• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.582-591
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• 2009

The pyramid graph is an interconnection network topology based on regular square mesh and tree structures. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square mesh as a base sub-graph constituting of each layer in the pyramid graph. Edge set in the mesh can be divided into two disjoint sub-sets called as NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or shared in the upper layer of pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges in the original graph within the shrunk super-vertex on the resulting graph. In this paper, we analyze that the lower and upper bound on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n\times2^n$ mesh is $2^{2n-2}$ and $3*(2^{2n-2}-2^{n-1})$ respectively. By expanding this result into the pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}-3*2^{n-1}$-2n+7 in the n-dimensional pyramid.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.43-58
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• 2014

As the use of trading systems has increased rapidly, many researchers have become interested in developing effective stock market prediction models using artificial intelligence techniques. Stock market prediction involves multifaceted interactions between market-controlling factors and unknown random processes. A successful stock prediction model achieves the most accurate result from minimum input data with the least complex model. In this research, we develop a combination model of ${\pi}$-fuzzy logic and support vector machine (SVM) models, using a genetic algorithm to optimize the parameters of the SVM and ${\pi}$-fuzzy functions, as well as feature subset selection to improve the performance of stock market prediction. To evaluate the performance of our proposed model, we compare the performance of our model to other comparative models, including the logistic regression, multiple discriminant analysis, classification and regression tree, artificial neural network, SVM, and fuzzy SVM models, with the same data. The results show that our model outperforms all other comparative models in prediction accuracy as well as return on investment.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.117-131
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• 2017

This study was conducted to draw vegetation landscape elements in the ancient literature, investigate plant community structure, understand vegetation structure, and suggest reasonal conservation management methods. As a result of analyzing ancient literature, geomorphological landscapes in Guryong valley were canyon landscape and valley surrounded in Mt. Chiak. Plant landscape factors were as followed. Rhododendron spp. spread around valley. Also, Pinus densiflora communities were distributed in Guryong valley around. Especially, the entrance zones of Guryong valley were described as covered with Pinus densiflora and Whangchangkumpyo(黃腸禁標). Therefore, it was estimated that entry of Guryong valley was covered with Pinus densiflora community landscape. As for current vegetation result, the main vegetation was divided into mixed deciduous broad-leaved trees community and Pinus densiflora community. As a result of analysis by TWINSPAN for community classification, five communities(Deciduous broadleaved trees, Pinus densiflora, Pinus densiflora-Abies holophylla, Abies holophylla, and Pinus koraiensis community) were classified. To maintain historic plant landscape and conserve crucial resources, Pinus densiflora community was classified as concentrated conservation management area($105,472m^2$). To maintain Pinus densiflora landscape which has high historical and cultural value of Guryong valley, it was considered that active density control of lower layer vegetation would be necessary. Accordingly, to conserve P. densiflora landscape, Whangchangkumpyo(?腸禁標), that area was separated into Pinus densiflora lower layer forest management area($84,029m^2$) and Pinus densiflora seedling conservation management area($21,443m^2$). In understory of Pinus densiflora lower layer flora, the target tree species for elimination and management were Quercus serrata and Quercus mongolica. They were $4{\sim}6trees/100m^2$ and their average diameter was 7.1cm. To preserve Pinus densiflora seedlings, areas with Sasa borealis, the ground vegetation of Pinus densiflora community, rate of 80% or more should be selected as priority management areas and concentrated elimination and management of Sasa borealis should be implemented. Likewise, traditional Pinus densiflora forest is a historically cultural heritage to preserve with sustainable interest and survey. Efficient management method through systematic monitoring system should be made.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.511-544
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• 2016

Standards boost technological innovation by promoting information sharing, compatibility, stability and quality. Identifying groups of companies that particularly benefit from these functions of standards in their technological innovation and commercialization helps to customize planning and implementation of standards-related policies for demand groups. For this purpose, this study engages in profiling of SMEs whose R&D objective is to respond to standards as well as those who need to implement standards system for technological commercialization. Then it suggests a prediction model that can distinguish such companies from others. To this end, decision tree analysis is conducted for profiling of characteristics of subject SMEs through data mining. Subject SMEs include (1) those that engage in R&D to respond to standards (Group1) or (2) those in need of product standard or technological certification policies for commercialization purposes (Group 2). Then the study proposes a prediction model that can distinguish Groups 1 and 2 from others based on several variables by adopting discriminant analysis. The practicality of discriminant formula is statistically verified. The study suggests that Group 1 companies are distinguished in variables such as time spent on R&D planning, KoreanStandardIndustryClassification (KSIC) category, number of employees and novelty of technologies. Profiling result of Group 2 companies suggests that they are differentiated in variables such as KSIC category, major clients of the companies, time spent on R&D and ability to test and verify their technologies. The prediction model proposed herein is designed based on the outcomes of profiling and discriminant analysis. Its purpose is to serve in the planning or implementation processes of standards-related policies through providing objective information on companies in need of relevant support and thereby to enhance overall success rate of standards-related projects.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1183-1193
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• 2010

