• The Korean Journal of Community Living Science
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• v.27 no.spc
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• pp.681-688
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• 2016

This study examined the effective uses of an ecosystem service value assessment in the fields of rural planning and development through archiving and reviewing/analyzing existing concepts, evaluation methods and prior examples of Ecosystem services. Based on land cover analysis, this study evaluated the usability changes in the ecosystem service value for a period spanning 1975 to 2000. The results from the countrywide data survey (with an exception of Jeju island) showed a 33.15% decrease in ESV by 2000. The total ESV represented 5,385 million USD in 1975, and 3,600 million USD in 2000 of the study area. In addition, the ecosystem service value with a scale of metro cities and provinces was also examined. The ESV of most regions decreased by 2000, but Daejeon and Kyeongnam, and Kyeongbuk provinces increased. The trends of year to year changes in the ESV were very diverse throughout the country. Jeonnam showed the smallest decrease, 747 million USD, which is 59% of the ESV in 1975. Nevertheless, the despite the regional differences in available natural resources, the natural resource assets value is ultimately determined by rural development policies and regional economic attributes. Therefore, an ecosystem service must be considered as an important criterion for rural planning and development policy.

• Journal of the Korean earth science society
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• v.33 no.4
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• pp.309-319
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• 2012

In order to clarify the characteristics of satellite based sea wind data assimilations applied for the estimation of wind resources around the Korean peninsula, several numerical experiments were carried out using WRF. Satellite sea wind data used in this study are QuikSCAT from NASA and ASCAT from ESA. When the wind resources are estimated with data assimilation, its estimation accuracy is improved clearly. Since the band width is broad for QuikSCAT, statistical accuracy of the estimated wind resources with QuikSCAT assimilations is better than that with ASCAT assimilations. But the wind estimated around sub-satellite point matches better with of ASCAT compared to QuikSCAT assimilation. The impact of sea wind data assimilation on the prediction of wind resources lasts for 6 hours after data assimilation starts, therefore the data assimilation processes using both fine spatial and temporal resolutions of sea wind are needed to make a more useful wind resource map of the Korean Peninsula.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.587-594
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• 2005

In the paper, after we propose a viterbi decoder which has multiple buffering and parallel processing decoding scheme through expanding time-divided imput signal, and map a FPGA, we implement a channel coding system together with PC-based software. Continuous input signal is buffered as order of decoding length and is parallel decoded using a high speed cell for viterbi decoding. Output data rate increases linearly with the cell formed the viterbi decoder, and flexible operation can be satisfied by programming controller and modifying input buffer. The tell for viterbi decoder consists of HD block for calculating hamming distance, CM block for calculating value in each state, TB block for trace-back operation, and LIFO. The implemented cell of viterbi decoder used 351 LAB(Logic Arrary Block) and stably operated in maximum 139MHz in APEX20KC EP20K600CB652-7 FPGA of ALTERA. The whole viterbi decoder including viterbi decoding cells, input/output buffers, and a controller occupied the hardware resource of $23\%$ and has the output data rate of 1Gbps.

• Korean Journal of Pharmacognosy
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• v.46 no.1
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• pp.52-58
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• 2015

Neural stem cells (NSCs), with self-renewal and neuronal differentiation capacity, are a feasible resource in cell-based therapies for various neurodegenerative diseases and neural tissue injuries. In this study, we investigated the effects of Schisandrae Fructus (SF) on proliferation and differentiation of human embryonic NSCs. Treatment with 70% ethanol extract of SF increased the viability of NSCs derived from human embryonic stem cells, which was accompanied by increased mRNA expression of cyclin D1. Whereas 70% ethanol extract of SF also decreased the mRNA expression of nestin, it increased class III ${\beta}$-tublin (Tuj-1) and MAP2 in both growth and differentiation media. Lastly, we found increased mRNA expression of BDNF in SF-treated NSCs. In conclusion, our study demonstrates for the first time that SF induced proliferation and neuronal differentiation of NSCs and increased mRNA expression of BDNF, suggesting its potential as a regulator of NSC fate in NSC-based therapy for neuronal injuries from various diseases.

• Journal of Korean society of Dental Hygiene
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• v.15 no.6
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• pp.1053-1061
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• 2015

Objectives: The purpose of the study is to investigate the influencing factors of community scaling rate using community health survey data. Methods: The data were extracted from 2013 Community Health Survey, Ministry of education, Korea Dental Association, Statistics Korea, Health Insurance Review and Assessment Service, and Ministry of the Interior. The resource factors of independent variables were analysed by Geographical Information System(GIS) using Map Wizard for Excel 17.0. The data were analyzed by descriptive analysis, pearson correlation and multiple linear regression analysis(p<0.05). Results: Seocho-gu in Seoul had the highest annual scaling rate(55.5%) and Goheung-gun had the lowest rate(11%) showing 44.5 percent gap. The influencing factors of scaling included the number of dental hygienists(r=0.316), dentists(r=0.332), dental hospitals(r=0.470), high school graduation rate(r=0.757) and equivalence scales household income(r=0.764)(p<0.05). Multiple linear regression analysis showed that community scaling rate was closely associated with community education level and monthly income(p<0.05). Conclusions: Community scaling rate was closely related to the community education and income level. It is necessary to provide the equal distribution of the oral health service to the community society.

