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This paper presents an approach for underdetermined blind source separation that can be applied even if the number of sources is unknown. Moreover, the proposed approach is applicable in the case of separating I+3 sources from I mixtures without additive noise. This situation is more challenging and suitable to practical real world problems. Also, the sparsity conditions are not imposed unlike to...
The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each...
In this paper the capacitated vehicle routing problem with time windows is tackled with a beam-search based approximate algorithm. An instance of this problem is defined by a set of customers and a fleet of identical vehicles. A time window is associated with each customer and a maximum capacity characterizes a vehicle. The aim is then to serve all the customers by minimizing the number of vehicles...
In this paper, we investigate the problem of quality analysis of clustering results using semantic annotations given by experts. We propose a novel approach to construction of evaluation measure, which is based on the Minimal Description Length (MDL) principle. In fact this proposed measure, called SEE (Semantic Evaluation by Exploration), is an improvement of the existing evaluation methods such...
With the new technological advances and strong move towards Future Internet and Internet as a Platform a new environment is emerging. This environment is generative, social, strongly interactive and collaborative, so users play a fundamental role in it. Business applications are simplifying, webifying and getting more user-centric. In this environment, context and context-awareness plays a fundamental...
One of the methods most commonly used for learning and classification is using decision trees. The greatest advantages that decision trees offer is that, unlike classical trees, they provide a support for handling uncertain data sets. The paper introduces a new algorithm for building fuzzy decision trees and also offers some comparative results, by taking into account other methods. We will present...
2D color barcodes have been introduced to obtain larger storage capabilities than traditional black and white barcodes. Unfortunately, the data density of color barcodes is substantially limited by the redundancy needed for correcting errors, which are due not only to geometric but also to chromatic distortions introduced by the printing and scanning process. The higher the expected error rate, the...
Liver cancer is one of the major death factors in the world. Transplantation and tumor resection are two main therapies in common clinical practice. Both tasks need image assisted planning and quantitative evaluations. An efficient and effective automatic liver segmentation is required for corresponding quantitative evaluations. Computed Tomography (CT) is highly accurate for liver cancer diagnosis...
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