• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.3
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• pp.388-392
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• 1997

The random amplified polymorphic DNAs (RAPD) technique was used to characterize seven isolates of the green seaweed Ulvales collected from Songjeng, Haeundae, Jumunjin, Dadaepo and Wando in Korea. Total DNA was extracted by the LiCl extraction method from thalli of green seaweed. The extracted DNA (3 ng) in $25{\mu}\ell$ reaction volume was amplified by 45 cycles of the polymerase chain reaction with arbitrary primers. Thirty-four primers resulted in 1227 PCR products ranged 240 bp to 1.5 kb of both conserved and polymorphic bands. Genetic similarities of the seven isolates calculated by Jaccard's equation were ranged from $7\%\;to\;36\%$. Monostroma nitidum (Wando) was shown to be most distantly related with the others based on genetic similarity and did not produce the amplified band of 630 bp, common in Ulvales using primer OPB-01 (CATCCCCTG).

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.123-134
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• 2002

The requirement for QoS (Quality of Service) has become an important Issue as real-time or high bandwidth services are increasing, such as Internet Telephony, Internet broadcasting, and multimedia service etc. In order to guarantee the QoS of Internet application services, several approaches are being sought including IntServ (Integrated Service) DiffServ(Differentiated Srvices), and MPLS(Multi-Protocol Label Switching). In this paper, we describe the performance analysis of QoS guarantee mechanism using the DiffServ. To analyze how the DiffServ performance was affected by diverse input traffic models and the weight value in WFQ(Weighted Fair Queueing), we simulated and performed performance evaluation under a random, bursty, and self-similar input traffic models and for diverse input parameters. leased on the results of performance analysis, it was confirmed that significant difference exist in packet delay and loss depending on the input traffic models used. However, it was revealed that QoS guarantee is possible to the EF (expedited Forwarding) class and the service separation between RF and BE (Best Effort) classes may also be achieved. Next, we discussed the performance synthesis problem. (i. e. derived the conservation laws for a DiffServ networks, and analysed the performance variation and dynamic behavior based on the resource allocation (i.e., weight value) in WFQ.

• Journal of the Korean association of regional geographers
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• v.3 no.1
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• pp.35-50
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• 1997

The purpose of this research seeks to analyze the spatial variations in the sex age structure which have been shown to exist within the study atrea, the Kyonggi province in Korea. In this study it is desired to use the Age Structure Index developed by Coulson in order to describe thi sex age structure of each of 186 tracts that comprise the tracted portion of the Kyonggi province. The mechanics of computing the Age Structure Index are found in the equation describing a linear least squares trend line: y=a+bx. For each census tract, the percentage of the population in each age group(y) was plotted against the middle age of each age group(x). The a is a constant representing the value of y, when x equals zero. The b is the regression coefficient and is a measure of the angle of the slope of the least squares trend line. Thus the value of b is the Age Structure Index for each census tract. The major results of this investigation can be summarized as follows: The spatial distributions of sex age structures in the Kyonggi province are far from random. They have exhibited great regularity with the yonger sex age structures near Seoul and a sharp decline to the older sex age structures out in all derections towards rural region. The results of this investigation should have important general significance for the study of the Kyonggi province Age Structure Index is a flexible, operational definition shich allows sex age structure to be measured, mapped, and incorporated in a wide variety of methods of statistical analysis. Futurer, it has been demonstrated that sex age structure varies spatially within Seoul metropolitan finge and that this variation is relagfed to many other attributes of the population. Especially, Age Structure Index is strongly related to the variables-rate of population growth rate. density, rate of numbers of manufacturing, land price. At the same time, considerably more research is needed before a genmeral body of knowlege concerning sex age structure can be developed.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.1-8
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• 2006

The objective of this study is to assess impacts of sorption heterogeneity on the transport of leachate leaked from unlined landfill sites and is accomplished by examining the results from a series of Monte-Carlo simulations. For random distribution coefficient ($K_{d}$) fields with four different levels of heterogeneity ranging from homogeneous to highly heterogeneous, the transport of leachate was investigated by linking a saturated flow model with a contaminant transport model. Impacts of a chemical heterogeneity were evaluated using point statistics values such as mean, standard deviation, and coefficient of variation of the concentration obtained at monitoring wells from 100 Monte-Carlo trials. Inspection of point statistics shows that the distribution of distribution coefficient in the landfill site proves to be an important parameter in controlling leachate concentrations. In comparison to homogeneous sorption, heterogeneous $K_{d^-}$ fields produce the variability in the leachate concentration for different realizations. The variability increases significantly as the variance in the $K_{d^-}$ field and the travel time between source and monitoring well increase. These outcomes indicate that use of a constant homogeneous $K_{d}$ value for predicting the transport of leachate can result in significant error, especially when variability in $K_{d}$ is high.

