• Food Engineering Progress
• /
• v.14 no.4
• /
• pp.335-341
• /
• 2010

The extraction of polyphenol and flavonoid from black rice bran was performed by diverse extraction methods using the sugar solution, ethanol, hot water ($80^{\circ}C$), and by subcritical water extraction (SWE) method. By SWE under operating conditions of $190^{\circ}C$, 1,300 psi, and 10 min, the maximum yields of total polyphenolic compounds (35.06${\pm}$1.28 mg quercetin equivalent (QE)/g dried material and flavonoids (7.08${\pm}$0.31 mg QE/g dried material) could be obtained. These results were over 11.77- and 12.21-fold higher than those of the ethanol extraction, which showed the highest extraction efficiency among tested conventional methods in total polyphenols (2.98${\pm}$0.74 mg QE/g dried material) and flavonoids (0.58${\pm}$0.21 mg QE/g dried material), respectively. Though the highest antioxidant activity (87.14${\pm}$1.14%) was observed at the dried extract obtained from ethanol method, the relative antioxidant activity per 1 g dried black rice bran by SWE ($190^{\circ}C$, 10 min) was over 11.53-fold higher than that by the ethanol extraction.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.5
• /
• pp.65-71
• /
• 2008

Recently, the research is progressing on the SWE(Sensor Web Enablement) platform of OGC(Open Geospatial Consortium) to provide the sensing data and moving pictures collected in a sensor network through the Internet Web. However, existed research does not deal with moving objects like cars, trains, ships, and person. Therefore, we present a method to deal with integrated sensing data collected by GPS device, sensor network, and image devices. Also, this paper proposes an integrated processing method for image and sensing data based on location in mobile sensor networks. Additionally, according to proposed methods, we design and implement the combine adapter. This combine adapter receives a contexts data, and provides the common interface included parsing, queueing, creating unified message function. We verity the proposed method which deal with the integrated sensing data based on combine adapter efficiently. Therefore, the research is expected to help the development of a various context information service based on location in future.

• Journal of the Korean Society of Radiology
• /
• v.17 no.7
• /
• pp.1057-1065
• /
• 2023

Non-invasive liver fibrosis diagnosis is crucial for patients with chronic liver diseases. Many patients cannot undergo liver tissue biopsy, so predicting the degree of liver fibrosis early through meaningful methods can reduce complications related to chronic liver diseases, such as liver cell carcinoma and cirrhosis. This study compared and analyzed the quantitative measurement of liver fibrosis using shear wave elastography in conjunction with liver ultrasound findings and their associations with serum biomarkers (p<0.05). The results showed that the shear wave elastography measurement in the normal group was 4.55 ± 0.69 kPa, while the abnormal contrast group with echogenic patterns had a measurement of 8.27 ± 1.83 kPa. The hepatitis B carrier group exhibited higher shear wave elastography measurements, and among serum biomarkers, AST, ALT, GGT, and PT showed statistically significant positive correlations with fibrosis severity according to SWE categories (p<0.05), while ALP and TB did not demonstrate statistically significant differences (p=0.163, p=0.567). Conversely, Albumin and PLT showed significant negative correlations (p<0.05). Clinically, utilizing shear wave elastography measurements through liver ultrasound in the tracking and repeat testing of liver fibrosis in chronic hepatitis B patients without cirrhosis can assist in achieving more objective diagnoses among healthcare providers.

• Nuclear Engineering and Technology
• /
• v.41 no.8
• /
• pp.1045-1052
• /
• 2009

A calculation model is developed to predict the transient free surface flow on the containment floor following a loss-of-coolant accident (LOCA) of pressurized water reactors (PWR) for the use of debris transport evaluation. The model solves the two-dimensional Shallow Water Equation (SWE) using a finite volume method (FVM) with unstructured triangular meshes. The numerical scheme is based on a fully explicit predictor-corrector method to achieve a fast-running capability and numerical accuracy. The Harten-Lax-van Leer (HLL) scheme is used to reserve a shock-capturing capability in determining the convective flux term at the cell interface where the dry-to-wet changing proceeds. An experiment simulating a sudden break of a water reservoir with L-shape open channel is calculated for validation of the present model. It is shown that the present model agrees well with the experiment data, thus it can be justified for the free surface flow with accuracy. From the calculation of flow field over the simplified containment floor of APR1400, the important phenomena of free surface flow including propagations and interactions of waves generated by local water level distribution and reflection with a solid wall are found and the transient flow rates entering the Holdup Volume Tank (HVT) are obtained within a practical computational resource.

