• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.651-660
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• 2018

The purpose of this study was to investigate the effects of task-oriented circuit training(: TOCT) on upper extremity function and quality of life in chronic stroke patients. 20 stroke patients were randomized and divided into 2 groups: a preservation therapy group and TOCT group. The intervention sessions were given five times a week for four weeks. The Stroke Impact Scale(: SIS), EuroQual-5Domains(: EQ-5D), Fugl-Myer Assessment(: FMA), Motor Activity Log(: MAL), Canadian Occupational Performance Measure(: COPM) were used to measure the upper extremity function and the quality of life. In results, Two groups improved in upper extremity function after the intervention(p<.05). The EQ-5D scores of TOCT group were a significantly higher than preservation group(p<.05). The Ironing, Folding towels, Hang out towels on drying rack in COPM scores in both of performance and satisfaction have improved more than preservation group(p<.05). In conclusion, the TOCT has significant helpful effect to chronic stroke patients. These findings can be used to chronic stroke patient as an intervention for upper extremity function and quality of life.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1256-1256
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• 2001

The physico-chemical and texture characteristics of meat determine the nutritional, technological and sensory quality. However, the analysis of meat quality requires expensive, laborious and time consuming analytical methods. The objective of this study was to evaluate NIR spectroscopy using transmittance for determining the moisture, fat, protein and total pigment content, the water holding capacity (WHC) and the toughness of beef meat. A total of 318 spectra were recorded from ground beef samples by a Feed Analyzer 1265 of Infratec. The samples were obtained from the Longissimus muscle of the 10$^{th}$ rib of yearling bulls, ground with an electrical chopper, vacuum packaged, aged during 7 days and frozen at -24$^{\circ}C$ until the analyses were done. Moisture content was measured by oven drying at 10$0^{\circ}C$, fat content was determined by Soxhlet extraction and protein content was estimated from nitrogen content using the Kjeldahl analysis. The total pigment content was determined by the method of Hornsey and the WHC using the method of filter paper press. The instrumental evaluation of texture (maximum load WB, maximum stress MS and toughness) was conducted in an Instron equipment with a Warner-Bratzler shearing device. This analysis was performed on a chop of 3.5 cm obtained from the longissimus of the 8$^{th}$ rib, aged during 7 days, kept frozen at -24$^{\circ}C$ and cooked before the analysis. Near infrared spectra were recorded as log 1/T (T=transmittance) at 2 nm intervals from 850 to 1050 nm using a Feed Analyzer 1265 of Infratec. Calibrations were performed with the WinISI software (vs. 1.02) using the MPLS method. To examine the effect of scatter correction o. derivation of spectra on the calibration performance, calibrations were calculated with the crude spectra or pretreated with different mathematical treatments (inverse MSC, SNVD) and/or second derivative operation. For chemical composition, the use of the scatter corrections improved the calibration statistics, in terms of lower SECV and higher $r^2$. In most of the variables, the use of the 2$^{nd}$ derivative improved the predictions, mainly when combined with the SNVD treatment. However, for predicting the texture traits, the best estimation was obtained from the crude spectrum. These results showed that the equations obtained for predicting moisture, fat and total pigments were very accurate, with $r^2$ being higher that 0.9. However, the prediction of the texture traits (WB, MS, toughness) from ground meat was poor.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Journal of Environmental Health Sciences
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• v.40 no.3
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• pp.255-263
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• 2014

Objectives: This study evaluated the fungicidal efficacy of a fumigant containing 20% ortho-phenylphenol against Trichophytone mentagrophytes (T. mentagrophytes), Candida albicans (C. albicans) and Aspergillus niger (A. niger). Methods: Five replicates of each carrier were contaminated by depositing 0.05 mL of each fungal suspension. After drying, two carriers without exposure to the fumigant and three carriers with exposure to the fumigant were left in a sealed room ($25m^3$) at $21{\pm}0.5^{\circ}C$ and $60{\pm}10%$ relative humidity for 15 hours. Immediately after removal from the test room, each carrier was transferred into recovery diluent and suspended, diluted and inoculated. After incubation, the numbers of each colony were counted, and the parameter values (N, T, d) were calculated. Results: The working culture suspension number (N value) of T. mentagrophytes, C. albicans and A. niger were $1.0{\times}10^8$, $1.2{\times}10^8$ and $5.7{\times}10^7CFU/mL$, respectively. All the colony numbers on the carriers exposed to the fumigant (n1, n2, n3) were higher than 0.5N1 (the number of fungal test suspensions by pour plate method), 0.5N2 (the number of fungal test suspensions by filter membrane method) and 0.5N1, respectively. In addition, all mean numbers of test strains recovered on the control-carriers (T value) were over $10^6CFU/mL$. For the fungicidal effect of the fumigant, all numbers of fungal reductions after exposure of the fumigant (d value) were 4 logCFU/mL. Conclusions: The present study showed that fumigant containing 20% ortho-phenylphenol has effective fungicidal activity against T. mentagrophytes, C. albicans and A. niger.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• The Korean Journal of Pesticide Science
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• v.20 no.1
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• pp.14-22
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• 2016

A trial of combining and quantifying the effects of food processing on various pesticides was carried out using a meta-analysis. In this study, weighted mean response ratios and confidence intervals about the reduction of pesticide residue levels in fruits and vegetables treated with various food processing techniques were calculated using a statistical tool of meta-analysis. The weighted mean response ratios for tap water washing, peeling, blanching (boiling) and oven drying were 0.52, 0.14, 0.34 and 0.46, respectively. Among the food processing methods, peeling showed the greatest effect on the reduction of pesticide residues. Pearsons's correlation coefficient (r=0.624) between weighted mean response ratios and octanolwater partition coefficients ($logP_{ow}$) for twelve pesticides processed with tap water washing was confirmed as having a positive correlation in the range of significance level of 0.05 (p=0.03). This means that a pesticide having the higher value of $logP_{ow}$ was observed as showing a higher weighted mean response ratio. These results could be used effectively as a reference data for processing factor in risk assessment and as an information for consumers on how to reduce pesticide residues in agricultural products.

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.257-266
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.400-406
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• 2021

The purpose of this study was to evaluate the microbial contamination level of Korean traditional rice cakes (Garaetteok, Injeolmi, Gyeongdan), as well as manufacturing environment of small-sized businesses in Korea. The contamination levels of total aerobic bacteria, coliforms, and Bacillus cereus in raw materials were 3.76-4.48, 2.21-4.14, and 1.02-1.15 log CFU/g respectively. On the other hand, Escherichia coli was not found. It has been found that the contamination level of total aerobic bacteria, coliforms, and B. cereus in the raw material decreased after the washing process, but it increased again during the soaking and grinding process. However, after the steaming stage, the contamination level increased again during the molding and cooling process, suggesting the need to take cautions in managing cooling water and molded rice cakes in the process. These results suggest that the safe management of cooling water and taking cautions in the drying process after steaming of rice cakes are necessary for controlling cross-contamination. No E. coli was detected during the manufacturing process involving all tested rice cakes. The microbial contamination level of manufacturing environment such as rice grinder and rice cake forming machine was high. Therefore, in terms of food safety strategy, it is necessary to consider introducing systematic cleansing and disinfection procedure to processing equipment and environment for the sake of reducing microbiological risks.