• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8221-8226
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• 2016

Background: Misreporting self-reported family history may lead to biased estimations. We used Bayesian methods to adjust for exposure misclassification. Materials and Methods: A hospital-based case-control study was used to identify breast cancer risk factors among Iranian women. Three models were jointly considered; an outcome, an exposure and a measurement model. All models were fitted using Bayesian methods, run to achieve convergence. Results: Bayesian analysis in the model without misclassification showed that the odds ratios for the relationship between breast cancer and a family history in different prior distributions were 2.98 (95% CRI: 2.41, 3.71), 2.57 (95% CRI: 1.95, 3.41) and 2.53 (95% CRI: 1.93, 3.31). In the misclassified model, adjusted odds ratios for misclassification in the different situations were 2.64 (95% CRI: 2.02, 3.47), 2.64 (95% CRI: 2.02, 3.46), 1.60 (95% CRI: 1.07, 2.38), 1.61 (95% CRI: 1.07, 2.40), 1.57 (95% CRI: 1.05, 2.35), 1.58 (95% CRI: 1.06, 2.34) and 1.57 (95% CRI: 1.06, 2.33). Conclusions: It was concluded that self-reported family history may be misclassified in different scenarios. Due to the lack of validation studies in Iran, more attention to this matter in future research is suggested, especially while obtaining results in accordance with sensitivity and specificity values.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.61-70
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• 2006

This paper presents photogrammetric processing to generate digital elevation models using SPOT-5 HRG stereo images and deals with the accuracy potential of HRG (High Resolution Geometry) supermode imagery for DEM generation. After bundle adjustment was preformed for sensor modelling, digital surface models were generated through the procedures of Epipolar image resampling and image matching. The DEM extracted from HRG imagery was compared along several test sections with the the refernce DEM which was obtained from the digital topographic maps of a scale of 1 to 5000. The ratio of the zone with DEM errors less than 5m to the whole zone was 53.8%, and about 2.5m RMSE was showed when assuming that the zones larger than 5m were affected by clouds, water bodies and buildings and excluding those zones from accuracy evaluation. In addition, the three-dimensional bird's eye view model and 3D building model were producted based on the DSM which was extracted from SPOT-5 HRG data.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.27-36
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• 2006

Conventionally, in order to get accurate geolocation of satellite images we need a set of ground control points with respect to individual scenes. In this paper, we tested the possibilities of modeling satellite orbits from individual scenes by establishing a sensor model for one scene and by applying the model, which was derived from the same orbital segment, to other scenes that has been acquired from the same orbital segment. We investigated orbit-attitude models with several interpolation methods and with various parameter sets to be adjusted. We used 7 satellite images of SPOT-3 with a length of 420km and ground control points acquired from GPS surveying. Results of the conventional individual scene modeling hardly introduced differences among different interpolation methods and different adjustment parameter sets. As the results of orbit modeling, the best model was the one with Lagrange interpolation for position/velocity and linear interpolation for attitude and with position/angle bias as parameter sets. The best model showed that it is possible to model orbital segments of 420km with ground control points measured within one scene (60km).

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5787-5792
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• 2015

Background: Reported age standardized incidence rates for esophageal cancer in Iran are 0.88 and 6.15 for females and males, at fifth and the eighth ranks, respectively, of cancers overall. The present study aimed to map relative risk using more realistic and less problematic methods than common estimators. Materials and Methods: In this ecological investigation, the studied population consisted of all esophageal cancer patients in Iran from 2005 to 2007. The Bayesian multilevel space-time model with three levels of county, province, and time was used to measure the relative risk of esophageal cancer. Analyses were conducted using R package INLA. Results: The total number of registered patients was 7,160. According to the results, the three-level model with adjustment for risk factors of physical activity and smoking had the best fit among all models. The overall temporal trend was significantly increasing. At county level, Ahar, Marand, Salmas, Bojnoord, Saghez, Sarakhs, Shahroud and Torbatejam had the highest relative risks. Physical activity was found to have significant direct association with risk of developing esophageal cancer. Conclusions: Given to great variation across geographical areas, many different factors affect the incidence of esophageal cancer. Conducting further studies at the individual level in areas with high incidence could provide more detailed information on risk factors of esophageal cancer.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.204-211
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• 2015

This study made fundamental approaches on the significance of social enterprises on minority protection policies. In particular, it offered discussions focused on the relationship between social enterprises and North Korean defectors which greatly affect minority policies. Study results can be summed up as follows. First, the greatest difficulties for North Korean defectors in their adjustment to Korean society are economic activities and a sense of social differences and social enterprises are a policy which can resolve these problems in the most effective way. Second, existing social enterprises were excessively run by the central government and they were support models which lacked creativity and development. To resolve such problems, a lesson was learned that these must change into policy models with local coproduction. Third, a lesson was learned that social enterprises offer more than simple economic activity, offering the proper functions of society, culture, living, and language, and thus the participation of North Korean defectors in social enterprises should be made mandatory in certain sectors. Such research results will contribute to theoretically explaining the relationship between North Korean defectors and social enterprises as minority policies.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.23-32
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• 2020