The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2037-2042
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• 2013

Background: Different methods of diagnosis have been found to be inefficient in terms of screening and early diagnosis of lung cancer. Cancer cells produce proteins whose serum levels may be elevated during the early stages of cancer development. Therefore, those proteins may be recognized as potential cancer markers. The aim of this study was to differentiate healthy individuals and lung cancer cases by analyzing their serum protein profiles and evaluate the efficacy of this method in the early diagnosis of lung cancer. Materials and Methods: 170 patients with lung cancer, 53 under high risk of lung cancer, and 47 healthy people were included in our study. Proteomic analysis of the samples was performed with the SELDI-TOF-MS approach. Results: The most discriminatory peak of the high risk group was 8141. When tree classification analysis was performed between lung cancer and the healthy control group, 11547 was determined as the most discriminatory peak, with a sensitivity of 85.5%, a specificity of 89.4%, a positive predictive value (PPV) of 96.7% and a negative predictive value (NPV) of 62.7%. Conclusions: We determined three different protein peaks 11480, 11547 and 11679 were only present in the lung cancer group. The 8141 peak was found in the high-risk group, but not in the lung cancer and control groups. These peaks may prove to be markers of lung cancer which suggests that they may be used in the early diagnosis of lung cancer.

• Korean Journal of Agricultural Science
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• v.20 no.2
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• pp.145-152
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• 1993

Vegetational data obtained from 15 quadrats of Mt. Daeam area were analysed by applying two multivariate methods : two-way indicator species analysis(TWINSPAN) for classification and detrended canonical correspondence analysis(DCCA) for ordination. The dominant tree species were Quercus mongolica, Acer pseudo-sieboldianum, Betula costata, and Acer mono in descending order. The pH ranges were 5.0 to 5.5 in the 15 sites near bog and 5.3 to 5.4 in the 3 sites within bog. The forest communities in Mt. Daeam were classified into Quercus mongolica-Acer mono, Quercus mongolica-Prunus sargentii, Quercus mongolica-Abies nephrolepis-Acer tschonoskii var, rubripes, and Quercus mongolica-Abies nephrolepis-Betula costata according to the TWINSPAN. The relationships between the distribution of dominant species of forest vegetation and soil in the forest of Mt. Daeam were investigated by analyzing soil nutrition gradient. Quercus mongolica-Prunus sargentii forests were distributed in the good sites in nutrition levels of total nitrogen, cation exchange capacity, $Mg^{+{+}}$ and $Ca^{+{+}}$ but Quercus mongolica-Abies nephrolepis-Betula costata forests in the poor sites in the nutrition levels.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.3
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• pp.1-17
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• 1999

