• 제목/요약/키워드: cluster identification

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The Formation of Innovative Clusters in Kazakhstan: Analysis and Methods for Identifying Specialization

  • Kireyeva, Anel A.;Nurlanova, Nailya K.
    • The Journal of Asian Finance, Economics and Business
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    • 제1권1호
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    • pp.23-30
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    • 2014
  • The aim of this research is theoretical and methodological approaches to the necessity of formation of innovation clusters as growth poles on the basis of statistical analysis and identification of specialization. In this research, we used methods, which will allow to analyze of innovative processes and to identify of prospective branches of specialization of the formation of innovative clusters in the spatial context. Keeping with the previous literature, the present study is determined by the novelty of the problem, concerning the formation and development of innovative clusters as growth poles, as well as large specifics of problems in our country in the framework of use of innovative clusters. An analysis was showed that Kazakhstan's regions have substantial differences in the groups of regions for most of the indicators have presented form a tightly located clusters and in the ratings of innovative susceptibility and innovative activity. This research has some practical implications, which have proved that innovative clusters become platforms as growth poles for introduction of advanced technologies, development of innovative companies, thereby providing a certain stability of the economy of the regions.

Unity in HIV-1 Sequence Diversity: Identification and Characterization of Korean Clade in HIV-1 Isolated from Korean

  • Lee, Chan-Hee
    • 한국미생물학회:학술대회논문집
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    • 한국미생물학회 2006년도 International Meeting of the Microbiological Society of Korea
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    • pp.129-131
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    • 2006
  • Through molecular phylogenetic analysis using the nef gene sequences of HIV-l isolated from Korean registered in the NCBI GenBank together with 41 reference strains and 94 foreign isolates, we verified that most (${\sim}80%$) of Korean isolates belonged to subtype B and 78% of subtype B were clustered together exclusively of foreign isolates, and this cluster was named Korean clade subtype B ($K_cB$). Similarity study suggested that the $K_cB$ cluster was more homogeneous than and clearly distinctive from the non-Korean subtype B ($NK_cB$). Comparison of the consensus amino acid sequences of the $K_cB\;or\;NK_cB$ revealed characteristic $K_cB$ signature amino acid pattern comprised of 13 amino acid residues. The $K_cB$ signature amino acid residues were critical in separating the $K_cB$ ftom the $NK_cB$, since substitution of the $NK_cB$ sequences with $K_cB$ signature amino acids relocated them to the Koran clade, and vice versa. Synonymous and nonsynonymous substitution rate study suggested positive selection event for the $K_cB$.

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Identification of failure mechanisms for CFRP-confined circular concrete-filled steel tubular columns through acoustic emission signals

  • Li, Dongsheng;Du, Fangzhu;Chen, Zhi;Wang, Yanlei
    • Smart Structures and Systems
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    • 제18권3호
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    • pp.525-540
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    • 2016
  • The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

건설사고 분석을 위한 텍스트 마이닝 기반 데이터 전처리 및 사고유형 분석 (Text mining-based Data Preprocessing and Accident Type Analysis for Construction Accident Analysis)

  • 윤영근;이재윤;오태근
    • 한국안전학회지
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    • 제37권2호
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    • pp.18-27
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    • 2022
  • Construction accidents are difficult to prevent because several different types of activities occur simultaneously. The current method of accident analysis only indicates the number of occurrences for one or two variables and accidents have not reduced as a result of safety measures that focus solely on individual variables. Even if accident data is analyzed to establish appropriate safety measures, it is difficult to derive significant results due to a large number of data variables, elements, and qualitative records. In this study, in order to simplify the analysis and approach this complex problem logically, data preprocessing techniques, such as latent class cluster analysis (LCCA) and predictor importance were used to discover the most influential variables. Finally, the correlation was analyzed using an alluvial flow diagram consisting of seven variables and fourteen elements based on accident data. The alluvial diagram analysis using reduced variables and elements enabled the identification of accident trends into four categories. The findings of this study demonstrate that complex and diverse construction accident data can yield relevant analysis results, assisting in the prevention of accidents.

