• Korean Journal of Medicinal Crop Science
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• v.24 no.1
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• pp.47-54
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• 2016

Background : A new extraction method-heated ultrasonic extraction was qualitatively and quantitatively analyzed for the extraction of major ginsenosides from ginseng extract; this new high-performance liquid chromatography (HPLC) method was compared with the official extraction method of Korean industrial standards and standard for health functional food. Methods and Results : Ginsenoside compounds were analyzed for 35 minutes by the new HPLC analysis method using a Halo$^{(R)}$ RP-Amide column. The new HPLC analysis method was validated by the measurement of intra-day and inter-day precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of each ginsenoside. The correlation coefficients (r2) for the calibration curves of the ginsenoside compounds were over 0.9997 in terms of linearity. The heated ultrasonic extraction method using ultrasonication for 30 minutes at $50^{\circ}C$ yielded higher amount of ginsenosides than the extraction method of the Korean industrial standards owing to the enhancement of extraction efficiency. Conclusions : Compared to the other extraction methods, the heated ultrasonic extraction method yielded a higher amount of ginsenoside Rb1 than Rg1 index compounds for the quality evaluation of ginseng roots.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.5
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• pp.519-526
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• 2000

Osteoporosis has recently been recognized as a major health problem in the elderly population. The disorder is manifested as a loss of bone mass accompanied by structural alteration of bone and increased incidence of fracture. Mandible also may be affected. So, I evaluated panoramic views of 66 postmenopausal women for finding the possibility of useful diagnostic mandibular parmeters of osteoporosis. To know the correlationship between skeleton and mandible, the average of the bone mineral density of lumbar from 2nd to 4th by the dual energy X-ray absorptiometry(DEXA, LUNAR DPZ. USA), and age and mandibular parameters, that is, the number of residual teeth, alveolar ridge resorption ratio, panoramic mandibular index (PMI), mandibular cortical width (MCW), angular cortical thickness (ACT), ramus cortical thickness (RCT), morphology of mandibular inferior cortical (MIC) were compared. And I divided the all tested women to the osteoporotic group and non-osteoporotic group by the use of T-score -2.0, which was derived from skeletal bone mineral density (BMD). To find the correlationship of the each group with mandibular parameters, t-test and discriminant analysis were done. The results of the t-test were that all parameters were highly related with 2 groups (p<0.05). Especially ACT, MIC, age have had even higher correlationship than others (p<0.001). The results of the discriminant analysis by the use of these ACT, MIC and age were that the discriminant function was Z = -2.973+(-1.447)$\times$(ACT)+1.131$\times$(MIC score)+(0.052)$\times$(age), the cutting score was 0.257 and the classification accuracy was 84.8%. Therefore I suggest that the consideration of the angular cortical thickness (ACT), the age of patient and the morphology of mandibular inferior cortical(MIC) may help find the osteoporosis.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• Journal of the Korean earth science society
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• v.22 no.2
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• pp.138-146
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• 2001

The land cover over Korean peninsula was classified using a multi-temporal NOAA/AVHRR (Advanced Very High Resolution Radiometer) data. Four types of phenological data derived from the 10-day composited NDVI (Normalized Differences Vegetation Index), maximum and annual mean land surface temperature, and topographical data were used not only reducing the data volume but also increasing the accuracy of classification. Self organizing feature map (SOFM), a kind of neural network technique, was used for the clustering of satellite data. We used a decision tree for the classification of the clusters. When we compared the classification results with the time series of NDVI and some other available ground truth data, the urban, agricultural area, deciduous tree and evergreen tree were clearly classified.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.11-30
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• 2019

Smartcards are used as the basic data for utilizing the various transportation policies and evaluations, etc. and provided the transportation basic statistics index. However, the main problem of the smartcard data is that the most of users do not take the alighting tag at the stop, so there is a limit to the scope of use for the total O-D trip data because incomplete O-D traffic data of transportation card users. In this study, a decision tree of learning model is estimated for the alighting stop of smartcard users. The model estimation accuracy in range less than 2 stops interval was 89.7% on average. By eliminating the incompleteness alighting stop of smartcard data through this model, it is expected to be used as the basic data for various transportation analyses and evaluations.

