• Asian-Australasian Journal of Animal Sciences
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• v.21 no.3
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• pp.434-442
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• 2008

The objective of this study was to determine the optimum ratio of methionine to methionine plus cystine for growing pigs. A nitrogen balance trial was conducted using a total of 21 barrows (Large WhiteLandrace) over two replicates. The initial body weight was $20.36{\pm}1.22kg$ (mean${\pm}$SD) in the first replicate and $23.54{\pm}1.02kg$ (mean${\pm}$SD) in the second. For each replicate, the 21 pigs were randomly assigned to one of seven dietary treatments with three observations per treatment. The diets included a methionine and cystine-deficient basal diet with all other essential nutrients meeting nutrient requirements and six diets formulated with graded levels of DL-methionine (0.00, 0.03, 0.06, 0.10, 0.13, 0.16%) and $L-Cystine{\cdot}HCl{\cdot}H_2O$ (0.19, 0.15, 0.11, 0.07, 0.04, 0.00%). This resulted in ratios of methionine to methionine plus cystine of 41.3, 29.6, 35.3, 41.2, 46.0, 51.6 and 57.5%. Each experimental period lasted 12 days consisting of a seven-day adaptation period followed by a five-day total collection of urine and feces. During the collection period, pigs were fed 900 g/day for the first replicate and 1,200 g/day for the second replicate. The feed was provided in three equal portions at 0800, 1500, and 2200 h daily. Pigs had ad libitum access to water after feeding. There was a linear (p<0.01) and quadratic (p<0.01) effect on daily gain and feed conversion as the ratio of methionine to methionine plus cystine increased. Pigs receiving the diets providing a methionine to methionine plus cystine ratio of 51.6% had the best daily gain and feed conversion. Plasma urea nitrogen was also lowest for this treatment. Nitrogen retention increased (p<0.01) as the relative proportion of methionine increased up to 51.6% and then a downward trend occurred at 57.5%. The quadratic regression model, as well as one- and two- slope regression line models, were used to determine the optimum ratio of methionine to methionine plus cystine. Eliminating the 35.3% methionine to methionine plus cystine treatment resulted in $R^2$ values in excess of 0.92. The optimal ratio of methionine to methionine plus cystine was estimated to be 54.15% for nitrogen retention and 56.72% for plasma urea nitrogen.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3D
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• pp.205-212
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• 2012

The national highway traffic counts system consists of short duration counts and continuous counts. Unlike continuous counts, short duration counts are performed by collection of a few days period and thus, the magnitude of deviation of collected data from AADT varies depending upon when data collection takes place. Therefore, this study was done to find out the best months and days of data collection of each highway classification in order to enhance the accuracy of AADT estimation. Continuous counts, another type of the national traffic counts system, are performed by collection of 365-day period using a permanent traffic counter. Therefore, it is necessary to keep the number of days for which the counter malfunctions to a minimum in order to enhance the accuracy of data. However, from time to time the permanent traffic counter malfunctions due to various causes and thus, cannot collect data. Therefore, this study was done to find out whether the age of counter, the ratio of heavy vehicle volume to total traffic volume, etc. could be the direct causes of counter's malfunction based on the number of maintenance for a certain time period.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.149-155
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• 2012

SSD is a storage device of having high-performance controller and cache buffer and consists of many NAND flash memories. Because NAND flash memory does not support in-place update, valid pages are invalidated when update and erase operations are issued in file system and then invalid pages are completely deleted via garbage collection. However, garbage collection performs many erase operations of long latency and then it reduces I/O performance and increases wear leveling in SSD. In this paper, we propose a new method of de-duplicating valid data and recycling invalid data. The method de-duplicates valid data and then recycles invalid data so that it improves de-duplication ratio. Due to reducing number of writes and garbage collection, the method could increase I/O performance and decrease wear leveling in SSD. Experimental result shows that it can reduce maximum 20% number of garbage collections and 9% I/O latency than those of general case.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.4
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• pp.639-650
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• 2000

The main object of this study was to investigate experimentally the characteristics of cyclone-bag filter with bottom inlet to decrease the high pressure drop which was one of main problems of fabric bag filter. The experiment was executed for the analysis of collection efficiency and pressure drop(specially, pressure drop of fabric filter) characteristics of the cyclone-bag filter in comparison with those of general fabric bag filter with various experimental parameters such as the inlet velocity, dust loading and variation of vortex region, etc. In the results, the tangential inlet type showed higher collection efficiency for submicron particles below $1{\mu}m$ in diameter than of center inlet, and over 99% for overall collection efficiency. For the inlet particle concentration $100mg/m^3$, pressure drop reduction ratios were shown as 15~38% with the inlet velocity in case of large bag, while 30~48% for small bag due to the increase of vortex region.

