• Title, Summary, Keyword: derived subgroup

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Subgroup Discovery Method with Internal Disjunctive Expression

  • Kim, Seyoung;Ryu, Kwang Ryel
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.1
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    • pp.23-32
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    • 2017
  • We can obtain useful knowledge from data by using a subgroup discovery algorithm. Subgroup discovery is a rule model learning method that finds data subgroups containing specific information from data and expresses them in a rule form. Subgroups are meaningful as they account for a high percentage of total data and tend to differ significantly from the overall data. Subgroup is expressed with conjunction of only literals previously. So, the scope of the rules that can be derived from the learning process is limited. In this paper, we propose a method to increase expressiveness of rules through internal disjunctive representation of attribute values. Also, we analyze the characteristics of existing subgroup discovery algorithms and propose an improved algorithm that complements their defects and takes advantage of them. Experiments are conducted with the traffic accident data given from Busan metropolitan city. The results shows that performance of the proposed method is better than that of existing methods. Rule set learned by proposed method has interesting and general rules more.

FINITE NON-NILPOTENT GENERALIZATIONS OF HAMILTONIAN GROUPS

  • Shen, Zhencai;Shi, Wujie;Zhang, Jinshan
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.6
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    • pp.1147-1155
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    • 2011
  • In J. Korean Math. Soc, Zhang, Xu and other authors investigated the following problem: what is the structure of finite groups which have many normal subgroups? In this paper, we shall study this question in a more general way. For a finite group G, we define the subgroup $\mathcal{A}(G)$ to be intersection of the normalizers of all non-cyclic subgroups of G. Set $\mathcal{A}_0=1$. Define $\mathcal{A}_{i+1}(G)/\mathcal{A}_i(G)=\mathcal{A}(G/\mathcal{A}_i(G))$ for $i{\geq}1$. By $\mathcal{A}_{\infty}(G)$ denote the terminal term of the ascending series. It is proved that if $G=\mathcal{A}_{\infty}(G)$, then the derived subgroup G' is nilpotent. Furthermore, if all elements of prime order or order 4 of G are in $\mathcal{A}(G)$, then G' is also nilpotent.

3-DESIGNS DERIVED FROM PLANE ALGEBRAIC CURVES

  • Yu, Ho-Seog
    • Bulletin of the Korean Mathematical Society
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    • v.44 no.4
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    • pp.817-823
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    • 2007
  • In this paper, we develop a simple method for computing the stabilizer subgroup of a subgroup of $$D(g)={{\alpha}{\in}\mathbb{F}_q|there\;is\;a\;{\beta}{\in}{\mathbb{F}}^x_q\;such\;that\;{\beta}^n=g(\alpha)}$$ in $PSL_2(\mathbb{F}_q)$, where q is a large odd prime power, n is a positive integer dividing q-1, and $g(x){\in}\mathbb{F}_q[x]$. As an application, we construct new infinite families of 3-designs (cf. Examples 3.4 and 3.5).

Comparison of Association Rule Learning and Subgroup Discovery for Mining Traffic Accident Data (교통사고 데이터의 마이닝을 위한 연관규칙 학습기법과 서브그룹 발견기법의 비교)

  • Kim, Jeongmin;Ryu, Kwang Ryel
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.1-16
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    • 2015
  • Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

Phylogenetic Analysis of New Isolates of Cucumber mosaic virus from Iran on the Basis of Different Genomic Regions

  • Nematollahi, Sevil;Sokhandan-Bashir, Nemat;Rakhshandehroo, Farshad;Zamanizadeh, Hamid Reza
    • The Plant Pathology Journal
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    • v.28 no.4
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    • pp.381-389
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    • 2012
  • Molecular characterization of Cucumber mosaic virus (CMV) was done by using samples from tomato and cucurbitaceous plants collected from different locations in the northwest region of Iran. After screening by enzyme-linked immunosorbent assay, 91 CMV-infected samples were identified. Biological properties of eight representative isolates were compared with each other revealing two distinct phenotypes on squash and tomato plants. Phylogenetic analyses based on nucleotide sequences of the coat protein (CP), movement protein (MP) and 2b of the new isolates, together with that of previously reported isolates, led to the placement of the Iranian isolates in subgroups IA and IB according to CP and MP genes, but in subgroup IA according to the 2b gene. These data suggest that reassortment may have been a major event in the evolution of CMV in Iran, and that the Iranian isolates are derived from a common recent ancestor that had passed through a bottleneck event.

