• 제목/요약/키워드: cluster sets

검색결과 223건 처리시간 0.024초

합리적 농촌지역정책 추진을 위한 지역선정방법 개선방안 (The Improvement of Planning Area Specifying Method for Rational Rational Rural Policy Implementaion)

  • 송두범;김남선
    • 한국농촌계획학회:학술대회논문집
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    • 한국농촌계획학회 1998년도 임시총회 및 추계 학술논문발표회
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    • pp.25-27
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    • 1998
  • The objective of this study is by analyzing villages("Ri" units) to specify the proper unit of the area that the rural development policy is suitable for, and to examine whether the current rural development policy considers the characteristics of community and region. The study included twelve districts(in Korean "Eup" or "Myun") and one hundred one villages(in Korean ri) in Poryong-si, Chungchungnam-do. Twelve and fifteen variables are respectively employe for the analysis of Myun`s and Ri`s. Using Factor Analysis, Cluster Analysis, and Z-Score Analysis, the study examines the degree of disadvantage and the process of growth pattern of each Myun or Ri. The Ri`s are also classified according to their functional characteristics. The results of this study could be summarized as follows; 1) There exist some problems in the current rural development policy because it does not take into consideration the characteristics community and region. 2) Except a few distinct of areas, the proper unit of the area for the rural development policy should be set being based on regional characteristics rather than the administrative units. 3) The spatial boundary of rural development policy should be sets from villages(ri) to beyond the unit of administrative units("Si" or "Gun"), according to the village unit analysis. 4) It is needed that community and region data should be consistently accumulated after specifying Standard Statistical Districts. 5) The application of indicators should be in accordance with the characteristics of the policy.

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점진적 프로젝션을 이용한 고차원 글러스터링 기법 (High-Dimensional Clustering Technique using Incremental Projection)

  • 이혜명;박영배
    • 한국정보과학회논문지:데이타베이스
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    • 제28권4호
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    • pp.568-576
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    • 2001
  • 대부분의 클러스터링 알고리즘들은 고차원 공간에서 성능이 급격히 저하되는 경향이 있다. 더욱이 고차원 데이타는 상당한 양의 잡음 데이타를 포함하고 있으므로 알고리즘의 추가적인 효과성 문제를 야기한다. 그러므로 고차원 데이타의 구조와 특성을 지원하는 적합한 클러스터링 기법이 개발되어야 한다. 본 논문에서는 선형변환 프로젝션을 이용한 클러스터링 알고리즘 CLIP을 제안한다. CLIP은 고차원 클러스터링의 효율성 및 효과성 문제를 극복하기 위해 개발되었으며, 클러스터 형성에 밀접하게 연관된 부분 공간에서 클러스터를 탐사하는 기법이다. 알고리즘의 주요 사상은 각1차원적 부분공간에서의 클러스터링에 기본을 두고 있지만. 점진적인 프로젝션을 이용하여 고차원 클러스터를 탐사한 뿐만 아니라 연산을 획기적으로 줄인다. CLIP의 성능을 평가하기 위해 합성 데이타를 이용한 일련의 실험을 통하여 효율성 및 효과성을 증명한다

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광역지질도 작성을 위한 ISODATA 응용 (An Application of ISODATA Method for Regional Lithological Mapping)

  • 朴鍾南;徐延熙
    • 대한원격탐사학회지
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    • 제5권2호
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    • pp.109-122
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    • 1989
  • The ISODATA method, which is one of the most famous of the square-error clustering methos, has been applied to two Chungju multivariate data sets in order to evaluate the effectiveness of the regional lithological mapping. One is an airborne radiometric data set and the other is a mixed data set of the airborne radiometric and Landsat TM data. In both cases, the classification of the Bulguksa granite and the Kyemyongsan biotite-quartz gneiss are the most successful. Hyangsanni dolomitic limestone and neighboring Daehyangsan quartzite are also classified by their typical lowness of the radioactive intensities, though it is still confused with some others such as water-covered areas and nearby alluvials, and unaltered limestone areas. Topographically rugged valleys are also classified as the same cluster as above. This could be due to unavoidable variations of flight height and the attitude of the airborne system in such rugged terrains. The regional geological mapping of sedimentary rock units of the Ockchun System is in general confused. This might be due to similarities between different sediments. Considarable discrepancies occurred in mapping some lithological boundaries might also be due to secondary effects such as contamination or smoothing in digitizing process. Further study should be continued in the variable selection scheme as no absolutely superior method claims to exist yet since it seems somewhat to be rather data dependent. Study could also be made on the data preprocessing in order to reduce the erratic effects as mentioned above, and thus hoprfully draw much better result in regional geological mapping.

