Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/3920
Mon, 24 Jul 2017 08:14:31 GMT2017-07-24T08:14:31ZGreen's function of a weighted $n$-cycle
http://hdl.handle.net/2117/106599
Green's function of a weighted $n$-cycle
Carmona Mejías, Ángeles; Encinas Bachiller, Andrés Marcos; Gago Álvarez, Silvia; Jiménez Jiménez, M. Jose; Mitjana Riera, Margarida
Wed, 19 Jul 2017 08:53:18 GMThttp://hdl.handle.net/2117/1065992017-07-19T08:53:18ZCarmona Mejías, ÁngelesEncinas Bachiller, Andrés MarcosGago Álvarez, SilviaJiménez Jiménez, M. JoseMitjana Riera, MargaridaExplicit inverse of a tridiagonal (p,r)-Toeplitz matrix
http://hdl.handle.net/2117/106597
Explicit inverse of a tridiagonal (p,r)-Toeplitz matrix
Encinas Bachiller, Andrés Marcos; Jiménez Jiménez, M. Jose
Wed, 19 Jul 2017 08:46:53 GMThttp://hdl.handle.net/2117/1065972017-07-19T08:46:53ZEncinas Bachiller, Andrés MarcosJiménez Jiménez, M. JoseBounded solutions of second order lineal difference equations with periodic coefficients
http://hdl.handle.net/2117/106577
Bounded solutions of second order lineal difference equations with periodic coefficients
Encinas Bachiller, Andrés Marcos; Jiménez Jiménez, M. Jose
Tue, 18 Jul 2017 11:45:35 GMThttp://hdl.handle.net/2117/1065772017-07-18T11:45:35ZEncinas Bachiller, Andrés MarcosJiménez Jiménez, M. JoseExplicit inverse of a tridiagonal (p,r)-Toeplitz matrix
http://hdl.handle.net/2117/106576
Explicit inverse of a tridiagonal (p,r)-Toeplitz matrix
Encinas Bachiller, Andrés Marcos; Jiménez Jiménez, M. Jose
Tue, 18 Jul 2017 11:38:41 GMThttp://hdl.handle.net/2117/1065762017-07-18T11:38:41ZEncinas Bachiller, Andrés MarcosJiménez Jiménez, M. JoseEstimation of the synaptic conductance in a McKean-model neuron
http://hdl.handle.net/2117/106463
Estimation of the synaptic conductance in a McKean-model neuron
Guillamon Grabolosa, Antoni; Prohens Sastre, Rafel; Teruel Aguilar, Antonio E.; Vich Llompart, Catalina
Estimating the synaptic conductances impinging on a single neuron directly from its membrane potential is one of the open problems to be solved in order to understand the flow of information in the brain. Despite the existence of some computational strategies that give circumstantial solutions ([1-3] for instance), they all present the inconvenience that the estimation can only be done in subthreshold activity regimes. The main constraint to provide strategies for the oscillatory regimes is related to the nonlinearity of the input-output curve and the difficulty to compute it. In experimental studies it is hard to obtain these strategies and, moreover, there are no theoretical indications of how to deal with this inverse non-linear problem. In this work, we aim at giving a first proof of concept to address the estimation of synaptic conductances when the neuron is spiking. For this purpose, we use a simplified model of neuronal activity, namely a piecewise linear version of the Fitzhugh-Nagumo model, the McKean model ([4], among others), which allows an exact knowledge of the nonlinear f-I curve by means of standard techniques of non-smooth dynamical systems. As a first step, we are able to infer a steady synaptic conductance from the cell's oscillatory activity. As shown in Figure ¿Figure1,1, the model shows the relative errors of the conductances of order C, where C is the membrane capacitance (C<<1), notably improving the errors obtained using filtering techniques on the membrane potential plus linear estimations, see numerical tests performed in [5].
