• Journal of KIISE:Databases
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• v.32 no.6
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• pp.650-661
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• 2005

As the Internet is growing, the use of XML which is a standard of semi-structured document is increasing. Therefore, there are on going works about integration and retrieval of XML documents. However, the basis of efficient integration and retrieval of documents is to cluster XML documents with similar structure. The conventional XML clustering approaches use the hierarchical clustering algorithm that produces the demanded number of clusters through repeated merge, but it have some problems that it is difficult to compute the similarity between XML documents and it costs much time to compare similarity repeatedly. In order to address this problem, we use clustering algorithm for transactional data that is scale for large size of data. In this paper we use common structures from XML documents that don't have DTD or schema. In order to use common structures of XML document, we extract representative structures by decomposing the structure from a tree model expressing the XML document, and we perform clustering with the extracted structure. Besides, we show efficiency of proposed method by comparing and analyzing with the previous method.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.193-203
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• 2005

XML (extensible Markup Language) is recognized as a standard of data representation and transmission on Internet. XPath is a standard for specifying parts of XML documents anda suitable language for both query processing and access control of XML. In this paper, we use the XPath expression for representing user queries and access control for XML. And we propose an access control method for XML, where we control accesses to XML documents by filtering query XPath expressions through access control XPath expressions. In the proposed method, we directly search XACT (XML Access Control Tree) for a query XPath expression and extract the access-granted parts. The XACT is our proposedstructure, where the edges are structural summary of XML elements and the nodes contain access-control information. We show the query XPath expressions are successfully filtered through the XACT by our proposed method, and also show the performance improvement by comparing the proposed method with the previous work.

• Mycobiology
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• v.37 no.4
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• pp.258-266
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• 2009

Pleurotus eryngii, known as king oyster mushroom has been widely used for nutritional and medicinal purposes. This study was initiated to screen the suitable conditions for mycelial growth and to determine the phylogenetic relationship of the selected strains. Optimal mycelial growth was observed at $30{^{\circ}C}$ and minimum mycelial growth observed at $10{^{\circ}C}$. This mushroom tolerates a broad pH range for mycelial growth, with most favorable growth observed at pH 6. Results also indicated that glucose peptone, yeast malt extract and mushroom complete media were favorable growth media, while Hennerberg and Hoppkins media were unfavorable. Dextrin was the best and xylose the least effective carbon sources. Results revealed that inorganic nitrogen sources were less effective than organic sources for the mycelial growth of P. eryngii. Investigation of genetic diversity is necessary to identify the strains. The ITS region of rDNA were amplified using PCR. The size of the ITS1 and ITS2 regions of rDNA from the different strains varied from 214 to 222 bp and 145 to 236 bp, respectively. The sequence of ITS2 was more variable than that of ITS1, and the 5.8S sequences were identical. A phylogenetic tree based on the ITS region sequences indicated that selected strains could be classified into six clusters. Fourteen IUM and ATCC- 90212 strains were also analyzed by RAPD with 20 arbitrary primers. Fourteen of these primers were efficiently amplified the genomic DNA. The number of amplified bands varied with the primers and strains, with polymorphic fragments in the range from 0.2 to 2.3 kb.

• Food Science and Biotechnology
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• v.17 no.4
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• pp.787-793
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• 2008

A major polyphenolic compound extracted from omija (Schisandra chinensis) fruit was structurally identified, and its composition of major nutrients was investigated as well in this study. A dominating high performance liquid chromatography (HPLC) peak of water-extracted anthocyanin represented 94.1% of total absorbable compounds at 520 nm, which was further identified with HPLC-mass spectrometry (MS). As a result, mass-to-charge ratio (m/z) of the predominant anthocyanin was determined to be 727, and it was identical to molecular mass of cyanidin-3-xylosylrutinoside (Cya-3-O-xylrut). This is the first report that colorant of omija is predominantly composed of Cya-3-O-xylrut. Omija fruit contained exclusively 3 types of monosaccharide such as glucosc (0.68 g), galactose (0.01 g), and fructose (0.52 g) per 100 g of fruits. Several organic acids, citric (3.29 g), malic (1.4 g), acetic (0.4 g), and succinic acids (0.36 g) per 100 g of fruits, were detected by high performance anion exchange chromatography (HPAEC) analysis. During the compositional analysis of tree amino acid by HPLC, it was noticed that omija fruit contained substantial amount (0.01 g/100 g of fruits) of $\gamma$-amino butyric acid (GABA).

