated with both track maintenance and energy to operate the train. In this study, a numerical method for evaluating the optimal vertical stiffness of the fasteners used on ballast track is presented on the basis of the process proposed by L$\acute{o}$pez-Pita et al. They used an approximation formula while calculating the dynamic wheel load. The evaluated fastener stiffness is mainly affected by the calculated dynamic wheel load. In this study, the dynamic wheel load is more precisely evaluated with an advanced vehicle-track interaction model. An appropriate range of the stiffness of the fastener applicable to the design of ballast track along domestic high-speed lines is proposed.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.885-901
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• 2021

This paper illustratesthe impact of the temporal gap between satellite images and targetsize in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a targetsize between 8×8 and 40×40. Resultsshow the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the targetsize are closely related to the spatial and temporalscale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVsrequires considering them. This paper recommendsthat the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16×16 pixel target size, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.375-380
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• 2022

High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.469-480
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• 2017

On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.