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In this study, we consider the dynamics of the Babesiosis transmission on bovine populations and ticks. The most important role in the transmission of the parasite is the ticks from the Ixodidae family. The vector tick takes factors (merozoites in erythrocytes) from the diseased animal while sucking the blood. To model and investigate the transmissions of this parasite and address this important issue, we have considered the disease in a fractional epidemiological model. This paper, therefore, discusses the mechanisms of transmission of Babesiosis defined in the fractional derivative sense. The Caputo-Fabrizio (CF) derivative is considered to study the propagation mechanisms of Babesiosis. First, the important characteristics of the model have been presented, and then the transmission of the Babesiosis model defined in CF is discussed. The application of fixed-point theory is used to derive the concept of the qualitative properties of the mentioned model. The solution is obtained by using the Homotopy perturbation Elzaki transform method (HPETM). Numerical simulations are performed, and the effects of the arbitrary-order derivatives are investigated graphically.

Feature extraction for Speech Emotion Recognition (SER) is a challenging task and there is no consensus among researchers on a single set of features which works best. Different speech features such as pitch, energy, formants, Mel-Scale Coefficients, Predictive Coding are used for classification but results are still not satisfactory enough. In this article, a new feature set is proposed which uses Discrete Wavelet Transform (DWT) to decompose the speech signal and computes dissimilarity with the neutral emotional state. The new feature set is used for emotion classification using three different classification techniques to establish that the feature set is giving better or competitive results compared to the contemporary features.

Scattering of neutron collision inside a reactor depends upon geometry of the reactor, diffusion coefficient and absorption coefficient etc. In general these parameters are not crisp and hence we may get uncertain neutron diffusion equation. In this paper we have investigated the above problem for a bare triangular homogeneous reactor. Here the uncertain governing differential equation is modelled by a modified fuzzy finite element method using newly proposed interval arithmetic. Obtained eigenvalues by the proposed method are studied in detail. Further the eigenvalues are compared with the classical finite element method in special cases and various uncertain results have been discussed.

A major problem of causal inference is the arrangement of dependent nodes in a directed acyclic graph (DAG) with path coefficients and observed confounders. Path coefficients do not provide the units to measure the strength of information flowing from one node to the other. Here we proposed the method of causal structure learning using collider v-structures (CVS) with Negative Percentage Mapping (NPM) to get selective thresholds of information strength, to direct the edges and subjective confounders in a DAG. The NPM is used to scale the strength of information passed through nodes in units of percentage from interval from 0 to 1. The causal structures are constructed by bottom up approach using path coefficients, causal directions and confounders, derived implementing collider v-structure and NPM. The method is self-sufficient to observe all the latent confounders present in the causal model and capable of detecting every responsible causal direction. The results are tested for simulated datasets of non-Gaussian distributions and compared with DirectLiNGAM and ICA-LiNGAM to check efficiency of the proposed method.

This paper presents a fault classification method which makes use of a Takagi-Sugeno neuro-fuzzy model and Pseudomodal energies calculated from the vibration signals of cylindrical shells. The calculation of Pseudomodal Energies, for the purposes of condition monitoring, has previously been found to be an accurate method of extracting features from vibration signals. This calculation is therefore used to extract features from vibration signals obtained from a diverse population of cylindrical shells. Some of the cylinders in the population have faults in different substructures. The pseudomodal energies calculated from the vibration signals are then used as inputs to a neuro-fuzzy model. A leave-one-out cross-validation process is used to test the performance of the model. It is found that the neuro-fuzzy model is able to classify faults with an accuracy of 91.62%, which is higher than the previously used multilayer perceptron., 8 pages, In Proceedings of the Asia-Pacific Workshop on Structural Health Monitoring, Yokohama, Japan, 2006

Tuned Mass Damper (TMD) devices have been widely studied and optimised in the framework of persistent dynamic loadings, such as harmonic and white noise excitations, in order to reduce as much as possible the steady-state response of an assigned primary structure. In this sense, the present paper arises as a complementary study on the topic, since here shock input is assumed as dynamic loading, so as to investigate the effectiveness of TMDs in reducing the transient structural response. In particular, an impulsive loading has been considered, acting as a base displacement, which is a situation that may occur in real applications. First, a comprehensive dynamic analysis of the system comprising of a primary structure and an attached passive TMD is carried out in the time domain. Focus is placed on the relationships between the load input and the system properties, in order to explore the dynamic behaviour of such system and to identify the main response trends, mostly as a function of the free TMD parameters, namely mass, frequency and TMD damping ratios. Subsequently, a hybrid TMD has been considered, by adding a feedback controller to the previously optimised passive TMD, so as to improve the performance of such a device, especially in reducing the peak response of the primary structure. The contents of the present work have the final aim of identifying the potential level of effectiveness of the TMD devices and to supply important guidelines towards their optimal design in reducing the structural response also to shock excitations. This should display significant relevance in different practical applications, including in the field of earthquake engineering.