Fri, 14 Jul 2017 12:07:45 GMThttp://hdl.handle.net/2117/1064632017-07-14T12:07:45ZGuillamon Grabolosa, AntoniProhens Sastre, RafelTeruel Aguilar, Antonio E.Vich Llompart, CatalinaEstimating the synaptic conductances impinging on a single neuron directly from its membrane potential is one of the open problems to be solved in order to understand the flow of information in the brain. Despite the existence of some computational strategies that give circumstantial solutions ([1-3] for instance), they all present the inconvenience that the estimation can only be done in subthreshold activity regimes. The main constraint to provide strategies for the oscillatory regimes is related to the nonlinearity of the input-output curve and the difficulty to compute it. In experimental studies it is hard to obtain these strategies and, moreover, there are no theoretical indications of how to deal with this inverse non-linear problem. In this work, we aim at giving a first proof of concept to address the estimation of synaptic conductances when the neuron is spiking. For this purpose, we use a simplified model of neuronal activity, namely a piecewise linear version of the Fitzhugh-Nagumo model, the McKean model ([4], among others), which allows an exact knowledge of the nonlinear f-I curve by means of standard techniques of non-smooth dynamical systems. As a first step, we are able to infer a steady synaptic conductance from the cell's oscillatory activity. As shown in Figure ¿Figure1,1, the model shows the relative errors of the conductances of order C, where C is the membrane capacitance (C<<1), notably improving the errors obtained using filtering techniques on the membrane potential plus linear estimations, see numerical tests performed in [5].Ideal hierarchical secret sharing schemes
http://hdl.handle.net/2117/106120
Ideal hierarchical secret sharing schemes
Farràs Ventura, Oriol; Padró Laimon, Carles
Hierarchical secret sharing is among the most natural generalizations of threshold secret sharing, and it has attracted a lot of attention from the invention of secret sharing until nowadays. Several constructions of ideal hierarchical secret sharing schemes have been proposed, but it was not known what access structures admit such a scheme. We solve this problem by providing a natural definition for the family of the hierarchical access structures and, more importantly, by presenting a complete characterization of the ideal hierarchical access structures, that is, the ones admitting an ideal secret sharing scheme. Our characterization deals with the properties of the hierarchically minimal sets of the access structure, which are the minimal qualified sets whose participants are in the lowest possible levels in the hierarchy. By using our characterization, it can be efficiently checked whether any given hierarchical access structure that is defined by its hierarchically minimal sets is ideal. We use the well known connection between ideal secret sharing and matroids and, in particular, the fact that every ideal access structure is a matroid port. In addition, we use recent results on ideal multipartite access structures and the connection between multipartite matroids and integer polymatroids. We prove that every ideal hierarchical access structure is the port of a representable matroid and, more specifically, we prove that every ideal structure in this family admits ideal linear secret sharing schemes over fields of all characteristics. In addition, methods to construct such ideal schemes can be derived from the results in this paper and the aforementioned ones on ideal multipartite secret sharing. Finally, we use our results to find a new proof for the characterization of the ideal weighted threshold access structures that is simpler than the existing one.
Tue, 04 Jul 2017 05:40:29 GMThttp://hdl.handle.net/2117/1061202017-07-04T05:40:29ZFarràs Ventura, OriolPadró Laimon, CarlesHierarchical secret sharing is among the most natural generalizations of threshold secret sharing, and it has attracted a lot of attention from the invention of secret sharing until nowadays. Several constructions of ideal hierarchical secret sharing schemes have been proposed, but it was not known what access structures admit such a scheme. We solve this problem by providing a natural definition for the family of the hierarchical access structures and, more importantly, by presenting a complete characterization of the ideal hierarchical access structures, that is, the ones admitting an ideal secret sharing scheme. Our characterization deals with the properties of the hierarchically minimal sets of the access structure, which are the minimal qualified sets whose participants are in the lowest possible levels in the hierarchy. By using our characterization, it can be efficiently checked whether any given hierarchical access structure that is defined by its hierarchically minimal sets is ideal. We use the well known connection between ideal secret sharing and matroids and, in particular, the fact that every ideal access structure is a matroid port. In addition, we use recent results on ideal multipartite access structures and the connection between multipartite matroids and integer polymatroids. We prove that every ideal hierarchical access structure is the port of a representable matroid and, more specifically, we prove that every ideal structure in this family admits ideal linear secret sharing schemes over fields of all characteristics. In addition, methods to construct such ideal schemes can be derived from the results in this paper and the aforementioned ones on ideal multipartite secret sharing. Finally, we use our results to find a new proof for the characterization of the ideal weighted threshold access structures that is simpler than the existing one.Optimal non-perfect uniform secret sharing schemes
http://hdl.handle.net/2117/106119
Optimal non-perfect uniform secret sharing schemes
Farràs Ventura, Oriol; Hansen, Torben; Kaced, Tarik; Padró Laimon, Carles
A secret sharing scheme is non-perfect if some subsets of participants that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes. To this end, we extend the known connections between polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information that every subset of participants obtains about the secret value. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, the ones whose values depend only on the number of participants, generalize the threshold access structures. Our main result is to determine the optimal information ratio of the uniform access functions. Moreover, we present a construction of linear secret sharing schemes with optimal information ratio for the rational uniform access functions.
