• 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.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.1-23
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• 2009

The Survey on the Industrial Research and Development(R&D) is the primary source of information on R&D performed by Korea industrial sector. The results of the survey are used to assess trends in R&D expenditures. Government agencies, corporations, and research organizations use the data to investigate productivity determinants, formulate tax policy, and compare individual company performance with industry averages. Recently, Korea Industrial Technology Association(KOITA) has collected the data by complete enumeration. Koita has, currently, considered sample survey because the number of R&D institutions in industry has been dramatically increased. This study develops survey design for the industrial research and development(R&D) statistics by introducing a sample survey. Companies are divided into 8 groups according to the amount of R&D expenditures and firm size or type. We collect the sample from 24 or 8 sampling strata and compare the results with those of complete enumeration survey. The estimates from 24 sampling strata are not significantly different to the results of complete enumeration survey. We propose the survey design as follows: Companies are divided into 11 groups including the companies of which R&D expenditures are unknown. All large companies are included in the survey and medium and small companies are sampled from 70% and 3%. Simple random sampling (SRS) is applied to the small company partition since they show uniform distribution in R&D expenditures. The independent probability proportionate to size (PPS) sampling procedure may be applied to those companies identified as 'not R&D performers'. When respondents do not provide the requested information, estimates for the missing data are made using imputation algorithms. In the future study, new key variables should be developed in survey questionnaires.

• Korean Journal of Veterinary Research
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• v.25 no.1
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• pp.7-17
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• 1985

Many investigators have been pursuing various attempts so far to produce hepatitis B surface antigen(HBsAg) vaccines using the techniques such as isolation from plasma of chronic HBsAg carrier, recombinant DNA technique or preparation of synthetic peptides specific for immunogenic determinants. Hepatitis B virus can not grow on any cell lines by the tissue culture technique at the present time. The plasma of chronic HBsAg carrier is expensive and its source is limited. The HBsAg from the recombinant DNA technique gave still very low yield. Another approach, therefore, has been initiated to develop a synthetic hepatitis B virus vaccine. The possible use of several distinct synthetic vaccines in prophylaxis can be facilitated by availability of full synthetic immunogens. Peptides synthesized for potential application as antiviral vaccines have been mostly tested in the form of conjugates with carrier proteins, although the free synthetic peptide can be immunogenic. To understand basic knowledges on the antigenicity and immunogenicity of a synthetic peptide specific for major immunogenic determinant of HBsAg, a nonapeptide, $H_2N^{139}Cys-Thr-Lys-Pro-Thr-Asp-Gly-^{146}Asn-Aba$ COOH, which corresponds to HBsAg amino acid residues 139 to 147, was synthesized by the Merrifield's solid-phase method with a slight modification. The antigenicity and immunogenicity of this specific synthetic peptide were examined comparing with purified plasma-derived natural HBsAg. The results obtained are as follows; 1. The peptide synthesized showed the identical amino acid composition to the theoretical value. The degree of purification and molecular weight were acertained by methods of high performance liquid chromatography and mass spectrometry. 2. Using m-maleimidobenzoyl-N-hydroxysuccinimide ester as a conjugating agent, the synthetic peptide was conjugated to rabbit albumin and ${\gamma}$-globulin, tetanus and diphtheria toxoids, and keyhole limpet hemocyanin. Their conjugation yields were 8.3, 9.5, 15.8, 13.5, and 11.2%, respectively. 3. The natural HBsAg was purified from plasma of chronic HBsAg carrier. By the electron microscopic observation of the purified natural HBsAg preparation, no Dane particles were observed and the preparation showed negative DNA polymerase activity. 4. Antigenicity of the synthetic peptide and the plasma-derived natural HBsAg was determined by competition radioimmunoassay using $^{125}I$-natural HBsAg. Their 50% inhibitions appeared as $90{\mu}g/ml$ and $0.12{\mu}g/ml$ for the synthetic peptide and the natural HBsAg, respectively. This indicates that the former was about 750-fold less antigenic than the latter. 5. Immunogenicity of the synthetic peptide was determined by administering the peptide-carrier conjugates into rabbits with and without Freund's complete adjuvant. Regardless the carrier proteins and adjuvant, positive immune responses to the synthetic peptide were observed. The higher antibody titers, however, were shown in the groups administered with Freund's complete adjuvant. 6. Immunizing dose 50% in mice of the various peptide-carrier conjugates was 5.47, 6.00, 65.16, 31.25 and $13.03{\mu}g/dose$ for rabbit albumin and ${\gamma}$-globulin, tetanus and diphtheria toxoids, and keyhole limpet hemocyanin, respectively, while the natural HBsAg showed $0.65{\mu}g/dose$. 7. It was postulated that homologous proteins prefer to heterologous ones as the carriers.