Journal of the Institute of Electronics Engineers of Korea SP
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v.42
no.4
s.304
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pp.1-12
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2005
Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. This paper presents a new algorithm for robust registration of the images acquired by multiple sensors having different modalities; the EO (electro-optic) and IR(infrared) ones in the paper. The two feature-based and intensity-based approaches are usually possible for image registration. In the former selection of accurate common features is crucial for high performance, but features in the EO image are often not the same as those in the R image. Hence, this approach is inadequate to register the E0/IR images. In the latter normalized mutual Information (nHr) has been widely used as a similarity measure due to its high accuracy and robustness, and NMI-based image registration methods assume that statistical correlation between two images should be global. Unfortunately, since we find out that EO and IR images don't often satisfy this assumption, registration accuracy is not high enough to apply to some applications. In this paper, we propose a two-stage NMI-based registration method based on the analysis of statistical correlation between E0/1R images. In the first stage, for robust registration, we propose two preprocessing schemes: extraction of statistically correlated regions (ESCR) and enhancement of statistical correlation by filtering (ESCF). For each image, ESCR automatically extracts the regions that are highly correlated to the corresponding regions in the other image. And ESCF adaptively filters out each image to enhance statistical correlation between them. In the second stage, two output images are registered by using NMI-based algorithm. The proposed method provides prospective results for various E0/1R sensor image pairs in terms of accuracy, robustness, and speed.
Development of transgenic plant increasing crop yield or disease resistance is good way to solve the world food shortage. However, the persistence of marker genes in crops leads to serious public concerns about the safety of transgenic crops. In the present paper, we developed marker-free transgenic rice inserted high molecular-weight glutenin subunit (HMW-GS) gene ($D{\times}5$) from the Korean wheat cultivar 'Jokyeong' using Agrobacterium-mediated co-transformation method. Two expression cassettes comprised of separate DNA fragments containing only the $D{\times}5$ and hygromycin resistance (HPTII) genes were introduced separately into Agrobacterium tumefaciens EHA105 strain for co-infection. Each EHA105 strain harboring $D{\times}5$ or HPTII was infected into rice calli at a 3: 1 ratio of EHA105 with $D{\times}5$ gene and EHA105 with HPTII gene expressing cassette. Then, among 66 hygromycin-resistant transformants, we obtained two transgenic lines inserted with both the $D{\times}5$ and HPTII genes into the rice genome. We reconfirmed integration of the $D{\times}5$ and HPTII genes into the rice genome by Southern blot analysis. Wheat $D{\times}5$ transcripts in $T_1$ rice seeds were examined with semi-quantitative RT-PCR. Finally, the marker-free plants containing only the $D{\times}5$ gene were successfully screened at the $T_1$ generation. These results show that a co-infection system with two expression cassettes could be an efficient strategy to generate marker-free transgenic rice plants.
Korean Journal of Agricultural and Forest Meteorology
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v.16
no.3
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pp.233-245
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2014
Nighttime correction of $CO_2$ flux is one of the most important and challenging tasks in eddy covariance measurements over a complex mountainous terrain. In this study, we have scrutinized the quality and the credibility of the $CO_2$ flux datasets which were produced by employing three different methods of nighttime correction, i.e., (1) friction velocity ($u^*$) correction, (2) light response curve (LRC) correction, and (3) advection-based van Gorsel (VG) correction. The whole year datasets used in our analysis were collected at the two KoFlux tower sites (i.e., GDK deciduous forest site at the upper hill and GCK coniferous forest site at the lower hill) located in the valley of Gwangneung National Arboretum in central Korea. The resultant magnitudes and patterns of ecosystem respiration ($R_E$), gross primary productivity (GPP), and net ecosystem exchange (NEE) of $CO_2$ showed marked differences among the datasets produced with three different correction methods, which were also site-specific. The examination from micrometeorological and ecological perspectives suggests that the major cause of some inconsistency seems to be associated with the advection of $CO_2$ along the sloping terrain and the inappropriate selection of the correction data that might have been already affected by advective flows. The comparison with the results from other studies indicated that the overall characteristics of the corrected $CO_2$ fluxes at GDK and GCK (except those with LRC correction) were well within the ranges reported in the literature for various ecosystems in East Asia in similar latitudes. However, our study also implies that there will be always a room for further improvement in the present datasets. Therefore, caution must be exercised for the data users in order to properly use the updated version of datasets through transparent, open and participatory communication with data producers.
