• Journal of Dairy Science and Biotechnology
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• 제38권4호
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• pp.230-236
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• 2020

Heat treatment is a fundamental processing technology in the dairy industry. The main purpose of heat treatment is to destroy pathogenic and spoilage promoting microorganisms to ensure milk safety and shelf life. Despite the development of alternative technologies, such as high-pressure processing and pulse field technology for microbial destruction, heat treatment is widely used in the dairy industry and in other food processes to destroy microorganisms. Heat treatment has contributed greatly to the success of food preservation since Pasteur's early discovery that heat treatment of wine and beer could prevent their deterioration, and since the introduction of milk pasteurization in the 1890s. In Korea, food labeling standards do not stratify heat treatments into low temperature, high temperature, and ultra-high temperature methods. Most milk is produced in Korea by pasteurization, with extended shelf life (ESL : 125--140℃ / 1-10 s). Classification based on temperature (i.e. low, high, and ultra-high), is meaningless.

• 한국초전도ㆍ저온공학회논문지
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• 제8권2호
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• pp.1-10
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• 2006

This paper reviews the magnetic refrigeration technology that is a novel cooling method utilizing magnetic field to obtain low temperature. The key component of the refrigeration is a novel magnetic refrigerant which should possess sufficiently large magneto-caloric effect so that a pseudo-Carnot magnetic refrigeration cycle can cover reasonably large temperature span. Otherwise, a regenerative concept should be employed to expand the temperature span of the refrigeration cycle. There is a growing interest in magnetic refrigeration as a viable refrigeration technology not only for cryogenics as well as room temperature range. This paper covers historical developments, fundamental concepts, key components, application classification, and recent research trend of magnetic refrigerators.

• ETRI Journal
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• 제37권2호
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• pp.283-294
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• 2015

A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1252-1252
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• 2001

The aim of this study was to evaluate the possibility to characterize and classify waxes applied on some type of cheeses to obtain good stability during handling and transportation. Generally, waxes are obtained from the petrochemical industry, nowadays there is the possibility to also use biodegradable waxes produced from microorganisms. Preliminary studies were carried out to optimize sample presentation in NIR analysis, such as melting conditions (influence of temperature) and coat thickness of wax. 12 waxes (biodegradable or not) were analysed by using an InfraAlyzer 500 (Bran+Luebbe). The sample size was performed cutting pieces of 1.5 cm (height) x 1.5 cm (width) x 1.5 mm (thickness), previously melted at 9$0^{\circ}C$. NIR spectra were collected at room temperature, and data were processed by Sesame Software (Bran+Luebbe) to evaluate qualitative differences among samples by cluster analysis. Waxes were gathered on the basis of their origin (petrochemical or microbial). To better understand the significance of the NIRS bands discriminating among waxes, a two-dimensional correlation with FT-IR spectra, collected by a FT-IR/ATR 420 (JASCO) instrument, was made using 2DCORR program (Galactic Industries). On the basis of its classification power, NIRS appears to be a promising tool when used in routine analysis for a qualitative control of raw materials.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.722-725
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• 2006

Studies on the ways to construct agreeable sound-amenity have been processed in Korea recently and Virtual Acoustics Field Simulation System (VAFSS) which is an active acoustics reproducing system has been made as a technique to realize the results of the study. This system catches the changes of surroundings and produce sounds which go well with the mood of the space. The fact that a man thinks a sound goes well with factors of the environment should be an individual evaluation. Thus, the standards to classify factors influencing the preference of the sound, which can be judged by the environment, are needed. This study suggests the standards of factors to provide agreeable sound for people according to changes of the time and other elements. Among the factors influencing environment, the temperature, the humidity and the wind were suggested as standards of discomfort Index and wind chin temperature. Besides, only the intensity of illumination has been chosen to estimate the intensity of radiation as a part of factors of the whether.