Identification of pollutant sources and evaluation of water quality improvement alternatives of the Geum river

  • shiferaw, Natnael;Kim, Jaeyoung;Seo, Dongil
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.475-475
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    • 2022
  • The aim of this study is to identify the significant pollutant sources from the tributaries that are affecting the water quality of the study site, the Geum River and provide a solution to enhance the water quality. Multivariate statistical analysis modles such as cluster analysis, Principal component analysis (PCA) and positive matrix factorization (PMF) were applied to identify and prioritize the major pollutant sources of the two major tributaries, Gab-cheon and Miho-cheon, of the Geum River. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant (WWTP), urban, and agricultural pollutions are identified as major pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. On the contrary, PMF identifies three pollutant sources in Gab-cheon, same as PCA result and two pollutant sources in Miho-cheon. Water quality control scenarios are formulated and improvement of water quality in the river locations are simulated and analyzed with the Environmental Fluid Dynamic Code (EFDC) model. Scenario results were evaluated using a water quality index developed by Canadian Council of Ministers of the Environment. PCA and PMF appears to be effective to identify water pollution sources for the Geum river and also its tributaries in detail and thus can be used for the development of water quality improvement alternative of the above water bodies.

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Identifying Cluster Patterns in Relationship Between Municipal Revenue Configuration and Fiscal Surplus: Application of Machine Learning Methodologies

  • Im Chunghyeok;Ryou Jaemin;Han JunHyun;Bae Jayon
    • International Journal of Advanced Culture Technology
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    • 제12권3호
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    • pp.159-164
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    • 2024
  • Net surplus serves as a crucial indicator of how efficiently local governments utilize their resources. This study aims to analyze and categorize the patterns of net surplus across 75 local governments in Korea. By employing machine learning techniques such as K-means clustering and silhouette analysis, this research delves into surplus patterns, revealing insights that differ from those provided by traditional analytical methods. Machine learning enables a broader spectrum of discoveries, leading us to identify three distinct clusters in the net surplus of Korean local finances. The characteristics of these three clusters show that the wealthiest cities have the highest surplus ratios. In contrast, mid-sized municipalities, constrained by limited central government support and scarce local resources, exhibit the lowest surplus ratios. Interestingly, a significant number of cities maintain a median surplus ratio even under challenging fiscal conditions. Additionally, we identify critical thresholds that differentiate the three clusters: a grant-in-aid ratio of 19.31%, a debt ratio of 3.52%, and a local tax ratio of 25.58%. This identification of thresholds is a key contribution of our study, as these specific thresholds have not been previously addressed in the literature.

SSR Marker를 이용한 감귤속 품종 및 유전자원에 대한 DNA Profile Data Base 구축 (A Database of Simple Sequence Repeat (SSR) Marker-Based DNA Profiles of Citrus and Related Cultivars and Germplasm)

  • 홍지화;채치원;최근진;권용삼
    • 원예과학기술지
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    • 제34권1호
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    • pp.142-153
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    • 2016
  • 국내외에서 재배되고 있는 감귤속 식물 108 품종 및 유전자원과 SSR 마커를 활용하여 유전적 유사도 분석을 통한 품종식별력 검정 등에 대한 연구를 수행하였다. 감귤 8품종을 203개의 SSR 마커로 검정하여 반복 재현성이 높은 뿐만 아니라 다형성 정도가 높은 18개를 선정하였다. 이들 마커와 국내외에서 재배되고 있는 감귤 108품종을 검정하였을 때 마커당 평균 대립유전자수는 9.28개로 나타났고, 5-14개까지 다양한 분포를 나타내었다. PIC 값은 분자표지에 따라 0.417-0.791 범위에 속하였으며 평균값은 0.606으로 나타났다. 감귤류 108품종에 대하여 계통도를 작성하였을 때 감귤류 식물의 분류학적 특성 및 품종 육성의 계보도에 따라 13개의 그룹으로 크게 나누어졌다. 감귤류 식물 품종중 오렌지나 온주 밀감의 경우 대부분의 품종이 SSR 마커의 유전자형에 의해 구분이 되지 않은 것으로 나타났다. 본 연구에서 개발된 감귤속 식물의 품종별 SSR DNA 프로파일 데이터베이스는 감귤속 식물의 유전자원 특성평가와 육종가의 지식재산권 보호의 수단으로 유용하게 활용될 수 있을 것이다.

Identification of the Hybrid Cluster Protein, HCP, from Amitochondriate Eukaryotes and Its Phylogenetic Implications

