• Journal of Energy Engineering
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• v.23 no.3
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• pp.186-190
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• 2014

Nuclear Power Plants require the control ability of chemical condition (pH) because pH control during transient accident such as LOCA makes an able the fission product removal capability to be maintained, stress corrosion cracking of stainless steel equipment to be prevented and the production of hydrogen by aluminum and zinc to be minimized. An NPP is designed to control the pH of containment spray and sump coolant using the spray additives 30% NaOH in the event of loss of coolant accident. In this paper, the pH of sump coolant of an NPP during LOCA was analyzed and the fission products removal constant and decontamination factor were calculated according to Standard Review Plan 6.5.2 related to spray chemical conditions of pH. The calculated pH value of recirculation mode using the computer code corresponds to 8.09~9.67, which meets the chemical environment regulation requirements. The fission product removal capability caused by containment spray system is performed to provide input to radiation analysis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.170-178
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• 2015

In this study, it was developed eco-friendly alkali-activated slag fiber reinforced concrete using ground granulated blast furnace slag, alkali activator (water glass, sodium hydroxides), and steel fiber. Eight reinforced concrete beam using alkali-activated slag concrete were constructed and tested under monotonic loading. The major variables were mixture ratio of alkali activator, mixed/without of steel fiber. Experimental programs were carried out to improve and evaluate the flexural performance of such test specimens, such as the load-displacement, the failure mode, the maximum load carrying capacity, and ductility capacity. All the specimens were modeled in scale-down size. The reinforced concrete beams using the eco-friendly alkali-activated slag fiber reinforced concrete was failed by the flexure or flexure-shear in general. In addition, the maximum strength increased with the adding the mol of sodium hydroxide, and the specimen reinforced the steel fiber showed the value of maximum strength which is increased by 15.8% through 25.9%. It is thought that eco-friendly alkali-activated slag fiber reinforced concrete can be used with construction material and product to replace normal concrete. If there is applied to structures such as precast concrete member and production of 2nd concrete product, it could be improved the productivity and reduction of construction duration etc.

• The Journal of Korean Academy of Prosthodontics
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• v.39 no.2
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• pp.157-170
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• 2001

The bond strength is the most important factor in establishing long-term success of resin-retained fixed prostheses. So, various surface treatment methods have been introduced to improve the bond strength of metal surface and bonding resin till now This study was performed to compare the effect of silicoating with that of metal primer and analyze the correlation between treatment time of sandblasting and the bond strength, so that meant to find more effective surface treatment method that could enhance the bond strength of resin-retained fixed prostheses. The surfaces of all specimens made of $Verabond^{(R)}$ alloys were air abraded with $250{\mu}m\;Al_2O_3$ according to treatment time of sandblasting and they were subdivided to be treated with only sandblasting(S group), silicoating following sandblasting(SS group) and metal primer application after sandblasting(SM group). Then pairs of metal specimens (${\phi}10mm{\times}h\;2mm,\;{\phi}6{\times}h\;2mm$) were bonded with Super bond $C&B^{(R)}$. The specimens were stored in $38^{\circ}C$ water for 48 hours and shear bond strength was measured using the universal testing machine. The results were as follows, 1. In the comparison of shear bond strength according to treatment time of sandblasting, bond strength was increased in the order of 0', 15', 30', 45', 60' group. 0' group had significantly lower value than any other, while 0', 15' group were significantly different with 30', 45', 60' group(p<0.05). 2. In the comparison of shear bond strength according surface treatment methods, bond strength was increased in the order of S group. SS group and SM group. S group was significantly different with SS group and SM group(p<0.05). 3. Observing the mode of bond failure. 0', 15' group showed only adhesive failure, and 30', 45', 60' group did mostly adhesive & cohesive failure in S group. In SS group and SM group, all other groups except 0', 15' group showed mostly cohesive failure. From the above results, it is considered that sandblasting should be treated for more than 30 seconds, and metal primer be more effective and available clinically than silicoater system which is complicate, technique-sensitive and time-consuming method, when nonprecious metal surface is planning be treated with in order enhance the bond strength of resin-retained fixed prostheses.

