• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.43-50
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• 2012

Two typical animal waste management practices, composting and stockpiling, were evaluated for their effect on the degradation of three veterinary antibiotics (VAs), chlortetracycline (CTC), tylosin (TYL), and monensin (MNS). The VAs were applied to horse manure plots subject to composting or stockpiling, and core samples were collected over a period of time. Selected buffer solutions were used to extract the VAs and analysis for concentration was conducted with solid phase extraction (SPE) followed by high performance liquid chromatography tandem mass spectrometry (HPLC/MS/MS) technique. The VAs demonstrated rapid dissipation within ten days followed by a gradual decrease in concentration until the end of the experimental period (141 days). All three VAs degraded more rapidly in the composting samples than in the stockpiling samples, particularly between 20 and 60 days of the observation period. Degradation of the three VAs generally followed a first-order kinetic model, and a fitted model with a calculated rate constant was determined for each treatment. TYL in composting showed the fastest degradation, with a calculated rate constant of $0.91day^{-1}$; the slowest degradation was exhibited by MNS in stockpiling, with rate constant of $0.17day^{-1}$. Calculated correlation coefficients ranged from 0.89 to 0.96, indicating a strong correlation between measured concentrations and fitted values in this study. Although concentration of TYL in composting treatment showed below detection limit during the test period, this study suggests that composting can reduce animal waste contaminants prior to field application as fertilizer.

• Journal of Veterinary Clinics
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• v.8 no.2
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• pp.147-152
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• 1991

Trichophyton mentagrophytes was described as a primary cause of mycotic dermatitis in two young goats housed together in a humid, ill-ventilated and unhygienic byre. The diagnosis in both the cases was established on the detection of fungal element in the skin scrapings by potassium hydroxide technique and isolation of the pathogen in pure growth on mycological medium at 30$^{\circ}C$. The lesions were found on the face of one kid and on the neck and ear of another one. Two adult goats housed in the same enclosure were found to be free from this disease. Further, there was no evidence of ringworm in the goat owner and his family members. Genetic crossing of both the isolates on modified sunflower seed medium indicated that they belonged to (―) mating type. Hair performation test revealed the keratolytic activity of both the strains of T. mentagrophytes. The public health significance and chemotherapy are also discussed. The question of source of infection could not be emphatically established.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1245-1245
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1156-1156
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• 2001

This work aimed to prove the feasibility of NIR spectroscopy to detect vegetable protein isolates (soy, pea and wheat) in milk powder. Two hundred and thirty-nine samples of genuine and adulterated milk powder (NIZO, Ede, NL) were analysed by NIRS using an InfraAlyzer 500 (Bran+Luebbe). NIR spectra were collected at room temperature, and data were processed by using Sesame Software (Bran+Luebbe). Separated calibrations for each non-milk protein added, in the range of 0-5%, were calculated. NIR data were processed by using Sesame Software (Bran+Luebbe). Prediction and validation were made by using a set of samples not included into the calibration set. The best calibrations were obtained by the PLSR. The type of data pre-treatment (normalisation, 1$\^$st/ derivative, etc..) was chosen to optimize the calibration parameters. NIRS technique was able to predict with good accuracy the percentage of each vegetable protein added to milk powder (soy: R$^2$ 0.994, SEE 0.193, SEcv 0.301, RMSEPall 0.148; pea: R$^2$ 0.997, SEE 0.1498, SEcv 0.207, RMSEPall 0.148, wheat: R$^2$ 0.997, SEE 0.1418, SEcv 0.335, RMSEPall 0.149). Prediction results were compared to those obtained using other two techniques: capillary electrophoresis and competitive ELISA. On the basis of the known true values of non-vegetable protein contents, the NIRS was able to determine more accurately than the other two techniques the percentage of adulteration in the analysed samples.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1269-1269
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• 2001

