Search results for "cluster analysis."
showing 10 items of 805 documents
A Study on Engineering Freshman Conceptual Understanding of Newtonian Mechanics
2021
Force concept inventory is a multiple-choice questionnaire commonly used to assess students’ conceptual understanding of Newtonian mechanics. We here show that a cluster analysis method can be used to study student answers to the force concept inventory to investigate their understanding of Newtonian mechanics and provide new insights into the use of the force concept inventory. We identi- fied groups of students characterized by similar correct answers as well as by non- correct answers to the questionnaire, whose analysis allowed us to highlight student misconceptions/non-normative conceptions. Such an analysis of student answers gave us insights into the relationships between the student…
STUDY ON CONSUMERS' BEHAVIOR CONCERNING BERRIES CONSUMPTION IN ITALY
2014
In Italy, the cultivated land of berries shows a positive trend, nevertheless berries still remain a productive segment of niche and luxury in the Italian agri-food system. In the world, the interest for these productions is high for their healthy aspects that have a strong appeal to the consumers. The objectives of this study are to know the consumers behavior of berries and the determinants of purchase in Italy in order to improve the management of the producing and retailers companies for increase the competitiveness of the supply chain. The results obtained through a multivariate analysis show some difference among the consumers interviewed. The most important results of this study is t…
A study on science teaching efficacy beliefs during pre-service elementary training
2020
Two science teaching workshops for students of the elementary teacher education degree course at the University of Palermo, Italy are discussed, one based on inquiry-based methods and the other on "traditional" teaching methods. A questionnaire aimed to understand the teaching styles preferred by students, their reasons for learning/teaching science, and their beliefs about the difficulties a teacher faces when planning and trying out science teaching activities in the class were completed by the students before the first workshop, at its end, and the end of the second workshop. The answers given by the students were studied using cluster analysis methods. The results of the analysis of ans…
Individuazione di cavità attraverso tomografie elettriche e sismiche
2020
Le tecniche geofisiche sono i metodi più efficienti per ottenere informazioni sulle strutture presenti nel sottosuolo. Ad oggi, la tomografia di resistività elettrica (ERT) è il metodo più utilizzato per il rilevamento di vuoti sotterranei, tuttavia, la combinazione con dati derivanti da diversi metodi geofisici è l’approccio più adatto per la determinazione delle cavità. Negli ultimi anni, la ERT è stata sempre più spesso congiunta alla tomografia sismica a rifrazione (SRT) al fine di ottenere interpretazioni più robuste anche utilizzando un approccio di tipo statistico. La cluster analysis eseguita su unità statistiche definite da valori di resistività elettrica, velocità delle onde P e d…
The Urban Landscape and the Real Estate Market. Structures and Fragments of the Axiological Tessitura in a Wide Urban Area of Palermo
2016
The proposed study deals with the urban landscape of Palermo and its possible representation from the perspective of the real estate market analysis. Real estate is one of the most significant types of capital asset and the wide range of its possible utilizations makes complex the interpretation of the market phenomena. The multi-layered reality of such a large city (represented through the sample of 500 properties) needs to be articulated into a significant set of sub-markets in order to outline the complexity and to map the distribution of homogeneous groups of properties within the whole city area. The comparison between quality and price within each cluster allows us to elicit the degre…
SMART: Unique splitting-while-merging framework for gene clustering
2014
© 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named "splitting merging awareness tactics" (SMART), which does not require any a priori knowledge of either the number …
Computation Cluster Validation in the Big Data Era
2017
Data-driven class discovery, i.e., the inference of cluster structure in a dataset, is a fundamental task in Data Analysis, in particular for the Life Sciences. We provide a tutorial on the most common approaches used for that task, focusing on methodologies for the prediction of the number of clusters in a dataset. Although the methods that we present are general in terms of the data for which they can be used, we offer a case study relevant for Microarray Data Analysis.
GenClust: A genetic algorithm for clustering gene expression data
2005
Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …
Data Analysis and Bioinformatics
2007
Data analysis methods and techniques are revisited in the case of biological data sets. Particular emphasis is given to clustering and mining issues. Clustering is still a subject of active research in several fields such as statistics, pattern recognition, and machine learning. Data mining adds to clustering the complications of very large data-sets with many attributes of different types. And this is a typical situation in biology. Some cases studies are also described.
Distance Functions, Clustering Algorithms and Microarray Data Analysis
2010
Distance functions are a fundamental ingredient of classification and clustering procedures, and this holds true also in the particular case of microarray data. In the general data mining and classification literature, functions such as Euclidean distance or Pearson correlation have gained their status of de facto standards thanks to a considerable amount of experimental validation. For microarray data, the issue of which distance function works best has been investigated, but no final conclusion has been reached. The aim of this extended abstract is to shed further light on that issue. Indeed, we present an experimental study, involving several distances, assessing (a) their intrinsic sepa…