• KAPE Magazine
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• s.110
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• pp.2-3
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• 2005

• KAPE Magazine
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• s.110
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• pp.8-13
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• 2005

• Journal of Dairy Science and Biotechnology
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• v.24 no.1
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• pp.1-7
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• 2006

This experiment was performed to identify the improvement of raw milk quality after introducing raw milk grading system(1993, June). The purpose of this experiment was to investigate chemical component and microbiological quality of raw milk in jeju. This experiment made it possible to spread high standard of quality of raw milk or milk product including yoghurt, ice cream etc., and to provide dairy industry information for the construction of Jeju international free city master plan. As a result, automatic milking system is improved a lot after introducing raw milk grading system and sustained good condition compared with other provinces. High ratio was shown dairy farm in jeju for pre-milking, pre-cooling system equipment and self laboring. Otherwise, the ratio of dairy farm doing test of mastitis is low. The ratio of first grade distribution in Jeju is 80.64%, which means that was improved before introducing raw milk grading system. The number of somatic cells found in summer more than that of other seasons in raw milk. However, these data is a little higher than the nation wide data medium. Also, general components, annual lipid ratio is 3.90% that improved compared with before introducing raw milk grading system. These data showed low in summer and similar to nation wide.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.607-614
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• 1996

A computer vision based automatic intelligent sorting system for dried oak mushrooms has been developed. The developed system was composed of automatic devices for mushroom feeding and handling, two sets of computer vision system for grading , and computer with digital I/O board for PLC interface, and pneumatic actuators for the system control. Considering the efficiency of grading process and the real time on-line system implementation, grading was done sequentially at two consecutive independent stages using the captured image of either side. At the first stage, four grades of high quality categories were determined from the cap surface images and at the second stage 8 grades of medium and low quality categories were determined from the gill side images. The previously developed neuro-net based mushroom grading algorithm which allowed real time on-line processing was implemented and tested. Developed system revealed successful performance of sorting capability of approximate y 5, 000 mushrooms/hr per each line i.e. average 0.75 sec/mushroom with the grading accuracy of more than 88%.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.186-195
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• 2021

In Korea, groundwater quality is monitored through National Groundwater Quality Monitoring Network (NGQMN) administered by Ministry of Environment. For a given contaminant, compliance to groundwater quality standards is assessed on a annual basis by monitoring the number of incidents that concentration exceeds the regulatory limit. However, this approach provides only a fractional information about groundwater quality degradation, and more crucial information such as location and severity of the contamination cannot be obtained. For better groundwater quality management on a watershed, a more spatially informative and intuitive method is required. This study presents two statistical methods to convert point-wise monitoring data into information on groundwater quality status of a watershed by using a proposed grading scale. The proposed grading system is based on readily available reference standards that classify the water quality into 4 grades. The methods were evaluated with NO₃^-, Cl^-, and total coliform data in Geum River basin. The analyses revealed that groundwater in most watersheds of Geum River basin is good for domestic or/and drinking with no treatment. But, there was notable quality degradation in Bunam seawall and So-oak downstream standard watersheds contaminated by NO₃^- and Cl^-, respectively.

• Ocean and Polar Research
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• v.33 no.1
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• pp.13-20
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• 2011

Comprehensive data collection was carried out between 2001-2006 to investigate the concentration levels of chlorophyll-a, nutrients (DIN and DIP), and COD for surface waters of Korean coastal areas. A statistical analysis of these parameters was carried out on the basis of the frequency distribution of their concentration. Furthermore, the numeric grading for chlorophyll-a, DIN, DIP, and COD concentrations were derived statistically from the normalized frequency distribution of log-transformed data. The statistical grading clearly reflects the water quality characteristics of three Korean coastal water bodies (Western, Southern and Eastern coastal zones), which indicate common environmental and ecological characteristics. So, this study could provide useful information to set up the guideline for water quality assessment of Korean coasts.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.8-15
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• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• KIEAE Journal
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• v.10 no.6
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• pp.55-66
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• 2010

The government is enacted "Housing Performance Grading Indication System" from qualitative housing supply policy and performance of housing under the background of looking for new plan to secure good housing stock and housing performance. This system consists of 5 main performance section, 14 performance categories and 20 detailed performance items. 5 main performance parts are sound insulation related grading(Light-weight impact sound insulation, heavy-weight floor impact sound insulation, noise emission in bathroom, airborne sound insulation for wall between units), Long-life housing related grading(flexibility, remodeling & maintenance, durability), environment related grading(landscape, indoor air quality and ventilation, energy performance), Living environment related grading(common resident facilities such as playground and consideration for the socially underprivileged such as the aged), Fire fire prevention grading(fire fire prevention). The purpose of this research is to analyze characteristics and assessment results of 20 detailed performance items on "Housing Performance Grading Indication System" which was enforced 240 cases from Jan 9th, 2006 to Sep 30th, 2010. The analysis of approval condition of detailed performance items will be important comments for understanding the current domestic level and development of technology.

• Ocean and Polar Research
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• v.33 no.1
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• pp.85-97
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• 2011

The tidal flats of Korea today have reduced by 40% in size compared to 1964. To manage this important habitat properly, development of well-organized and nationwide-applicable grading systems is required. There have been several assessment systems proposed previously in Korea, but they are critically flawed in that selected biological indicators are not adequate and grading criteria are obscure and arbitrary. We reviewed the indicators used in these previous evaluation systems (e.g., diversity indices, quantity and quality of benthic macrofauna, halophytes, water birds, etc.) and subsequently proposed new indicators and an improved grading scheme. For the quantitative assessment of macrobenthic community, biomass reflecting production and ecosystem function is recommended over density, which is much less discriminatory among habitats. Of biodiversity indices used, within-, between-habitat and regional biodiversity indices that accurately reflect sampling efforts are suggested. In addition, we proposed to include species rarity, ecosystem engineers, and the ecological quality index ISEP (Inverse function of Shannon-Wiener Evenness Proportion). As for halophytes, their low spatial coverage on benthic habitat suggests that their presence can be used as an ecological indicator of benthic habitat, regardless of their protective status. We stress the need to introduce 1) quantile approach for quantitative indicators (e.g., diversity, biomass, etc.) in relation to grading, 2) presence-absence approach for spatial or aggregate indicators (e.g., boundaries of halophytes and feeding ground of water birds) and 3) benthic habitat mapping that combines all of these indicators.