  • Han, Kyu-Lee;Yong, Tai-Soon;Ryu, Jae-Sook;Hwang, Ui-Wook;Park, Soon-Jung
    • Journal of Microbiology and Biotechnology
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    • 제14권1호
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    • pp.134-139
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    • 2004
  • Hybrid cluster protein (HCP) was investigated because of its unique iron-sulfur clusters, which have been found in bacteria and archaea. Here, HCP homologous proteins from the third domain, 'eukarya'(3 amitochondriate protozoans, Giardia lamblia, Entamoeba histolytica, and Trichomonas vaginalis), were identified. All three amitochondriate protozoan HCPs (GlHCP, EhHCP, and TvHCP) belonged to Class I on the basis of two key characters, the cysteine spacing, Cys-(Xaa)₂Cys(Xaa)/sub 7-8/-Cys(Xaa)/sub 5/-Cys, and the absence of N-terminal deletion characteristic to the Class III. In phylogenetic analysis performed with amino acid sequences of 3 eukaryal, 5 bacterial, and 4 archaeal HCPs, the maximum likelihood (ML) tree indicated that TvHCP was clustered with Class I HCPs, whereas the other two HCPs (GlHCP and EhHCP) formed an independent clade with a high bootstrapping value (96%) not belonging to any previously recognized HCP class. In spite of the relatively lower bootstrapping value (61%), the position of the new eukaryal GlHCP-EhHCP clade was close to Class I, including the TvHCP, and Classes II and III were closely related with each other. The finding of eukaryal HCPs would help to understand the evolutionary history of HCP.

Genetic Diversity Studies and Identification of Molecular and Biochemical Markers Associated with Fusarium Wilt Resistance in Cultivated Faba Bean (Vicia faba)

  • Mahmoud, Amer F.;Abd El-Fatah, Bahaa E.S.
    • The Plant Pathology Journal
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    • 제36권1호
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    • pp.11-28
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    • 2020
  • Faba bean (Vicia faba L.) is one of the most important legume crops in Egypt. However, production of faba bean is affected by several diseases including fungal diseases. Fusarium wilt incited by Fusarium oxysporum Schlecht. was shown to be the most common wilt disease of faba bean in Assiut Governorate. Evaluation of 16 faba bean genotypes for the resistance to Fusarium wilt was carried out under greenhouse conditions. Three molecular marker systems (inter-simple sequence repeat [ISSR], sequence related amplified polymorphism [SRAP], and simple sequence repeat [SSR]) and a biochemical marker (protein profiles) were used to study the genetic diversity and detect molecular and biochemical markers associated with Fusarium wilt resistance in the tested genotypes. The results showed that certain genotypes of faba bean were resistant to Fusarium wilt, while most of the genotypes were highly susceptible. The percentage of disease severity ranged from 32.83% in Assiut-215 to 64.17% in Misr-3. The genotypes Assiut-215, Roomy-3, Marut-2, and Giza2 were the most resistant, and the genotypes Misr-3, Misr-1, Assiut-143, Giza-40, and Roomy-80 performed as highly susceptible. The genotypes Assiut-215 and Roomy-3 were considered as promising sources of the resistance to Fusarium wilt. SRAP markers showed higher polymorphism (82.53%) compared with SSR (76.85%), ISSR markers (62.24%), and protein profile (31.82%). Specific molecular and biochemical markers associated with Fusarium wilt resistance were identified. The dendrogram based on combined data of molecular and biochemical markers grouped the 16 faba bean genotypes into three clusters. Cluster I included resistant genotypes, cluster II comprised all moderate genotypes and cluster III contained highly susceptible genotypes.

Identification the Key Odorants in Different Parts of Hyla Rabbit Meat via Solid Phase Microextraction Using Gas Chromatography Mass Spectrometry

  • Xie, Yuejie;He, Zhifei;Lv, Jingzhi;Zhang, En;Li, Hongjun
    • 한국축산식품학회지
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    • 제36권6호
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    • pp.719-728
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    • 2016
  • The aim of this study was to explore the volatile compounds of hind leg, foreleg, abdomen and Longissimus dorsi in both male and female Hyla rabbit meat by solid phase microextraction tandem with gas chromatography mass spectrometry, and to seek out the key odorants via calculating the odor activity value and principal component analysis. Cluster analysis is used to study the flavor pattern differences in four edible parts. Sixty three volatile compounds were detected, including 23 aldehydes, 4 alcohols, 5 ketones, 11 esters, 5 aromatics, 8 acids and 7 hydrocarbons. Among them, 6 aldehydes and 3 acids were identified as the potential key odorants according to the ratio of concentration and threshold. The contents of volatile compounds in male Hyla rabbit meat were significantly higher than those in female one (p<0.05). The results of principal component analysis showed that the first two principal component cumulative variance contributions reach 87.69%; Hexanal, octanal, 2-nonenal, 2-decenal and decanal were regard as the key odorants of Hyla rabbit meat by combining odor activity value and principal component analysis. Therefore volatile compounds of rabbit meat can be effectively characterized. Cluster analysis indicated that volatile chemical compounds of Longissimus dorsi were significantly different from other three parts, which provide reliable information for rabbit processing industry and for possible future sale.