• Korean Journal of Agricultural Science
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• v.46 no.3
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• pp.661-670
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• 2019

In this study, we constructed a model of an area where the production and production amount of wild vegetables which are designated as short term income forest products for the whole country are self-sufficient for the representative Eastern Braken fern(Pteridium aquilinum)and Edible aster(Aster scaber). The difference between the existing cultivation site and the model result was examined, and the distribution of the cultivable area was simulated according to the near future climate change by the 2050s. The degree of agreement between the cultivated area and the actual native area was very low at 14.5% for Eastern Braken fern and 12.9% for Edible aster. Using the Maxent model, which has already been proven by many research examples, the cultivation maps through the model can guarantee statistical accuracy by considering many variables. To analyze future location changes, the RCP 4.5 scenario and the RCP 8.5 scenario were applie Edible aster d to predict potential future cultivable areas and compare them to the present. There was no decrease in the cultivable area due to climate change nationwide. However, in the RCP 8.5 scenario for Eastern Braken fern and the RCP 4.5 scenario for Edible aster, declining areas such as Gangwon-do, Jeollabuk-do and Gyeongsangbuk-do showed prominence according to the scenarios. The result of this study suggests that various models can be used for the production of short-term forest productivity maps and it will be used as a climate change impact assessment data for competitive forest products considering the influence of future climate change.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.39-58
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• 2019

This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R²) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R², and VCI results.

• Progress in Medical Physics
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• v.3 no.1
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• pp.71-78
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• 1992

This study describes the design of the biophysiological signal processing analyzer which can collect and analyze the biosignal raw data. System hardware is consisted of the IBM PC AT. pre-amplifier. AID converter, Counter/Timer. and RS-232C processor. Biophysiological signal data were processed by the software digital filter. FFT and graphic processing routine. The tachogram and FFT of the the peak to peak interval time was accomplished by the Graphic user interface software using the biophysiological signal processed data. Using this system. the powerspectrum of the heart rate variability during the long term could be observed. Experimental results of this system approach our purpose. which is improved the cost performance. easy to use. reducing raw-data noise and optimizing model for digital filter.

• Journal of Korean Biological Nursing Science
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• v.19 no.3
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• pp.170-177
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• 2017

Purpose: This study was to identify factors influencing the quality of sleep in elderly women with urinary incontinence and examine the relationship among the factors. Methods: The study investigated 113 elderly women with urinary incontinence who were subject to the visiting care program at health centers in D-gu, D-si, South Korea. The collected data were analyzed using IBM SPSS version 19.0 along with ${\chi}^2-test$, t-test, ANOVA, Pearson's correlation, and multiple regression. Results: The total Pittsburgh Sleep Quality Index (PSQI) of the participants was found to be $11.41{\pm}4.34$. As a result of the correlation analysis, PSQI was found to have significant correlations with Female Lower Urinary Tract Symptoms (BFLUTS) (r= .32, p< .001). The Korean version of Physical Activity Scale for Elderly (K-PASE) was (r= -.34, p< .001) and the Geriatric Depression Scale Short Form (GDS-SF) was (r= .23, p= .012). Multiple regression analysis found sleeping pill use (${\beta}=-.35$, p< .001) had the strongest influence on PSQI, followed by physical activity (${\beta}=-.20$, p< .001), depression (${\beta}=.20$, p< .001), and lower urinary tract symptoms (${\beta}=.19$, p< .001). The total model explanatory power was 28.3% (F= 12.07, p< .001). Conclusion: The study findings are expected to be useful for enhanced understanding of the quality of sleep in elderly women with urinary incontinence.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.111-127
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• 2017

Computing Performance, sensor, storage, memory, and network costs have been steadily declining, and IoT services have recently become more active. The Internet of Things is linked with Big Data to create new business, and public institutions and corporations are hurry to import Internet of things. As the importance of the Internet of things has increased, the number of devices supporting the IoT has rapidly increased. With the development of the Internet of Things, various types of Internet services are being developed. For this reason, there is an increasing demand for IoT service designers and developers for IoT service case automatic search technology. IoT service designers can avoid duplication with existing services through service case retrieval and developers can save cost and time by combining existing reusable service equipment. This paper proposes IoT-Lite ontology for IoT and Semantic Web service to solve the above-mentioned problems. The existing ontologies for IoT, despite its many advantages, are not widely used by developers because it has not overcome the relatively slow drawbacks of increasing complexity and searching for development. To complement this, this study uses the IoT-Lite ontology introduced by W3C as a model and a semantic web service for automatic system retrieval. 3D camera, GPS, and 9-axis sensor, and IoT-Lite designed by IoT-Lite technique are integrated with the semantic technique and implemented directly.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.73-84
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• 2005

