• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.135-147
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• 2003

This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.

• Journal of the Korean Chemical Society
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• v.65 no.4
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• pp.254-259
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• 2021

The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R², and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918-18.055, 9.014-23.825, and 9.040-13.350 mg/g of dry sample, respectively.

• Education of Primary School Mathematics
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• v.22 no.1
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• pp.1-12
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• 2019

This study examined the attention and attention shift of general students and mathematically gifted students about pattern by the types of mathematical patterns. For this purpose, we analyzed eye movements during the problem solving process of 5th general and mathematically gifted students using eye tracker. The results were as follows: first, there was no significant difference in attentional style between the two groups. Second, there was no significant difference in attention according to the generation method between the two groups. The diversion was more frequent in the incremental strain generation method in both groups. Third, general students focused more on the comparison between non-contiguous terms in both attributes. Unlike general students, mathematically gifted students showed more diversion from geometric attributes. In order to effectively guide the various types of mathematical patterns, we must consider the distinction between attention and attention shift between the two groups.

• Animal Bioscience
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• v.34 no.12
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• pp.1895-1902
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• 2021

Objective: Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that can reveal inbreeding levels, selection pressure, and mating schemes. In this study, ROHs were evaluated in Wannan Black pigs to assess the inbreeding levels and the genome regions with high ROH frequency. Methods: In a previous study, we obtained 501.52 GB of raw data from resequencing (10×) of the genome and identified 21,316,754 single-nucleotide variants in 20 Wannan Black pig samples. We investigated the number, length, and frequency of ROH using resequencing data to characterize the homozygosity in Wannan Black pigs and identified genomic regions with high ROH frequencies. Results: In this work, 1,813 ROHs (837 ROHs in 100 to 500 kb, 449 ROHs in 500 to 1,000 kb, 527 ROHs in >1,000 kb) were identified in all samples, and the average genomic inbreeding coefficient (F_ROH) in Wannan Black pigs was 0.5234. Sixty-one regions on chromosomes 2, 3, 7, 8, 13, 15, and 16 harbored ROH islands. In total, 105 genes were identified in 42 ROH islands, among which some genes were related to production traits. Conclusion: This is the first study to identify ROH across the genome of Wannan Black pigs, the Chinese native breed of the Anhui province. Overall, Wannan Black pigs have high levels of inbreeding due to the influence of ancient and recent inbreeding due to the genome. These findings are a reliable resource for future studies and contribute to save and use the germplasm resources of Wannan Black pigs.

• Journal of Periodontal and Implant Science
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• v.51 no.2
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• pp.77-87
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• 2021

Purpose: The aim of this study was to compare the efficacy of the tunnel technique for root coverage using a new xenogeneic acellular dermal matrix vs. connective tissue grafting (CTG) for the treatment of multiple maxillary adjacent recessions (recession type 1) at 12 months postoperatively. Methods: This study enrolled 12 patients with at least 3 contiguous, bilateral, symmetrical maxillary gingival recessions (i.e., at least 6 recessions per patient). In total, 74 recessions were treated using the modified coronally advanced tunnel (MCAT) technique combined with a novel porcine-derived acellular dermal matrix (PADM) at 37 test sites or CTG at 37 control sites. The following clinical parameters were measured: recession height, clinical attachment level, width of keratinized tissue, probing depth, recession width, gingival thickness, mean root coverage (MRC), and complete root coverage (CRC). Comparisons between test and control groups were made for pain visual analog scale scores at 14 days. Results: At 12 months, the MCAT with PADM (test) yielded a statistically significant improvement in all clinical parameters studied. MRC was significantly higher on the control sides (80.6%±23.7%) than on the test sides (68.8%±23.4%). Similarly, CRC was 48.7%±6.8% on the control sides (CTG), in contrast to 24.3%±8.2% on the test sides (PADM). Statistically significant differences were observed in favor of the control sides for all clinical parameters studied. Nevertheless, the MCAT in adjunction with PADM was clearly superior at reducing mean and maximum patient-reported postoperative pain intensity and pain duration in the first week after surgery. Conclusions: The use of PADM to treat multiple recessions improved clinical parameters at 12 months, but these outcomes were nevertheless poorer than those observed for CTG. However, PADM reduced morbidity, particularly the pain experienced by patients.

