• Korean Journal of Organic Agriculture
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• v.15 no.1
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• pp.109-121
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• 2007

For developing standard method for diease, pest and weed control in environmental friendly 'Ssam' vegetable cultivation, this study was carried out to investigating agriculture material use in organic agriculture and no pesticide cultivation for lettuce, kale, leafy perilla and korean cabbage. The 28.6% of investigated farmer carried out seed sterilization by seed selection with salt solution and soaking in chitosan that not validated. For raising seedling periods, the 55.6% of farmer did not use environmental-friendly agriculture material for, diease control and the 50% of farmer used one time for. pest control. Therefore, the control of disease and pest could be achieved with one or two times use of environmental-friendly agriculture material. Seed sterilization was carried out by soil solar sterilization, one time per year in 71.4% of farmer. Weed was controled by black PE film for weed germination of furrow in many farmer, by man-power weeding for weed of ridge in 85% of farmer and by machine weeding and mulching in some farmer. During cultivation period, the major pest were Aphis gossypii in lettuce, Plutella xylostella in kale, Plutella xylostella and Phyllotreta striolata (Fabricius) in korean cabbage and Pyrausta panopealis (Walke) in feat perilla. The many farmers used environ-mental-friendly agriculture material for control of pest over 10 times for spring season, and more used sold materials in market than home-made materials. In result, it needs to develop standardized method and validate cultivation methods for control of disease and pest, and seed sterilization treatment environmental-friendly 'Ssam' vegetable.

• Horticultural Science & Technology
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• v.31 no.4
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• pp.473-482
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• 2013

Molecular markers, as an efficient selection tool, have been and is being used for practical breeding program in chili pepper (Capsicum annuum L.). Recently, a lot of researches on inheritance and genetic analysis for quantitative traits including capsaicinoids, carotenoids, and sugar content in pepper are being performed worldwide. It has been also reported that QTL mapping is a necessary tool to develop molecular markers associated with the quantitative traits. In this study, we suggested a new method to construct a pepper genetic map using SNP (HRM) markers generated from NGS resequencing of female and male parents. Plant materials were C. annuum 'NB1' (female parent), C. chinense 'Jolokia' (male parent), and their $F_2$ population consisting of 94 progenies. Sequences of 4.6 Gbp and 6.2 Gbp were obtained from NGS resequencing of 'NB1' and 'Jolokia', respectively. Totally, 4.29 million SNPs between 'NB1' and 'Jolokia' were detected and the 1.76 million SNPs were clearly identified. Among them, total 145 SNP (HRM) primer pairs covering pepper genetic map were selected, and the 116 SNP (HRM) markers of them were located on this map. Total distance of the map, which consisted of 12 linkage groups and matched with basic chromosome numbers of pepper, was 1,167.9 cM. According to the mapping result, we concluded that our mapping method was suitable to construct a pepper genetic map fast and accurately. In addition, the genetic map could be directly used for QTL analysis of traits different between both parents.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.123-126
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• 2012

This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

• Journal of Food Hygiene and Safety
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• v.27 no.3
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• pp.317-324
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• 2012

In order to determine an authenticity of food ingredient, we used DNA barcode method by universal primers. For identification of animal food ingredients, LCO1490/HCO2198 and VF2/FISH R2 designed for amplifying cytochrome c oxidase subunit1 (CO1) region and L14724/H15915 for cytochrome b (cyt b) region on mitochondrial DNA were used. Livestock (cow, pig, goat, sheep, a horse and deer) was amplified by LCO1490/HCO 2198, VF2/FISH R2 and L14724/H15915 primers. Poultry (chicken, duck, turkey and ostrich) was amplified by LCO1490/HCO 2198 and VF2/FISH R2 primers. But, Fishes (walleye pollack, herring, codfish, blue codfish, trout, tuna and rockfish) were only amplified by VF2/FISH R2 primers. For plant food ingredients, 3 types of primers (trnH/psbA, rpoB 1F/4R and rbcL 1F/724R) have been used an intergenic spacer, a RNA polymerase beta subunit and a ribulose bisphosphate carboxylase region on plastid, respectively. Garlic, onion, radish, green tea and spinach were amplified by trnH/psbA, rpoB 1F/4R and rbcL 1F/724R. The PCR product sizes were same by rpoB 1F/4R and rbcL 1F/724R but, the PCR product size using trnH/psbA primer was different with others for plants each. We established PCR condition and universal primer selection for 17 item's raw materials for foods and determine base sequences aim to PCR products in this study. This study can apply to determine an authenticity of foods through making an comparison between databases and base sequences in gene bank. Therefore, DNA barcode method using universal primers can be a useful for species identification techniques not only raw materials but also processed foods that are difficult to analyze by chemical analysis.

