• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.39-46
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• 2018

Breeding bird surveys provide the reference information for understanding bird community structure and function in the ecosystem and conserving biodiversity. Recent rapid change of biodiversity due to climate change and other factors has made it necessary to utilize acoustic sensors for accuracy and spatial expansion of forest bird survey data and for time-series monitoring of forest birds. The objective of this study is to investigate the possibility of using acoustic recording sensor to evaluate the diversity of forest birds at breeding season by comparing and analyzing the recorded data of bird songs and field bird survey data. We conducted the site survey and recording in 186 points in 48 areas of 4 regions of Gombaeryeong and Jochimryeong around Jeombongsan Mountain and Jugryeong and Gochiryeong around Sobaeksan Mountain from May 2nd to 16th in 2013. The analysis of the correlation between the recording result and Bird Community Index based on the field survey showed that the number of bird species, population, and the number of bird songs by recording was significantly correlated to the number of species and population by field survey. Moreover, the number of bird species and the number of bird songs by recording showed a significant correlation to species diversity and species richness but no or low significant correlation to species evenness by the field study (observation and listing in parallel). As a result, it was possible to check species composition and species diversity of bird communities by analyzing acoustic recording data on the field. The acoustic recordings of bird songs in the breeding period were more reliable than the non-breeding period in the correlation of recording result and species diversity and for utilization.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.61-72
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• 2003

Recently, demands with practical applications using high resolution imagery are increasing, according to addressing new sensor data. Since late 1990s, attempts for application to transportation problems of satellite imagery data have been intensively carried out in US, and these kinds of studies are being categorized into the name of RS-T(remote sensing in transportation). Further, this study is also linked with GIS-T(GIS for transportation), being in the matured stage, and then it contributes to wide uses of remotely sensed imagery. In this study, RS-T is briefly summarized. Later, in order to apply urban transportation analysis with satellite imagery as ancillary data, implementation, as prototyped extension program, for extraction of gravity-typed accessibility indices of transportation geography is performed in the ArcView-GIS environment. It is thought that applied results by two models among implemented models in this study can be utilized to characterize transportation accessibility in a region and to apply as useful statistics related to urban transportation status for regional transportation planning, if time series data are used.

• Child Health Nursing Research
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• v.7 no.1
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• pp.21-34
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• 2001

The impact of childhood experience has lifelong significance on subsequent health and development. Especially, the experience of infant is mostly affected by the quality of parental care and rearing environment. But the new mothers usually do not know what to do because of the lack of experience in these days. Therefore, an educational program regarding maternal role would be necessary. This study was conducted to evaluate the effectiveness of the maternal role education program for mother-infant interaction, child-rearing environment, and infant development. Non-equivalent control group time-series design was used, and Barnard's mother-infant interaction model was used as a conceptual framework of this study. The subjects were the healthy infants weighing over 2,500gm at birth, whose gestational age was more than 37 weeks, and their mothers. The final sample consisted of 19 mother-infant dyads for intervention group and 18 dyads for control group. Data were collected from March 15th to September 3rd in 1999. For the intervention group, programmed education which focused on mother-infant interaction, breast feeding, and infant care was provided before discharge. Telephone counselling was provided within one week after discharge. Home visiting for maternal role education was provided twice, one month and three months postpartum. For the control group, home visiting was also conducted but only for data collection. The data were analyzed using chi-square test and t-test to test the equivalence of two groups, and the effectiveness of intervention program was determined with repeated measure ANCOVA and t-test. The results were as follows: 1. Significant differences were found in mother-infant interaction between two groups(p=.000). It indicates that intervention program was effective in improving mother- infant interaction. In subscale analysis, four out of six subscale showed significant differences between the groups: sensitivity to cues (p=.000), social-emotional growth fostering (p=.000), cognitive growth fostering(p=.000) in mothers, and responsiveness to caregiver (p=.019) in infants. 2. The difference in the mean score of childrearing environment (HOME) between the intervention group and control group was significant(p=.003). When each subscale of HOME was examined individually, intervention group showed significantly higher scores in the diversity of stimulation(p=.000), and mother's involvement(p=.001). 3. Three-month-Infants of the intervention group showed higher GQ in the Griffiths mental development scale(p=.026). In subscale analysis, significant differences were found in the personal-social(p=.005), and the hearing and speech(p=.003). In conclusion, the maternal role education program proved to be effective in promoting the mother-infant interaction, organizing the childrearing environment, and fostering the infant development. These results are very meaningful that we found maternal role education necessary for normal infants' mothers, and that nurses can make a great contribution in promoting health of infants and mothers.

