scholarly journals Correlation clustering with a fixed number of clusters

2006 ◽  
Author(s):  
Ioannis Giotis ◽  
Venkatesan Guruswami
Keyword(s):  
Fixed Number ◽  
Number Of Clusters ◽  
Correlation Clustering

A Cluster Modelling Study of Conductivity of Yttria-Stabilized Zirconia

1992 ◽  
Vol 293 ◽  
Author(s):  
Laura E. Depero ◽  
Marcello Zocchi ◽  
Fulvio Parmigiani
Keyword(s):  
Structural Model ◽  
Fixed Number ◽  
Yttria Stabilized Zirconia ◽  
Experimental Results ◽  
Stabilized Zirconia ◽  
Number Of Clusters ◽  
Cluster Modelling ◽  
Modelling Study

AbstractOn the basis of a previously described structural model for the Yttria-Stabilized Zirconia, the conductivity for this material can be calculated. A fixed number of clusters is generated in a structure of 70×28 polyhedra to simulate different Y contents in the structure. The results are compared with the experimental results obtained by others and discussed.

Sample Size Issues for Cluster Randomized Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 146-158 ◽  
Author(s):  
Mirjam Moerbeek
Keyword(s):  
Discrete Time ◽  
Cluster Size ◽  
Randomized Trials ◽  
Cluster Randomized Trial ◽  
Smoking Initiation ◽  
Fixed Number ◽  
Cluster Randomized Trials ◽  
Number Of Clusters ◽  
Sufficient Power ◽  
Cluster Randomized

With cluster randomized trials complete groups of subjects are randomized to treatment conditions. An important question might be whether and when the subjects experience a particular event, such as smoking initiation or recovery from disease. In the social sciences the timing of such events is often measured in discrete time by using time intervals. At the planning phase of a cluster randomized trial one should decide on the number of clusters and cluster size such that parameters are estimated accurately and sufficient power on the test on treatment effect is achieved. On basis of a simulation study it is concluded that regression coefficients are estimated more accurately than the variance of the random cluster effect. In addition, it is shown that power increases with cluster size and number of clusters, and that a sufficient power cannot always be achieved by using larger cluster sizes at a fixed number of clusters.

scholarly journals A randomized PTAS for the minimum Consensus Clustering with a fixed number of clusters

2012 ◽  
Vol 429 ◽  
pp. 36-45 ◽  
Author(s):  
Paola Bonizzoni ◽  
Gianluca Della Vedova ◽  
Riccardo Dondi
Keyword(s):  
Fixed Number ◽  
Consensus Clustering ◽  
Number Of Clusters

Interactive multiobjective DEA target setting using lexicographic DDF

2020 ◽  
Vol 54 (6) ◽  
pp. 1703-1722 ◽  
Author(s):  
Narges Soltani ◽  
Sebastián Lozano
Keyword(s):  
Efficient Frontier ◽  
Directional Distance Function ◽  
Fixed Number ◽  
Optimization Approach ◽  
Target Setting ◽  
Interactive Process ◽  
Decision Making Unit ◽  
Setting Approach ◽  
Promising Area ◽  
Current Region

In this paper, a new interactive multiobjective target setting approach based on lexicographic directional distance function (DDF) method is proposed. Lexicographic DDF computes efficient targets along a specified directional vector. The interactive multiobjective optimization approach consists in several iteration cycles in each of which the Decision Making Unit (DMU) is presented a fixed number of efficient targets computed corresponding to different directional vectors. If the DMU finds one of them promising, the directional vectors tried in the next iteration are generated close to the promising one, thus focusing the exploration of the efficient frontier on the promising area. In any iteration the DMU may choose to finish the exploration of the current region and restart the process to probe a new region. The interactive process ends when the DMU finds its most preferred solution (MPS).

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.

Phospholipid-Protein Interactions in the Formation of Prothrombin Activator

1965 ◽  
Vol 14 (03/04) ◽  
pp. 431-444 ◽  
Author(s):  
E. R Cole ◽  
J. L Koppel ◽  
J. H Olwin
Keyword(s):  
Complex Formation ◽  
Protein Interactions ◽  
Calcium Ions ◽  
Fixed Number ◽  
Factor V ◽  
Clotting Factors ◽  
Number Of Binding Sites ◽  
C Complex ◽  
Autoprothrombin C

SummarySince Ac-globulin (factor V) is involved in the formation of prothrombin activator, its ability to complex with phospholipids was studied. Purified bovine Ac-globulin was complexed to asolectin, there being presumably a fixed number of binding sites on the phospholipid micelle for Ac-globulin. In contrast to the requirement for calcium ions in the formation of complexes between asolectin and autoprothrombin C, calcium ions were not required for complex formation between asolectin and Ac-globulin to occur ; in fact, the presence of calcium prevented complex formation occurring, the degree of inhibition being dependent on the calcium concentration. By treating isolated, pre-formed aso- lectin-Ac-globulin complexes with calcium chloride solutions, Ac-globulin could be recovered in a much higher state of purity and essentially free of asolectin.Complete activators were formed by first preparing the asolectin-calcium- autoprothrombin C complex and then reacting the complex with Ac-globulin. A small amount of this product was very effective as an activator of purified prothrombin without further addition of calcium or any other cofactor. If the autoprothrombin C preparation used to prepare the complex was free of traces of prothrombin, the complete activator was stable for several hours at room temperature. Stable preparations of the complete activator were centrifuged, resulting in the sedimentation of most of the activity. Experimental evidence also indicated that activator activity was highest when autoprothrombin C and Ac-globulin were complexed to the same phospholipid micelle, rather than when the two clotting factors were complexed to separate micelles. These data suggested that the in vivo prothrombin activator may be a sedimentable complex composed of a thromboplastic enzyme, calcium, Ac-globulin and phospholipid.

A Correspondence-Free Color Chart Design for Color Calibration

2020 ◽  
Vol 2020 (1) ◽  
pp. 100-104
Author(s):  
Hakki Can Karaimer ◽  
Rang Nguyen
Keyword(s):  
Color Space ◽  
Fixed Number ◽  
New Approach ◽  
Color Chart ◽  
Color Calibration ◽  
Space Transformation ◽  
Color Space Transformation ◽  
Chart Design ◽  
Calibration Approach

Colorimetric calibration computes the necessary color space transformation to map a camera's device-specific color space to a device-independent perceptual color space. Color calibration is most commonly performed by imaging a color rendition chart with a fixed number of color patches with known colorimetric values (e. g., CIE XYZ values). The color space transformation is estimated based on the correspondences between the camera's image and the chart's colors. We present a new approach to colorimetric calibration that does not require explicit color correspondences. Our approach computes a color space transformation by aligning the color distributions of the captured image to the known distribution of a calibration chart containing thousands of colors. We show that a histogram-based colorimetric calibration approach provides results that are onpar with the traditional patch-based method without the need to establish correspondences.

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