• Microbiology and Biotechnology Letters
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• v.38 no.3
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• pp.295-301
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• 2010

Sheath rot and dry rot disease caused by Pseudomonas marginalis and Fusarium oxysporum were serious problems in garlic farmland. In this study, total of 160 indigenous antagonistic bacteria were isolated from 16 farmlands in Yeongcheon, Korea. Among these, 15 strains were able to inhibited P. marginalis and F. oxysporum. The 16s rDNA genes of the selected 15 strains were amplified and sequenced. The strains has strong antagonistic ability against garlic pathogens was achieved Bacillus subtilis YC82, B. vallismortis YC84, B. amyloliquefaciens YC240. The selected 3 strains tested for investigation of antifungal mechanisms further analyses; 3 strains of these validated for production of siderophore, ${\beta}$-glucanase and chitinase using CAS (chrome azurol S) blue agar, CMC-congo red agar and DNS method. The 3 strains were able to utilized insoluble phosphate as dertermined by vanado-molybdate method. The 3 strains verified for production of auxin and gibberellic acid using Salkowski test and holdbrook test. Also, 3 strains showed stimulation germination, stem growth promoting activity on the in vivo test. The 3 strains were able to effectively suppress P. marginalis and F. oxysporum causing sheath rot and dry rot diseases on the in vivo pot test.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.1000-1007
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• 2005

The aim of the present study was to examine the relationship of maternal factors such as knowledge, attitude and practice of weaning with infant feeding. The subjects were 103 mothers visiting a public health center in Gumi, Kyungbook who filled out self-administered Questionnaires. First of all, about $90\%$ of the participants recognized the importance of complementary foods and proper weaning practices. The response for the recognition of the importance of infant weaning process showed a significant difference by education levels. Concerning an appropriate time for the introduction of weaning foods, $53\%$ of mothers had commenced weaning at age $4\~6$ months, while $38\%$ had done so at age $6\~8$ months. Approximately $76\%$ of mothers fed their babies without the knowledge of age-related weaning method and type of weaning foods. There were no statistical differences in maternal weaning knowledges between levels of education and house income. Mothers with higher levels of education and family income tended to show high perception scores regarding possibility of food allergies caused by baby foods. A demand for reliable sources and education related to nutritious weaning foods and weaning practices were strong in the group with higher education. Knowledge of weaning method and baby foods were obtained by 59 of the 103 mothers from mass media, 35 from friends caring babies, and 9 obtained advice from health professionals or family. Advice from the heath professionals was not the main influence on their decision to introduce weaning foods. Although commercial baby foods are the most commonly used as first weaning foods, those with higher education groups considered commercial baby food are not nutritionally better than home-maid foods. The current findings suggest to us that to improve weaning process, mothers should be educated on the selection and preparation of nutritious, balanced weaning foods and on good weaning practices. It is advised that supportive health professionals from community public health centers should lead the education of infant feeding practices based on maternal characteristics and on basic food and nutritional knowledge.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• 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.

• Korean Journal of Weed Science
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• v.7 no.1
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• pp.90-97
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• 1987

An attempt was done at the Yeongnam Crop Experiment Station in 1986-'87 to obtain herbicide tolerant variant through cell culture. Immatured rice grain was more rapidly and efficiently formed callus in dehulled rice culture method for both rice cultivar types, Tongil type (Indica/Japonica) and Japonica-type. However, Japonica-type cultivar was generally superior than Tongil-type Cultivar in callus formation. Expression rate of herbicide tolerant variant varied depending upon rice cultivar, plant species and herbicide properties. In case of Nagdongbyeo (Japonica) at the first subculture, 46.3% of total callus pieces appeared as herbicide tolerant variant in herbicide media of CGA142464 and followed by NC-311 (11.6%), Butachlor (7.5%), 2.4-D (2.1%), Quinclorac (0.89%), and Propanil (0.25%), in order. This degree of appearance of herbicide tolerant variants rapidly increased as passage of subculture was advanced. Herbicide tolerant callus hardly regenerated as normal plant even though large variations exhibited among culture media.

• The Journal of Korean society of community based occupational therapy
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• v.7 no.1
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• pp.59-70
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• 2017

Objective : The purpose of this study was to examine the effect of virtual reality-based remote rehabilitation on stroke patients systematically and to look for its effect and how to apply it domestically. Methods : In order to search data, EMBASE and CINAHL database were used. Relevant research used those terms of virtual reality, telerehabilitation, and stroke. A total of 10 studies satisfying the selection criteria was analyzed according to their qualitative level, general characteristics, and PICO method. Results : Based on the selected 10 studies, virtual reality-based telerehabilitation system was applied. Sensory and motor feedback was provided with inputting visual and auditory senses through a video in the home environment, and it stimulated changes in the client's nervous system. Tools to measure the results were upper extremity function, balance and gait, activities of daily living, etc. Those virtual reality-based telerehabilitation method had an effect on upper extremity function and ability of sense of balance in all studies, and on the activities of daily living partially. Telerehabilitation service to make up environmental specificity improved satisfaction of client. That meaned the effect of the intervention to maintain the function. Conclusion : The virtual reality-based telerehabilitation system was applied to upper extremity function, sense of balance, and activities of daily living largely, and it showed that it helped to improve functions through intervention, supervision, and training of therapist in the home environment as well. This study suggests the basis and possibility of clinical application on virtual-reality based telerehabilitation. Additional research is needed to diverse virtual reality intervention methods and the effect of telerehabilitation in the future.