Tue, 04 Jul 2017 05:19:35 GMThttp://hdl.handle.net/2117/1061192017-07-04T05:19:35ZFarràs Ventura, OriolHansen, TorbenKaced, TarikPadró Laimon, CarlesA secret sharing scheme is non-perfect if some subsets of participants that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes. To this end, we extend the known connections between polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information that every subset of participants obtains about the secret value. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, the ones whose values depend only on the number of participants, generalize the threshold access structures. Our main result is to determine the optimal information ratio of the uniform access functions. Moreover, we present a construction of linear secret sharing schemes with optimal information ratio for the rational uniform access functions.The Stanford-ESA integrity diagram: focusing on SBAS integrity
http://hdl.handle.net/2117/105966
The Stanford-ESA integrity diagram: focusing on SBAS integrity
Tossaint, Michel Mathias Maria; Samson, Jaron; Toran, Felix; Ventura Traveset, Javier; Sanz Subirana, Jaume; Hernández Pajares, Manuel; Juan Zornoza, José Miguel
In this article, a new concept for SBAS integrity validation is presented. The proposed concept is a modification of the well known Stanford diagram [2], where a 2D histogram shows the relationship of position errors against protection levels for a set of measurements using an all in view satellite selection. The new method consists on two diagrams: the Worse-Safety Index diagram and the “All-Geometries” diagram, known here as the Stanford-ESA and the All-Stanford-ESA, respectively. The first consist on taking, at each sample time and given location, the worst possible satellite geometrical combination (out of all possible combinations) from a SBAS integrity margin viewpoint. In the second, all possible geometries are displayed and, in case of MIs, the geometries associated to each epoch are leveled with different symbols and colors. It allows, to easily identify the different clusters and to assess the time correlation of the events. Real measurement results are presented here showing that the EGNOS integrity margins remain safe under this very exigent criterion, a certainly very positive result. It is suggested here to use the Stanford-ESA Integrity concept, for routine performance monitoring and to support and complement the safety case of the EGNOS system with real experimental data.