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.105-105
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• 2019

Dendropanax morbifera H.Lev is an evergreen tree that lives in subtropical climates. About 75 species of D. morbifera live in East Asia, but only one species live in Korea(Korean dendropanax). D. morbifera belonging to Aralicacae family 98% of D. morbifera are distributed in Jeollanam-do in the Korea and the grow wild in Gyeongsangnam-do and Jeju Island. The harvest time and usage of D. morbifera were recorded in traditional medicinal books. The roots and stems of D. morbifera had been used for traditional medicine to treat migraine, menstrual irregularity and skin disease. And D. morbifera leaves are contain flavonoids and polyacetylene compounds. In this study, we were investigated the physiological activity of D. morbifera by different areas collected at the same time, and compared to characteristics of plants. D. morbifera collected from Jeollanam-do (Goheung-gun), Gyeongsangnam-do (Namhae-gun) and Jeju Island, and dried at $50^{\circ}C$ for three days. We used dried D. morbifera powder for antioxidant tests. Each sample was extracted with hot water under the same conditions. The contents of total polyphenols and total flavonoids from D. morbifera were identified. Also, we performed to DPPH radical scavenging activity, ABTS cation radical scavenging activity and Superoxide anion scavenging activity efficacy for antioxidant activity determination. The contents of total polyphenols and total flavonoids in hot water extract of D. morbifera harvested from Gyeongsangnam-do and Jeollanam-do were higher than Jeju. However, D. morbifera harvested from Gyeongsangnam-do and Jeollanam-do showed no significant difference those content of total polyphenols and total flavonoids. And the antioxidant capacity was showed the similar patterns in antioxidant activity.

• Natural Product Sciences
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• v.24 no.4
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• pp.235-240
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• 2018

Betula platyphylla var. japonica (Betulaceae), also known as Asian white birch, is an endemic medicinal tree, the bark of which has been used in Chinese traditional medicine for the treatment of various inflammatory diseases. In our continuing search for bioactive compounds from Korean natural resources, a phytochemical investigation of the bark of B. platyphylla var. japonica led to the isolation of 7-oxo-${\beta}$-sitosterol (1) and soyacerebroside I (2) from its ethanol extract as main components by liquid chromatography (LC)/mass spectrometry (MS)-based analysis. The structures of isolates were identified by comparison of $^1H$ and $^{13}C$ nuclear magnetic resonance spectroscopic data and physical data with the previously reported values and LC/MS analyses. To the best of our knowledge, this is the first study to demonstrate that the isolated compounds, 7-oxo-${\beta}$-sitosterol and soyacerebroside I, were isolated in B. platyphylla var. japonica. We examined the effects of the isolates on the regulation of adipocytes and osteoblast differentiation. These isolates (1 and 2) produced fewer lipid droplets compared to the untreated negative control in Oil Red O staining of the mouse mesenchymal stem cell line without altering the amount of alkaline phosphatase staining. The results demonstrated that both compounds showed marginal inhibitory effects on adipocyte differentiation but did not affect osteoblast differentiation.