• Management & Information Systems Review
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• v.36 no.3
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• pp.185-202
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• 2017

This study suggests the estimation of the demand for the exhibition center in Busan and to valid reasons for the establishment of the 2nd Convention Center in Busan. The validity for the estimated demand is acquired by examining the studies conducted by the Ministry of Commerce Industry and Energy. The qualitative data for the phased establishment of the area is suggested in accordance to the results of the demand estimation. From previous study(Oh, 2017), Kangseo-gu, Busan has been evaluated to be the final candidate for building a new convention center in the city of Busan. The potential synergy effects of on-going developmental projects in Kangseo region is one of the influential factors for the MICE professionals' opinion in the qualitative analysis. Moreover, the region has available land to hold the facility of more than 100,000 square meter to overcome the current drawback of BEXCO, insufficient space to hold large events. Lastly, the expansion of Gimhae International Airport would bring an increased international flights that would also lead to an increase in MICE industry for the region. The virtual effect of the more than one million $m^2$-sized oconvention center is examined via Huff Model and the results suggests a logical estimated data for further demand needed for the south east regions, not just within the city of Busan.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.63-87
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• 2010

The purpose of this paper is to measure the efficiency of Korean container terminals by using SFA(Stochastic Frontier Analysis). Inputs[Number of Employee, Quay Length, Container Terminal Area, Number of Gantry Crane], and output[TEU] are used for 3 years(2002,2003, and 2004) for 8 Korean container terminals by applying both SFA and DEA models. Empirical main results are as follows: First, Null hypothesis that technical inefficiency is not existed is rejected and in the trasnslog model, the estimate is significant. Second, time-series models show the significant results. Third, average technical efficiency of Korean container terminals are 73.49% in Cobb-Douglas model, and 79.04% in translog model. Fourth, to enhance the technical efficiency, Korean container terminals should increase the handling amount of TEUs. Fifth, both SFA and DEA models have the high Spearman ranking of correlation coefficients(84.45%). The main policy implication based on the findings of this study is that the manager of port investment and management of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the SFA with DEA models for measuring the efficiency of Korean ports and terminals.

• Journal of Korea Water Resources Association
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• v.48 no.9
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• pp.729-741
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• 2015

This study examined the applicability of MBLRP (Modified Bartlett-Lewis Rectangular Pulse) rainfall generation model for an urban flood simulation which is a type of Poisson cluster rainfall generation model. This study constructed XP-SWMM model for Namgajwa area of Hongjecheon basin, which is a two-dimensional pipe network-surface flood simulation program and computed a flood discharge and a flooded area with input data of synthetic rainfall time series of 200 years that were generated by the MBLRP model. This study compared the data of flood with synthetic rainfall and flood with corresponding values which were based on design rainfall. The results showed that the flooded area computed with MBLRP model was somewhat smaller than the corresponding values on the basis of the design. A degree of underestimation was from 8% (5 year) to 34% (200 year) and the degree of underestimation increased as a return period increased. This study is meaningful in that it proposes methodology that enables quantifiability of uncertain variables which are related to a flooding through Monte Carlo analysis of urban flooding simulation and applicability and limitations thereof.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.457-469
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• 2016

Nakdong river barrage was affected by artificial interference such as construction of port, industrial complex and estuary barrage. This change in Nadong river lead to environmental changes and affected the ability of barrier islands. Therefore, it is decided that the observation of changes in the Nakdong river estuary is very important. In this paper, the topographic change of the Nakdong river barrage observe based on Landsat TM, ETM+ images from 1984 to 2015. In addition, this study tried to conduct a comparative analysis on the area for change of sandy sediment according to tide level. This results could estimate height and volume about sandy sediment accumulated on the lower sand dune. Also, these results are expected to be the basis for prediction of the changing topography of the sand dune. The area of the average change in region 1,2,3 was calculated as 3,015m², 167,550m², 14,596m². This result is expected to be very useful for the continuous observation for sediment changes of Nakdong river.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.733-742
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to this reason, memory usage for data stream analysis should be confined finitely although new data elements are continuously generated in a data stream. To satisfy this requirement, data stream processing sacrifices the correctness of its analysis result by allowing some errors. The old distribution statistics are diminished by a predefined decay rate as time goes by, so that the effect of the obsolete information on the current result of clustering can be eliminated without maintaining any data element physically. This paper proposes a grid based clustering algorithm for a data stream. Given a set of initial grid cells, the dense range of a grid cell is recursively partitioned into a smaller cell based on the distribution statistics of data elements by a top down manner until the smallest cell, called a unit cell, is identified. Since only the distribution statistics of data elements are maintained by dynamically partitioned grid cells, the clusters of a data stream can be effectively found without maintaining the data elements physically. Furthermore, the memory usage of the proposed algorithm is adjusted adaptively to the size of confined memory space by flexibly resizing the size of a unit cell. As a result, the confined memory space can be fully utilized to generate the result of clustering as accurately as possible. The proposed algorithm is analyzed by a series of experiments to identify its various characteristics