• Progress in Medical Physics
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• v.30 no.4
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• pp.128-138
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• 2019

Purpose: Segmental analysis of volumetric modulated arc therapy (VMAT) is not clinically used for compositional error source evaluation. Instead, dose verification is routinely used for plan-specific quality assurance (QA). While this approach identifies the resultant error, it does not specify which machine parameter was responsible for the error. In this research study, we adopted an approach for the segmental analysis of VMAT as a part of machine QA of linear accelerator (LINAC). Methods: Two portal dose QA plans were generated for VMAT QA: a) for full arc and b) for the arc, which was segmented in 12 subsegments. We investigated the multileaf collimator (MLC) position and dosimetric accuracy in the full and segmented arc delivery schemes. A MATLAB program was used to calculate the MLC position error from the data in the dynalog file. The Gamma passing rate (GPR) and the measured to planned dose difference (DD) in each pixel of the electronic portal imaging device was the measurement for dosimetric accuracy. The eclipse treatment planning system and a MATLAB program were used to calculate the dosimetric accuracy. Results: The maximum root-mean-square error of the MLC positions were <1 mm. The GPR was within the range of 98%-99.7% and was similar in both types of VMAT delivery. In general, the DD was <5 calibration units in both full arcs. A similar DD distribution was found for continuous arc and segmented arcs sums. Exceedingly high DD were not observed in any of the arc segment delivery schemes. The LINAC performance was acceptable regarding the execution of the VMAT QA plan. Conclusions: The segmental analysis proposed in this study is expected to be useful for the prediction of the delivery of the VMAT in relation to the gantry angle. We thus recommend the use of segmental analysis of VMAT as part of the regular QA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.109-116
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• 2010

In this paper, we propose a method for extracting predominant melody of polyphonic music based on harmonic structure. Since polyphonic music contains multiple sound sources, the process of melody detection consists of extraction of multiple fundamental frequencies and determination of predominant melody using those fundamental frequencies. Harmonic structure is an important feature parameter of monophonic signal that has spectral peaks at the integer multiples of its fundamental frequency. We extract all fundamental frequency candidates contained in the polyphonic signal by verifying the required condition of harmonic structure. Then, we combine those harmonic peaks corresponding to each extracted fundamental frequency and assign a rank to each after calculating its harmonic average energy. We finally run pitch tracking based on the rank of extracted fundamental frequency and continuity of fundamental frequency, and determine the predominant melody. We measure the performance of proposed method using ADC 2004 DB and 100 Korean pop songs in terms of MIREX 2005 evaluation metrics, and pitch accuracy of 90.42% is obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1100-1108
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• 1992

The evaluation of coded error probabilities for antijam communication systems is usually difficult to do and, thus, easy-to-evaluate upper bounds are used. Since it is relatively easy to evaluate the cutoff rate for the coding channel, the coded bit error bounds for most antijam systems of interest can be easily expressed directly in terms of this cutoff rate parameter using the relationship between the bit error bounds and cutoff rate for AWGN channel. The key feature of these bounds is the decoupling of the coding aspects of the system from the remaining part of the communication system which includes jamming, suboptimum detectors, and arbitrary decoding metrics which may or may not use jammer state knowledge. In this paper the bit error bounds for the Trumpis coded FH/MFSK with an AWGN channel are translated into the corresponding bit error bounds for boradband and partial band noise jammer. And the impact of the side information about jammer state is also evaluated with these upper bounds. Although it is considered for the soft decision detector, it is also applicable to the hard decision detector.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9731-9737
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• 2014

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.507-516
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• 2011

Comparative studies on generalized binomial models (Moon, 2003; Ng, 1989; Paul, 1985; Kupper and Haseman, 1978; Griffiths, 1973) are restrictive in that the models compared are rather limited and MSE of the estimates is the only measure considered for the model adequacy. This paper is aimed to report simulation results which provide possible guidelines for selecting a proper model. We examine Pearson type of goodness-of-fit statistic to its degrees of freedom and AIC for the overall model quality. MSE and Bias of the individual estimates are also considered as the component fit measures. Performance of some models varies widely for a certain range of the parameter space while most of the models are quite competent. Our evaluation shows that the Extended Beta-Binomial model (Prentice, 1986) turns out to be particularly favorable in the point that it provides consistently excellent fit almost all over the values of the intra-class correlation coefficient and the probability of success.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1148-1156
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• 2015

The maritime cognitive radio networks (MCRNs) provide the high throughput with a low communication cost because the secondary ships opportunistically access to unused licensed bands of primary ships. In the ground cognitive radio networks, the busy and idle state of a primary user during a frame is not nearly changed because the state of the primary user are slowly changed. However, the state of the primary ship in the MCRNs may be frequently changed in the frame. Therefore, this paper evaluates the throughput of a primary ship and secondary ships in the MCRNs taking the state change of a primary ship into consideration when the fusion center uses the cooperative spectrum sensing. The simulation results show that trade-off between the throughput of a primary ship and that of secondary ships according to the system parameter such as the cooperative spectrum sensing scheme, the number of secondary ships, and the target detection probability.

