This paper presents a methodology to extract classes and inheritance relations from procedural software. The methodology is based on the idea of generating all groups of class candidates, based on the combinatorial groups of object candidates, and their inheritance with all possible combinations and selecting a group of object candidates, and their inheritance with all possible combinations and selecting a group with the best or optimal combination of candidates with respect to the degree of relativity and similarity between class candidates in the group and classes in a domain model. The methodology has innovative features in class candidates in the group and classes in a domain model. The methodology has innovative features in class and inheritance extraction: a clustering method based on both static (attribute) and dynamic (method) clustering, the combinatorial cases of grouping class candidate cases based on abstraction, a signature similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement, that is, the horizontal measurement for overall group similarity between n class candidates and m classes, and the vertical measurement for specific similarity between a set of classes in a group of class candidates and a set of classes with the same class hierarchy in a domain model, etc. This methodology provides reengineering experts with a comprehensive and integrated environment to select the best or optimal group of class candidates.
Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.
HVOF thermal spray coating of 80%WC-CoFe powder is one of the most promising candidate for the replacement of the traditional hard chrome plating and hard ceramics coating because of the environmental problem of the very toxic $Cr^{6+}$ known as carcinogen by chrome plating and the brittleness of ceramics coatings. 80%WC-CoFe powder was coated by HVOF thermal spraying for the study of durability improvement of the high speed spindle such as air bearing spindle. The coating procedure was designed by the Taguchi program, including 4 parameters of hydrogen and oxygen flow rates, powder feed rate and spray distance. The surface properties of the 80%WC-CoFe powder coating were investigated roughness, hardness and porosity. The optimal condition for thermal spray has been ensured by the relationship between the spary parameters and the hardness of the coatings. The optimal coating process obtained by Taguchi program is the process of oxygen flow rate 34 FRM, hydrogen flow rate 57 FRM, powder feed rate 35 g/min and spray distance 8 inch. The coating cross-sectional structure was observed scanning electron microscope before chemical etching. Estimation of coating porosity was performed using metallugical image analysis. The Friction and wear behaviors of HVOF WC-CoFe coating prepared by OCP are investigated by reciprocating sliding wear test at $25^{\circ}C$ and $450^{\circ}C$. Friction coefficients (FC) of coating decreases as sliding surface temperature increases from $25^{\circ}C$ to $450^{\circ}C$.
Members of Chlorociboria are soft-rot ascomycetes that produce blue-green pigment. We investigated the growth characteristics of two Korean species of Chlorociboria, eight strains of Chlorociboria aeruginascens and Chlorociboria poutoensis, under various culture conditions (solid media, temperature, pH) and screened them for extracellular enzyme activity. Although the growth rate was slow, all tested strains of Chlorociboria spp. grew well on potato dextrose agar (PDA; 16.3~42.6 mm after 60 days) or Sabouraud dextrose agar (SDA), but not on malt extract agar (MEA). Compared with C. aeruginascens strains, C. poutoensis strains exhibited higher expression of blue-green pigments on both PDA and SDA media. The optimal temperature for mycelial growth was $20{\sim}25^{\circ}C$, and mycelial growth was lower at $30^{\circ}C$ than at $10^{\circ}C$. All strains tended to have increased mycelial growth as the incubation temperature increased in the range of 10 to $20^{\circ}C$. The optimal pH of potato dextrose broth (PDB) for mycelial growth varied according to the strain under static culture conditions. Maximum biomass production was obtained at pH 6.0 for NIFoS 579 ($114.3{\pm}5.1mg/60days$), but it maintained a stable pigment expression under a broad pH spectrum. The activities of both cellulase and laccase were observed in all tested strains of Chlorociboria spp. Enzyme activities of NIFoS 579 were remarkably higher than those of the other strains. From these results, we suggest that C. poutoensis NIFoS 579 is a potential candidate for use as a source of natural blue-green dye.