Geochemistry of Geothermal Waters in Korea: Environmental Isotope and Hydrochemical Characteristics I. Bugok Area (한반도 지열수의 지화학적 연구: 환경동위원소 및 수문화학적 특성 I. 부곡 지역)

  • Yun, Seong-Taek;Koh, Yong-Kwon;Kim, Chun-Soo;So, Chil-Sup
    • Economic and Environmental Geology
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    • v.31 no.3
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    • pp.185-199
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    • 1998
  • Hydrogeochemical and environmental isotope studies were undertaken for various kinds of water samples collected in 1995-1996 from the Bugok geothermal area. Physicochemical data indicate the occurrence of three distinct groups of natural water: Group I ($Na-S0_4$ type water with high temperatures up to $77^{\circ}C$, occurring from the central part of the geothermal area), Group II (warm $Na-HCO_{3}-SO_{4}$ type water, occurring from peripheral sites), Group III ($Ca-HCO_3$ type water, occurring as surface waters and/or shallow cold groundwaters). The Group I waters are further divided into two SUbtypes: Subgroup Ia and Subgroup lb. The general order of increasing degrees of hydrogeochemical evolution (due to the degrees of water-rock interaction) is: Group III$\rightarrow$Group II$\rightarrow$Group I. The Group II and III waters show smaller degrees of interaction with rocks (largely calcite and Na-plagioclase), whereas the Group I waters record the stronger interaction with plagioclase, K-feldspar, mica, chlorite and pyrite. The concentration and sulfur isotope composition of dissolved sulfate appear as a key parameter to understand the origin and evolution of geothermal waters. The sulfate was derived not only from oxidation of sedimentary pyrites in surrounding rocks (especially for the Subgroup Ib waters) but also from magmatic hydrothermal pyrites occurring in restricted fracture channels which extend down to a deep geothermal reservoir (typically for the Subgroup Ia waters). It is shown that the applicability of alkaliion geothermometer calculations for these waters is hampered by several processes (especially the mixing with Mg-rich near-surface waters) that modify the chemical composition. However, the multi-component mineral/water equilibria calculation and available fluid inclusion data indicate that geothermal waters of the Bugok area reach temperatures around $125^{\circ}C$ at deep geothermal reservoir (possibly a cooling pluton). Environmental isotope data (oxygen-18, deuterium and tritium) indicate the origin of all groups of waters from diverse meteoric waters. The Subgroup Ia waters are typically lower in O-H isotope values and tritium content, indicating their derivation from distinct meteoric waters. Combined with tritium isotope data, the Subgroup Ia waters likely represent the older (at least 45 years old) meteoric waters circuated down to the deep geothermal reservoir and record the lesser degrees of mixing with near-surface waters. We propose a model for the genesis and evolution of sulfate-rich geothermal waters.

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Eight-week healing of grafted calvarial bone defects with hyperbaric oxygen therapy in rats

  • Oh, Seo-Eun;Hu, Kyung-Seok;Kim, Sungtae
    • Journal of Periodontal and Implant Science
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    • v.49 no.4
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    • pp.228-236
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    • 2019
  • Purpose: The purpose of this study was to evaluate the synergistic effect of adjunctive hyperbaric oxygen (HBO) therapy on new bone formation and angiogenesis after 8 weeks of healing. Methods: Sprague-Dawley rats (n=28) were split into 2 groups according to the application of adjunctive HBO therapy: a group that received HBO therapy (HBO group [n=14]) and another group that did not receive HBO therapy (NHBO group [n=14]). Each group was divided into 2 subgroups according to the type of bone graft material: a biphasic calcium phosphate (BCP) subgroup and an Escherichia coli-derived recombinant human bone morphogenetic protein-2-/epigallocatechin-3-gallate-coated BCP (mBCP) subgroup. Two identical circular defects with a 6-mm diameter were made in the right and left parietal bones of each rat. One defect was grafted with bone graft material (BCP or mBCP). The other defect was not grafted. The HBO group received 2 weeks of adjunctive HBO therapy (1 hour, 5 times a week). The rats were euthanized 8 weeks after surgery. The specimens were prepared for histologic analysis. Results: New bone (%) was higher in the NHBO-mBCP group than in the NHBO-BCP and control groups (P<0.05). Blood vessel count (%) and vascular endothelial growth factor staining (%) were higher in the HBO-mBCP group than in the NHBO-mBCP group (P<0.05). Conclusions: HBO therapy did not have a positive influence on bone formation irrespective of the type of bone graft material applied after 8 weeks of healing. HBO therapy had a positive effect on angiogenic activity.

