• International Journal of Highway Engineering
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• v.14 no.6
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• pp.139-148
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• 2012

PURPOSES : The accuracy of travel time information is a key measure of effectiveness and reliability of advanced traveler information systems. This study aims at investigating drivers' perception on the acceptable level of information accuracy and their corresponding valuations. METHODS : A questionnaire survey was executed for collecting driver perception data to capture the expectation level of travel time information provided and their willingness to pay for the information. A Tobit model was adopted for exploring the relationship among the acceptable level, driver socioeconomic characteristics and travel attributes. Since drivers' willingness to pay for accurate travel time information can be different according to their travel lengths, a piecewise linear regression model was developed to capture the sensitivity of values of travel time information to travel length. RESULTS : The analysis results suggest that trip purpose and travel time are two dominant factors to determine drivers' acceptable level of travel time information. For business and short trips, drivers want more accurate information than for non-business and long trips. Drivers' willingness to pay for travel time information also varies depending on their incomes, trip purposes and travel lengths. The results also show that drivers' valuation of travel time information provided is sensitive to their travel length. For longer trips, drivers are less sensitive to travel time information and then put less value on the information provided. CONCLUSIONS : Censored nonlinear regression models are developed to estimate drivers' acceptable accuracy for travel time information and their valuation using questionnaire survey data. The findings on drivers perception to the required accuracy of travel time information and their corresponding willingness to pay can be used in the design and deployment of advanced traveler information system to improve its effectiveness and usefulness through high compliance.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.6
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• pp.788-795
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• 2015

Two dimensional-fluorescence difference gel electrophoresis (2D DIGE) is an emerging technique for comparative proteomics, which improves the reproducibility and reliability of differential protein expression analysis between samples. The purpose of this study was to investigate bovine pregnancy-specific proteins in the proteome between bovine pregnant and non-pregnant serum using DIGE technique. Serums of 2 pregnant Holstein dairy cattle at day 21 after artificial insemination and those of 2 non-pregnant were used in this study. The pre-electrophoretic labeling of pregnant and non-pregnant serum proteins were mixed with Cy3 and Cy5 fluorescent dyes, respectively, and an internal standard was labeled with Cy2. Labeled proteins with Cy2, Cy3, and Cy5 were separated together in a single gel, and then were detected by fluorescence image analyzer. The 2D DIGE method using fluorescence CyDye DIGE flour had higher sensitivity than conventional 2D gel electrophoresis, and showed reproducible results. Approximately 1,500 protein spots were detected by 2D DIGE. Several proteins showed a more than 1.5-fold up and down regulation between non-pregnant and pregnant serum proteins. The differentially expressed proteins were identified by MALDI-TOF mass spectrometer. A total 16 protein spots were detected to regulate differentially in the pregnant serum, among which 7 spots were up-regulated proteins such as conglutinin precursor, modified bovine fibrinogen and IgG1, and 6 spots were down-regulated proteins such as hemoglobin, complement component 3, bovine fibrinogen and IgG2a three spots were not identified. The identified proteins demonstrate that early pregnant bovine serum may have several pregnancy-specific proteins, and these could be a valuable information for the development of pregnancy-diagnostic markers in early pregnancy bovine serum.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.11
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• pp.1700-1713
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• 2018

Objective: The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods: A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results: The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam's sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion: The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5759-5765
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• 2014

Electrical impedance tomography (EIT) is a potential supplement for mammogram screening. This study aimed to evaluate and feasibility of EIT as opposed to mammography and to determine pain perception with both imaging methods. Women undergoing screening mammography at the Radiology Department of National University of Malaysia Medical Centre were randomly selected for EIT imaging. All women were requested to give a pain score after each imaging session. Two independent raters were chosen to define the image findings of EIT. A total of 164 women in the age range from 40 to 65-year-old participated and were divided into two groups; normal and abnormal. EIT sensitivity and specificity for rater 1 were 69.4% and 63.3, whereas for rater 2 they were 55.3% and 57.0% respectively. The reliability for each rater ranged between good to very good (p<0.05). Quantitative values of EIT showed there were significant differences in all values between groups (ANCOVA, p<0.05). Interestingly, EIT scored a median pain score of $1.51{\pm}0.75$ whereas mammography scored $4.15{\pm}0.87$ (Mann Whitney U test, p<0.05). From these quantitative values, EIT has the potential as a health discriminating index. Its ability to replace image findings from mammography needs further investigation.

