• Korean Journal of Food Science and Technology
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• v.30 no.2
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• pp.425-433
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• 1998

The characteristics of the reaction of calcium carbonate $(CaCO_3)$ immobilized with alginate as buffer system for the high concentration cultivation of bifidobacteria in fermenter are described by the mathematical model, and tested for the reusing possibility of the used $CaCO_3$ beads. When$CaCO_3$ beads with the various diameters were reacted in 0.1 M of the mixed organic acids (0.6 M of acetic acid and 0.4 M lactic acid) and in fermenter inoculated Bifidobacterium longum ATCC 15707, the change of bead diameters can be calculated with the amount of the decreased $CaCO_3$ from the surface of bead using the mathematical model. These values was similar to the directly measured bead diameter by a micrometer. Therefore, it was considered that the mathematical model could be used for explaining the reaction charateristics of the $CaCO_3$ bead reacted with the organic acids. When Bifidobacterium longum was incubated at $37^{\circ}C$ for 20 hours in fermenter with $CaCO_3$ beads, the buffering effect of $CaCO_3$, the reduce rate of the bead diameter, and the growth rate of Bifidobacterium longum were higher at the smaller beads than beads with the larger diameters. Also, when Bifidobacterium longum was incubated in fermenter with the mixed beads which were added new beads to the recovered beads in order to equalize with the total surface area of initial beads, the buffering effect of $CaCO_3$ bead and the growth rate of Bifidobacterium longum were very corresponded with the results of the fermentation using the only initial beads. Therfore, it is expected that the used beads can be reused by adding the initial beads.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.3 no.2
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• pp.59-70
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• 1998

Two-dimensional trend-vector model of sediment transport is first tested in the tidal flat of Garolim Bay, mid-western coast of the Korean Peninsula. Three major parameters of surface sediment, i.e., mean grain size, sorting and skewness, are used for defining the best-fitting transport trend-vector on the sand ridge and muddy sand flat. These trend vectors are compared with the real transport directions determined from morphology, field observation and bedforms. The 15 possible cases of trend vectors are calculated from total sediments. In order to find the role of coarse sediments, trend vectors from sediments coarser than < 4.5 ${\phi}$, (sand size) are separately calculated from those of total sediments. As compared with the real directions, the best-fitting transport-vector model is the "case M" of coarse sediments which is the combined trend vectors of two cases: (1) finer, better sorted and more negatively skewed and (2) coarser, better sorted and more positively skewed. This indicates sand-size grains are formed by simpler hydrodynamic processes than total sediments. Transported sediment grains are better sorted than the source sediment grains. This indicates that consistent hydrodynamic energy can make sediment grains better sorted, regardless of complicated mechanisms of sediment transport. Consequently, both transported vector model and real transported direction show that the source of sediments are located outside of bay (offshore Yellow Sea) and in the baymouth. These source sediments are transported through the East Main Tidal Channel adjacent the baymouth. Some are transported from the subtidal zone to the upper tidal flat, but others are transported farther to the south, reaching the south tidal channel in the study area. Also, coarse sediment grains on the sand ridge are originally from the baymouth, and transported through the subtidal zone to the south tidal channel. These coarse sediments are moved to the northeast, but could not pass the small north tidal channel. It is interpreted that the great amount of coarse sediments is returned back to the outside of the bay (Yellow Sea) again through the baymouth during the ebb tide. The distribution of muddy sand in the northeastern part of study area may result from the mixing of two sediment transport mechanisms, i.e., suspension and bedload processes. The landward movement of sand ridge and the formation of the north tidal channel are formed either by the supply of coarse sediments originating from the baymouth and outside of the bay (subaqueous sand ridges including Jang-An-Tae) or by the recent relative sea-level rise.

