• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.39-48
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• 2010

Recreation forests are in the spotlight as the place for personality development, mind and body comfort, companionship, and environment education in forests and valleys. Visitors to recreation forests have been on the increase along with booming in recreation forest building since 1988. Recreation forests are being categorized according to some features such as regional and environmental condition. Recreation forests, however, have not met the expectations of some visitors who want to take a rest with calmness due to the influence of the 5-day-work-week system, increasing interest in rest, leisure, and well-being, and users converge during weekends, summer, and the tourist season. In order to improve visitors' satisfaction efficiently, this study surveyed the level of satisfaction in each cluster based on the precedent study which had classified 85 national or public recreation forests in Korea into clusters. Questionnaires were distributed properly to each cluster and, of the 1,132 questionnaires collected, 1,015 were valid and used for analysis. Reliability of questionnaires and statistical validity of the model were verified. As a result, there are meaningful differences in the ranking of independent variables which affect the level of satisfaction according to clusters. Variables in rest and fatigue recovery have the strongest influence on the level of satisfaction in the clusters of potential factor, internal activation factor, and mixed potential capacity factor. In the use performance and visiting condition factor cluster, appropriateness of visit cost is most influential and, in the education cluster, connectivity with tourist attractions around it is most affective. These results can provide priority in services and maintenance of recreation forests for improving the level of satisfaction and differentiate the distribution of resources according to clusters.

• 대한공업교육학회지
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• v.41 no.2
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• pp.119-133
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• 2016

This study is aimed at verifying the effect of scratch programming education for middle school students on their information science creative personality and technological problem solving tendency. The results of such study can be used as basic data for raising 'future creative talents' armed with problem-solving capability they honed in software education. The results of this research are as follows. First, a statistically significant difference was confirmed between ex ante and ex post samples in a t-test which was performed to verify information science creative personality of the middle school students (t(37)=4.305, p<.01). Their information science creative personality was high in the average score as it dropped from 3.00 in the ex-ante test to 2.51 in the ex post test. It was confirmed that the education of scratch programming influences information science creative personality for middle school students positively, suggesting that middle school students are interested in new problematic situations they found in information science and discover new problem-solving methods in the programming education, thereby showing positive feedback in the education performance. However, it was revealed that the middle school students were unable to immerse themselves in the scratch programming course completely and change their psychological states. Second, a statistically significant difference was confirmed between ex ante and ex post samples in a t-test which was performed to verify their technological problem solving tendency (t(37)=3.074, p<.01). Their technological problem solving tendency was high in the average score as it dropped from 4.06 in the ex-ante test to 3.55 in the ex post test. It was confirmed that the education of scratch programming influences technological problem solving tendency for middle school students positively: they understood problems associated with technology, explored diverse breakthroughs for the identified problems and assessed and improved resolutions. Third, a moderate correlation was confirmed between their information science creative personality and technological problem solving tendency (r=.343, p<.05). Therefore, it is judged that the middle school students who took scratch programming education demonstrated its influence in the correlation between the imagination for problem solving, positivity in the information science creative personality and the confidence for problem solving in the technological problem solving tendency.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.161-170
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• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.

• The Korean Journal of Malacology
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• v.31 no.2
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• pp.73-81
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• 2015

This study was conduct to investigate the effect of intermediate culture types on the growth and survival rate of the juvenile abalone, Haliotis discus hannai fed seaweed and artificial diet. Intermediate cultures were to determine there that was to fed seaweed (SW) of artificial diet (A) of floor culture (FC), net floor culture (NFC), double shelter culture (DSC) and indoor net cage culture (INCC) in land-based tank, in two replicate. In the growth performance of juvenile abalone reared through intermediate culture to fed SW of A, that the absolute growth rate ($AGR_{SL}$, $AGR_{SB}$), daily growth rate ($DGR_{SL}$, $DGR_{SB}$), and specific growth rate ($SGR_{SL}$, $SGR_{SB}$) to the shell length (SL) and shell breadth (SB) of experimental groups were not significant. As weight gain (WG), daily weight gain (DWG) and specific weight gain (SWG) to body weight through intermediate culture types in land-based tank was not significant. However, as to survival rate to experimental groups, A-FC was higher than those of different groups (P < 0.05). Therefore, these results is showed that was not difference to growth of juvenile abalone over 2 cm fed seaweed diet and artificial diet according to intermediate culture types. But floor culture with artificial diet indicate that was highest to survival rate, therefore, it is beneficial for higher productivity in floor culture with artificial diet among intermediate culture types.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.39 no.3
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• pp.195-203
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• 2013

