Magnetoelasticity and magnetoresistance in Cu-Al-Mn shape-memory alloys

We study the effect of a magnetic field on the martensitic transition of a Cu-Al-Mn shape-memory alloy. The martensitic transition has been studied through resistance measurements under applied magnetic fields ranging from 0 to 50 kOe. Negative magnetoresistance showing an almost linear dependence with the square of the magnetization has been observed. This magnetoresistive effect is associated with the existence of small ferromagnetic Mn-clusters. Its strength and thermal dependence is different in both phases. The martensitic transition temperature is slightly increased and its spread in temperature significantly reduced upon increasing the field. These results show the existence of magnetoelastic coupling, which favors the nucleation of those martensitic variants with the easy magnetization axis aligned with the field.

Chaotic, memory, and cooling rate effects in spin glasses: Evaluation of the Edwards-Anderson model

We investigate chaotic, memory, and cooling rate effects in the three-dimensional Edwards-Anderson model by doing thermoremanent (TRM) and ac susceptibility numerical experiments and making a detailed comparison with laboratory experiments on spin glasses. In contrast to the experiments, the Edwards-Anderson model does not show any trace of reinitialization processes in temperature change experiments (TRM or ac). A detailed comparison with ac relaxation experiments in the presence of dc magnetic field or coupling distribution perturbations reveals that the absence of chaotic effects in the Edwards-Anderson model is a consequence of the presence of strong cooling rate effects. We discuss possible solutions to this discrepancy, in particular the smallness of the time scales reached in numerical experiments, but we also question the validity of the Edwards-Anderson model to reproduce the experimental results.

Parrondo-like behavior in continuous-time random walks with memory

The continuous-time random walk (CTRW) formalism can be adapted to encompass stochastic processes with memory. In this paper we will show how the random combination of two different unbiased CTRWs can give rise to a process with clear drift, if one of them is a CTRW with memory. If one identifies the other one as noise, the effect can be thought of as a kind of stochastic resonance. The ultimate origin of this phenomenon is the same as that of the Parrondo paradox in game theory.

A comparative long-memory Analysis between Spanish, Mexican and U.S. interest rates

Evidence exists that many natural facts are described better as a fractal. Although fractals are very useful for describing nature, it is also appropiate to review the concept of random fractal in finance. Due to the extraordinary importance of Brownian motion in physics, chemistry or biology, we will consider the generalization that supposes fractional Brownian motion introduced by Mandelbrot.The main goal of this work is to analyse the existence of long range dependence in instantaneous forward rates of different financial markets. Concretelly, we perform an empirical analysis on the Spanish, Mexican and U.S. interbanking interest rate. We work with three time series of daily data corresponding to 1 day operations from 28th March 1996 to 21st May 2002. From among all the existing tests on this matter we apply the methodology proposed in Taqqu, Teverovsky and Willinger (1995).

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

Ferromagnetic shape memory alloys: structural and thermal properties

The most extensively studied Heusler alloys are those based on the Ni-Mn-Ga system. However, to overcome the high cost of Gallium and the usually low martensitic transformation temperature, the search for Ga-free alloys has been recently attempted, particularly, by introducing In, Sn or Sb. In this work, two alloys (Mn50Ni35.5In14.5 and Ni50Mn35In15) have been obtained by melt spinning. We outline their structural and thermal behaviour. Mn50Ni35.5In14.5 alloy has the transformation above room temperature whereas Ni50Mn35In15 does not have this transformation in the temperature range here analyzed

Atomic Ordering and Martensitic Transitions in Cu-Zn-Al Shape Memory Alloys

We present results from both, calorimetric and dilatometric studies of the isothermal ordering process taking place in a Cu-Zn-Al shape memory alloy after quenches from Tq temperatures ranging from 350 K to 1200 K. The dissipated energy and the length variations of the system are obtained during the process. The change of these quantities in the whole process have been compared with the difference [MATH] between Ms, measured after the relaxation and Ms measured just after the quench. We obtain that these three quantities present, as a function of Tq, the same qualitative behaviour. These changes are then associated with changes of the L21 ordering after the quench in the system. The relaxational process does not follow a single exponential decay. Instead, a continuous slowing down is observed. A relaxation time [MATH] has been defined to characterize the relaxation rate. We show that [MATH] depends on both the annealing and the quenching (Tq [MATH] 800 K) temperatures through an Arrhenius law.

Memory Revisited in Julian Barnes's The Sense of an Ending

An accumulation of years brings with it an accumulation of experiences. The revision of such experiences usually becomes more recurrent after retirement, a transition time from one period of life to another and, as such, a time in which we, human beings, have a tendency to take stock of our lives. This is actually one of the main issues present in Julian Barnes's last novel The Sense of an Ending (2011). When the main protagonist, a retired man quite comfortable and contented with his present life, receives an unexpected inheritance from the mother of a girlfriend from his university years, he is forced to track down a part of his life that he had left at the back of his mind a long time ago. As he explains his story, the protagonist and narrator of the novel raises a number of questions related to the quality and function of memory as one gets into old age. He experiments the unreliability of memory and questions to what extent memory is constructed through the remembered emotions that invaded him over that episode of his life rather than through the events as they actually took place. On the other hand, the act of revisiting and revising that specific episode, brings with it feelings of guilt and remorse as the protagonist realises that his past acts were not as noble as he remembered them to be. However, these acts are part of the past and they cannot be changed; thus, another question that the novel raises is how to account for those actions of which one does not feel proud and, more importantly, how to manage those bad memories as one gets older.