The purpose of this study is to evaluate the creation techniques of artificial wetland, one of biotopes developed to promote biodiversity in urban areas, and to look for improvement steps. Specifically, artificial wetland creation techniques were categorized into living environment and living creature classification. Being living conditions for creations, habitat environment was reviewed with a focus on water and soil environments. Living creatures were classified into plants, insects, fish, and birds. The evaluation of creation techniques was done in post-construction evaluation while considering the creation of habitats for living creatures. Intervention by users, changes in living environment and living species, and relevance of creation techniques were reviewed. Key results of this study are as follows. (1) Water environment for the living environment of creatures provides a suitable environment conditions for the living of creatures through a process easing the use of piped water. Various water depths and embankment appear to have a positive impact on the living of aquatic life. In particular, embankment covered in soil naturally played an important role as a place for the activities of aquatic insects and young fish as well as the growth of aquatic plants. (2) Various aquatic and ground plants to promote insect-diversity, shallow water, and old-tree logs had contributed greatly in increasing the types and number of insects. Aquatic insects. Aquatic insects were seen much particularly in areas where aquatic plants are rich but water is shallow than any other areas. (3) A space piled with stone to provide habitats for fish was not much used. However, it was observed that fish used embankment built with natural stones and embankment using logs in areas where water is deep. In addition, it was confirmed that 1,500 fish that had been released propagated using various depths and places for birth. (4) It was analyzed that techniques (creation of island, log setting, and creation of man-made bird nests) to provide habitats and to attract birds are not serving their roles. In such a case, it is believed that species had not increased due to the smallness as well as isolated features of the area. Based on theoretical review, they are judged to be areas that are likely to be used when a greater variety of birds is introduced. It is judged that attracting and keeping more birds at the site, such spaces need to be linked systematically in the future in terms of building eco-network while ensuring an adequate living areas. (5) In the study areas, users intervened greatly. As a result, a blockage was created preventing the normal growth of plants and non-indigenous plants were introduced. In order to limit the intervention by users, setting enough buffer zones, and environment education programs were urgently required. D/H=1>Hyangkyo> houses on the river>temples>lecture halls. D/H ratio of the backside areas is as follows. D/H=1>Hyangkyo>houses on the river>lecture halls. 4. Inner garden were planted deciduous than evergreen trees with Lagerstroemia indica. Enclosed dominant trees were planted by Pinus densiflora, Querces seuata. construct GEM strain, and examined for the expression and functional stability in microcosms.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.929-933
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• 2010

According to the IPCC guideline (2006), uncertainty assessment is very important in terms of the greenhouse gas inventory. Therefore, the purpose of this study is to estimate the basic wood density (BWD) and its uncertainty for Pinus densiflora in Korea. In this study, Pinus densiflora forests were divided into two ecotypes which were Gangwon and Jungbu regions. A total of 33 representative sampling plots was selected to collect sample trees after considering the tree ages and DBH distributions. The BWD showed statistically no difference between age classes based on IPCC's classification. While, it showed statistically difference(pvalue=0.0017) between eco-types. The BWD and uncertainty was 0.396(g/$cm^3$) and 12.9(%) for Pinus densiflora in Gangwon, while it was 0.470(g/$cm^3$) and 3.8(%) for Pinus densiflora in Jungbu. The values of the BWD uncertainty for Pinus densiflora were more precised than the values given by the IPCC guideline.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6673-6680
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• 2013

Objective: Insulin resistance (IR) is an established risk factor for colorectal cancer (CRC). Given that CRC and IR physiologically overlap and the calpain-10 gene (CAPN10) is a candidate for IR, we explored the association between CAPN10 and CRC risk. Methods: Blood samples of 400 case-control pairs were genotyped, and the lifestyle and dietary habits of these pairs were recorded and collected. Unconditional logistic regression (LR) was used to assess the effects of CAPN10 SNP43 and SNP19, and environmental factors. Both generalized multifactor dimensionality reduction (GMDR) and the classification and regression tree (CART) were used to test gene-environment interactions for CRC risk. Results: The GA+AA genotype of SNP43 and the Del/Ins+Ins/Ins genotype of SNP19 were marginally related to CRC risk (GA+AA: OR = 1.35, 95% CI = 0.92-1.99; Del/Ins+Ins/Ins: OR = 1.31, 95% CI = 0.84-2.04). Notably, a high-order interaction was consistently identified by GMDR and CART analyses. In GMDR, the four-factor interaction model of SNP43, SNP19, red meat consumption, and smoked meat consumption was the best model, with a maximum cross-validation consistency of 10/10 and testing balance accuracy of 0.61 (P < 0.01). In LR, subjects with high red and smoked meat consumption and two risk genotypes had a 6.17-fold CRC risk (95% CI = 2.44-15.6) relative to that of subjects with low red and smoked meat consumption and null risk genotypes. In CART, individuals with high smoked and red meat consumption, SNP19 Del/Ins+Ins/Ins, and SNP43 GA+AA had higher CRC risk (OR = 4.56, 95%CI = 1.94-10.75) than those with low smoked and red meat consumption. Conclusions: Though the single loci of CAPN10 SNP43 and SNP19 are not enough to significantly increase the CRC susceptibility, the combination of SNP43, SNP19, red meat consumption, and smoked meat consumption is associated with elevated risk.