• 제목/요약/키워드: Cluster observation

검색결과 159건 처리시간 0.024초

의료서비스에서 혼합모형(Mixture model) 및 분석적 계층과정(AHP)를 이용한 입원환자의 시장세분화에 관한 연구 (Segmenting Inpatients by Mixture Model and Analytical Hierarchical Process(AHP) Approach In Medical Service)

  • 백수경;곽영식
    • 보건행정학회지
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    • 제12권2호
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    • pp.1-22
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    • 2002
  • Since the early 1980s scholars have applied latent structure and other type of finite mixture models from various academic fields. Although the merits of finite mixture model are well documented, the attempt to apply the mixture model to medical service has been relatively rare. The researchers aim to try to fill this gap by introducing finite mixture model and segmenting inpatients DB from one general hospital. In section 2 finite mixture models are compared with clustering, chi-square analysis, and discriminant analysis based on Wedel and Kamakura(2000)'s segmentation methodology schemata. The mixture model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture model is to unfix the sample, to Identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. In section 3 and 4 we illustrate results of segmenting 4510 patients data including menial and ratio scales. And then, we show AHP can be identify the attractiveness of each segment, in which the decision maker can select the best target segment.

비유사도 척도를 이용한 퍼지 데이터에 대한 퍼지 클러스터링 (Fuzzy Clustering of Fuzzy Data using a Dissimilarity Measure)

  • 이건명
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권9호
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    • pp.1114-1124
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    • 1999
  • 클러스터링은 동일한 클러스터에 속하는 데이타들 간에는 유사도가 크도록 하고 다른 클러스터에 속하는 데이타들 간에는 유사도가 작도록 주어진 데이타를 몇 개의 클러스터로 묶는 것이다. 어떤 대상을 기술하는 데이타는 수치 속성뿐만 아니라 정성적인 비수치 속성을 갖게 되고, 이들 속성값은 관측 오류, 불확실성, 주관적인 판정 등으로 인해서 정확한 값으로 주어지지 않고 애매한 값으로 주어지는 경우가 많다. 본 논문에서는 애매한 값을 퍼지값으로 표현하는 수치 속성과 비수치 속성을 포함한 데이타에 대한 비유사도 척도를 제안하고, 이 척도를 이용하여 퍼지값을 포함한 데이타에 대하여 퍼지 클러스터링하는 방법을 소개한 다음, 이를 이용한 실험 결과를 보인다. Abstract The objective of clustering is to group a set of data into some number of clusters in a way to minimize the similarity between data belonging to different clusters and to maximize the similarity between data belonging to the same cluster. Many data for real world objects consist of numeric attributes and non-numeric attributes whose values are fuzzily described due to observation error, uncertainty, subjective judgement, and so on. This paper proposes a dissimilarity measure applicable to such data and then introduces a fuzzy clustering method for such data using the proposed dissimilarity measure. It also presents some experiment results to show the applicability of the proposed clustering method and dissimilarity measure.

The Effect of Membership Concentration in FVQ/HMM for Speaker-Independent Speech Recognition

  • Lee, Chang-Young;Nam, Ho-Soo;Jung, Hyun-Seok;Lee, Chai-Bong
    • 음성과학
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    • 제12권4호
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    • pp.7-16
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    • 2005
  • We investigate the effect of membership concentration on the performance of the speaker-independent recognition system by FVQ/HMM. For the membership function, we adopt the result obtained from the objective function approach by Bezdek. Membership concentration is done by varying the exponent in the membership function. The number of selected clusters is constrained to two for the sake of cheap computational cost. Experimental results showed that the recognition rate has its maximum value when the membership function was taken to be inversely proportional to the distance of the input vector from the cluster centroid. When the membership concentration was two weak or too strong, the performance was found to be relatively poor as expected. Except these extreme cases, the membership concentration was not shown to affect the recognition rate significantly. This is in accordance with the general observation that the fuzzy system is not much sensitive. to the detailed shape of the membership function as long as it is overlapped over multiple classes.