In this study, antioxidative effects of the extracts of different species and flowering periods of Inula britannica were investigated. According to the free radical (1,1-diphenyl-2-picrylhydrazyl, DPPH) scavenging activity of the extracts, The I. britannica var. chinensis flower extract (500 ${\mu}g/mL$) was measured in a 79.89% free radical scavenging activity, but the flower extracts of similar species (I. britannica var. linariaefolia Regel, I. britannica var. ramosa, I. salicina var. asiatica) did not show any effect on the free radical scavenging activity. The effects of the free radical scavenging activity of I. britannica var. chinensis flower extracts were exhibited in the order of full bloom (93.68%), bud (43.28%), and fallen blossom (14.11%). Next, we established optimum condition of extract solvent, temperature, extraction time. The extract from ethanol at $60^{\circ}C$ showed the most free radical scavenging activity among other conditions and extraction time not relevant in free radical scavenging activity. The protective effects of the extract of I. britannica var. chinensis flower on the photohemolysis of human erythrocytes by using rose bengal were increased in a concentration-dependent manner (5 ~ 50 ${\mu}g/mL$). In particular, the extract in 50 ${\mu}g/mL$ concentration exhibited better protective activity (${\tau}_{50}$ = 116.1 min) than (+)-${\alpha}$-tocopherol (${\tau}_{50}$ = 73.44 min), which is a known lipophilic antioxidant. Principle component of I. britannica var. chinensis flower was identified as quercetin of flavonoids by high-performance liquid chromatography (HPLC). These results indicate that the extract of I. britannica var. chinensis flower can function as antioxidants in biological systems, particularly skin exposed to UV radiation by scavenging free radical and $^1O_2$, and protect cellular membranes against ROS. It is concluded that the antioxidative effects of the extract of I. britannica var. chinensis flower could be applicable to functional cosmetics.

• Tuberculosis and Respiratory Diseases
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• v.40 no.6
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• pp.669-676
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• 1993

Background: DNA content analysis of human solid tumor is now widely performed by flow cytometric study. One of the most interesting and potentially important observation in this field is that proliferative activity(S-Phase fraction of cell cycle) may profoundly affect prognosis. Method: S-Phase fraction(SPF) have been measured by flow cytometric method using tumor cells isolated from paraffin embedded tissue. To evaluate the prognostic significance, SPF of squamous lung cancer cell was assessed in 21 patients who died without any specific treatment. Results: 1) Mean survival time of squamous lung cancer patients was 225(${\pm}162$) days. Survival time were shortened, when TNM stage and PS scale were advanced. 2) Mean value of SPF of squamous lung cancer patients was 23.4(${\pm}11.3$)%. SPF had nothing to do with advance of TNM stage and PS scale. 3) Mean survival time of high SPF group(more than 20% of cell proliferation cycle) and low SPF group were 153(${\pm}99$) days and 342(${\pm}180$) days(p<0.01). In each identical TNM stage and PS scale, there were also statistic significant differences in mean survival time between high and low SPF group. Conclusion: On multivariate analysis including TNM stage and performance status, SPF was the significant and independent prognostic factor in the primary squamous lung cancer patients group.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.233-241
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• 2016

Experiments were carried out to quantify the topographic effects on attenuation of sunshine in complex terrain and the results are expected to help convert the coarse resolution sunshine duration information provided by the Korea Meteorological Administration (KMA) into a detailed map reflecting the terrain characteristics of mountainous watershed. Hourly shaded relief images for one year, each pixel consisting of 0 to 255 brightness value, were constructed by applying techniques of shadow modeling and skyline analysis to the 3m resolution digital elevation model for an experimental watershed on the southern slope of Mt. Jiri in Korea. By using a bimetal sunshine recorder, sunshine duration was measured at three points with different terrain conditions in the watershed from May 15, 2015 to May 14, 2016. The brightness values of the 3 corresponding pixel points on the shaded relief map were extracted and regressed to the measured sunshine duration, resulting in a brightness-sunshine duration response curve for a clear day. We devised a method to calibrate this curve equation according to sky condition categorized by cloud amount and used it to derive an empirical model for estimating sunshine duration over a complex terrain. When the performance of this model was compared with a conventional scheme for estimating sunshine duration over a horizontal plane, the estimation bias was improved remarkably and the root mean square error for daily sunshine hour was 1.7hr, which is a reduction by 37% from the conventional method. In order to apply this model to a given area, the clear-sky sunshine duration of each pixel should be produced on hourly intervals first, by driving the curve equation with the hourly shaded relief image of the area. Next, the cloud effect is corrected by 3-hourly 'sky condition' of the KMA digital forecast products. Finally, daily sunshine hour can be obtained by accumulating the hourly sunshine duration. A detailed sunshine duration distribution of 3m horizontal resolution was obtained by applying this procedure to the experimental watershed.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.37-52
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• 2015

The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.