The Bovine Spongiform Encephalopathy (BSE) is one of the more important problems that have affected the economy of european cattles and the Public Safety. Their transmission is mainly through digestive system, and the compound feeds made with animal proteins are one source of infection for healthy cows. Nowadays the official method for meat and bone meal (MBM) detection in compound feeds is a microscopy technique. However, this methodology is subjective, and that alter the fact to make one exhaustive quantitative analysis and one differentiation between mammalian and poultry bones. In addition, the separation of the differents fractions in a sample by density before the analysis, requires the use of organochlorates products as $CCl_4$, which produce serious damages in the atmosphere ozone content. NIR methodology is another possible way to confirm and identifying animal ingredients in compound feeds, Its capabilities for quantitative and qualitative analysis of foods and feeds has been enought demonstrated. The objective of this work was to use NIR as a tool to make an qualitative and quantitative analysis and a prediction of the meat and bone meal presence in compound feeds from North Spain cattle farms. Using a global population of compound feeds, on make three different groups depending of MBM percentage presence (0, 0-100, 100), to build and validate one calibration equation to determine MBM content and make one discriminant analysis between these three groups. The preliminary dates obtained with another differents samples of known composition showed promising results.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1152-1152
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Journal of Microbiology and Biotechnology
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• v.20 no.4
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• pp.798-802
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• 2010

Recently, a total of 74 Staphylococcus pseudintermedius isolates were collected from clinical cases of canine pyoderma and otitis externa in Korea. In this study, we examined in vitro fluoroquinolone resistance among those isolates using a standard disc diffusion technique. The results demonstrated that, except for one isolate, approximately 18.9% to 27.0% of the isolates possessed bacterial resistance to both veterinary- and human-licensed fluoroquinolones including moxifloxacin (18.9% resistance), levofloxacin (20.3% resistance), ofloxacin (24.3% resistance), ciprofloxacin (25.7% resistance), and enrofloxacin (27.0% resistance). Most surprisingly, 14 out of 74 (18.9%) isolates were resistant to all the five fluoroquinolones evaluated. Moreover, a PCR detection of the methicillin resistance gene (mecA) among the 74 isolates revealed that 13 out of 25 (52.0%) mecApositive isolates, but only 7 out of 49 (14.3%) mecA-negative isolates, were resistant to one or more fluoroquinones. Taken together, our results imply that bacterial resistance to both veterinary- and human-use fluoroquinolones becomes prevalent among the S. pseudintermedius isolates from canine pyoderma and otitis externa in Korea, as well as that the high prevalence of the mecA-positive S. pseudintermedius isolates carrying multiple fluoroquinolones resistance could be a potential public health problem.

• Journal of Oral Medicine and Pain
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• v.21 no.1
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• pp.37-54
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• 1996

In this thesis, a new superimposition scheme using a computer vision system was proposed with 7 pairs of skull and ante-mortem photographs, which were already identified through other tests and DNA fingerprints at the Korea National Institute of Scientific Investigation. At this computer vision system, an unidentified skull was caught by video-camcoder with the MPEG and a ante-mortem photograph was scanned by scanner. These two images were processed and superimposed using pixel processing. Recognition of the individual identification by anatomical references was performed on the two superimposed images. These results were as followings. 1. For the enhancement of skull and ante-mortem photographs, various image processing schemes, such as SMOOTH, SHARPEN, EMBOSS, MOSAIC, ENGRAVE, INVERT, NEON and COLOR TO MONO, were applied using 3*5 window processing. As an image processing result of these methods, the optimal techniques were NEON, INVERT and ENGRAVE for the edge detection of skull and ante-mortem photograph. 2. Using various superimposition image processing techniques (SRCOR, SRCAND, SRCINVERT, SRCERASE, DSTINVERT, MERGEPAINT) were compared for the enhancement of image recognition. 3. By means of the video camera, the skull image was inputed directly to a computer system : superimposing it on the ante-mortem photograph made the identification more precise and time-saving. As mentioned above, this image processing techniques for the superimposition of skull and ante-mortem photographs simply used the previous approach, In other wrods, taking skull photographs and developing it to the same size as the ante-mortem photographs. This system using various image processing techniques on computer screen, a more precise and time-saving superimposition technique could be able to be applied in the area of individual identification in forensic practice.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.45-52
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• 2004

We propose ESS_WMCE. This paper explains the design and implementation of the EDSS running on ESS_WMCE. EDSS is a synchronization error control system for web based multimedia collaboration environment. We have an error detection approach by using hooking method. The technique of an error transmission is a mended model of utilizing an application sharing system. DOORAE is a good framework model for supporting development on application for computer supported cooperated works. It has primitive service functions. Service functions are implemented with an object oriented concept. It is a system that is suitable for detecting and sharing a software error rapidly occurring on web based multimedia collaboration environment by using software techniques. It is able to share an error as well as providing URL synchronization to access shared objects. When an error occurs, this system detects an error by using hooking methods in MS-Windows API(Application Program Interface) function. If an error is found, it is able to provide an error sharing to access shared objects.