Search results for "Cluster Analysis"

Detecting multiple copies in tampered images

2010

Copy-move forgeries are parts of the image that are duplicated elsewhere into the same image, often after being modified by geometrical transformations. In this paper we present a method to detect these image alterations, using a SIFT-based approach. First we describe a state of the art SIFT-point matching method, which inspired our algorithm, then we compare it with our SIFT-based approach, which consists of three parts: keypoint clustering, cluster matching, and texture analysis. The goal is to find copies of the same object, i.e. clusters of points, rather than points that match. Cluster matching proves to give better results than single point matching, since it returns a complete and co…

Influence of bio-based additives on RAP clustering and asphalt binder rheology

2017

The use of high Reclaimed Asphalt Pavement (RAP) content in Hot Mix Asphalt (HMA) allows developing innovative materials for the construction and/or rehabilitation of sustainable infrastructures. The chemo-physical phenomena occurring during production of HMA containing high RAP content should be investigated and considered for the mix design optimization. In fact, when additives are used as rejuvenators of the aged bitumen, these phenomena can be affected causing significant variations in the mixture characteristics. This paper aims at studying the influence of two bio-based additives specifically on RAP clustering, phenomena which can significantly affect the performance of high-content R…

VIII Colloque International –VIII International Conference - A.S.I. Analyse Statistique Implicative ––Statistical Implicative Analysis

2015

Le huitième colloque A.S.I. 8 s’est déroulé dans un contexte d’espérance stimulée pour la démocratie tunisienne avec l’attribution du Prix Nobel de la Paix pour 2015. Comme on a pu le lire dans les journaux : « Le comité Nobel norvégien a décidé de récompenser, vendredi 9 octobre 2015, le quartet menant le dialogue national en Tunisie, qui s’est distingué pour «sa contribution décisive dans la construction d’une démocratie pluraliste en Tunisie après la “révolution du jasmin” de 2011 » ». (Le Monde) Un tel contexte est de toute évidence plus propice à la créativité scientifique, à l’exercice de la pensée critique qui fonde les dimensions épistémologique et méthodologique des champs scientif…

VI Colloque International –VI International Conference - A.S.I. Analyse Statistique Implicative ––Statistical Implicative Analysis

2012

HIERARCHICAL AND NON-HIERARCHICAL CLUSTERING METHODS TO ANALYSE AN OPEN-ENDED QUESTIONNAIRE ON ALGEBRAIC THINKING

2016

In recent years, some papers have tried to develop detailed models of the reasoning competences of the student populations tested, or to subdivide a sample of students into intellectually similar subgroups, by using quantitative or qualitative analysis methods. It is worth noting that research papers using quantitative analysis methods to study student responses to open-ended questionnaire can be found in Science and Physics education (Springuel et al., 2007), but the same cannot be said for research in Mathematics education. In this paper we focus on the application of hierarchical and non-hierarchical clustering methods referred to dendrograms and k-means approaches (Everitt, et al., 2011…

Field estimation in wireless sensor networks using distributed kriging

2012

In this paper, we tackle the problem of spatial interpolation for distributed estimation in Wireless Sensor Networks by using a geostatistical technique called kriging. We present a novel Distributed Iterative Kriging Algorithm (DIKA) which is composed of two main phases. First, the spatial dependence of the field is exploited by calculating semivariograms in an iterative way. Second, the kriging system of equations is solved by an initial set of nodes in a distributed manner, providing some initial interpolation weights to each node. In our algorithm, the estimation accuracy can be improved by iteratively adding new nodes and updating appropriately the weights, which leads to a reduction i…

Constrained Clusterwise Linear Regression

2005

In market segmentation, Conjoint Analysis is often used to estimate the importance of a product attributes at the level of each single customer, clustering, successively, the customers whose behavior can be considered similar. The preference model parameter estimation is made considering data (usually opinions) of a single customer at a time, but these data are usually very few as each customer is called to express his opinion about a small number of different products (in order to simplify his/her work). In the present paper a Constrained Clusterwise Linear Regression algorithm is presented, that allows simultaneously to estimate parameters and to cluster customers, using, for the estimati…

Apparel sizing using trimmed PAM and OWA operators

2012

This paper is concerned with apparel sizing system design. One of the most important issues in the apparel development process is to define a sizing system that provides a good fit to the majority of the population. A sizing system classifies a specific population into homogeneous subgroups based on some key body dimensions. Standard sizing systems range linearly from very small to very large. However, anthropometric measures do not grow linearly with size, so they can not accommodate all body types. It is important to determine each class in the sizing system based on a real prototype that is as representative as possible of each class. In this paper we propose a methodology to develop an …

Projector operators in clustering

2016

In a recent paper the notion of {\em quantum perceptron} has been introduced in connection with projection operators. Here we extend this idea, using these kind of operators to produce a {\em clustering machine}, i.e. a framework which generates different clusters from a set of input data. Also, we consider what happens when the orthonormal bases first used in the definition of the projectors are replaced by frames, and how these can be useful when trying to connect some noised signal to a given cluster.

Randomized heuristics for the Capacitated Clustering Problem

2017

In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memory-based method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent l…