The purpose of this research was to investigate the critical issues and practical strategies that Korean technology teachers perceived. To accomplish the purpose of this study, a qualitative study was conducted to identify critical issues and practical strategies of Korean technology education targeted on Korean technology teachers. A purposeful sampling for choosing technology teachers was used for this study with three selection conditions: 1) 'Excellent Korean technology teacher' award winning teachers, or 2) technology teachers actively involved in both on-line and off-line teachers' association, and 3) leaders in local technology teachers' association. This study conducted exploratory in-depth interviews with selective 15 technology teachers regarding critical issues and practical strategies of Korean technology teachers. The interpretation of the interview content was conducted by two researchers using the thematic analysis which analyzed the frequency of concepts, words, and meanings held from collected data. In the conclusion, critical issues researchers identified were 1) curriculum problems, 2) education environment and facilities problems, 3) teachers' problems, 4) students' problems, 5) related research institution and college problems, 6) social problems. Secondly, Korean technology teachers agreed with following practical strategies 1) separating technology education from home economic education, 2) sharing practices on managing and improving educational environment and laboratory for technology education, 3) actively involving in technology teachers' group, 4) motivating students using hands-on activity 5) improving the quality and the quantity on technology teachers preparatory institution, 6) advertising the values of technology education to the public. Lastly, the positive factors to succeed technology education were 1) technology education satisfying social needs and 2) technology teachers' will or passion toward improving their technology classrooms. The negative factors to hinder technology education were 1) low self-respect of Korean technology teachers and 2) rejection or retarded acceptance toward social transition. Several recommendations based the conclusion were suggested as 1) implementing supplementary study toward selected critical issues and 2) conducting exemplary case studies regarding concrete practical strategies for improving challenges of Korean technology education.
Journal of the Korean Institute of Traditional Landscape Architecture
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v.36
no.2
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pp.21-29
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2018
This study was wanted to select a value evaluation item to maintain the authenticity of the Planting Landscape in Hahoe and Yangdong villages. Above all, after checking the suitability of the 43 selected items by the Focus Group Interview, the weight was calculated in the Analytic Hierarchy Process expert questionnaire to establish the importance of the indicators for the development of the assessment items. The expert analysis analyzed the importance of 2 sections, 6 divisions and 11 detailed categories, and summarized the results of the study as follows : First, the comparative importance of each category and selection of the assessment items for the stabilization of the Planting Landscape of Hahoe and Yangdong indicated that cultural values are more important than biological values. In particular, details of the biological values of trees were derived with relatively low estimates, except for the specific characteristics of species and items of type of tree. Second, as a result of verification of the suitability of the 43 items selected by the Focus Group Interview, the source diameter, the collection width, reception, flushing, supersonality, records, memorials, 11 items were selected, Third, the results of the importance evaluation of the value properties for maintaining the resistance of vegetation through the Analytic Hierarchy Process were : specific in biological values (0.187), steady (0.094), and water pipe width (2007). There was relatively little difference in the highest weights, the width of the pipe except for the lowest value received, and the source diameter flushing. Fourth, the results of an evaluation of the importance of a value property aimed at historical values were whether or not the cultural asset was designated (0.134), the record value (0.092), the time (0.088), and the monument (0.063). In terms of the importance of evaluating the historical values of Planting sites consisting of Hahoe and Yangdong, the importance of designation of cultural properties was considered to be relative to the maintenance of the Planting Landscape including culture and history. Based on the assessment items and weighted values of the Planting Landscape of Yangdong Village and the World Cultural Heritage below and below, this study's Analytic Hierarchy Process can be applied to actual criteria for the assessment of the authenticity of trees in the village. Based on the assessment items and weighted values of the Planting Landscape in Hahoe and Yangdong villages, a follow-up study on the assessment standards for the authenticity of trees in the village will be left as a future task.
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.