Kim, Seung Tae;Kim, Hee Jung;Jang, Su Kil;Lee, Do Ik;Joo, Seong Soo
Korean Journal of Food Science and Technology
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v.45
no.1
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pp.77-83
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2013
In this study, we observed optimal conditions and suitable bacteria for the fermentation of steam-dried ginseng berry extracts (SGB) and determined antioxidant effects of the fermented extracts. Five bacteria (Lactobacillus fermentarum, L. plantarum, L. brevis, L. casei, Bacillus subtillis) were examined on their growth activities and viabilities in various culture temperatures ($25-35^{\circ}C$) and concentrations (25-100%). L. plantarum was considered to be the most suitable bacteria for the fermentation in both growth activity and viability. Moreover, the extracts fermented with L. plantarum showed more potent antioxidant efficacy in both 1,1-diphenyl-2-picrylhydrazyl radical and hydroxyl radical scavenging assay. High performance liquid chromatography analysis revealed that fermentation with L. plantarum changed the contents and components of ginsenosides. In conclusion, these data suggest that L. plantarum efficiently ferment SGB and the fermented extracts may have therapeutical values against oxidative stress and be a good candidate in adjuvant therapy where ginsenoside would be the main composition.
This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.
In this study, a comprehensive exploration and evaluation of washland candidate locations by means of field monitoring as well as spatial analysis in six major river system (Han, Nakdong, Nam, Geum, Youngsan, and Seomjin Rivers). Washland(in other words, river detention basin) is an artificial wetland system which is connected to streams or rivers likely to riverine wetlands. Major purpose of washland creation is to control floodings, water supply and purification, providence of eco-cultural space to human and natural populations. Characteristics and functions of riverine wetlands can be expected as well, thus it is believed to be an efficient multi-purpose water body that is artificially created, in terms of hydrology and ecology. Geographical information and field monitoring results for the washland candidate locations were evaluated in 2009, with respect to optimal location exploration, ecosystem connectivity and educational-cultural circumstances. A total of $269\;km^2$ washland candidate locations were found from spatial analysis (main channel of Rivers South Han, 71.5; Nakdong 54.1; Nam, 2.3; Geum, 79.0; Youngsan 46.4; Seomjin 15.7), and they tended to be distributed in mid- to lower part of the rivers to which tributaries are confluent. Field monitoring at 106 sites revealed that some sites located in the Rivers Nam and Geum is appropriate for restoration or artificial creation as riverine wetlands. Several sites in the Nakdong and Seomjin Rivers were close to riverine wetlands (e.g., Upo), habitats of endangered species (e.g., otters), or adjacent to educational facility (e.g., museums) or cultural heritages (e.g., temples). Those sites can be utilized in hydrological, ecological, educational, and cultural ways when evidence of detailed hydrological evaluation is provided. In conclusion, determination of washland locations in the major river basins has to consider habitat expansion as well as hydrological function (i.e. flood control) basically, and further utility (e.g. educational function) will increase the values of washland establishment.
This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.