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도시 대피시설 기능을 고려한 지하철역 지하 출입구의 파사드 디자인에 관한 연구 - 부산광역시 지하철역 1호선을 중심으로 - (A Study on the Facade Design of the Underground Entrance at Subway Station Considering the City Shelters' Functions - Focused on the Subway Station Line 1 in Busan -)

  • 허레이;김동식
    • 한국실내디자인학회논문집
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    • 제26권6호
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    • pp.180-190
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    • 2017
  • The subway station is not only an effective means to solve urban traffic problems, but also a kind of representative city shelters with a variety of functions such as urban beauty and disaster prevention. At the same time, the subway station as public facilities need activate the urban functions and through the effective design schemes for a variety of the facade of underground entrance to improve users' awareness and reliability for the subway station as a city shelters. This study is conducted to purpose the design direction considering design and disaster preventing characteristics of the underground subway station entrance. In addition, it will provide a basic reference for the subway station in the renovation and construction. The study is composed of literature reviews and field survey. The literature reviews through papers and documents related to the city shelters, the components and characteristics of city shelters, and components and characteristics of facade design of underground entrance at subway station. Before the field survey through the online surveys with evacuation capabilities and screening only the subway station. And field survey is conducted on the site with careful observation and confirmation. Last cluster analysis were applied to the finally selected samples by the SPSS Win18.0

Secure and Robust Clustering for Quantized Target Tracking in Wireless Sensor Networks

  • Mansouri, Majdi;Khoukhi, Lyes;Nounou, Hazem;Nounou, Mohamed
    • Journal of Communications and Networks
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    • 제15권2호
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    • pp.164-172
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    • 2013
  • We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

Genetic Distances of Rainbow Trout and Masu Salmon as Determined by PCR-Based Analysis

  • Yoon, Jong-Man
    • 한국발생생물학회지:발생과생식
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    • 제24권3호
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    • pp.241-248
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    • 2020
  • This study used a PCR-based genetic analysis platform to create a hierarchical polar dendrogram of Euclidean genetic distances for two salmonid species, Oncorhynchus mykiss (rainbow trout, RT) and Oncorhynchus masou (masu salmon, MS). The species were distantly related to other fish species based on PCR results from using the designed oligonucleotide primer series. Five oligonucleotide primers were used to generate 330 and 234 scorable fragments in the RT and MS populations, respectively. The DNA fragments ranged in size from approximately 50 bp to more than 2,000 bp. The bandsharing (BS) results showed that the RT population had a higher average BS value (0.852) than that for the MS population (0.704). The genetic distance between individuals supported the presence of adjacent affiliation in cluster I (RT 01-RT 11). The observation of a significant genetic distance between the two Oncorhynchus species verifies that this PCR-based technique can be a useful approach for individual- and population-based biological DNA investigations. The results of this type of investigation can be useful for species safekeeping and the maintenance of salmonid populations in the mountain streams of Korea.

The Effect of Corporate Governance on Tax Avoidance: The Role of Profitability as a Mediating Variable

  • SUNARTO, Sunarto;WIDJAJA, Budiadi;OKTAVIANI, Rachmawati Meita
    • The Journal of Asian Finance, Economics and Business
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    • 제8권3호
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    • pp.217-227
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    • 2021
  • This study aims to examine the effect of institutional ownership, independent board of commissioners, audit committee, and profitability (RNOA) on tax avoidance in banking companies listed on the Indonesia Stock Exchange over the 2014-2018 period. The sampling method employed in this study was the cluster sampling method. The population was all banking companies listed on the Indonesia Stock Exchange for the period 2014-2018. The sample selection results using the purposive sampling method during the observation includes 209 companies that published complete annual reports and their financial report notes as of December 31, 2018. The results revealed that institutional ownership and independent board of commissioners did not affect profitability. Profitability also did not affect tax avoidance. Further findings showed that institutional ownership and audit committee positively affect tax avoidance. From the result of Sobel test, this study indicated that profitability cannot mediate the effect of institutional ownership, independent board of commissioners, and audit committee on tax avoidance. This study has succeeded in proving empirically that there was a significant effect of the audit committee on profitability, institutional ownership on tax avoidance, and the audit committee on tax avoidance. Therefore, this study supports the agency theory and the research model from previous studies.

Improving Web Service Recommendation using Clustering with K-NN and SVD Algorithms

  • Weerasinghe, Amith M.;Rupasingha, Rupasingha A.H.M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권5호
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    • pp.1708-1727
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    • 2021
  • In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

A Metaheuristic Approach Towards Enhancement of Network Lifetime in Wireless Sensor Networks

  • J. Samuel Manoharan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권4호
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    • pp.1276-1295
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    • 2023
  • Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

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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