Thu, 29 Jun 2017 07:26:46 GMThttp://hdl.handle.net/2117/1059662017-06-29T07:26:46ZTossaint, Michel Mathias MariaSamson, JaronToran, FelixVentura Traveset, JavierSanz Subirana, JaumeHernández Pajares, ManuelJuan Zornoza, José MiguelIn this article, a new concept for SBAS integrity validation is presented. The proposed concept is a modification of the well known Stanford diagram [2], where a 2D histogram shows the relationship of position errors against protection levels for a set of measurements using an all in view satellite selection. The new method consists on two diagrams: the Worse-Safety Index diagram and the “All-Geometries” diagram, known here as the Stanford-ESA and the All-Stanford-ESA, respectively. The first consist on taking, at each sample time and given location, the worst possible satellite geometrical combination (out of all possible combinations) from a SBAS integrity margin viewpoint. In the second, all possible geometries are displayed and, in case of MIs, the geometries associated to each epoch are leveled with different symbols and colors. It allows, to easily identify the different clusters and to assess the time correlation of the events. Real measurement results are presented here showing that the EGNOS integrity margins remain safe under this very exigent criterion, a certainly very positive result. It is suggested here to use the Stanford-ESA Integrity concept, for routine performance monitoring and to support and complement the safety case of the EGNOS system with real experimental data.Ensemble learning as approach for pipeline condition assessment
http://hdl.handle.net/2117/105753
Ensemble learning as approach for pipeline condition assessment
Camacho-Navarro, Jhonatan; Ruiz Ordóñez, Magda; Villamizar Mejía, Rodolfo; Mujica Delgado, Luis Eduardo; Moreno Beltran, Gustavo Adolfo
The algorithms commonly used for damage condition monitoring present several drawbacks related to unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures. Data from an active system based on piezoelectric sensors are stored and characterized through the T2 and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.
Fri, 23 Jun 2017 08:03:32 GMThttp://hdl.handle.net/2117/1057532017-06-23T08:03:32ZCamacho-Navarro, JhonatanRuiz Ordóñez, MagdaVillamizar Mejía, RodolfoMujica Delgado, Luis EduardoMoreno Beltran, Gustavo AdolfoThe algorithms commonly used for damage condition monitoring present several drawbacks related to unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures. Data from an active system based on piezoelectric sensors are stored and characterized through the T2 and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.Structural damage localization through an innovative hybrid ensemble approach
http://hdl.handle.net/2117/105748
Structural damage localization through an innovative hybrid ensemble approach
Moreno Beltran, Gustavo Adolfo; Villamizar Mejía, Rodolfo; Camacho-Navarro, Jhonatan; Ruiz Ordóñez, Magda; Mujica Delgado, Luis Eduardo
Damage localization in structures can be achieved by using an appropriate data
interpretation algorithm based on the expected structural response. According to the several algorithms reported in literature, a different degree of accuracy is obtained according to complexity requirements. This paper presents a hybrid algorithm approach as alternative to combine some of the reported methods by employing an ensemble architecture. Thus, this damage assessment
algorithm integrates advantage of individual techniques in order to increase the performance of the whole expert system. The proposed architecture employs a network of piezoelectric devices to produce guided waves along the structure. The traveling of guided waves is affected by damage producing scattering, reflection and mode conversion, which can be characterized with statistical processing and pattern recognition methods. In this paper, supervised learning by means on ensemble learning, cross-correlation features, and PCA statistical indices are combined
for locating damages. An experimental validation is conducted on an aircraft turbine blade structure instrumented with an array of piezoelectric devices (PZT), where it is demonstrated the potential of the methodology to significantly enhance localization tasks.
Fri, 23 Jun 2017 07:28:21 GMThttp://hdl.handle.net/2117/1057482017-06-23T07:28:21ZMoreno Beltran, Gustavo AdolfoVillamizar Mejía, RodolfoCamacho-Navarro, JhonatanRuiz Ordóñez, MagdaMujica Delgado, Luis EduardoDamage localization in structures can be achieved by using an appropriate data
interpretation algorithm based on the expected structural response. According to the several algorithms reported in literature, a different degree of accuracy is obtained according to complexity requirements. This paper presents a hybrid algorithm approach as alternative to combine some of the reported methods by employing an ensemble architecture. Thus, this damage assessment
algorithm integrates advantage of individual techniques in order to increase the performance of the whole expert system. The proposed architecture employs a network of piezoelectric devices to produce guided waves along the structure. The traveling of guided waves is affected by damage producing scattering, reflection and mode conversion, which can be characterized with statistical processing and pattern recognition methods. In this paper, supervised learning by means on ensemble learning, cross-correlation features, and PCA statistical indices are combined
for locating damages. An experimental validation is conducted on an aircraft turbine blade structure instrumented with an array of piezoelectric devices (PZT), where it is demonstrated the potential of the methodology to significantly enhance localization tasks.