Clustering Algorithms I

Theodoridis, Sergios; Koutroumbas, Konstantinos

doi:10.1016/b978-012369531-4/50012-3

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…For instance, with as few as ten sectors, the number of possible cluster arrangements is nearly 116,000. 5 Although in reality, spatial contiguity would preclude many of these sector combinations from consideration, it is clear that solving the problem is not trivial due to the combinatorial size of the solution space which grows exponentially with the number of sectors. The greedy heuristic approach described in Ref.…”

Section: Iiia the Mixed Integer Linear Programming Modelmentioning

confidence: 99%

“…Because k spans all sectors I (since all sectors are possible sinks), d kt must be zero for all non-sink sectors. This is accomplished by constraint (5). Here, and throughout the remainder of this section, L represents an arbitrary number sufficiently large enough to prevent the quotient on the left from being greater than one.…”

Section: Iiib3 Objective Function and Constraintsmentioning

confidence: 99%

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A Method of Optimally Combining Sectors

Drew

2009

9th AIAA Aviation Technology, Integration, and Operations Conference (ATIO)

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This paper describes a procedure for combining under-utilized sectors so that controllers can be allocated to the busiest sectors at the busiest times. A Mixed Integer Linear Programming model for systematically combining under-utilized sectors is described and its performance is compared to another recently-developed greedy heuristic algorithm. The MILP model produces slightly better results than the greedy algorithm. Improvements are greater as the number of sectors considered for combining increases. While the improvements are modest, over time they become significant. Lengthy computation times associated with large data sets are addressed by using the greedy algorithm as a starting solution for the optimal solver.

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Section: Iiia the Mixed Integer Linear Programming Modelmentioning

confidence: 99%

Section: Iiib3 Objective Function and Constraintsmentioning

confidence: 99%

A Method of Optimally Combining Sectors

Drew

2009

9th AIAA Aviation Technology, Integration, and Operations Conference (ATIO)

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An Investigation Into the Feasibility of Real-Time Soccer Offside Detection From a Multiple Camera System

D’Orazio

Leo

Spagnolo

et al. 2009

IEEE Trans. Circuits Syst. Video Technol.

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In this paper, we investigate on the feasibility of multiple camera system for automatic offside detection. We propose six fixed cameras, properly placed on the two sides of the soccer field (three for each side) to reduce perspective and occlusion errors. The images acquired by the synchronized cameras are processed to detect the players' position and the ball position in real-time; a multiple view analysis is carried out to evaluate the offside event, considering the position of all the players in the field, determining the players who passed the ball, and determining if active offside condition occurred. The whole system has been validated using real-time images acquired during official soccer matches, and quantitative results on the system accuracy were obtained comparing the system responses with the ground truth data generated manually on a number of extracted significant sequences. Index Terms-3-D trajectory analysis, multiple cameras, player and ball tracking.

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Wavelet Feature Extraction and Genetic Algorithm for Biomarker Detection in Colorectal Cancer Data

et al. 2013

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Abstract:Biomarkers which predict patient's survival can play an important role in medical diagnosis and treatment. How to select the significant biomarkers from hundreds of protein markers is a key step in survival analysis. In this paper a novel method is proposed to detect the prognostic biomarkers of survival in colorectal cancer patients using wavelet analysis, genetic algorithm, and Bayes classifier.One dimensional discrete wavelet transform (DWT) is normally used to reduce the dimensionality of biomedical data. In this study one dimensional continuous wavelet transform (CWT) was proposed to extract the features of colorectal cancer data. One dimensional CWT has no ability to reduce dimensionality of data, but captures the missing features of DWT, and is complementary part of DWT. Genetic algorithm was performed on extracted wavelet coefficients to select the optimized features, using Bayes classifier to build its fitness function. The corresponding protein markers were located based on the position of optimized features. Kaplan-Meier curve and Cox regression model 2 were used to evaluate the performance of selected biomarkers. Experiments were conducted on colorectal cancer dataset and several significant biomarkers were detected. A new protein biomarker CD46 was found to significantly associate with survival time.

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Clustering Algorithms I

Cited by 3 publications

References 27 publications

A Method of Optimally Combining Sectors

A Method of Optimally Combining Sectors

An Investigation Into the Feasibility of Real-Time Soccer Offside Detection From a Multiple Camera System

Wavelet Feature Extraction and Genetic Algorithm for Biomarker Detection in Colorectal Cancer Data

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