• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2007년도 학술대회
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• pp.20-20
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• 2007

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2007년도 추계학술대회 논문집
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• pp.319-321
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• 2007

• 한국섬유공학회:학술대회논문집
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• 한국섬유공학회 1997년도 추계총회 및 학술발표회 논문집
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• pp.275-278
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• 1997

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2017년도 추계학술논문요약집
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• pp.339-340
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• 2017

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1620-1620
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• 2001

Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

• 산업경영시스템학회지
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• 제26권1호
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.

• Mass Spectrometry Letters
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• 제4권4호
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• pp.75-78
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• 2013

A gas chromatography/mass spectrometric (GC/MS) method was developed as a candidate reference method for the accurate determination of essential fatty acids (linoleic acid, ${\alpha}$- and ${\gamma}$-linolenic acids) in food supplemental oil products. Samples were spiked with three internal standards (stearic acid-$d_{35}$, $^{13}C_{18}$-linoleic acid, and $^{13}C_{18}$-${\alpha}$-linolenic acid). Samples were then subject to saponification, derivatization for methylation, and extraction by organic solvent. For GC/MS measurement, an Agilent HP-88 column, designed for the separation of fatty acid methyl esters, was selected after comparing with other columns as it provided better separation for target analytes. Target analytes and internal standards were detected by selected ion monitoring of molecular ions of their methyl ester forms. The GC/MS method was applied for the measurement of three botanical oils in NIST SRM 3274 (borage oil, evening primrose oil, and flax oil), and measurement results agreed with the certified values. Measurement results for target analytes which have corresponding isotope-labeled analogues as internal standard were calculated based on isotope dilution mass spectrometry (IDMS) approach, and compared with results calculated by using the other two internal standards. Results from the IDMS approach and the typical internal standard approach were in good agreement within their measurement uncertainties. It proves that the developed GC/MS method can provide similar metrological quality with IDMS methods for the measurement of fatty acids in natural oil samples if a proper fatty acid is used as an internal standard.

• Bulletin of the Korean Chemical Society
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• 제31권11호
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• pp.3139-3144
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• 2010

A model system has been established for the evaluation of the uncertainty of the value from measurements of multiple subsamples by isotope dilution mass spectrometry (IDMS). In this report, we apply this model system for the evaluation of measurement uncertainty in determination of folic acid in infant formula. Five subsamples were analyzed by IDMS. The mean of the measurement results of the five subsamples was assigned as the final measurement value. The standard deviation (s) of the results from five subsamples was attributable to repeatability of the measurement. The uncertainty components in the IDMS measurement methods were categorized into two groups. Group I includes uncertainty components which give common systematic effects to all subsamples and do not contribute to the variation among multiple measurements (repeatability). Group II includes uncertainty components that give random effects on the measurement results, and are related with the measurement repeatability. These random effects are attributed to s. Therefore, the uncertainty of the final value was calculated by combining the standard deviation of the mean of multiple measurements, $s/{\surd}n$ (where n = 5), and the measurement uncertainty associated with the uncertainty components that give systematic effects.

• Journal of information and communication convergence engineering
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• 제9권4호
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• pp.475-482
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• 2011

In this research, we have attempted to estimate the water quality of fish farms in terms of parameters such as water temperature, dissolved oxygen, pH, and salinity by employing observational data obtained from a coastal ocean observatory of a national institution located close to the fish farm. We requested and received marine data comprising nine factors including water temperature from Korea Hydrographic and Oceanographic Administration. For verifying our results, we also established an experimental fish farm in which we directly placed the sensor module of an optical mode, YSI-6920V2, used for self-cleaning inside fish tanks and used the data measured and recorded by a environment monitoring system that was communicating serially with the sensor module. We investigated the differences in water temperature and salinity among three areas - Goheung Balpo, Yeosu Odongdo, and the experimental fish farm, Keumho. Water temperature did not exhibit significant differences but there was a difference in salinity (significance <5%). Further, multiple regression analysis was performed to estimate the water quality of the fish farm at Keumho based on the data of Goheung Balpo. The water temperature and dissolved-oxygen estimations had multiple regression linear relationships with coefficients of determination of 98% and 89%, respectively. However, in the case of the pH and salinity estimated using the oceanic environment with nine factors, the adjusted coefficient of determination was very low at less than 10%, and it was therefore difficult to predict the values. We plotted the predicted and measured values by employing the estimated regression equation and found them to fit very well; the values were close to the regression line. We have demonstrated that if statistical model equations that fit well are used, the expense of fish-farm sensor and system installations, maintenances, and repairs, which is a major issue with existing environmental information monitoring systems of marine farming areas, can be reduced, thereby making it easier for fish farmers to monitor aquaculture and mariculture environments.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1267-1267
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• 2001

The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.