• Food Science and Preservation
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• v.22 no.1
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• pp.134-144
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• 2015

The anti-diabetic effects of Allium tuberosum Rottler extracts (ATE) and ATE fermented with lactic acid bacteria in db/db mice were evaluated. The electron donating activity of ATE fermented with Lactobacillus plantarum, and Lactobacillus casei, respectively, increased compared to that of ATE, but the superoxide radical scavenging activity of the ATE incubated with L. plantarum decreased. The superoxide radical scavenging activity of the ATE fermented with both L. plantarum and L. casei was similar to that of the ATE. Therefore, fermented ATE (FATE) was prepared for in vivo testing by incubating it with both L. plantarum and L. casei. The db/db mice were divided into six groups: normal (non-diabetic mice), diabetic control (DM), and four experimental groups administered 200 or 400 mg/kg/day ATE (ATE200 and ATE400) and 200 or 400 mg/kg/day FATE (FATE200 and FATE400). Weight gain was significantly inhibited in the FATE200 group compared with that in the other db/db mice groups (p<0.05). The areas under the curve of the ATE400 and FATE400 groups were significantly smaller than that of the DM group in the glucose tolerance evaluation. The serum glucagon-like peptide-1 levels in the ATE400 and FATE400 groups increased. These results indicate that administering ATE and FATE may be effective against anti-hyperglycemia by regulating insulin resistance. In particular, FATE may be beneficial for controlling obesity in type 2 diabetes.

• Korean Journal of Environmental Agriculture
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• v.42 no.1
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• pp.35-43
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• 2023

The fine particulate structure of biochar limits its use as a heavy metal adsorbent, and makes separation of the biochar from the solution technically challenging, thereby reducing recovery of the heavy metals. To address this issue, this study prepared biochar beads under various mixing conditions and investigated their efficiency in removing Pb from aqueous solutions using adsorption models. The biochar beads were produced by mixing alginate and biochar at different ratios: alginate bead (AB), 1% biochar + bead (1-BB), 2.5% biochar + bead (2.5-BB), and 5% biochar + bead (5-BB). The results revealed that the Freundlich isothermal adsorption pattern of the biochar beads to Pb was of the L-type. The highest Langmuir isothermal adsorption capacity (28.736 mg/g) was observed in the 2.5-BB treatment. The dominant mechanism among the kinetic adsorption characteristics of biochar beads for Pb was chemical adsorption. Additionally, the optimal pH range for Pb adsorption was found to be between 4 and 5.5. The highest Pb removal efficiency (97.9%) was achieved when 26.6 g/L of biochar beads were used. These findings suggest that biochar beads are an economical and highly efficient adsorbent that enables separation and recovery of fine biochar particles.

• Journal of Life Science
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• v.33 no.11
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• pp.923-935
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• 2023

Rubus crataegifolius (RC), Ulmus macrocarpa (UM), and Gardenia jasminoides (GJ) are well-known folk medicines in Asia used to treat various gastrointestinal disturbances. The present study evaluated the gastroprotective effect of LS-RUG-com, a mixture of commercially prepared powders of RC, UM, and GJ with a ratio of 3:1:2(w/w/w) against HCl/ethanol-induced gastritis, indomethacin-induced ulcers, and esophageal reflux-induced esophageal mucosal damage and Helicobacter pylori infections. In addition, TNF-α and IL-1β expressions were also determined and measured in esophageal tissue. As to HCl/ethanol-induced gastritis, the LS-RUG-com treatment at a dose of 150 mg/kg showed a remarkable anti-gastritis effect. Regarding indomethacin-induced gastric ulcers, the LS-RUG-com treatment had a significant anti-gastric ulcer effect. Furthermore, in the gastroesophageal reflux disease (GERD) model experiment, the LS-RUG-com treatment resulted in the histological recovery of stomach damage and mucosal injuries. Furthermore, the LS-RUG-com treatment led to an increase in gastric content pH, an increase in mucus protection, and a decrease in gastric pepsin output with a significant decrease in TNF-α and IL-1β. As to the Helicobacter pylori infected animal model, LS-RUG-com had a notable inhibitory effect on Helicobacter growth. The use of RC, UM, or GJ in isolation or the LS-RUG-com treatment as whole had good effects in terms of anti-oxidation, anti-neutralization, gastric acid secretion inhibition, and anti-lipid peroxidation, which supported the use of natural products as systemic gastric protective agents. Our results suggest that the LS-RUG-com might be a significant systemic gastroprotective agent that could be utilized for the treatment and/or protection from gastric disturbances and related damage.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Soil and Groundwater Environment
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• v.12 no.4
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• pp.1-7
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• 2007