• KSBB Journal
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• v.16 no.1
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• pp.87-94
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• 2001

The biosynthesis of Lovastatin, a cholesterol lowering agent formed by the filamentous fungus, cerulenin-resistant Aspergillus terreus mutant was studied in shake flasks and bioreactors. The lovastatin production could be improved by fed-batch under the limited condition of carbon source. The relationship between the fungal morphology and the lovastatin production was also examined during the fed-batch cultures. The fed-batch studies in shake flasks were carried out to find the optimum glucose feeding method, and the pulsed feeding of glucose from 3 days onward at 24 hours intervals was found to be optimal to increase the lovastatin production and reduce the average pellet size. When the pH was controlled at around 5.8 during the whole fermentation period, the lovastatin concentration reached 384 mg/L, which is much higher than the values obtained pH-uncontrolled and pH 7.4. The optimal glucose feeding strategies was found that 30 g/L of glucose was added initially in batch mode, and then fed-batch was conducted by continuous addition of glucose solution(180 g/L) from 72 to 240 hr at a rate of 1.2 mL/hr at $28^{\circ}C$, pH 5.8, 400 rpm, and 1.0 vvm. The lovastatin concentration of 547 mg/L was obtained in 168 hr. It was about 1.5 times higher than the value of the batch fermentation.

• Korean Journal of Pharmacognosy
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• v.25 no.3
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• pp.238-248
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• 1994

The hypoglycemic and metabolic effects of Commelina communis L. extract were investigated in alloxan induced diabetic rats. The increased blood glucose level in the diabetic rats was significantly reduced and the loss of body weight was recovered with the treatment of the plant protein fractions($30{\sim}70%$ ammonium sulfate precipitates). Administration of the plant protein fractions elicited the significant increase of glucose-6-phosphate dehydrogenase (G-6-P DH) activity and liver weight which were decreased in the diabetic rat liver. G-6-P DH was partially purified from extract- or insulin-treated diabetics, diabetic control, and normal rat liver and studied for the biochemical properties. The $K_m$ value(9.002 mM) of diabetic rat liver enzyme was greatly higher than that (0.033 mM) of normal enzyme indicating the affinity of enzyme for the substrate was significantly reduced in the diabetic rat liver. This reduced affinity of enzyme for the substrate in the diabetic rat was recovered in the extract- or insulin-treated rat liver enzyme having 0.164 or 0.208 mM of their $K_m$ values, respectively. Although there was no significant difference in the optimum pH(6.0) and optimum temperature($37^{\circ}C$) of enzyme among the experimental groups, the dependence of their activities on pH appeared to be slightly resistant in the extract- or insulin-treated group compared to the diabetic group. In order to investigate the antigenicity of rat liver enzyme among experimental groups, enzyme-linked immunosorbent assay was carried out by using anti-G-6-P DH anti-serum. Absorbance(0.102) shown in the normal rat liver was reduced even below zero in the alloxan-diabetic rat liver, but increased again in the extract- or insulin-treated rat liver(0.096 or 0.118, respectively). The result of this study suggested that G-6-P DH may be used as a marker enzyme to diagnose and to indicate the progress of the diabetics, and the hypoglycemic effect of the extracts of Commelina communis L. was certainly associated with action or mode of G-6-P DH on the rat liver.