• Journal of Construction Engineering and Project Management
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• v.3 no.3
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• pp.23-34
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.375-385
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• The Mathematical Education
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• v.44 no.1 s.108
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• pp.67-85
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• 2005

This study investigated elementary teachers' subject matter knowledge and pedagogical content knowledge of fractions. The subject for data collection were 12 in-service elementary teachers and data were collected through written test problems. The finding imply that most elementary teachers understand fraction construct as part-whole, show low level of understanding of operator, ratio, and measurement constructions and word problem posing, using models, and developing the algorithms to divide fractions. The research results indicates that experienced teachers possess poor knowledge of fractions against novice teachers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6009-6027
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• 2019

Support vector machine (SVM) classifiers have been widely used for object detection. These methods usually locate the object by finding the region with maximal score in an image. With bag-of-features representation, the SVM score of an image region can be written as the sum of its inside feature-weights. As a result, the searching process can be executed efficiently by using strategies such as branch-and-bound. However, the feature-weight derived by optimizing region classification cannot really reveal the category knowledge of a feature-point, which could cause bad localization. In this paper, we represent a region in an image by a collection of local feature-points and determine the object by the region with the maximum posterior probability of belonging to the object class. Based on the Bayes' theorem and Naive-Bayes assumptions, the posterior probability is reformulated as the sum of feature-scores. The feature-score is manifested in the form of the logarithm of a probability ratio. Instead of estimating the numerator and denominator probabilities separately, we readily employ the density ratio estimation techniques directly, and overcome the above limitation. Experiments on a car dataset and PASCAL VOC 2007 dataset validated the effectiveness of our method compared to the baselines. In addition, the performance can be further improved by taking advantage of the recently developed deep convolutional neural network features.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.1
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• pp.53-61
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• 2024

Purpose: Although the 24-hours urinary copper excretion is useful for the diagnosis of Wilson disease (WD), there are practical difficulties in the accurate and timed collection of urine samples. The purpose of this study was to verify if the spot morning urinary Copper/Zinc (Cu/Zn) ratio could be used as a replacement parameter of 24-hours urinary copper excretion in the diagnosis of WD. Methods: A cross-sectional study was conducted at the Department of Pediatric Gastroenterology and Nutrition, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, from June 2019 to May 2021 on 67 children over three years of age who presented with liver disease. Twenty-seven children who fulfilled the inclusion criteria for WD were categorized into the test group, and the remaining forty children were considered to have non-Wilsonian liver disease and were categorized into the control group. Along with other laboratory investigations, spot morning urinary samples were estimated for the urinary Cu/Zn ratio in all patients and were compared to the 24-hour urinary copper excretion. The diagnostic value of the Cu/Zn ratio was then analyzed. Results: Correlation of spot morning urinary Cu/Zn ratio with 24-hours urinary copper excretion was found to be significant (r=0.60). The area under ROC curve with 95% confidence interval of morning urinary Cu/Zn ratio measured using 24-hours urine sample was 0.84 (standard error, 0.05; p<0.001). Conclusion: Spot morning urinary Cu/Zn ratio seems to be a promising parameter for the replacement of 24-hours urinary copper excretion in the diagnosis of WD.

• Investigative Magnetic Resonance Imaging
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• v.3 no.1
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• pp.13-19
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• 1999

MRI imaging provides many benefits such as noninvasive, 3-dimensional imaging capabilities. But it has relatively serious drawback that is the long data collection time, compared with other imaging modality. Many studies have been performed for fast MR imaging. But EPI and SEPI (4-6) are required to expensive hardware. In this paper, we introduce to Burst imaging technique. It can reduce imaging time by use of a mulitple RF excitation technique. Further it is easily implemented to the normal MRI system. But a pixel profile in the conventional burst sequence is so poor that excited area by burst sequence is a small portion of a pixel. This causes poor signal to noise ratio in burst image. therefore frequency sweeping of RF pulse for burst imaging sequence is proposed to improve pixel profile. A burst pulse train is shaped by liner or nonlinear frequency sweeping function so that all the spins within a pixel are excited, thereby improving the signal to noise ratio. It also shows that the pixel profiles are dependent on how frequency sweep is made. Computer simulations with Bloch equation and experimental results obtained using a 1.0 T NMR imaging system are presented.