EF-Index: Determining number of clusters (K) to estimate number of segments (S) in an image

2019 ◽  
Vol 88 ◽  
pp. 29-40
Author(s):  
Mrinal Kanti Bhowmik ◽  
Tathagata Debnath ◽  
Debotosh Bhattacharjee ◽  
Paramartha Dutta
Keyword(s):  
Number Of Clusters ◽  
Number Of Segments ◽  
Estimate Number

Cluster Analysis of Antigenic Profiles of Tumors: Selection of Number of Clusters Using Akaike’s Information Criterion

1990 ◽  
Vol 29 (03) ◽  
pp. 200-204 ◽  
Author(s):  
J. A. Koziol
Keyword(s):  
Cluster Analysis ◽  
Basic Problem ◽  
Information Criterion ◽  
Akaike's Information Criterion ◽  
Cell Surface Antigens ◽  
Number Of Clusters ◽  
Akaike’S Information Criterion ◽  
Multinomial Data ◽  
Tumor Types ◽  
Selection Of

AbstractA basic problem of cluster analysis is the determination or selection of the number of clusters evinced in any set of data. We address this issue with multinomial data using Akaike’s information criterion and demonstrate its utility in identifying an appropriate number of clusters of tumor types with similar profiles of cell surface antigens.

HEXACO personality factors and their associations with Facebook use and Facebook network characteristics

2018 ◽  
Author(s):  
Riana Brown ◽  
Sam G. B. Roberts ◽  
Thomas V. Pollet
Keyword(s):  
Social Networks ◽  
Network Size ◽  
Openness To Experience ◽  
Personality Factors ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Online Networks ◽  
Facebook Use ◽  
Objectively Measured ◽  
Size And Structure

Personality factors affect the properties of ‘offline’ social networks, but how they are associated with the structural properties of online networks is still unclear. We investigated how the six HEXACO personality factors (Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness and Openness to Experience) relate to Facebook use and three objectively measured Facebook network characteristics - network size, density, and number of clusters. Participants (n = 107, mean age = 20.6, 66% female) extracted their Facebook networks using the GetNet app, completed the 60-item HEXACO questionnaire and the Facebook Usage Questionnaire. Users high in Openness to Experience spent less time on Facebook. Extraversion was positively associated with network size and the number of network clusters (but not after controlling for size). These findings suggest that personality factors are associated with Facebook use and the size and structure of Facebook networks, and that personality is an important influence on both online and offline sociality.

Clustering Count-based RNA Methylation Data Using a Nonparametric Generative Model

2018 ◽  
Vol 14 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Lin Zhang ◽  
Yanling He ◽  
Huaizhi Wang ◽  
Hui Liu ◽  
Yufei Huang ◽  
...  
Keyword(s):  
Clustering Analysis ◽  
Methylation Level ◽  
Optimal Number ◽  
Generative Model ◽  
Methylation Data ◽  
Sequencing Data ◽  
Number Of Clusters ◽  
Rna Methylation ◽  
Clustering Effect ◽  
Optimal Number Of Clusters

Background: RNA methylome has been discovered as an important layer of gene regulation and can be profiled directly with count-based measurements from high-throughput sequencing data. Although the detailed regulatory circuit of the epitranscriptome remains uncharted, clustering effect in methylation status among different RNA methylation sites can be identified from transcriptome-wide RNA methylation profiles and may reflect the epitranscriptomic regulation. Count-based RNA methylation sequencing data has unique features, such as low reads coverage, which calls for novel clustering approaches. <P><P> Objective: Besides the low reads coverage, it is also necessary to keep the integer property to approach clustering analysis of count-based RNA methylation sequencing data. <P><P> Method: We proposed a nonparametric generative model together with its Gibbs sampling solution for clustering analysis. The proposed approach implements a beta-binomial mixture model to capture the clustering effect in methylation level with the original count-based measurements rather than an estimated continuous methylation level. Besides, it adopts a nonparametric Dirichlet process to automatically determine an optimal number of clusters so as to avoid the common model selection problem in clustering analysis. <P><P> Results: When tested on the simulated system, the method demonstrated improved clustering performance over hierarchical clustering, K-means, MClust, NMF and EMclust. It also revealed on real dataset two novel RNA N6-methyladenosine (m6A) co-methylation patterns that may be induced directly by METTL14 and WTAP, which are two known regulatory components of the RNA m6A methyltransferase complex. <P><P> Conclusion: Our proposed DPBBM method not only properly handles the count-based measurements of RNA methylation data from sites of very low reads coverage, but also learns an optimal number of clusters adaptively from the data analyzed. <P><P> Availability: The source code and documents of DPBBM R package are freely available through the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/DPBBM/.

A Multi-parameter Joint Warning Mechanism for Physical Condition Monitoring System in Physical Education

2020 ◽  
Vol 14 (1) ◽  
pp. 113-119
Author(s):  
Zhang Su
Keyword(s):  
Physical Education ◽  
False Alarm ◽  
Real Time ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Early Warning ◽  
Physical Condition ◽  
School Students ◽  
Early Warning Mechanism ◽  
Number Of Segments

Background: In recent years, sudden deaths of primary and secondary school students caused by sports activities have drawn great attention in education and medical circles. It is necessary for schools to monitor the physical condition of the students in order to reasonably set the duration of their physical activity. At present, the physical condition monitoring instruments used in various hospitals are expensive, bulky, and difficult to operate, and the detection process is complicated. Therefore, existing approaches cannot meet the needs of physical education teachers on campus for detecting the physical condition of students. Methods: This study designs a portable human-physiological-state monitoring and analysis system. Real-time communication between a wearable measurement device and a monitoring device can be ensured by real-time detection of the environment and power control of the transmitted signal. Results: From a theoretical point of view, the larger the number of segments M, the more significantly the reduction of false alarm probability. The simulation results also show this fact. Compared with the conventional early warning mechanism, the probability of a false alarm for the proposed system is lower, and the greater the number of segments, the faster its reaction speed. Conclusion: The portable monitoring system of student physical condition for use in physical education of primary and middle school students proposed in this paper ensures real-time monitoring of the members within the system in an open environment, and further proposes an early warning mechanism for combining multiple vital sign parameters. In addition, the proposed system functions faster; the average early warning time required is only one-quarter of that of the conventional system.

