Study on Confectionary Properties of Chou made with Flour of Rice and Rice-Wheat mixture (미분을 이용한 chou의 제과특성 연구)
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- Korean journal of food and cookery science
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- v.11 no.1
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- pp.69-76
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- 1995
This study was concentrated on the subject of chou formation and physicochemical characteristics on medium flour mixed with 0, 25, 50, 75, 100% of rice flour in order to clarify the possibility to substitute rice flour for wheat flour on chou preparation. The water holding capacity, swelling power, and maximum viscosity were higher in rice flour than those in medium flour but the initial pasting temperature was equal to 65
Sterilization of Neurospora crassa has been investigated in this research by using a surface air plasma with dielectric barrier discharged (DBD) structure under atmospheric pressure. The sinusoidal alternating current has been used in this experiment with discharge voltage of 1.4~2.3 kV. The phase difference between the voltage and current signals are found to be almost 80 degree due to the capacitive property of dielectric barrier. Temperature on the biomaterials has been minimized by radiating the heat with the air cooling system. It is noted that the substrate temperature remains under 37 degree for plasma exposure time of 10 minutes with operation of cooler system. It is found that the ozone,
This study was attempted to investigate physicochemical properties, molecular structural properties of native and acid-treated chestnut starch and chestnut starch gel. The amylose content was 18.9% and X-ray diffraction pattern showed Cb type. Swelling power was increased abruptly in the range of
Arsenic (As) has been considered as the most toxic one among various hazardous materials and As contamination can be caused naturally and anthropogenically. Major forms of arsenic in groundwater are arsenite [(As(III)] and/or arsenate [(As(V)], depending on redox condition: arsenite and arsenate are predominant in reduced and oxidized environments, respectively. Because arsenite is much more toxic and mobile than arsenate, there have been a number of studies on the reduction of its toxicity through oxidation of As(III) to As(V). This study was initiated to develop photocatalytic oxidation process for treatment of groundwater contaminated with arsenite. The performance of two types of light sources (UV lamp and UV LED) was compared and the feasibility of goethite as a photocatalyst was evaluated. The highest removal efficiency of the process was achieved at a goethite dose of 0.05 g/L. Based on the comparison of oxidation efficiencies of arsenite between two light sources, the apparent performance of UV LED was inferior to that of UV lamp. However, when the results were appraised on the basis of their emitting UV irradiation, the higher performance was achieved by UV LED than by UV lamp. This study demonstrates that environmentally friendly process of goethite-catalytic photo-oxidation without any addition of foreign catalyst is feasible for the reduction of arsenite in groundwater containing naturally-occurring goethite. In addition, this study confirms that UV LED can be used in the photo-oxidation of arsenite as an alternative light source of UV lamp to remedy the drawbacks of UV lamp, such as long stabilization time, high electrical power consumption, short lifespan, and high heat output requiring large cooling facilities.
Purpose : This study proposes the keyhole method in order to improve the time resolution of the proton resonance frequency(PRF) MR temperature monitoring technique. The values of Root Mean Square (RMS) error of measured temperature value and Signal-to-Noise Ratio(SNR) obtained from the keyhole and full phase encoded temperature images were compared. Materials and Methods : The PRF method combined with GRE sequence was used to get MR temperature images using a clinical 1.5T MR scanner. It was conducted on the tissue-mimic 2% agarose gel phantom and swine's hock tissue. A MR compatible coaxial slot antenna driven by microwave power generator at 2.45GHz was used to heat the object in the magnetic bore for 5 minutes followed by a sequential acquisition of MR raw data during 10 minutes of cooling period. The acquired raw data were transferred to PC after then the keyhole images were reconstructed by taking the central part of K-space data with 128, 64, 32 and 16 phase encoding lines while the remaining peripheral parts were taken from the 1st reference raw data. The RMS errors were compared with the 256 full encoded self-reference temperature image while the SNR values were compared with the zero filling images. Results : As phase encoding number at the center part on the keyhole temperature images decreased to 128, 64, 32 and 16, the RMS errors of the measured temperature increased to 0.538, 0.712, 0.768 and 0.845
Geothermal heat pump system (GHPS) is an energy-efficient technology that use the relatively constant and renewable energy stored in the earth to provide heating and cooling. With the aim of using GHPS as a heating source, it's possibilities of application in farrowing house were examined by measuring environmental assessment and sow's performance. A total of 96 sows were assigned to 2 pig housings (GHPS and conventional housing) with 48 for four weeks in winter season. During the experimental period, indoor maximum temperature in GHPS-housing was measured up to
The entry of an aging society and the extension of human life expectancy, the increasing interest in women's social advancement and men's appearance, and the natural interest in K-culture through media media, while receiving worldwide attention, Focus on K-Bueaty. Recently, looking at the occupation of the medical tourism field, in the case of aesthetic medicine tourism such as molding and dermatology, it has gained popularity not only in Asia such as China and Japan, but also in North America and Europe. The first external confirmation of human aging is the wrinkles on the skin of the face. Clean, wrinkle-free, elastic and healthy skin is a desire of most people. Skin condition and condition such as focused ultrasonic stimulation (HIFU: High Intensity Focused Utrasound) and low frequency, high frequency (RF: Radio Frequency), galvanic therapy using microcurrent, cryotherapy using rapid cooling, etc. Depending on the method of management, the effect of the treatment differs depending on the output and the stimulation site, etc., even in the treatment of medical equipment and beauty equipment using the same mechanism. In this research, in order to develop invasive high-frequency dermatological devices using a large number of beauty medical devices and microneedles of beauty devices, the international standards IEC 60601-2 (standards for individual medical devices) and MFDS (Ministry of) We designed and developed a high-frequency output device in compliance with the high-frequency stimulation standard announced in the Food and Drug Safety (Ministry of Food and Drug Safety). The circuit design consists of an amplifier (AMP: Amplifier) using Class-A Topology and a power supply device using Half-Bridge Topology. As a result of measuring the developed high-frequency output device, an average efficiency of 63.86% was obtained, and the maximum output was measured at 116.7W and 50.67dBm.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.