Highway design criteria are considering roadway safety and smooth driving maneuver. However, a certain highway alignment within design criteria often leads drivers to undesirable situation due to the differences between the original intention of design criteria and the unintended result of drivers' cognition. The differences between them often result in traffic accidents. In order to reduce accident process, highway safety facilities are installed on those roadway sections. However, the relationship between highway environments and human factors has not been deeply studied in Korea. In this study. vertical roadway sections are constructed with 3-D graphical tools. This vertical roadway sections are simulated on a driving simulator in order to identify the differences of drivers' cognition on different roadway environments. Based upon the collected data from the driving simulator, canonical correlation analysis and canonical discriminant analysis of quantification theory II have been performed in order to figure out impacting factors on the degree of roadway safety. Also, based upon quantification theory I. the relationship between roadway safety facilities and the degree of safety has been analyzed.

• Journal of Ginseng Research
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• v.31 no.3
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• pp.159-174
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• 2007

Pharmacology of Korean Red ginseng gives us unique possibility to develop new class of antiepileptic drugs today and to improve one's biological activity. The chemical structures of ginsenosides (GS) have some principal differences from well-known antiepileptic new generation drugs. The antiepileptic effect of GS was also demonstrated in all models of epilepsy in rats (young and adult), which have studied, in all models of epilepsy including status epilepticus (SE), induced by lithium - pilocarpine. In our experiments in rats new evidences on protective effects were exerted as a result of premedication by GS. Pre-treatment of several GS could induce decrease of the seizures severity and brain structural damage (by MRI), neuronal degeneration in hippocampus. Wave nature of severity of motor seizures during convulsive SE was observed during lithium-pilocarpine model of SE in rats (the first increase of seizures was 30 min after the beginning of SE and the second - 90 min after. The efficacy of treatment on SE by ginsenoside as expected was observed after no less 3 weeks by daily GS i.p. administration. It is blocked SE or significantly decrease the severity of seizures during SE. The implication of presented data is that combination of ginsenosides from Korean Red ginseng and ginseng cell culture Dan25 that could be applied for prevention of epileptical status development. However, a development of optimal ratio of different ginsenosides $(Rb_1$ Rc, Rg, Rf,) should consummate in the new antiepileptic drug development.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.237-242
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• 2023

Research on high-performance walking robots is being actively conducted, and quadruped walking robots are receiving a lot of attention due to their excellent mobility and adaptability on uneven terrain, but they are difficult to introduce and utilize due to high cost. In this paper, to increase utilization by applying intelligent functions to a low-cost quadruped robot, we present a method of improving uneven terrain overcoming ability by mounting IMU and reinforcement learning on embedded board and automatically detecting objects using camera and deep learning. The robot consists of the legs of a quadruped mammal, and each leg has three degrees of freedom. We train complex terrain in simulation environments with designed 3D model and apply it to real robot. Through the application of this research method, it was confirmed that there was no significant difference in walking ability between flat and non-flat terrain, and the behavior of performing person detection in real time under limited experimental conditions was confirmed.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.468-488
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• 2018

The maker movement is a phenomenon of society and culture where people who make necessary things come together and share knowledge and experience through creativity. However, as the maker movement has grown rapidly over the past decade, there is still a lack of consensus for how far they will be viewed as a maker movement. We need to look at how the maker movement has changed so far in order to find the direction of development of the maker movement. This study analyzes the media articles using text-based big data analysis methodology to understand how the issue of the maker movement has changed in general media. In particular, we apply Keyword Network Analysis and DTM(Dynamic Topic Model) to analyze changes of interest according to time. The Keyword Network Analysis derives major keywords at the word level in order to analyze the evolution of the maker movement, and DTM helps to identify changes in interest in different areas of the maker movement at three levels: word, topic, and document. As a result, we identified major topics such as start-ups, makerspaces, and maker education, and the major keywords have changed from 3D printer and enterprise to education.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.797-804
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• 2006

A development of regression model for asphalt concrete pavements using Falling Weight Deflectometer deflections is presented in this paper. A backcalculation program based on layered elastic theory was used to generate the synthetic modulus database, which was used to generate 95% confidence intervals of modulus in each layer. Using deflection basins of FWD data used in developing this procedure were collected from Pavement Management System in flexible pavements. Assumptions of back-calculation are that one is 3 layered flexible pavement structure and another is depth to bedrock is finite. It is found that difference of between 95% confidence intervals and modulus ranges of other papers does not exist. So, the data of 95% confidence intervals in each layer was used to develop multiple regression models. Multiple regression equations of each layer were established by SPSS, package of Statics analysis. These models were proved by regression diagnostics, which include case analysis, multi-collinearity analysis, influence diagnostics and analysis of variance. And these models have higher degree of coefficient of determination than 0.75. So this models were applied to predict modulus of domestic asphalt concrete pavement at FWD field test.