• Journal of the Korean Society for Heat Treatment
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• v.23 no.4
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• pp.198-204
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• 2010

Modified 9Cr-1Mo steels possess excellent high-temperature mechanical properties and are widely used in energy conversion industries. However, in-service materials degradation, such as softening, carbide-induced embrittlement, temper embrittlement, etc., can take place during long-term operation. Evolution of microstructure due to service exposure to high temperature has a strong effect on the performance of heat resistant steels. In case of modified 9Cr-1Mo steels, precipitation of $Fe_2Mo$-type laves phases and coarsening of $M_{23}C_6$-type carbides are the primary cause of degradation of mechanical properties such as toughness, hardness, tensile strength and creep resistance. This study was aimed at finding reliable parameter for assessing the integrity of modified 9Cr-1Mo steels. Characteristic parameters were attained between mechanical and ultrasonic properties.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.73-79
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• 2009

For the shake of control for movement object, control theory like neural network, nonlinear model predictive control(NMPC) is realized on digital high speed computer. Predictor of flight control system(FCS) based nonlinear model predictive control has to be satisfied with response for hard real-time to perform applications on each module in the FCS. Simultaneously, It gives a serious consideration accuracy to give full play to FCS's performance. Error of mathematical aspect affects realization of whole algorithm. But factors of bring mathematical error is not considered to calculate final accuracy on parameter of predictor. In this paper, Predictor was made using load control model on the digital computer for design FCS at hard real-time and is shown response time on realization algorithm. And is shown realization algorithm of high effective predictor over the accuracy. The predictor was realized on the load control model using Euler method, Heun method, Runge-Kutta and Taylor method.

• Atmosphere
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• v.32 no.4
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• pp.277-295
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• 2022

The global weather prediction model, Korean Integrated Model (KIM), has been in operation since April 2020 by the Korea Meteorological Administration. This study assessed the performance of heat waves (HWs) in Korea in 2020. Case experiments during 2018-2020 were conducted to support the reliability of assessment, and the factors which affect predictability of the HWs were analyzed. Simulated expansion and retreat of the Tibetan High and North Pacific High during the 2020 HW had a good agreement with the analysis. However, the model showed significant cold biases in the maximum surface temperature. It was found that the temperature bias was highly related to underestimation of downward shortwave radiation at surface, which was linked to cloudiness. KIM tended to overestimate nighttime clouds that delayed the dissipation of cloud in the morning, which affected the shortage of downward solar radiation. The vertical profiles of temperature and moisture showed that cold bias and trapped moisture in the lower atmosphere produce favorable conditions for cloud formation over the Yellow Sea, which affected overestimation of cloud in downwind land. Sensitivity test was performed to reduce model bias, which was done by modulating moisture mixing parameter in the boundary layer scheme. Results indicated that the daytime temperature errors were reduced by increase in surface solar irradiance with enhanced cloud dissipation. This study suggested that not only the synoptic features but also the accuracy of low-level temperature and moisture condition played an important role in predicting the maximum temperature during the HWs in medium-range forecasts.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.239-243
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• 2019

In this study, anthraquinone-2,7-disulfonic acid (2,7-AQDS) is used as negative active material and Tiron is used as positive active material for aqueous redox flow battery (RFB). In previous results that used the 2,7-AQDS and Tiron, sulfuric acid ($H_2SO_4$) was a supporting electrolyte. However, in this study, ammonium chloride ($NH_4Cl$) is suggested as the electrolyte for the first time. By changing the supporting electrolyte from $H_2SO_4$ to $NH_4Cl$, the cell voltage of RFB is improved from 0.76 V to 1.01 V. To investigate the effect of $NH_4Cl$ supporting electrolyte of the performance of RFB, the full-cell tests of RFB using 2,7-AQDS and Tiron that are dissolved in $NH_4Cl$ supporting electrolyte are carried out, while cut-off voltage range is a main parameter to determine their performance. When the cut-off voltage range is 0.2~1.6 V, the hydrogen evolution occurs during charging step. To address the side reaction effect, the cut-off voltage range is changed to 0.2~1.2 V. When the revised cut-off voltage range is used and the current density of $40mA/cm^2$ is applied, hydrogen evolution is not observed and the optimal RFB shows the charge efficiency of 99% and discharge capacity of 3.3 Ah/L at 10cycle.