• Journal of Veterinary Clinics
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• v.38 no.1
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• pp.27-31
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• 2021

Shea butter (Vitellaria paradoxa) is a fat extracted from shea tree nuts and contains relatively high levels of non-glycerides. Triterpenes, the main non-glyceride component, exhibit a variety of biological activities such as antitumor, antibacterial, and anti-inflammatory. Shea butter extract (SBE) has been used to treat various skin problems such as burns, eczema, and rash in human medicine, but little is known about the activity of SBE on canine skin. This study evaluated the cytotoxicity and anti-inflammatory effect of SBE in canine keratinocytes. Cytotoxicity of lipopolysaccharide (LPS, 5-50 ng/mL) and SBE (50-200 ㎍/mL) was evaluated using the CCK-8 assay. Non-cytotoxic concentrations of LPS and SBE were administered to canine cell cultures to evaluate anti-inflammatory effects. To evaluate the anti-inflammatory activity of SBE, the levels of IL-1β, IL-8, IL-12, and TNF-α were measured using ELISA kits. The concentration of each cytokine was quantified in control, LPS-treated, LPS + SBE-treated groups. Increased levels of IL-1β, IL-8, and IL-12 were found in LPS-treated groups relative to control groups. LPS + SBE-treated groups showed a lower level of IL-1β, IL-8, and IL-12 than LPS-treated groups. These results suggest that SBE may have application as a topical agent for canine inflammatory skin diseases. However, further in vivo study is needed to evaluate the safety and efficacy of SBE in dogs.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.173-182
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• 2021

It is important to extract and assess low-flow recession characteristics for water resources management in the upper reaches of a stream. It is difficult to express the groundwater flow recession characteristics for streamflow synthetically. The linear recession model has been widely used by baseflow recession analysis for reason of simplicity and convenience, but recent studies show that nonlinear recession models fit well, and the relationship between the reservoir storage of shallow unconfined aquifers and the groundwater discharge was to be identified as nonlinear in the literature based on the analysis of numerous streamflow recession curves. The objective of the study is to decode these nonlinear characteristics, including evaporation loss, storage, and recharge of groundwater using streamflow. By analyzing the observed time series of streamflow from the study area, which is the Pyeongchang River basin in Korea, the main components of the underlying groundwater balance, namely, discharge, evaporation loss, storage, and recharge, can be identified and quantified. As a result of the study, depletion of groundwater by evapotranspiration losses through the water uptake of tree roots was found to bias the recession curves and the estimated reservoir parameters. The seasonality of both rainfall and potential evaporation, analysis of the recession curves, stratified according to time of the year, allowed the quantification of evapotranspiration loss as a function of a calendar month and stored groundwater storage.

• Physical Therapy Korea
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• v.28 no.2
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• pp.123-131
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• 2021

Background: Only 2% of falls in older adults result in serious injuries (i.e., hip fracture). Therefore, it is important to differentiate injurious versus non-injurious falls, which is critical to develop effective interventions for injury prevention. Objects: The purpose of this study was to a. extract the best features of surface electromyography (sEMG) for classification of injurious falls, and b. find a best model provided by data mining techniques using the extracted features. Methods: Twenty young adults self-initiated falls and landed sideways. Falling trials were consisted of three initial fall directions (forward, sideways, or backward) and three knee positions at the time of hip impact (the impacting-side knee contacted the other knee ("knee together") or the mat ("knee on mat"), or neither the other knee nor the mat was contacted by the impacting-side knee ("free knee"). Falls involved "backward initial fall direction" or "free knee" were defined as "injurious falls" as suggested from previous studies. Nine features were extracted from sEMG signals of four hip muscles during a fall, including integral of absolute value (IAV), Wilson amplitude (WAMP), zero crossing (ZC), number of turns (NT), mean of amplitude (MA), root mean square (RMS), average amplitude change (AAC), difference absolute standard deviation value (DASDV). The decision tree and support vector machine (SVM) were used to classify the injurious falls. Results: For the initial fall direction, accuracy of the best model (SVM with a DASDV) was 48%. For the knee position, accuracy of the best model (SVM with an AAC) was 49%. Furthermore, there was no model that has sensitivity and specificity of 80% or greater. Conclusion: Our results suggest that the classification model built upon the sEMG features of the four hip muscles are not effective to classify injurious falls. Future studies should consider other data mining techniques with different muscles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3950-3969
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• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.