• Journal of Wetlands Research
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• v.15 no.4
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• pp.509-518
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• 2013

Understanding of the exchange between the water and energy which is happening between the surface and atmosphere is the basic of studying water resources. To study these, lots of researches using Noah Land Surface Model(LSM) are in progress. Noah LSM is based on energy and water balance equation and simulates various hydrological factors. There are diverse researches with Noah LSM are ongoing in overseas, on the other hand not enough study has been done. Especially there is almost no study using uncoupled Noah LSM in Korea. In this study we used data from Korea Flux Tower in Haenam(HFK) and Gwangneung(GDK) as forcing data to simulate the model and compared its result of net radiation, sensible heat flux and latent heat flux with the observation data to assess the applicability of Noah LSM in Korea. Regression coefficients of the comparison results of Noah LSM and observation show good agreement with the value of 0.83~0.99 at Haenam and 0.64~0.99 at Gwangneung which means Noah LSM can be trusted.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1032-1032
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• 2001

Artificial Neural Network (ANN) calibration techniques have been used commercially for agricultural applications since the mid-nineties. Global models, based on transmission data from 850 to 1050 nm, are used routinely to measure protein and moisture in wheat and barley and also moisture in triticale, rye, and oats. These models are currently used commercially in approx. 15 countries throughout the world. Results concerning earlier European ANN models are being published elsewhere. Some of the findings from that study will be discussed here. ANN models have also been developed for coarsely ground samples of compound feed and feed ingredients, again measured in transmission mode from 850 to 1050 nm. The performance of models for pig- and poultry feed will be discussed briefly. These models were developed from a very large data set (more than 20,000 records), and cover a very broad range of finished products. The prediction curves are linear over the entire range for protein, fat moisture, fibre, and starch (measured only on poultry feed), and accuracy is in line with the performance of smaller models based on Partial Least Squares (PLS). A simple bias adjustment is sufficient for calibration transfer across instruments. Recently, we have investigated the possible use of ANN for a different type of NIR spectrometer, based on reflectance data from 1100 to 2500 nm. In one study, based on data for protein, fat, and moisture measured on unground compound feed samples, dedicated ANN models for specific product classes (cattle feed, pig feed, broiler feed, and layers feed) gave moderately better Standard Errors of Prediction (SEP) compared to modified PLS (MPLS). However, if the four product classes were combined into one general calibration model, the performance of the ANN model deteriorated only slightly compared to the class-specific models, while the SEP values for the MPLS predictions doubled. Brix value in molasses is a measure of sugar content. Even with a huge dataset, PLS models were not sufficiently accurate for commercial use. In contrast an ANN model based on the same data improved the accuracy considerably and straightened out non-linearity in the prediction plot. The work of Mr. David Funk (GIPSA, U. S. Department of Agriculture) who has studied the influence of various types of spectral distortions on ANN- and PLS models, thereby providing comparative information on the robustness of these models towards instrument differences, will be discussed. This study was based on data from different classes of North American wheat measured in transmission from 850 to 1050 nm. The distortions studied included the effect of absorbance offset pathlength variation, presence of stray light bandwidth, and wavelength stretch and offset (either individually or combined). It was shown that a global ANN model was much less sensitive to most perturbations than class-specific GIPSA PLS calibrations. It is concluded that ANN models based on large data sets offer substantial advantages over PLS models with respect to accuracy, range of materials that can be handled by a single calibration, stability, transferability, and sensitivity to perturbations.

• Korean Journal of Food Science and Technology
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• v.43 no.2
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• pp.156-160
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• 2011

A tray type-infrared (IR) pasteurization system was developed for decreasing microorganisms in red pepper powder (RPP). The RPP was passed through a tray by a vibrating mode under the 4 IR lamps (total 8000 W) and by circulating water under the tray. Fungi was pasteurized by applying power higher than 2000 W to the RPP. The decrease in viable cell numbers of bacteria, however, was not observed under the same conditions. Conveying speed of RPP was optimized to 106-164 g/min on the basis of microbial reduction and retaining of moisture content of RPP. The water content of 32 mesh-RPP decreased rapidly after pasteurization. However, fungi in both RPPs could be sterilized regardless of particle sizes. The repetition of IR pasteurization was not favourable due to severe decrease of water content in RPP. The IR pasteurization of RPP did not cause significant difference in the capsaicinoid contents, ASTA colour value, and L, a, and b values under all investigated conditions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.