• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.257-271
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• 2016

The Structural SIMilarity (SSIM) index is one of the most widely-used methods for perceptual image quality assessment (IQA). It is based on the principle that the human visual system (HVS) is sensitive to the overall structure of an image. However, it has been reported that indices predicted by SSIM tend to be biased depending on the type of distortion, which increases the deviation from the main regression curve. Consequently, SSIM can result in serious performance degradation. In this study, we investigate the aforementioned phenomenon from a new perspective and review a constant that plays a big role within the SSIM metric but has been overlooked thus far. Through an experimental study on the influence of this constant in evaluating images with SSIM, we are able to propose a new solution that resolves this issue. In the proposed IQA method, we first design a system to classify different types of distortion, and then match an optimal constant to each type. In addition, we supplement the proposed method by adding color perception-based structural information. For a comprehensive assessment, we compare the proposed method with 15 existing IQA methods. The experimental results show that the proposed method is more consistent with the HVS than the other methods.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.685-692
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• 2016

This study aimed to develop the indicator-based approach to assess water use vulnerability in watersheds and applied to the unit watershed within the Han River watershed. Vulnerability indices were comprised of three sub-components (exposure, sensitivity, adaptive capacity) with respect to water use. The indicators were made up of 16 water use indicators. Then we estimated vulnerability indices using the Technique for Order of Preference by Similarity to Ideal Solution approach (TOPSIS). We collected environmental and socio-economic data from national statistics database, and used them for simulated results by the Soil and Water Assessment Tool (SWAT) model. For estimating the weighted values for each indicator, expert surveys for subjective weight and data-based Shannon's entropy method for objective weight were utilized. With comparing the vulnerability ranks and analyzing rank correlation between two methods, we evaluated the vulnerabilities for the Han River watershed. For water use, vulnerable watersheds showed high water use and the water leakage ratio. The indices from both weighting methods showed similar spatial distribution in general. Such results suggests that the approach to consider different weighting methods would be important for reliably assessing the water use vulnerability in watersheds.

• Korean Journal of Environment and Ecology
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• v.3 no.1
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• pp.42-50
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• 1989

A valley and a ridge forest in Mt. Gaya area was studied to investigate forest structure in relation to altitude and part of slope. Sixty-three quadrats were set up in the valley forest along altitude of 600m to 1,000m and part of slope, and thirty-eight quadrats were set up in the ridge forest along altitude of 700m to 1,430m. According to the importance values, the valley forest was Quercus mongolica-Lespedeza maximowiczii community and the ridge forest was Pinus densiflora, Quercus mongolica-Rhododendron mucronulatum community. Similarity index between the valley forest community and the ridge forest community was 37.2%. Shannon's species diversities of the valley forest community and the ridge forest community were 1.3402 and 1.0098, respectively. According to importance values by crown stories and DCA ordination, successional trends of tree species may be from Pinus densiflora and Pinus koraiensis through Quercus mongolica to Quercus serrata and Carpinus laxiflora. As going from the lower part to upper part of the slope in the valley forest, the importance values of Quercus mongolica, Quercus aliena, Rhododendron mucronulatum and Lespedeza maximowiczii increased while those of Carpinus laxiflora and Fraxinus rhynchophylla decreased. With increasing elevation in the valley and ridge forest, the importance value of Pinus densiflora decreased while that of Quercus mongolica increased. In the valley forest, densities of canopy and shrubstratum increased as increasing elevation, and the number of species and species diversity decreased as increasing elevation and going from the lower part to the upper of slope. The range of similarity indices between parts of the slope, and the elevation belts of 100m in the valley forest were 66.6-69.2 and 25.9-79.8%, respectively. In the ridge forest, density and basal area of canopy tended to decreased as increasing elevation, and the range of similarity indices between elevation belts of 100m was 27.9-98.2%.

• Parasites, Hosts and Diseases
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• v.33 no.4
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• pp.341-348
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• 1995

Genetic status of Acnnthamoebc sap. were tested on the basis of random amplified polymorphic DNA (RAPD) marker analysis. Four previously established Accnthcmoebn species, 4 Korean isolates of Acnnthamoeba sp., and one American isolate of Acanthcmoebc sp. were analyzed by RAPD-PCR using an arbitrary decamer primers. Amplification products were fractionated by agarose gel electrophoresis and slainrd by ethidium bromide . Eighteen primers produced DNA amplification profiles revealing clear differences among 4 species. Nine of them also produced DNA amplification profiles which included some isolate-specific amplification products. On the basis of amplified fragments by 18 primers, the pairwise similarity indices between A. culbensoni and other species (i.e. A. hntchetti, A. trinngularis, A. polyphaga) were 0.300, 0.308, and 0.313, respectively. Similarity index between A. hctchetti and A. triansulcris was 0.833. The mean similarity index among the 3 Korean isolates (YM-2, -3, -4) was 0.959 and 0.832 among them and 2 other species (A. hatchetti and A. triongulnris). The mean similarity index among YM-5 and other Korean isolates (YM-2, -3, -4) was 0.237. However, the similarity index between YM-5 and A. culbeksoni was 0.857, which suggests that YM-5 is genetically more similar to A. culbertsoni than other Korean isolates. Phonogram reconstructed by UPGMA method revealed that there are two groups: one group consists of A. hctchetti, A. tlonsulcns, and 3 Korean isolates (YM-2, -3, -4) , and the other group consists of A. cuLbensoni. A. polwphosc, HOV, and YM-5.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.660-669
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• 2020