Zhu, Xi-Shan;Lin, Zi-Ying;Du, Jing;Cao, Guang-Xin;Liu, Gang
Asian Pacific Journal of Cancer Prevention
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v.15
no.12
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pp.4773-4780
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2014
Background: To investigate the effects of small interference RNA (siRNA) targeting BCR/ABL mRNA on proliferation and apoptosis in the K562 human chronic myeloid leukemia (CML) cell line and to provide a theoretical rationale and experimental evidence for its potential clinical application for anti-CML treatment. Materials and Methods: The gene sequence for BCR/ABL mRNA was found from the GeneBank. The target gene site on the BCR/ABL mRNA were selected according to Max-Planck-Institute (MPI) and rational siRNA design rules, the secondary structure of the candidate targeted mRNA was predicted, the relevant thermodynamic parameters were analyzed, and the targeted gene sequences were compared with BLAST to eliminate any sequences with significant homology. Inhibition of proliferation was evaluated by MTT assay and colony-formation inhibiting test. Apoptosis was determined by flow cytometry (FCM) and the morphology of apoptotic cells was identified by Giemsa-Wright staining. Western blotting was used to analyze the expression of BCR/ABL fusion protein in K562 cells after siRNA treatment. Results: The mRNA local secondary structure calculated by RNA structure software, and the optimal design of specific siRNA were contributed by bioinformatics rules. Five sequences of BCR/ABL siRNAs were designed and synthesized in vitro. Three sequences, siRNA1384, siRNA1276 and siRNA1786, which showed the most effective inhibition of K562 cell growth, were identified among the five candidate siRNAs, with a cell proliferative inhibitory rate nearly 50% after exposure to 12.5nmol/L~50nmol/L siRNA1384 for 24,48 and 72 hours. The 50% inhibitory concentrations ($IC_{50}$) of siRNA1384, siRNA1276 and siRNA1786 for 24hours were 46.6 nmol/L, 59.3 nmol/L and 62.6 nmol/L, respectively, and 65.668 nmol/L, 76.6 nmol/L, 74.4 nmol/L for 72 hours. The colony-formation inhibiting test also indicated that, compared with control, cell growth of siRNA treated group was inhibited. FCM results showed that the rate of cell apoptosis increased 24 hours after transfecting siRNA. The results of annexinV/PI staining indicated that the rate of apoptosis imcreased (1.53%, 15.3%, 64.5%, 57.5% and 21.5%) following treamtne with siRNAs (siRNA34, siRNA372, siRNA1384, siRNA1276 and siRNA1786). Morphological analysis showed td typical morphologic changes of apoptosis such as shrunken, fragmentation nucleus as well as "apoptotic bodies" after K562 cell exposure to siRNA. Western blot analysis showed that BCR/ABL protein was reduced sharply after a single dose of 50nmol/L siRNA transfection. Conclusions: Proliferation of K562 cells was remarkbly inhibited by siRNAs (siRNA1384, siRNA1276 and siRNA1786) in a concentration-dependent manner in vitro, with effective induction of apoptosis at a concentration of 50 nmol/L. One anti-leukemia mechanism in K562 cells appeared that BCR/ABL targeted protein was highly down-regulated. The siRNAs (siRNA1384, siRNA1276 and siRNA1786) may prove valuable in the treatment of CML.
KIPS Transactions on Software and Data Engineering
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v.9
no.12
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pp.431-438
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2020
In this paper, the method to extract lip contour by multiple threshold is proposed. Spyridonos et. el. proposed a method to extract lip contour. First step is get Q image from transform of RGB into YIQ. Second step is to find lip corner points by change point detection and split Q image into upper and lower part by corner points. The candidate lip contour can be obtained by apply threshold to Q image. From the candidate contour, feature variance is calculated and the contour with maximum variance is adopted as final contour. The feature variance 'D' is based on the absolute difference near the contour points. The conventional method has 3 problems. The first one is related to lip corner point. Calculation of variance depends on much skin pixels and therefore the accuracy decreases and have effect on the split for Q image. Second, there is no analysis for color systems except YIQ. YIQ is a good however, other color systems such as HVS, CIELUV, YCrCb would be considered. Final problem is related to selection of optimal contour. In selection process, they used maximum of average feature variance for the pixels near the contour points. The maximum of variance causes reduction of extracted contour compared to ground contours. To solve the first problem, the proposed method excludes some of skin pixels and got 30% performance increase. For the second problem, HSV, CIELUV, YCrCb coordinate systems are tested and found there is no relation between the conventional method and dependency to color systems. For the final problem, maximum of total sum for the feature variance is adopted rather than the maximum of average feature variance and got 46% performance increase. By combine all the solutions, the proposed method gives 2 times in accuracy and stability than conventional method.
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