Search results for "Clustering"
showing 10 items of 446 documents
Using cluster analysis to study the modelling abilities of engineering undergraduate students: a case study
2016
In this contribution we discuss the application of a quantitative, non-hierarchical clustering method to make sense of the answers that 120 engineering undergraduates students at the University of Palermo, Italy, gave to four open-ended questions on the meaning of the modeling processes in Science. We will show that the use of non-hierarchical analysis allows us to easily separate students into groups that can be recognized and characterized by common traits in students’ answers without any prior knowledge on the part of the researcher of what form those groups would take (unbiased classification).
ERCP : Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks
2022
Wireless Sensor Networks (WSNs) have been around for over a decade and have been used in many important applications. Energy and reliability are two of the major problems with these kinds of applications. Reliable data delivery is an important issue in WSNs because it is a key part of how well data are sent. At the same time, energy consumption in battery-based sensors is another challenge. Therefore, efficient clustering and routing are techniques that can be used to save sensors energy and guarantee reliable message delivery. With this in mind, this paper develops an energy-efficient and reliable clustering protocol (ERCP) for WSNs. First, an efficient clustering technique is proposed for…
Mismatches between objective parameters and measured perception assessment in room acoustics: a holistic approach
2014
Psychoacoustic research in the field of concert halls has revealed that many aspects concerning listening perception have yet to be totally understood. On the one hand, the objective room acoustics of performance spaces are reflected in parameters, some standardized and some not, but these are related to a limited number of perceptual attributes of human response. In general, these objective parameters cannot accurately describe the acoustic details due to their inherent simplification. Under these premises, impulse responses (576 receivers) are measured in 16 concert halls, according to standard procedures, and the perception and satisfaction of the occupants of the rooms are evaluated by …
Time reduction for completion of a civil engineering construction using fuzzy clustering techniques
2017
In the civil engineering field, there are usually unexpected troubles that can cause delays during execution. This situation involves numerous variables (resource number, execution time, costs, working area availability, etc.), mutually dependent, that complicate the definition of the problem analytical model and the related resolution. Consequently, the decision-maker may avoid rational methods to define the activities that could be conveniently modified, relying only on his personal experience or experts’ advices. In order to improve this kind of decision from an objective point of view, the authors analysed the operation correction using a data mining technique, called Fuzzy Clustering. …
New statistical post processing approach for precise fault and defect localization in TRI database acquired on complex VLSI
2013
International audience; Timing issue, missing or extra state transitions or unusual consumption can be detected and localized by Time Resolved Imaging (TRI) database analysis. Although, long test pattern can challenge this process. The number of photons to process rapidly increases and the acquisition time to have a good signal over noise ratio (SNR) can be prohibitive. As a result, the tracking of the defect emission signature inside a huge database can be quite complicated. In this paper, a method based on data mining techniques is suggested to help the TRI end user to have a good idea about where to start a deeper analysis of the integrated circuit, even with such complex databases.
Neural Modeling of Greenhouse Gas Emission from Agricultural Sector in European Union Member Countries
2018
The present paper discusses a novel methodology based on neural network to determine agriculture emission model simulations. Methane and nitrous oxide are the key pollutions among greenhouse gases being a major contribution to climate changes because of their high potential global impact. Using statistical clustering (k-means and Ward’s method), five meaningful clusters of countries with similar level of greenhouse gases emission were identified. Neural modeling using multi-layer perceptron networks was performed for countries placed in particular groups. The parameters that characterize the quality of a network are the predictive errors (mainly validation and test) and they are high (0.97–…
Geographical spread of influenza incidence in Spain during the 2009 A(H1N1) pandemic wave and the two succeeding influenza seasons
2014
SUMMARYThe aim of this study was to monitor the spatio-temporal spread of influenza incidence in Spain during the 2009 pandemic and the following two influenza seasons 2010–2011 and 2011–2012 using a Bayesian Poisson mixed regression model; and implement this model of geographical analysis in the Spanish Influenza Surveillance System to obtain maps of influenza incidence for every week. In the pandemic wave the maps showed influenza activity spreading from west to east. The 2010–2011 influenza epidemic wave plotted a north-west/south-east pattern of spread. During the 2011–2012 season the spread of influenza was geographically heterogeneous. The most important source of variability in the m…
Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Abstract Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that …
Towards Evidence-Based Academic Advising Using Learning Analytics
2018
Academic advising is a process between the advisee, adviser and the academic institution which provides the degree requirements and courses contained in it. Content-wise planning and management of the student’ study path, guidance on studies and academic career support is the main joint activity of advising. The purpose of this article is to propose the use of learning analytics methods, more precisely robust clustering, for creation of groups of actual study profiles of students. This allows academic advisers to provide evidence-based information on the study paths that have actually happened similarly to individual students. Moreover, academic institutions can focus on management and upda…
Distributed and proximity-constrained C-means for discrete coverage control
2018
In this paper we present a novel distributed coverage control framework for a network of mobile agents, in charge of covering a finite set of points of interest (PoI), such as people in danger, geographically dispersed equipment or environmental landmarks. The proposed algorithm is inspired by C-Means, an unsupervised learning algorithm originally proposed for non-exclusive clustering and for identification of cluster centroids from a set of observations. To cope with the agents' limited sensing range and avoid infeasible coverage solutions, traditional C-Means needs to be enhanced with proximity constraints, ensuring that each agent takes into account only neighboring PoIs. The proposed co…