• Genomics & Informatics
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• v.7 no.2
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• pp.65-84
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• 2009

Sequences from the clones of full-length enriched cDNA libraries serve as valuable resources for functional genomics related studies, genome annotation and SNP discovery. We analyzed 7,392 high-quality chromatograms (Phred value ${\geq}$30) obtained from sequencing the 5' ends of clones derived from full-length enriched cDNA libraries of Korean native pigs including brainstem, liver, cerebellum, neocortex and spleen libraries. In addition, 50,000 EST sequence trace files obtained from GenBank were combined with our sequences to identify cSNPs in silico. The process generated 11,324 contigs, of which 2,895 contigs contained at least one SNP and among them 610 contigs had a minimum of one sequence from Korean native pigs. Of 610 contigs, we randomly selected 262 contigs and performed in silico analysis for the identification of cSNPs. From the results, we identified 1,531 putative coding single nucleotide polymorphisms (cSNPs) and the SNP detection frequency was one SNP per 465 bp. A large-scale sequencing result of clones from full-length enriched cDNA libraries and identified cSNPs will serve as a useful resource to functional genomics related projects such as a pig HapMap project in the near future.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.83-89
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• 2012

Natural Vegetation cover, which is very important earth resource, has been significantly altered by humans in some manner. Since this has currently resulted in a significant effect on global climate, various studies on vegetation environment including forest have been performed and the results are utilized in policy decision making. Remotely sensed data can detect, identify and map vegetation cover change based on the analysis of spectral characteristics and thus are vigorously utilized for monitoring vegetation resources. Among various vegetation indices extracted from spectral reponses of remotely sensed data, NDVI is the most popular index which provides a measure of how much photosynthetically active vegetation is present in the scene. In this study, for change detection in vegetation cover, a Multi-layer Perceptron Network (MLPN) as a nonparametric approach has been designed and applied to MODIS/Aqua vegetation indices 16-day L3 global 250m SIN Grid(v005) (MYD13Q1) data. The feature vector for change detection is constructed with the direct NDVI diffenrence at a pixel as well as the differences in some subset of NDVI series data. The research covered 5 years (2006-20110) over Korean peninsular.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• Journal of the Korean Solar Energy Society
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• v.31 no.6
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• pp.8-22
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• 2011

Investigations on modeling methods of a CFD wind resource prediction program, WindSim for a ccurate predictions of wind speeds were performed with the field measurements. Meteorological Masts having heights of 40m and 50m were installed at two different sites in complex terrain. The wind speeds and direction were monitored from sensors installed on the masts and recorded for one year. Modeling parameters of WindSim input variables for accurate predictions of wind speeds were investigated by performing cross predictions of wind speeds at the masts using the measured data. Four parameters that most affect the wind speed prediction in WindSim including the size of a topographical map, cell sizes in x and y direction, height distribution factors, and the roughness lengths were studied to find out more suitable input parameters for better wind speed predictions. The parameters were then applied to WindSim to predict the wind speed of another location in complex terrain in Korea for validation. The predicted annual wind speeds were compared with the averaged measured data for one year from meteorological masts installed for this study, and the errors were within 6.9%. The results of the proposed practical study are believed to be very useful to give guidelines to wind engineers for more accurate prediction results and time-saving in predicting wind speed of complex terrain that will be used to predict annual energy production of a virtual wind farm in complex terrain.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.41-50
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• 2008

Recent progress in state-of-the-art geospatial information technologies such as digital mapping, LiDAR(Light Detection And Ranging), and high-resolution satellite imagery provides various data sources fer Digital Elevation Model(DEM). DEMs are major source to extract elements of the hydrological terrain property that are necessary for efficient watershed management. Especially, watersheds extracted from DEM are important geospatial database to identify physical boundaries that are utilized in water resource management plan including water environmental survey, pollutant investigation, polluted/wasteload/pollution load allocation estimation, and water quality modeling. Most of the previous studies related with watershed extraction using DEM are mainly focused on the hydrological elements analysis and preprocessing without considering grid size of the DEMs. This study aims to analyze accuracy of the watersheds extracted from DEMs with various grid sizes generated by LiDAR data and digital map, and appropriate preprocessing methods.