• Journal of the Korean Geotechnical Society
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• v.19 no.1
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• pp.151-161
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• 2003

In this study, an interpretation method is proposed to evaluate the stress conditions, including individual excess pore pressure components ($\Delta{u}_{oct}$/ and $\Delta{u}_{shear}$), of normally consolidated clay elements adjacent to the cone face. It is assumed that the stress path of triaxial compression is representative f3r that of the soil element and the soil is elastic-perfectly plastic material. The proposed method is applied to the results of miniature piezocone tests conducted at Louisiana State University calibration chamber system. Based on the results of interpretation, it was found that the ratio of $\Delta{u}_{oct}$/ $\Delta{u}$and $\Delta{u}_{shear}$/$\Delta{u}$ estimated by the proposed method is affected only by the pore pressure parameter. The proposed method gives consistent and reliable values of $\Delta{u}_{oct}$/ $\Delta{u}$and $\Delta{u}_{shear}$/$\Delta{u}$ compared with early works, whereas those obtained by other solutions are significantly dependent on the accuracy in estimating soil properties such as undrained shear strength and rigidity index.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.7
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• pp.550-557
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• 2017

Ionospheric delay, which affect the accuracy of GNSS positioning, is generated by electrons in Ionosphere. Solar activity level, region and time could make change of this delay level. Dual frequency receiver could effectively eliminate the delay using difference of refractive index between L1 to L2 frequency. But, Single frequency receiver have to use limited correction such as ionospheric model in standalone GNSS or PRC(pseudorange correction) in Differential GNSS. Generally, these corrections is effective in normal condition. but, they might be useless, when TEC(total electron content) extremely increase in local area. In this paper, monitoring algorithm is proposed for local ionospheric anomaly using multiple reference stations. For verification, the algorithm was performed with specific measurement data in Ionospheric storm day (20. Nov. 2003). this algorithm would detect local ionospheric anomaly and improve reliability of ionospheric corrections for standalone receiver.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.23-34
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• 1999

The most widely used measure for indicating the accuracy of DEM is RMSE(nut Mean Square Error), which is used by many national mapping agencies such as the USGS and the Ordnance Survey. Its prevalent use can be followed by the relative ease of calculation and understanding the concepts. However, there are many problems with the measure and the way from which it is often derived. First of all, the index does not involve my description of the mean donation between the two measures of elevation,. This means that it cannot interpret the distributions or patterns of errors involved in DEMs. The distribution of errors in DEMs will show some forms of spatial patterning. In order to explore the real quality of DEMs as a useful database, alternative approaches are needed. In this paper, we examined so called ESDA(Exploratory Spatial Data Analysis) approaches, which were attributed by both aspatial and spatial exploration methods. Our experimental research shows that even simple ESDA methods reveal new aspects of errors, especially spikes, striation, and terracing effect in DEMs, which my be ignored by RMSE measure.

• Atmosphere
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• v.23 no.4
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• pp.539-547
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• 2013

The objective of this study is to standardize the calculation method of Palmer Drought Severity Index (PDSI) for the three Drought Management Agencies (DMA) in south Korea, and to evaluate the PDSI applicability. For comparison and review of the method, the code and input data of PDSI are collected from each DMA. The calculation method is the same, but the used input data (number of meteorological stations, normal year period, Available Water Capacity (AWC) of the soil) are different. Through discussions with drought experts and literature review, the standardized method is determined. 61 stations which have the data period more than 30 years are selected. Also the normal year is fixed for 30 years and updated every 10 years. The observed AWC is utilized using GIS data. Empirical equation of PDSI is re-estimated according to domestic climate characteristics. For evaluating the standardized PDSI, past drought events are investigated and drought indices including the existing SPI and PDSI are used for comparative analysis. As results, although the accuracy of standardized PDSI through ROC analysis is lower than SPI, the newly standardized PDSI is better than existing PDSI from DMA, Also it reasonably explain the spatial drought situation through the spatial analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2122-2140
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• 2020

Proper and precise embedding of commercial ads within Webpages requires Ad-hoc analysis and understanding of their content. By the successful implementation of this step, both publishers and advertisers gain mutual benefits through increasing their revenues on the one hand, and improving user experience on the other. In this research work, we propose a novel multi-level context-based ads serving approach through which ads will be served at generic publisher websites based on their contextual relevance. In the proposed approach, knowledge encoded in domain-specific and generic semantic repositories is exploited in order to analyze and segment Webpages into sets of contextually-relevant segments. Semantically-enhanced indexes are also constructed to index ads based on their textual descriptions provided by advertisers. A modified cosine similarity matching algorithm is employed to embed each ad from the Ads repository into one or more contextually-relevant segments. In order to validate our proposal, we have implemented a prototype of an ad serving system with two datasets that consist of (11429 ads and 93 documents) and (11000 documents and 15 ads), respectively. To demonstrate the effectiveness of the proposed techniques, we experimentally tested the proposed method and compared the produced results against five baseline metrics that can be used in the context of ad serving systems. In addition, we compared the results produced by our system with other state-of-the-art models. Findings demonstrate that the accuracy of conventional ad matching techniques has improved by exploiting the proposed semantically-enhanced context-based ad serving model.