• IEIE Transactions on Smart Processing and Computing
• /
• v.5 no.6
• /
• pp.430-439
• /
• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.4
• /
• pp.281-291
• /
• 2017

Nowadays, as traffic jams are a daily elementary problem in both developed and developing countries, systems to monitor, predict, and detect traffic conditions are playing an important role in research fields. Comparing them, researchers have been trying to solve problems by applying many kinds of technologies, especially roadside sensors, which still have some issues, and for that reason, any one particular method by itself could not generate sufficient traffic prediction results. However, these sensors have some issues that are not useful for research. Therefore, it may not be best to use them as stand-alone methods for a traffic prediction system. On that note, this paper mainly focuses on predicting traffic conditions based on a hybrid prediction approach, which stands on accuracy comparison of three prediction models: multinomial logistic regression, decision trees, and support vector machine (SVM) classifiers. This is aimed at selecting the most suitable approach by means of integrating proficiencies from these approaches. It was also experimentally confirmed, with test cases and simulations that showed the performance of this hybrid method is more effective than individual methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.119-125
• /
• 2019

Recently, it has become a social problem due to fine particles. There are more people wearing masks, weather alerts and disaster notices. Research and policy are actively underway. Meteorologically, the biggest damage caused by fine particles is the inversion layer phenomenon. In this study, we designed a system to warn fine Particles by analyzing inversion layer and wind direction. This weather information system proposes a system that can efficiently perform scalability and parallel processing by using OGC sensor web enablement system and NoSQL storage for sensor control and data exchange.

• Culinary science and hospitality research
• /
• v.18 no.5
• /
• pp.279-292
• /
• 2012

This study was performed to investigate the quality characteristics and antioxidant activity of noodle added freeze-dried purple sweet potato powder. For Hunter's color resulted, as the amount of purple sweet potato powder increased, L-value and b-value decreased, the a-value increased. Anthocyanin contents of purple sweet potato powder at concentration of (mg/100 g) were 99.62%. DPPH radical scavenging activities of purple swe et potato powder at concentration of $1,000{\mu}L/mL$ were 84.60%. The texture of cooked noodles appeared no significant differences in cohesiveness, Springiness, Hardness, Gumminess and Chewiness decreased as the am ount of purple sweet potato powder increased. The weight, volume, moisture contents of noodles were not significantly. Sensory evaluation of acceptability including color, aroma, taste, chewiness and overall-acceptabi lity appeared the 6% added group was the best for higher. According to the positively evaluated anthocyanin content, DPPH radical scavenging activities, quality characteristics and sensory evaluation, a purple sweet pota to powder content 6% appears to be most appropriate.

• Journal of Microbiology
• /
• v.45 no.3
• /
• pp.227-233
• /
• 2007

In budding yeast, septin plays as a scaffold to recruits protein components and regulates crucial cellular events including bud site selection, bud morphogenesis, Cdc28 activation pathway, and cytokinesis. Phosphorylation of Bni5 isolated as a suppressor for septin defect is essential to Swe1-dependent regulation of bud morphogenesis and mitotic entry. The mechanism by which Bni5 regulates normal septin function is not completely understood. Here, we provide evidence that Bni5 phosphorylation is important for interaction with septin component Cdc11 and for timely delocalization from septin filament at late mitosis. Phosphorylation-deficient bni5-4A was synthetically lethal with $hof1{\Delta}$. bni5-4A cells had defective structure of septin ring and connected cell morphology, indicative of defects in cytokinesis. Two-hybrid analysis revealed that bni5-4A has a defect in direct interaction with Cdc11 and Cdc12. GFP-tagged bni5-4A was normally localized at mother-bud neck of budded cells before middle of mitosis. In contrast, at large-budded telophase cells, bni5-4A-GFP was defective in localization and disappeared from the neck approximately 2 min earlier than that of wild type, as evidenced by time-lapse analysis. Therefore, earlier delocalization of bni5-4A from septin filament is consistent with phosphorylation-dependent interaction with the septin component. These results suggest that timely de localization of Bni5 by phosphorylation is important for septin function and regulation of cytokinesis.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.29 no.1
• /
• pp.39-45
• /
• 2015

This experiment was designed to investigate the effect of Added Chongmyung-tang (ACM) on Alzheimer's disease mouse model. Effects of ACM on learning behavior were investigated using the Morris water maze method. Expression levels of molecular factors related to Alzheimer's disease such as glial fibrillary acidic protein (GFAP), cluster of differentiation antigen 68 (CD68), and tau protein in the hippocampus of APP-SWE Tg2576 mice were analyzed by immunofluorescence staining method. ACM reduced escape latency in the Morris water maze test. ACM decreased the expression level of GFAP and tau protein in the hippocampus. These results suggest that ACM may be involved in regulating molecules that are known to play an important role in the pathogenesis of Alzheimer's disease.