• Korean Journal of Optics and Photonics
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• v.2 no.3
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• pp.139-148
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• 1991

A fiber-optic magnetic sensor system for the detection of small ac magnetic field(200Hz-2 kHz) was constructed. Magnetic field sensing part was fabricated by bonding a section of optical fiber to amorphous metallic glass(2605SC) having large magnetostriction effect. And with the directional coupler, all fiber type Mach-Zehnder interferometer was constructed to measure the variation of the external magnetic field by translating it into the optical phase shift in the interferometer. The signal fading problem of the interferometer, which is due to random phase drifts originated from the environment, i.e., temperature fluctuation, vibrations, etc., was elliminated by feedback phase compensation. This allows the sensitivity to be maintained at the maximum by keeping the interferometer in quadrature phase condition. The frequency response of metallic glass was found to be nearly flat in the range of 90 Hz-2 kHz and dc bias field for the maximum ac response was 3.5 Oe. The interferometer output showed good linearity over the range $\pm$0.5 Oe. For 1 kHz ac magnetic field the scale factor S and the minimum detectable magnetic field were measured to be 8.0 rad/Oe and $3X10^{-6} Oe/\sqrt{Hz}$at 1 Hz detection bandwidth respectively.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.197-206
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• 2004

In ranking data, respondents are required to rank a number of alternatives in order of their preferences and an exploded logit model is generally used. It assumes that each rank contains the same amount of random noise. This study investigates the reliability of ranking data and identifies whether there are different decision rules at each rank stage. The results show that there were differences in the amount of unexplained variation in different ranking stage. A single scaling parameter could not explain the difference of variations of individual coefficients between two ranking data average difference of variations. This paper also investigated the optimal explosion depth in the exploded logit model by using the suggested scaling approach. The scaling approach should be based on particular variables which have different variances rather than based on the whole data set. The empirical analysis show that an explosion depth of 2 is appropriate after scaling the second rank data set, while an explosion including the third rank is inappropriate even though the third rank data set is scaled.

• Journal of Preventive Medicine and Public Health
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• v.26 no.2 s.42
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• pp.293-309
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• 1993

With expanded and extended coverage of the national medical insurance and fast growing health care expenditures, appropriateness of health service utilization and quality of care are concerns of both health care providers and insurers as well as patients. An accurate patient classification system is a basic tool for effective health care policies and efficient health services management. A classification system applicable to Korean medical information-Korean Diagnosis Related Groups (K-DRGs)-was developed based on the U.S. Refined DRGs, and the performance of the developed system was assessed in this study. In the process of the development, first the Korean coding systems for diagnoses and procedures were converted to the systems used in the definition of the U.S. Refined DRGs using the mapping tables formulated by physician panels. Then physician panels reviewed the group definition, and identified medical practice patterns different in two countries. The definition was modified for the differences in K-DRGs. The process resulted in 1,199 groups in the system. Several groups in Refined DRGs could not be differentiated in K-DRGs due to insufficient medical information, and several groups could not be defined due to procedures which were not practiced in Korea. However, the classification structure of Refined DRGs was retained in K-DRGs. The developed system was evaluated fur its performance in explaining variations in resource use as measured by charges and length of stay(LOS), for both all and non-extreme discharges. The data base used in this evaluation included 373,322 discharges which was a random sample of discharges reviewed and payed by the medical insurance during the five-month period from September 1990. The proportion of variance in resource use which was reduced by classifying patients into K-DRGs-r-square-was comparable to the performance of the U.S. Refined DRGs: .39 for charges and .25 for LOS for all discharges, and .53 for charges and .31 for LOS for non-extreme discharges. Another measure analyzed to assess the performance was the coefficient of variation of charges within individual K-DRGs. A total of 966 K-DRGs (87.7%) showed a coefficient below 100%, and the highest coefficient among K-DRGs with more than 30 discharges was 159%.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.395-432
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• 2021

Groundwater recharge rates vary widely by location and with time. They are difficult to measure directly and are thus often estimated using simulations. This study employed frequency and regression analysis and a classification and regression tree (CART) algorithm in a machine learning method to estimate groundwater recharge. CART algorithms are considered for the distribution of precipitation by subbasin (PCP), geomorphological data, indices of the relationship between vegetation and landuse, and soil type. The considered geomorphological data were digital elevaion model (DEM), surface slope (SLOP), surface aspect (ASPT), and indices were the perpendicular vegetation index (PVI), normalized difference vegetation index (NDVI), normalized difference tillage index (NDTI), normalized difference residue index (NDRI). The spatio-temperal distribution of groundwater recharge in the SWAT-MOD-FLOW program, was classified as group 4, run in R, sampled for random and a model trained its groundwater recharge was predicted by CART condidering modified PVI, NDVI, NDTI, NDRI, PCP, and geomorphological data. To assess inter-rater reliability for group 4 groundwater recharge, the Kappa coefficient and overall accuracy and confusion matrix using K-fold cross-validation were calculated. The model obtained a Kappa coefficient of 0.3-0.6 and an overall accuracy of 0.5-0.7, indicating that the proposed model for estimating groundwater recharge with respect to soil type and vegetation cover is quite reliable.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.155-164
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• 2021

Many studies have been conducted on developing automatic plant identification algorithms using machine learning to various plant features, such as leaves and flowers. Unlike other plant characteristics, barks show only little change regardless of the season and are maintained for a long period. Nevertheless, barks show a complex shape with a large variation depending on the environment, and there are insufficient materials that can be utilized to train algorithms. Here, in addition to the previously published bark image dataset, BarkNet v.1.0, images of barks were collected, and a dataset consisting of 53 tree species that can be easily observed in Korea was presented. A convolutional neural network (CNN) was trained and tested on the dataset, and the factors that interfere with the model's performance were identified. For CNN architecture, VGG-16 and 19 were utilized. As a result, VGG-16 achieved 90.41% and VGG-19 achieved 92.62% accuracy. When tested on new tree images that do not exist in the original dataset but belong to the same genus or family, it was confirmed that more than 80% of cases were successfully identified as the same genus or family. Meanwhile, it was found that the model tended to misclassify when there were distracting features in the image, including leaves, mosses, and knots. In these cases, we propose that random cropping and classification by majority votes are valid for improving possible errors in training and inferences.