Objective: To evaluate the accuracy of a deep learning-based automated segmentation of the left ventricle (LV) myocardium using cardiac CT. Materials and Methods: To develop a fully automated algorithm, 100 subjects with coronary artery disease were randomly selected as a development set (50 training / 20 validation / 30 internal test). An experienced cardiac radiologist generated the manual segmentation of the development set. The trained model was evaluated using 1000 validation set generated by an experienced technician. Visual assessment was performed to compare the manual and automatic segmentations. In a quantitative analysis, sensitivity and specificity were calculated according to the number of pixels where two three-dimensional masks of the manual and deep learning segmentations overlapped. Similarity indices, such as the Dice similarity coefficient (DSC), were used to evaluate the margin of each segmented masks. Results: The sensitivity and specificity of automated segmentation for each segment (1-16 segments) were high (85.5-100.0%). The DSC was 88.3 ± 6.2%. Among randomly selected 100 cases, all manual segmentation and deep learning masks for visual analysis were classified as very accurate to mostly accurate and there were no inaccurate cases (manual vs. deep learning: very accurate, 31 vs. 53; accurate, 64 vs. 39; mostly accurate, 15 vs. 8). The number of very accurate cases for deep learning masks was greater than that for manually segmented masks. Conclusion: We present deep learning-based automatic segmentation of the LV myocardium and the results are comparable to manual segmentation data with high sensitivity, specificity, and high similarity scores.

• Ecology and Resilient Infrastructure
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• v.5 no.3
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• pp.145-155
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• 2018

In a monsoonal climate, the soil seed bank can play an important role in plant regeneration after the severe annual floods that disturb above-ground vegetation within the riparian zone. To investigate the relationship between the soil seed bank and vegetation, we measured the species composition of the soil seed bank and the extant above-ground vegetation in six major plant communities (Artemisia selengensis, Miscanthus sacchariflorus, Persicaria nodosa, Phalaris arundinacea, Phragmites japonica, and Rorippa palustris) in the Cheongmicheon Stream, Korea. A total of 21 species germinated from the floodplain soil seed banks. The most diverse seed bank (21 species) was found in the A. selengensis community, wheres the lowest number of species was found in the R. palustris community (2 species). Most soil seed banks were composed of annuals (90%), exceptions being Rumex crispus and Artemisia princeps, which are perennial ruderals. The similarity of species composition between the soil seed bank and above-ground vegetation was low with Sorensen's similarity indices averaging 29% (range 12 - 42%). Crucially, existing dominant perennials of the extant vegetation including A. selengensis, M. sacchariflorus, P. japonica and P. arundinacea were absent from the soil seed bank. In conclusion, the soil seed banks of the floodplains of the Cheongmicheon Stream were mainly composed of viable seeds of ruderal plants, which could germinate rapidly after severe flood disturbance. The soil seed bank may, therefore, be useful for the restoration of the early succession stages of riparian vegetation after flood disturbances.

• Korean Journal of Weed Science
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• v.2 no.1
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• pp.20-30
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• 1982

A field experiment was conducted in 1981 at the Crop Experiment Station, Suweon, Korea, in machine transplanted paddy rice field, to study the effectiveness of single herbicide, mixture, and systematic application of herbicides on diversity of weed control spectrum. The rice variety planted was Taebaegbyeo, Indica ${\times}$ Japonica cross bred. Experimental field was dominated by Echinochtoa crusgalli, Eleocharis kuroguwai, and Scirpus hotarui, and importance values based on dry weight of these weeds were 89%, 5%, and 3%, respectively. The mixture or systematic treatments of herbicide were generally more effective than single herbicide applications on weed control. Coefficients of similarity based on floristic composition after herbicide application between Perfluidone (5G) and Chloromethoxynil (7G), and between Pertluidone (5G) and Bifenox (7G), and between Perfluidone (5G) and three types of Butachlor (6G) were low, and these sets seemed to be a good mixture herbicide in paddy fields. While, Perfluidone (5G) had low coefficient of similarity with other single herbicides tested. The information on coefficient of similarity could be used as parameter for selecting herbicides to increase the efficiency of herbicidal performance. Simpson's indices from Butachlor (3.5G)/SL-49 (7G), Butachlor (3.5G)/Pyrazolate (6G), and Perfluidone (5G) treatments were high, and these herbicide treatments tended to the weed community type simplified, while the indices from Perfluidone (5G) + Chloromethoxynil (7G), Butachlor (6G) fb Perftuidone (5G), and Butachlor (4G)/Naproanilide (6G) treatments were low, and these herbicide treatments caused to the community type diversified in terms of floristic composition.

• The Korean Journal of Ecology
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• v.21 no.3
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• pp.283-290
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• 1998

The vegetation pattern of Mt. Odae based on the soil humidity gradient showed 3 types: (1) the forest of Pinus densiflora under the mesic or xeric conditions of the low altitudinal area, (2) the forest of Acer including A. mono, A. pseudo-sieboldianum and Tilia amurensis under the submesic or subxeric conditions and (3) the forest of Quercus including Q. mongolica of the higher elevational area and Q. variabilis of the lower elevational area under the xeric condition. Water content, organic matter and total nitrogen of soil were relatively low in Pinus densiflora and Quercus variabilis communities while they were relatively high in Betula platyphylla var. japonica and Quercus mongolica communities. According to the result of cluster analysis based on similarity indices of the communities, the proposed successional sere in the forest vegetation of Mt. Odae was as follows. P. densiflora community $\longrightarrow$ P. densiflore + Q. mongolica community $\longrightarrow$ Q. mongolica + A. pseudo-sieboldianum community. P. densiflora community $\longrightarrow$ P. densiflora + Q. variabilis community $\longrightarrow$ Q. variabilis community $\longrightarrow$ Q. mongolica + Q. variabilis community $\longrightarrow$ Q. mongolica + A. pseudo-sieboldianum community.