Slug/bail tests were conducted in sand layer (sbt-1 well), silty sand layer (sbt-2 well), and mixed sand and silty sand layer (sbt-3 well). Hydraulic conductivity and specific storage coefficient were estimated through slug/bail tests. Pore volumes of groundwater level drawdown zone for bail test were estimated by using hydraulic conductivity and specific storage coefficient. KGS model was most suitable interpretation method of slug/bail tests. Average hydraulic conductivity for slug/bail tests were estimated to be $6.65{\times}10^{-5}$ m/sec in sbt-1 well, $6.33{\times}10^{-6}$ m/sec in sbt-2 well, and $3.72{\times}10^{-5}$ m/sec in sbt-3 well. Average specific storage coefficient for slug/bail tests were estimated to be 0.0225 in sbt-1 well, 0.0177 in sbt-2 well, and 0.0259 in sbt-3 well. Dimensionless time and dimensionless wellbore storage were estimated by use of transmissivity, storativity, test time, and specification of test wells. And, dimensionless drawdown were selected by parameter ${\alpha}\;and\;{\beta}$ parameter from Cooper et al. (1967). Radius of influence were estimated by estimated dimensionless time, dimensionless wellbore storage, and dimensionless drawdown. The average radius of influnce for slug/bail tests were estimated to be 1.377 m in sbt-1 well, 1.253 m in sbt-2 well, and 1.558 m in sbt-3 well. Pore volume at groundwater level drawdown zone by dummy withdrawal for bail tests were estimated to be $145,636cm^3$ in sbt-1 well, $71,561cm^3$ in sbt-2 well, and $100,418cm^3$ in sbt-3 well. Pore volume excepted well volume at groundwater level drawdown zone by dummy withdrawal for bail tests were estimated to be $145,410cm^3$ in sbt-1 well, $71,353cm^3$ in sbt-2 well, and $100,192cm^3$ in sbt-3 well.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.11
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• pp.1611-1618
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• 2010

This study was conducted to evaluate the effects of Eriobotrya japonica and Saurus chinensis extracts and their fermented extracts on immune parameters in BALB/c mice treated with 1% 2,4-dinitrochlorobenzene (DNCB). The groups were Eriobotrya japonica extract (BI), Saurus chinensis extract (SA), mixture with E. japonica extract and S. chinensis extract (FB) and fermented mixture with E. japonica extract and S. chinensis extract (FA) and distilled water treated control. The level of serum immunoglobulin (Ig) E was decreased in FA compared to control group, but significant difference was not observed (p<0.05). The histamine and contents in FA and control group were $1.47{\pm}0.20$ ng/mL and $1.90{\pm}0.04$ ng/mL, respectively (p<0.05). Ceramide contents were significantly increased in FA compared to BI, SA, FB and control group (p<0.05). These results suggest that FA supplementation in the DNCB treated BALB/c mice affect anti-allergic activities positively, and may be used as functional material for suppression of atopy dermatitis in food industry.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1141-1153
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• 2010

This paper introduces ONLIS(Overlay Multicast Network for Live IPTV Service), a novel overlay multicast network optimized to deliver live broadcast IPTV stream. We analyzed IPTV reference model of ITU-T IPTV standardization group in terms of network and stream delivery from the source networks to the customer networks. Based on the analysis, we divide IPTV reference model into 3 networks; source network, core network and access network, ION(Infrastructure-based Overlay Multicast Network) is employed for the source and core networks and PON(P2P-based Overlay Multicast Network) is applied to the access networks. ION provides an efficient, reliable and stable stream distribution with very negligible delay while PON provides bandwidth efficient and cost effective streaming with a little tolerable delay. The most important challenge in live P2P streaming is to reduce end-to-end delay without sacrificing stream quality. Actually, there is always a trade-off between delay & stream quality in conventional live P2P streaming system. To solve this problem, we propose two approaches. Firstly, we propose DSPT(Distributed Streaming P2P Tree) which takes advantage of combinational overlay multicasting. In DSPT, a peer doesn't fully rely on SP(Supplying Peer) to get the live stream, but it cooperates with its local ANR(Access Network Relay) to reduce delay and improve stream quality. When RP detects bandwidth drop in SP, it immediately switches the connection from SP to ANR and continues to receive stream without any packet loss. DSPT uses distributed P2P streaming technique to let the peer share the stream to the extent of its available bandwidth. This means, if RP can't receive the whole stream from SP due to lack of SP's uploading bandwidth, then it receives only partial stream from SP and the rest from the ANR. The proposed distributed P2P streaming improves P2P networking efficiency.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.