• The Journal of Pediatrics of Korean Medicine
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• v.20 no.1
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• pp.1-14
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• 2006

Objective : As prevalence of atopic dermatitis(AD) rises and medicine of atopic dematitis develops, the methods of measurement for atopic dermatitis have developed. Therefore, we aimed to establish a new sconring system in oriental medicine for a childhood atopic dematitis, by comparison, analysis of various sconing systems. Method : We searched for the data related to severity sconing systems of atopic dermatitis in Entrez PubMed on abroad thesis and KISS(Korenstdued Information Service System) on domestic thesis from 1990 to 2005. Result : Severity sconing systems for atopic dermatitis satisfy validity, reliability, sensitivity of change and verification of this. The essential items of severity sconing systems are extent, intensity and subjective symptoms. The lesion is divided into 9 areas(head and neck, upper limbs, elbow, hands, trunk, hip and inguinal, lower limbs, knee, feet). The items of intensity are erythema, oedema and induration and papulation, oozing and weeping and erosion, excorition, scaling, lichenification. The subjective symptom is pruritis, evaluated according to sleep loss and obstruction of play and study. The extent and intensity is evaluated in combination. We suggested that extent and intensity occupied for 70% and subject symptoms accounted for 30% of total score.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.6
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• pp.1-10
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• 2013

Probabilistic nonlinear first ply failure loads of flat composite panels and nonlinear buckling loads of curved composite panels with cutouts are estimated to provide the more reliable main load carrying structure in the renewable energy industry and offshore structures. The response surface method approximates limit state surface to a second order polynomial form of random variables with the results of deterministic finite element analyses at given sampling design points. Furthermore, the iterative linear interpolation scheme is used to obtain a more accurate approximation of the limit state surface near the most probable failure point (MPFP). The advanced first order second moment method and the Monte Carlo method are performed on an approximated limit state surface to evaluate the probability of failure. Finally, the sensitivity of the reliability index with respect to transformed random variables is investigated to figure out the main random variables that have an effect on failures.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.49-56
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• 2012

Performance analysis on RAIM, which is one of the techniques for monitoring integrity to ensure the reliability of GPS, was conducted in this study. RAIM is such a method which allows its user to monitor integrity in the stand-alone mode. Among the existing RAIM procedures, the representative methods including the RCM (Range Comparison Method), LSRM (Least Square Residual Method), Parity approach and WRAIM (Weighted RAIM) were evaluated, and their performance was analyzed. To validate the performance of the implemented algorithms, fault detection was tried on the clock malfunctioning event of PRN 23 occurred on January 1st, 2004. As a result, it was identified that the LSRM and the WRAIM detected all the faults happened in the event. In the case of RCM, all the states of fault were detected except for the error which occurred as a false alarm at one epoch. Furthermore, simulated biases were added for each satellite to analyze the sensitivity of each algorithm. Consequently, when biases of the 9-13 meters range were simulated for the RCM and LSRM algorithm, all the malfunctions were detected. For the WRAIM method, it could detect range biases greater than 15 meters.

• Genomics & Informatics
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• v.10 no.3
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• pp.194-199
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• 2012

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

• Journal of Korean Society on Water Environment
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• v.33 no.5
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• pp.546-555
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• 2017

The Nutrient budget is one of the agricultural-environment indicators of OECD. A nutrient budget measures the surplus as the differential between the inputs and the outputs of within a certain boundary and within a specified period of time (i.e. one year). According to OECD, the annual nitrogen budget for Korea was $245kg\;N\;ha^{-1}$ in 2014, which corresponds to the first position among OECD countries. In Korea in 2014, about 90 % of livestock excreta was composted as solid and liquid manure, which are usually and customarily spread on agricultural land. The objectives of this study are intended to suggest methodology of the regional nitrogen budget as a nitrogen management tool, which considers conversion from raw excreta to composted manures based on the methodology of OECD/Eurostat, and application of the new method in an agricultural region of Korea. As a result, the calculated excess rate of hydrospheric nitrogen surplus was $251kg\;N\;ha^{-1}$ (in the region in 2014), which indicates the presence of potential risks emanating from excessive nitrogen, with regard to both export water and soil environments. The findings also assert that this was shown to be one of the most important elements in the nitrogen budget, which translates to the actual amounts of nitrogen lost during the solid composting process. To better understand the process and the reliability of the method, it is necessary to analyze the sensitivity of the relevant co-efficients used in the method in the near future.

• Journal of Biomedical Engineering Research
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• v.35 no.4
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• pp.87-94
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• 2014

Recent technological advances have increased interest in personal health monitoring. Electrocardiogram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascular system status. In this study, we developed a capacitive ECG measurement system that can be included within a cloth mattress pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However, it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high level of noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithm that can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated by determining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Polysomnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%, and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% for our capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of providing useful ECG information, even under noisy signal conditions.