Topic Analysis of Scholarly Communication Research

  • Ji, Hyun;Cha, Mikyeong
    • Journal of Information Science Theory and Practice
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    • 제9권2호
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    • pp.47-65
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    • 2021
  • This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

Parallel Algorithm of Improved FunkSVD Based on Spark

  • Yue, Xiaochen;Liu, Qicheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권5호
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    • pp.1649-1665
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    • 2021
  • In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

Cloud Task Scheduling Based on Proximal Policy Optimization Algorithm for Lowering Energy Consumption of Data Center

  • Yang, Yongquan;He, Cuihua;Yin, Bo;Wei, Zhiqiang;Hong, Bowei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권6호
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    • pp.1877-1891
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    • 2022
  • As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

중소병원 간호관리자의 직무경험에 대한 현상학적 연구 (A Phenomenological Study on the Job Experience of Nursing Managers in Small and Medium Hospitals)

  • 김가은;한숙정
    • 한국보건간호학회지
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    • 제36권2호
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    • pp.196-211
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    • 2022
  • Purpose: This is a phenomenological study to improve the quality of nursing and understand its essence by comprehensively analyzing job experience of nursing managers in small and medium. Methods: This study focused on deriving the common empirical attributes of all the study participants, rather than their individual attributes. Data on the job experiences of nine nurse managers in small and medium-sized hospitals were collected and analyzed using Colaizzi's phenomenological method. Result: The job experiences of nurse managers in small and medium hospitals were classified after analysis into 14 theme cluster sets and 34 themes in five categories. The categories derived were 'A feeling of pressure as if taking responsibility for the entire hospital', 'Taking on the difficulties of hiring a nurse alone.' 'Difficulty in mediating conflicts within the organization', 'Struggling to endure', 'To take root in the field with a sense of ownership'. Conclusion: This study is meaningful in helping nursing managers in small and medium hospitals perform their duties more efficiently and stably by understanding their job experience.

Comprehensive Transcriptomic Analysis of Cordyceps militaris Cultivated on Germinated Soybeans

  • Yoo, Chang-Hyuk;Sadat, Md. Abu;Kim, Wonjae;Park, Tae-Sik;Park, Dong Ki;Choi, Jaehyuk
    • Mycobiology
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    • 제50권1호
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    • pp.1-11
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    • 2022
  • The ascomycete fungus Cordyceps militaris infects lepidopteran larvae and pupae and forms characteristic fruiting bodies. Owing to its immune-enhancing effects, the fungus has been used as a medicine. For industrial application, this fungus can be grown on geminated soybeans as an alternative protein source. In our study, we performed a comprehensive transcriptomic analysis to identify core gene sets during C. militaris cultivation on germinated soybeans. RNA-Seq technology was applied to the fungal cultures at seven-time points (2, 4, and 7-day and 2, 3, 5, 7-week old cultures) to investigate the global transcriptomic change. We conducted a time-series analysis using a two-step regression strategy and chose 1460 significant genes and assigned them into five clusters. Characterization of each cluster based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases revealed that transcription profiles changed after two weeks of incubation. Gene mapping of cordycepin biosynthesis and isoflavone modification pathways also confirmed that gene expression in the early stage of GSC cultivation is important for these metabolic pathways. Our transcriptomic analysis and selected genes provided a comprehensive molecular basis for the cultivation of C. militaris on germinated soybeans.

A Hybrid Blockchain-Based Approach for Secure and Efficient IoT Identity Management

  • Abdulaleem Ali Almazroi;Nouf Atiahallah Alghanmi
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.11-25
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    • 2024
  • The proliferation of IoT devices has presented an unprecedented challenge in managing device identities securely and efficiently. In this paper, we introduce an innovative Hybrid Blockchain-Based Approach for IoT Identity Management that prioritizes both security and efficiency. Our hybrid solution, strategically combines the advantages of direct and indirect connections, yielding exceptional performance. This approach delivers reduced latency, optimized network utilization, and energy efficiency by leveraging local cluster interactions for routine tasks while resorting to indirect blockchain connections for critical processes. This paper presents a comprehensive solution to the complex challenges associated with IoT identity management. Our Hybrid Blockchain-Based Approach sets a new benchmark for secure and efficient identity management within IoT ecosystems, arising from the synergy between direct and indirect connections. This serves as a foundational framework for future endeavors, including optimization strategies, scalability enhancements, and the integration of advanced encryption methodologies. In conclusion, this paper underscores the importance of tailored strategies in shaping the future of IoT identity management through innovative blockchain integration.

이단계 군집분석에 의한 농촌관광 편의시설 유형별 소비자 선호 결정요인 (Determinants of Consumer Preference by type of Accommodation: Two Step Cluster Analysis)

  • 박덕병;윤유식;이민수
    • 마케팅과학연구
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    • 제17권3호
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    • pp.1-19
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    • 2007
  • 본 연구에서는 농촌관광 방문객에게 제공되는 편의시설을 유형화하고 어떤 특징을 가진 방문객이 어떤 편의시설을 선호하는지를 규명하기 위한 방법과 그 분석결과를 제시하였다. 이를 위하여 우선 2단계 군집분석법을 사용하여 농촌관광 편의시설을 유형화하였다. 그 다음으로 군집분석에 사용되는 변인이 범주형 변인이 있을 경우 전통적인 군집분석 방법을 적용할 수 없기 때문에 2단계 군집분석을 하였다. 본 연구는 2단계 군집분석법이 범주형 변인으로 측정된 농촌관광의 편의시설을 유형화하는 데 매우 유용하다는 것을 보여 주고 있다. 다중로짓 모형을 사용하여 특정 편의시설 유형을 선호할 확률에 영향을 미치는 농촌관광 방문자의 사회인구학적 특성과 여행특성을 규명하였다. 즉, 다중로짓 모형을 통해 참조항(일반농가형)으로 설정된 편의시설 유형에 비해 특정 편의시설을 선호할 확률에 영향을 미치는 소비자의 특성을 규명할 수 있다는 것이 본 연구의 특징이다.

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