• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.132-139
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• 2007

The Moderate Resolution Imaging Spectroradiometer (MODIS) regularly provides the eight-day gross primary productivity (GPP) at 1 km resolution. In this study, we evaluated the uncertainties of MODIS GPP caused by errors associated with the Data Assimilation Office (DAO) meteorology and a biophysical variable (fraction of absorbed photosynthetically active radiation, FPAR). In order to recalculate the improved GPP estimate, we employed ground weather station data and reconstructed cloud-free FPAR. The official MODIS GPP was evaluated as +17% higher than the improved GPP. The error associated with DAO meteorology was identified as the primary and the error from the cloud-contaminated FPAR as the secondary constituent in the integrative uncertainty. Among various biome types, the highest relative error of the official MODIS GPP to the improved GPP was found in the mixed forest biome with RE of 20% and the smallest errors were shown in crop land cover at 11%. Our results indicated that the uncertainty embedded in the official MODIS GPP product was considerable, indicating that the MODIS GPP needs to be reconstructed with the improved input data of daily surface meteorology and cloud-free FPAR in order to accurately monitor vegetation productivity in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.19-26
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• 2009

The standardization of eddy-covariance data processing is essential for the analysis and synthesis of vast amount of data being accumulated through continuous observations in various flux measurement networks. End users eventually benefit from the open and transparent standardization protocol by clear understanding of final products such as evapotranspiration and gross primary productivity. In this paper, we briefly introduced KoFlux efforts to standardize data processing methodologies and then estimated uncertainties of surface fluxes due to different processing methods. Based on our scrutiny of the data observed at Gwangneung KoFlux site, net ecosystem exchange and ecosystem respiration were sensitive to the selection of different processing methods. Gross primary production, however, was consistent within errors due to cancellation of the differences in NEE and Re, emphasizing that independent observation of ecosystem respiration is required for accurate estimates of carbon exchange. Nocturnal soil evaporation was small and thus the annually integrated evapotranspiration was not sensitive to the selection of different data processing methods. The implementation of such standardized data processing protocol to AsiaFlux will enable the establishment of consistent database for validation of models of carbon cycle, dynamic vegetation, and land-atmosphere interaction at regional scale.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.95-107
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• 2016

The axle weight of a vehicle in motion can be measured with a low-speed or high-speed weigh-in-motion (WIM). However, the axial load dynamically change depending on the vehicle's characteristics-such as the chassis or axle structure-or the characteristics of the driving environment such as road flatness. The changes in dynamic load lead to differences between the vehicle's weight measured at rest and the vehicle's weight measured in motion. For this Study, an experiment was conducted with an instrumented vehicle to analyze the range of errors caused by uncontrollable environmental factors by identifying the characteristics of the dynamic load changes of a vehicle in motion, and determine the appropriate scale for the accuracy evaluation of a high-speed WIM, as a preparatory research for the introduction of unmanned overweight enforcement systems in the future. The key findings from the experiment are summarized as follows. First, The gross weight of the tested vehicle changed by approximately 1% at low velocities and approximately by 4% at high velocities, and the vehicle's axle weight changed by approximately 1-3%, at low velocities and by 2-9% at high velocities. A single axle showed larger weight changes than individual axles in a group. Secondly, The vehicle's gross weight and the axle weight on the impact section were up to eight times and three-to-twelve times higher, respectively, than its gross weight and the axle weight on the flat section. The vibration frequency of the vehicle's dynamic load was measured at between 2.4 and 5.8Hz, and found to return to the normal amplitude after moving approximately 30 meters.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.214-222
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• 2002

Computer simulations are widely used to analyze passenger safety in simulated traffic accidents. ATB, Articulated Total Body, is a computer simulation model developed to predict gross human body response to such dynamic environments as vehicle crashes and pilot ejections. ATB, whose code is open, has high flexibility and application capability that users can easily insert defined modules and functions. ATB is, however, inconvenient as it was coded in FORTRAN and it needs a formated input file. Moreover, it takes much time to make input files and to modify coding errors. This study aims to increase user friendliness by adding a preprocessor program, WINATB(WINdows ATB), to the conventional ATB. WINATB, programmed in Visual C＋＋ and OpenGL, uses ATB IV as a dynamic solver. The preprocessor helps users prepare input files through graphic interface and dialog box. An additional postprocessor makes the graphical presentation of simulated results. In these case of the frontal crash, the rear impact and the side impact, the simulation results obtained by WINATB and MADYMO(MAthematical Dynamic Model) are compared to validate the effectiveness of WINAIB.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.471-477
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1cm, ${\pm}$24.7cm, ${\pm}$35.9cm, respectively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.241-243
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1㎝, ${\pm}$24.7㎝, ${\pm}$35.9㎝, respectively.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.219-220
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• 2021

It is considered that the construction industry is one of the pivotal players in the national economy in terms of Gross Domestic Production (GDP) and employment. Behind the positive role of this industrial sector to the national economy, the construction industry generates approximately 50 % of the total waste generation from all the industrial sectors. There are several measures to mitigate the adverse impacts of the construction waste such as reduce, reuse and recycle. Recycling would be one of the effective strategies for waste minimisation, which would be able to reduce the demand upon new resources as well as enhance reusing the construction materials on sites. The automated construction waste classification system would make it possible not only to reduce the amount of labour input but also mitigate the possibility of errors during the manual classification process. In this study, we proposed an automated waste segmentation and classification system for recycling the construction and demolition waste in the real construction site context. Since the practical application to the real-world construction sites was one of the significant factors to develop the system, a YOLACT (You Only Look At CoefficienTs) algorithm was chosen to conduct the study. In this study, it is expected that the proposed system would make it possible to enhance the productivity as well as the cost efficiency by reducing the manpower for the construction and demolition waste management at the construction site.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

• The korean journal of orthodontics
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• v.30 no.1 s.78
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• pp.53-66
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• 2000

This study was performed to find out the effect of projection errors on cephalometric linear and angular measurements according to head rotation during taking lateral cephalometric radiographs. Seventeen skulls with permanent dentition and no gross asymmetry were obtained from the Department of Anatomy, Medical School, Chosun University. Total 527 x-ray films were taken with $1^{\circ}$ interval from the reference position($0^{\circ}$) to ${\pm}15^{\circ}$ around the vertical axis (Z axis) which is perpendicular to the midpoint of the line connecting the center of two ear rods in submento-vertex direction. Statistical analysis was performed by paired t-test if there were statistically significant differences between the mean of the reference position($0^{\circ}$) and that of each rotation angle. The following results were obtained. 1. The projection errors of angular measurements were smaller than those of linear measurements. 2. The projection errors of angular measurements including midline landmarks were smaller than those including bilateral landmarks. 3. The horizontal linear measurements were gradually decreased when the stroll was rotated toward the film, but slightly increased and then decreased when the skull was rotated toward the focal spot. However, the changes were smaller in focal direction. 4. The projection errors of horizontal linear measurements were larger than those of vertical linear measurements. 5. The projection errors of vertical linear measurements were increased with increased distance from the rotation axis to vertical measurements. It is concluded that the use of angular measurements rather than linear measurements is recommended to minimize the projection errors.