There has been a significant decline in the number of rail accidents in Korea since system safety management activities were introduced. Nonetheless, analyzing and preventing human error-related accidents is still an important issue in railway industry. As a railway system is increasingly automated and intelligent, the mechanism and process of an accident occurrence are more and more complicated. It is now essential to consider a variety of factors and their intricate interactions in the analysis of rail accidents. However, it has proved that traditional accident models and methods based on a linear cause-effect relationship are inadequate to analyze and to assess accidents in complex systems such as railway systems. In order to supplement the limitations of traditional safety methods, recently some systemic safety models and methods have been developed. Of those, FRAM(Functional Resonance Analysis Method) has been recognized as one of the most useful methods for analyzing accidents in complex systems. It reflects the concepts of performance adjustment and performance variability in a system, which are fundamental to understanding the processes of an accident in complex systems. This study aims to apply FRAM to the analysis of a rail accident involving human errors, which occurred recently in South Korea. Through the application of FRAM, we found that it can be a useful alternative to traditional methods in the analysis and assessment of accidents in complex systems. In addition, it was also found that FRAM can help analysts understand the interactions between functional elements of a system in a systematic manner.

• Korean Journal of Agricultural Science
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• v.39 no.2
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• pp.279-289
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• 2012

This study was conducted to survey and diagnose operation status of the agricultural machinery rental service, analyse and compare operational efficiency among 82 city and county ATDEC (agricultural technology development and extension center) using the DEA (Data Envelopment Analysis) method, and recommend future direction, for improvement of the business. Input variables were invested budget and labor, and output variable was rental return. Percentages of return to investment on the rental service were calculated as 68.3% and 63.9% when analyzed with CCR (Charnes, Cooper and Rhodes) and BCC (Banker, Charnes and Cooper) models, respectively, indicating inefficiency of the service operation. Increase of rental charge would increase efficiency by 63.9~68.3% depending on models, and decrease of financial and labor investment would improve the efficiency by about 11.3%. Technical efficiency would be more important than scale efficiency, therefore adjustment of over-invested budget and labor needed to be made together with increase of rental charge to improve the operation. Among the ATDECs providing the rental service, 6 (7.3%), 43 (52.4%), and 33 (40.2%) were in state of CRS (constant return to scale), IRS (increasing return to scale), and DRS (decreasing return to scale), respectively. These indicated public aspects of the rental system, over-investment, lack of output component for input component, meaning that scale income would be increased by qualitative expand of rental charge. Efficiency analysis of the rental system by region showed that efficient ATDECs to be benchmarked by others were in the order of DMU-70, DMU-54, DMU-29, DMU-5, DMU-22, DMU-2, and DMU-61. More comprehensive and extensive survey and analyses would be necessary in the future.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.385-398
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• 2013

Opening wedge high tibial osteotomy (OWHTO) is widely used to treat unicompartmental osteoarthritis of the knee caused by degenerative deformations of the anatomical axes of the leg. However, since it is difficult to accurately plan the surgical degrees of adjustment such as coronal correction angle and tibial posterior slope angle to align the axes before the actual procedure, a number of studies have proposed analytical models to solve this problem. While previous analytical models for OWHTO were limited to specific cases, this study proposes an analytical osteotomy model (AOM) and a surgical planning system (SPS) that are suitable for a wide range of tibial morphologies and tibia conditions. The validity and generality of the model were verified in a total of 60 OWHTO cases. Results of the test showed that, as predicted, surgical degrees are affected quite significantly by tibia shape and slope of the resected surface. Comparison of the required surgical degrees and the degrees estimated from virtual surgery simulations using AOM showed a very small average difference of $0.118^{\circ}$. SPS, based on AOM, allows the operating surgeon to easily calculate surgical parameters needed to treat a patient.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.166-174
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• 2015

A direct demand model requires relatively little analysis time and incurs a low cost. It is also known to be useful for the preliminary screening of promising configurations or concepts. This study reviews direct demand models of 12 existing urban railways using demographic data based on a block group level which is approximately 1/24 of a traditional zone area. However, direct demand models are limited. Therefore, a new approach is suggested. The proposed method is based on a field study and an empirical analysis. The study finds factors that affect ridership at the station level. As a case study, the proposed approach is tested using 54 light railway transit stations. The results of this empirical study demonstrate its applicability to improve the error rates of the predicted ridership at the station level.