• Journal of the Korean Geotechnical Society
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• v.25 no.2
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• pp.5-15
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• 2009

The conventional reinforced earth retaining wall has the connector system to fix the reinforcement and block. However, this system defect may cause the crack of block and the rupture of reinforcement due to the stress concentration near the face of reinforced earth retaining wall. Hence, the new connector system which was able to allow the settlement of reinforcement was developed in this study and a test was carried out in the study area which is divided into the conventional reinforced earth retaining wall and reinforced Earth Retaining Wall driving the settlement. As the results of field monitoring in situ, the ratio of tensile force calculated at maximum value on contiguous portion of front block showed that the settlement type decreased the stress concentration near the face of front block greater than the conventional type.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.28-28
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• 2022

This paper presents the first genome assemblies of Philippine mangoes that provide valuable reference for varietal improvement and genomic studies on mango and related fruit crops. WE sequenced whole genomes of3 species, Mangifera odorata (Huani), Mangifera altissima (Paho), and Mangifera indica 'Carabao' (Sweet Elena). 'Carabao' is the major export variety of the Philippines; Paho is identified as vulnerable by the IUCN Red List of Threatened Species; Huani has fruit sap acrid which is the primary defense mechanism against insects and birds. We used Falcon, a diploid aware -de novo assembler to assemble SMRT generated long-read sequences. Falcon-unzip was employed to phase the output assembly producing larger contig sets (primary contigs) and shorter contigs corresponding to haplotypes (haplotigs). Assembly statistics were generated by comparing the assembly to a reference genome, Tommy Atkins, using Quality Assessment Tool (QUAST). Moreover, the extent of duplication and completeness of gene content was measured using Benchmarking Universal Single-Copy Orthologs (BUSCO). Draft assemblies with high duplications were processed using Purge Haplotigs and Purge Dups to lessen duplications with minimal impact on genome completeness. De novo assemblies of Huani, Paho and 'Carabao' were then generated with primary contig sizes of 463.64 Mb, 508.95 Mb and 401.51 Mb respectively. These draft assemblies of Huani, Paho and 'Carabao' showed 96.90%, 95.17% and 99.07% complete BUSCOs respectively which is comparable to 'Tommy Atkins' genome (98.6%). Using two mango transcriptome data (pooled RNA-seq from different mango varieties and tissues), 91-96% or 24-30 million reads were successfully mapped back for each generated assembly indicating high degree of completeness. The results obtained demonstrated the highly contiguous, phased, and near complete genome assembly of three Philippine mango species for structural and functional annotation of gene units, especially those with economic importance.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.78-78
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• 2003

Purpose: This event related fMRI study was to further our understanding about how different brain regions could contribute to effective access of specific information stored in long term memory. This experiment has allowed us to determine the brain regions involved in recognition of familiar faces among non familiar faces. Materials and Methods: Twelve right handed normal, healthy volunteer adults participated in face recognition experiment. The paradigm consists of two 40 familiar faces, 40 unfamiliar faces and control base with scrambled faces in a randomized order, with null events. Volunteers were instructed to press on one of two possible buttons of a response box to indicate whether a face was familiar or not. Incorrect answers were ignored. A 1.5T MRI system(GMENS) was employed to evaluate brain activity by using blood oxygen level dependent (BOLD) contrast. Gradient Echo EPI sequence with TR/TE= 2250/40 msec was used for 17 contiguous axial slices of 7mm thickness, covering the whole brain volume (240mm Field of view, 64 ${\times}$ 64 in plane resolution). The acquired data were applied to SPM99 for the processing such as realignment, normalization, smoothing, statistical ANOVA and statistical preference. Results/Disscusion: The comparison of familiar faces vs unfamiliar faces yielded significant activations in the medial temporal regions, the occipito temporal regions and in frontal regions. These results suggest that when volunteers are asked to recognize familiar faces among unfamiliar faces they tend to activate several regions frequently involved in face perception. The medial temporal regions are also activated for familiar and unfamiliar faces. This interesting result suggests a contribution of this structure in the attempt to match perceived faces with pre existing semantic representations stored in long term memory.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.3-14
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• 2019

The café has become an important representative "third place" where people study and rest. Hence, it is worthwhile for researchers to understand the needs of individual users as well as the requirements of people who visit such venues in groups. The identification of strategies that can help achieve larger, wider, higher, or deeper interior spaces in small and compact locations can generate benefits for both users and designers. In this study, where 56 interior design students participated, we used an eye-tracker and images of cafes to explore the relationships between spatial depth and the intention to visit a cafe space. The researchers digitally developed fifteen different conditions of space and measured the eye movements of the participants using an eye-tracker when they examined images that appeared to convey the most depth. Participants were also asked to imagine the proposed space images as cafes and to select one of the 15 images as the location that they would be most likely to visit individually and one that they would frequent in the company of other people. The research results revealed that certain ways of using interior design elements altered the participants' perceptions of spatial depth without any change being effected to the actual volume or the size of the space. The participants tended to perceive a space with a small decorative artwork on a dark toned wall with unconnected furniture as deeper than a space with no or large artwork on a light toned wall with contiguous furniture. Spatial depth was a more important consideration for an individual visit than for a group visit. The results of this exploratory study will help scholarly understanding of the role played by spatial depth in customer intentions to visit a cafe.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.