Search results for "Application"
showing 10 items of 5559 documents
Travaux sur le fonds d'autrui et couple : terrain glissant !
2009
International audience
A pattern recognition approach for peak prediction of electrical consumption
2016
Predicting and mitigating demand peaks in electrical networks has become a prevalent research topic. Demand peaks pose a particular challenge to energy companies because these are difficult to foresee and require the net to support abnormally high consumption levels. In smart energy grids, time-differentiated pricing policies that increase the energy cost for the consumers during peak periods, and load balancing are examples of simple techniques for peak regulation. In this paper, we tackle the task of predicting power peaks prior to their actual occurrence in the context of a pilot Norwegian smart grid network.
A network model for the short-term prediction of the evolution of cocaine consumption in Spain
2010
Cocaine consumption is a social problem with acute consequences and its dependency can be regarded as a health concern of social transmission. This fact leads us to develop the idea that its transmission dynamics can be studied using epidemiological mathematical models. Under this point of view, in this paper we propose a network model to study the short-term evolution of the cocaine consumer subpopulations. The model parameters are obtained from data source and from an analogue continuous model. Sensitivity of the model parameters is studied. The parameters are associated with prevention and treatment policies and the sensitivity study gives us information about which parameters have more …
Perceived-Value-driven Optimization of Energy Consumption in Smart Homes
2020
Residential energy consumption has been rising rapidly during the last few decades. Several research efforts have been made to reduce residential energy consumption, including demand response and smart residential environments. However, recent research has shown that these approaches may actually cause an increase in the overall consumption, due to the complex psychological processes that occur when human users interact with these energy management systems. In this article, using an interdisciplinary approach, we introduce a perceived-value driven framework for energy management in smart residential environments that considers how users perceive values of different appliances and how the us…
Alcohol consumption in Spain and its economic cost: A mathematical modeling approach
2010
In this paper, a mathematical model for alcohol consumption in Spanish population is proposed. Its parameters are estimated by fitting the model to real data from Spanish Ministry of Health. Predictions about the future behavior of the alcohol consumption in Spain are presented using this model. Results are applied to estimate the economic costs (sanitary and non-sanitary) assumed by Spanish society that are derived from this consumption.
Machine learning methods to forecast temperature in buildings
2013
Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optim…
mplicit Identification of Contact Parameters in a Continuous Chain Model
2011
Accurate contact modeling is of great importance in the field of dynamic chain simulations. In this paper emphasis is on contact dynamics for a time-domain simulation model of large chains guided in a closed loop track. The chain model is based on theory for unconstrained rigid multibody dynamics where contact within the chain and with the track is defined through continuous point contacts using the contact indentation and rate as means. This paper presents an implicit method to determine contact parameters of the chain model through the use of none gradient optimization methods. The set of model parameters are estimated by minimizing the residual between simulated and measured results. The…
MicroRNA-Based Therapeutic Perspectives in Myotonic Dystrophy
2019
Myotonic dystrophy involves two types of chronically debilitating rare neuromuscular diseases: type 1 (DM1) and type 2 (DM2). Both share similarities in molecular cause, clinical signs, and symptoms with DM2 patients usually displaying milder phenotypes. It is well documented that key clinical symptoms in DM are associated with a strong mis-regulation of RNA metabolism observed in patient’s cells. This mis-regulation is triggered by two leading DM-linked events: the sequestration of Muscleblind-like proteins (MBNL) and the mis-regulation of the CUGBP RNA-Binding Protein Elav-Like Family Member 1 (CELF1) that cause significant alterations to their important functions in RNA processing. It ha…
RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes
2015
Abstract Recommender systems are used to provide filtered information from a large amount of elements. They provide personalized recommendations on products or services to users. The recommendations are intended to provide interesting elements to users. Recommender systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This paper proposes a recommender system in the leisure domain, specifically in the movie showtimes domain. The system proposed is called RecomMetz, and it is a context-aware mobile recommender system based on Semantic Web technologies. In detail, a domain ontology primarily…
Tool Support for Model Driven Development of Pervasive Systems
2007
This work presents the PervML Generative Tool (PervGT) that supports a model driven method for the development of pervasive services in ubiquitous environments. The tool, which is based on the Eclipse platform, provides facilities for the graphical description of pervasive systems using PervML, a UML-like modeling language. Once the pervasive system is specified, the PervML model is used as input to a transformation engine that generates source code and other implementation assets. This generated code extends an OSGi-based framework in order to build the final pervasive applications