Deriving Local Association Rules by User Segmentation (사용자 구분에 의한 지역적 연관규칙의 유도)

  • Park, Se-Il;Lee, Soo-Wun
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.53-64
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    • 2002
  • Association rule discovery is a method that detects associative relationships between items or attributes in transactions. It is one of the most widely studied problems in data mining because it offers useful insight into the types of dependencies that exist in a data set. However, most studies on association rule discovery have the drawback that they can not discover association rules among user groups that have common characteristics. To solve this problem, we segment the set of users into user-subgroups by using feature selection and the user segmentation, thus local association rules in user-subgroup can be discovered. To evaluate that the local association rules are more appropriated than the global association rules in each user-subgroup, derived local association rules are compared with global association rules in terms of several evaluation measures.

Development of Reproducible EST-derived SSR Markers and Assessment of Genetic Diversity in Panax ginseng Cultivars and Related Species

  • Choi, Hong-Il;Kim, Nam-Hoon;Kim, Jun-Ha;Choi, Beom-Soon;Ahn, In-Ok;Lee, Joon-Soo;Yang, Tae-Jin
    • Journal of Ginseng Research
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    • v.35 no.4
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    • pp.399-412
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    • 2011
  • Little is known about the genetics or genomics of Panax ginseng. In this study, we developed 70 expressed sequence tagderived polymorphic simple sequence repeat markers by trials of 140 primer pairs. All of the 70 markers showed reproducible polymorphism among four Panax species and 19 of them were polymorphic in six P. ginseng cultivars. These markers segregated 1:2:1 manner of Mendelian inheritance in an $F_2$ population of a cross between two P. ginseng cultivars, 'Yunpoong' and 'Chunpoong', indicating that these are reproducible and inheritable mappable markers. A phylogenetic analysis using the genotype data showed three distinctive groups: a P. ginseng-P. japonicus clade, P. notoginseng and P. quinquefolius, with similarity coefficients of 0.70. P. japonicus was intermingled with P. ginseng cultivars, indicating that both species have similar genetic backgrounds. P. ginseng cultivars were subdivided into three minor groups: an independent cultivar 'Chunpoong', a subgroup with three accessions including two cultivars, 'Gumpoong' and 'Yunpoong' and one landrace 'Hwangsook' and another subgroup with two accessions including one cultivar, 'Gopoong' and one landrace 'Jakyung'. Each primer pair produced 1 to 4 bands, indicating that the ginseng genome has a highly replicated paleopolyploid genome structure.

Lack of Associations of the COMT Val158Met Polymorphism with Risk of Endometrial and Ovarian Cancer: a Pooled Analysis of Case-control Studies

  • Liu, Jin-Xin;Luo, Rong-Cheng;Li, Rong;Li, Xia;Guo, Yu-Wu;Ding, Da-Peng;Chen, Yi-Zhi
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.15
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    • pp.6181-6186
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    • 2014
  • This meta-analysis was conducted to examine whether the genotype status of Val158Met polymorphism in catechol-O-methyltransferase (COMT) is associated with endometrial and ovarian cancer risk. Eligible studies were identified by searching several databases for relevant reports published before January 1, 2014. Pooled odds ratios (ORs) were appropriately derived from fixed-effects or random-effects models. In total, 15 studies (1,293 cases and 2,647 controls for ovarian cancer and 2,174 cases and 2,699 controls for endometrial cancer) were included in the present meta-analysis. When all studies were pooled into the meta-analysis, there was no evidence for significant association between COMT Val158Met polymorphism and ovarian cancer risk (Val/Met versus Val/Val: OR=0.91, 95% CI=0.76-1.08; Met/Met versus Val/Val: OR=0.90, 95% CI=0.73-1.10; dominant model: OR=0.90, 95% CI=0.77-1.06; recessive model: OR=0.95, 95% CI=0.80-1.13). Similarly, no associations were found in all comparisons for endometrial cancer (Val/Met versus Val/Val: OR 0.97, 95% CI=0.77-1.21; Met/Met versus Val/Val: OR=1.02, 95% CI=0.73-1.42; dominant model: OR=0.98, 95% CI=0.77-1.25; recessive model: OR=1.02, 95% CI=0.87-1.20). In the subgroup analyses by source of control and ethnicity, no significant associations were found in any subgroup of population. This meta-analysis strongly suggests that COMT Val158Met polymorphism is not associated with increased endometrial and ovarian cancer risk.