• 설비공학논문집
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• 제16권10호
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• pp.932-941
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• 2004

The objective of this study is to detect the multi-fault of HVAC system using a new pattern classification technique. To classify the effect of single-fault in determining the pattern, supply air temperature, OA-damper, supply fan, and air flowrate were chosen as experimental parameters. The combination of supply temperature, flow rate, supply fan and OA-damper were chosen as multi-fault conditions. Three kinds of patterns were introduced in the analysis of multi-fault problem. To solve multi-fault problem, the new pattern classification technique using residual ratio analysis was introduced to detect the multi-fault as well as single-fault. The residual ratio could diagnose single-fault or multi-fault into several patterns.

• Safety and Health at Work
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• 제12권3호
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• pp.416-420
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• 2021

Hazardous area classification design is required to reduce the explosion risk in process plants. Among the international design guidelines, only IEC 60079-10-1 proposes a new type of zone, namely zone 2 NE, to prevent explosion hazards. We studied how to meet the zone 2 NE grade for a facility handling hydrogen gas, which is considered as most dangerous among explosive gases. Zone 2 NE can be achieved considering the grade of release, as well as the availability and effectiveness of ventilation, which are factors indicative of the facility condition and its surroundings. In the present study, we demonstrate that zone 2 NE can be achieved when the degree of ventilation is high by accessing temperature, pressure, and size of leak hole. The release characteristic can be derived by substituting the process condition of the hydrogen gas facility. The equations are summarized considering relation of the operating temperature, operating pressure, and size of leak hole. Through this relationship, the non-hazardous condition can be realized from the perspective of inherent safety by the combination of each parameter before the initial design of the hydrogen gas facility.

• 동의신경정신과학회지
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• 제20권3호
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• pp.121-132
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• 2009

Objectives : This study was done to investigate the relativity of thermography to HRV(heart rate variability) in Sasang constitutional groups. Methods : We investigated 87 healthy workers consisted of 10 Taeumin, 47 Soeumin, 30 Soyangin. After diagnosing the Sasang constitution by QSCCII(Questionnaire for the Sasang Constitutional Classification), we ana lysed their HRV -time domain and frequency domain and also checked their thermography in April 2009. Results & Conclusions : Analysing the thermography, The whole skin temperature was showed equaly in many Taeumin, the face, Upper burner skin temperature was showed high in many Soeumin, and the abdomen skin temperature was showed low in many Soyangin. The relativity of the sympathetic index to skin temperature was high in Taeumin. The higher sympathetic index, the higher Upper burner skin temperature in Taeumin, the higer most of the skin temperature in Soyangin, lower the whole skin temperature in Soeumin.

• 한국기후변화학회지
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• 제7권4호
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• pp.507-512
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• 2016

This study was conducted to classify agroclimatic zones in South Korea. To classify the agroclimatic zones, such climatic factors as amount of rainfall from April to May, amount of rainfall in October, monthly average air temperature in January, monthly average air temperature from April to May, monthly average air temperature from April to September, monthly average air temperature from December to March, monthly minimum air temperature in January, monthly minimum air temperature from April to May, Warmth Index were considered as major influencing factors on the crop growth. Climatic factors were computed from monthly air temperature and precipitation of climatological normal year (1981~2010) at 1 km grid cell estimated from a geospatial climate interpolation method. The agroclimatic zones using k-means cluster analysis method were classified into 6 zones.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2020년도 봄 학술논문 발표대회
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• pp.206-207
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• 2020

Accurate estimation of concrete strength development at early ages is a critical factor to secure structural stability as well as to speed up the construction process. The temperature generated from the heat of hydration is considered as a key parameter in predicting the early age strength. Conventionally, concrete temperature has been measured by temperature sensors installed inside concrete. However, considering the measurement on building structures with multiple floors, this method requires reinstallation and repositioning of hardware such as sensors, data loggers and routers for data transfer. This makes the temperature monitoring work cumbersome and inefficient. Concrete temperature monitoring by using thermal remote sensing can be an effective alternative to supplement those shortcomings. In this study, image processing was carried out through K-means clustering technique, which is a unsupervised learning method, and the classification results were analyzed accordingly. In the future, research will be conducted on how to automatically recognize concrete among various objects by using deep learning techniques.