Estimating the number of cases during COVID-19 pandemics using a web-based tool: first week results of “COVID-19 TRENDS” social media project in the Araba-Alava province in Basque country, Spain. (Preprint)

2020 ◽  
Author(s):  
Ignacio Garitano ◽  
Manuel Linares ◽  
Laura Santos ◽  
Ruth Gil ◽  
Elena Lapuente ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Response Rate ◽  
Basque Country ◽  
Case Definition ◽  
Public Health Action ◽  
Web Based ◽  
Health Action ◽  
Estimate Number ◽  
Media Project

UNSTRUCTURED On 28th February a case of COVID-19 was declared in Araba-Álava province, Spain. In Spain, a confinement and movement restrictions were established by Spanish Government at 14th March 2020. We implemented a web-based tool to estimate number of cases during the pandemic. We present the results in Áraba-Álava province. We reached a response rate of 10,3% out a 331.549 population. We found that 22,4 % fulfilled the case definition. This tool rendered useful to inform public health action.

Assessment of automatic segmentation accuracy with various point cloud density

2020 ◽  
Vol 961 (7) ◽  
pp. 47-55
Author(s):  
A.G. Yunusov ◽  
A.J. Jdeed ◽  
N.S. Begliarov ◽  
M.A. Elshewy
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Reference Data ◽  
Automatic Segmentation ◽  
Geometric Accuracy ◽  
Segmentation Method ◽  
Segmentation Methods ◽  
Segmentation Accuracy ◽  
Number Of Segments ◽  
Cloud Density

Laser scanning is considered as one of the most useful and fast technologies for modelling. On the other hand, the size of scan results can vary from hundreds to several million points. As a result, the large volume of the obtained clouds leads to complication at processing the results and increases the time costs. One way to reduce the volume of a point cloud is segmentation, which reduces the amount of data from several million points to a limited number of segments. In this article, we evaluated effect on the performance, the accuracy of various segmentation methods and the geometric accuracy of the obtained models at density changes taking into account the processing time. The results of our experiment were compared with reference data in a form of comparative analysis. As a conclusion, some recommendations for choosing the best segmentation method were proposed.

scholarly journals Population density, activity centres, and pandemic: Visualizing clusters of COVID-19 cases in Hong Kong

2021 ◽  
pp. 0308518X2110127
Author(s):  
Jiangping Zhou ◽  
Sam KS Ho ◽  
Shuyu Lei ◽  
Valarie CK Pang
Keyword(s):  
Hong Kong ◽  
Population Density ◽  
Spatial Patterns ◽  
Number Of Clusters ◽  
The Third ◽  
General Number

The impacts of coronavirus disease 2019 (COVID-19) on society and economy are wide-ranging, long-lasting, and global. The experience of multiple countries or regions in fighting the pandemic indicates that there could be multiple COVID-19 surges, where a growing number of cases can be observed in the more recent surge(s). Were COVID-19 cases and clusters of cases (across surges) randomly distributed in spaces? Did population density and activity centres influence clusters of cases and associated venues? Based on information on the associated venues of the four surges of COVID-19 cases between January 2020 and February 2021 as well as population density, visuals were made to distinguish the relationships between population density, activity centres, and clusters of cases in Hong Kong. Different spatial patterns were observed across the four surges: fewer cases were observed in the first surge with a more evenly distributed pattern of clusters; the second surge as compared to the first surge saw a wider distribution and an increase in the number/layer of clusters; compared to the second surge, the third surge suffered from many more cases but saw a decrease in the general number of clusters; and compared to the previous three surges, the fourth surge had the largest number of cases, yet even fewer clusters were observed, where several clusters are again concentrated in specific areas similar to the previous surge. Across the four surges, a few locales could see recurrent clusters of cases and a few communities were without cases.

scholarly journals Dependence of Power Characteristics on Savonius Rotor Segmentation

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2912
Author(s):  
Krzysztof Doerffer ◽  
Janusz Telega ◽  
Piotr Doerffer ◽  
Paulina Hercel ◽  
Andrzej Tomporowski
Keyword(s):  
High Wind ◽  
Horizontal Axis Wind Turbine ◽  
Savonius Rotor ◽  
Power Characteristics ◽  
Wind Speeds ◽  
Single Segment ◽  
High Elongation ◽  
Low Wind Speeds ◽  
Number Of Segments ◽  
Rotor Type

Savonius rotors are large and heavy because they use drag force for propulsion. This leads to a larger investment in comparison to horizontal axis wind turbine (HAWT) rotors using lift forces. A simple construction of the Savonius rotor is preferred to reduce the production effort. Therefore, it is proposed here to use single-segment rotors of high elongation. Nevertheless, this rotor type must be compared with a multi-segment rotor to prove that the simplification does not deteriorate the effectiveness. The number of segments affects the aerodynamic performance of the rotor, however, the results shown in the literature are inconsistent. The paper presents a new observation that the relation between the effectiveness of single- and multi-segment rotors depends on the wind velocity. A single-segment rotor becomes significantly more effective than a four-segment rotor at low wind speeds. At high wind speeds, the effectiveness of both rotors becomes similar.

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