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Diffusion MRI-based tractography, which is built by connecting the principal components of the estimated water diffusion pattern, is used to elucidate neuronal connectivity. However, the anatomical accuracy of the method is affected by factors such as noise and imaging misalignments. In this manuscript, we present a method to clean diffusion datasets by rotating the diffusion…

Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative…

The analysis of human sit down position is a research area allows for preventing health physical problems in the back. Many works have proposed systems that detect the sitting position, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an…

In order to increase the diagnosis accuracy of schizophrenia (SCZ) disease, it is essential to comprehensively employ complementary information from multiple types of data. It is well known that a network is a general method for analyzing relationships between patients, with its nodes representing patients and its edges showing relationships between them. In this study,…

Nowadays, compliant micro-motion stages offer high positioning accuracy and repeatability. When assembled with conventional stages, the resulting dual-range positioning systems allow for nanometer scale accuracy within a centimeter scale working area. However, such systems invoke a high cost and large footprint. This paper presents a low-cost, compact compliant XY micro-motion stage where dual-range manipulation has…

A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN). Most wormhole detection schemes reported in…

Breast cancer is one of the most common cancers among female diseases all over the world. Early diagnosis and treatment is particularly important in reducing the mortality rate. This research is focused on the prevention of breast cancer, therefore it is important to detect micro-calcifications (MCs) which are a sign of early stage breast cancer.…

In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine…

The unsupervised morphology processing in the emerging mutant languages has the advantage over the human/supervised processing of being more agiler. The main drawback is, however, their accuracy. This article describes an unsupervised morphemes identification approach based on an intuitive and formal definition of event dependence. The input is no more than a plain text of…

The article deals with the problem of increasing the accuracy of determination of aircraft’s navigation flight parameters. Increasing the accuracy and sensitivity of navigation parameters determination will improve the efficiency of air conveyance by optimizing the flight trajectories and reducing the flight time and simultaneously will ensure the sufficient level of air conveyance safety. The…

This paper extends some of our research results disseminated in the most recent awarded international conference paper concerning the implementation in real time of a sliding mode observer state estimator. For the same case study developed in the conference paper, more precisely a DC servomotor angular speed control system, we extend the proposed concept of…

Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer feed forward neural networks. Compared with the existing neural network learning algorithm it solves the slow training speed and over-fitting problems. It has been used in different fields and applications such as biomedical engineering, computer vision, remote sensing, chemical process…

Precision agriculture in recent times had assumed a different dimension in order to improve on the poor standard of agriculture. Similarly, the upsurge in technological advancement, most especially in the aspect of machine learning and artificial intelligence, is a promising trend towards a positive solution to this problem. Therefore, this research work presents a decision…

In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm  based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band.  Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD…

Over the years, pneumatic systems have recorded a remarkable performance in automated applications, based on their cost to efficiency ratio and ease of energy transmission.  Therefore, their drawback of not being totally controllable devices in terms of position accuracy, still represents a challenge task for engineers. In this paper, a traditional three term controller (PID)…