This study was carried out to evaluate the performance of sampling and analytical methodology used for the measurement of toxic volatile organic compounds (VOCs) in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis. Target analytes were 33 compounds including major aromatic compounds such as BTEX, and halogenated compounds. The methodology was investigated with a wide range of different adsorbents which are commercially available and have been frequently adopted for the VOC measurement. A total of 10 adsorbents were tested in this study: 6 carbon-based adsorbents such as Carbotrap, Carbopack B, Carbosieve S-III, Carboxen 1000, Carbotrap C, Activated Charcoal; and 4 polymer-based adsorbents including Tenax, Porapak Q, Chromosorb 102, and Chromosorb 106. The sampling performance was evaluated with respect to the sampling capacity of VOCs with single-adsorbent and multiple-adsorbents methods for standard samples and field samples. As a result, the best adsorbents for single-adsorbent method in the sampling of toxic organic compounds (including benzene, toluene, xylenes etc.) appeared to be Carbotrap, Carbopack B and Tenax TA. On the other hand, Chromosorb 102, Chromosorb 106 and Porapak Q were found to be unsuitable adsorbents for VOC measurement based on thermal desorption method. Multi-adsorbent packings were evaluated with 4 carbon-based adsorbents, which classified by 3 combination sets of double adsorbents and 2 combination sets of triple adsorbents. The results indicated that the most suitable combination for toixc VOC measurements is Carbotrap C with Carbotrap. Multi-sorbents tubes packed with a strong adsorbent such as Carbosieve S-III or Carboxen 1000 were found to be relatively unsuitable for several compounds, not only owing to the effect of migration of adsorbed compounds from weaker adsorbent to stronger adsorbent, but to hydrophobic nature of the adsorbents. Therefore, it should be addressed that selection of a proper adsorbent (or combination of multi sorbents) is extremely important to obtain reliable data for the concentrations of toxic VOCs in indoor and outdoor environments.
Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.
Jo, In-Sang;Hyun, Byung-Keun;Cho, Hyun-Jun;Jang, Yong-Seon
Korean Journal of Soil Science and Fertilizer
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v.30
no.1
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pp.56-61
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1997
A study was carried out to find out the basic information in physical properties for selection and manufacturing the good seedling media through the analysis of the physical properties, such as particle size, water retention and three phases of the major horticultural substrates. Easily available water(EAW), the water contents between 1kPa and 5kPa water potental, was highest in peatmoss with 39%, and perlite 34.0%, vermiculite 16.9%, but the values of osmunda and bark were lower than 4.8%. Water buffering capacity(WBC), the water content between 5kPa and 10kPa, was 6.1% in peatmoss and 2.3% in vermiculite but it was lower than 1.0% in other substrates. To adjust the suitable range of water potential at crossing point of water and air curves to 1.5~2.5kPa, more finer materials were needed in osmunda and bark, and more coarser materials must be added to peatmoss, perlite and vermiculite. Water potentials of substrates in saturated pot condition were equivalent to 2.2kPa in peatmoss and others were ranged in 1.0kPa to 4.3kPa of water potential in pressure chamber.
In order to get as ecological basic data for river restoration, vegetation investigation was conducted in natural river and analysed it synecological methods, such as ordination cluster. 29 plant communities units were identified and the major dominant plant communites were Quercus mongolica community, Pinus densiflora community, Populus davidiana community, Q. variabilis community and Prunus sargentii community. River vegetations were classified into ravine and gorge forest type and riverine softwood forest type. Ravine and gorge forest was dominanted by hardwood which located in steep slope and in high elevation, and riverine softwood forest by softwood, salix spp. Naturality was an important criterion for the selection of rivers, so many of the selected rivers are located in the upper stream and mid stream rather than the lower stream, where more human intervention is involved. Plant communities were consisted of hardwood forest(44 plots, 92%) and softwood forest(4 plot, 8%), respectively. PCA with total layer data showed 5 groups of communities: Q. mongolica community group, Prunus sargentii community group, Pinus densiflora community group, Prunus sargentii community - Pinus densiflora community group and the rest communities group. PCA with tree layer showed 3 groups: Q. mongolica community group, Prunus sargentii community group, and the rest community group. Cluster analysis also a showed a similar communities group to PCA ordination, but Magnolia sieboldii community and Prunus sargentii community were distinguished from the PCA result. From the result, it can be concluded that the plant communities of riparian be divided into hardwood and softwood forest by statistical techniques. It was appropriate to plant species such as Quercus mongolica, Pinus densiflora, Populus davidiana, Quercus variabilis and Prunus sargentii, at levee zone and high water level. And Sliax spp. were appropriate for planted plants at waterfront and low water level. The herb species to be planted on the floodplain were recommanded in the species composition co-occurred with the woody species.
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