When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every property in the classification. The classifier is according to Feed Forward Back Propagation Artificial Neural Network (FP-ANN) in the classification stage. The properties thereafter derived to be implemented to teach a neural network based binary classifier that will be automatically able to conclude whether the image is that of a pathological, suffering from brain lesion, or a normal brain. The proposed algorithm obtained the sensitivity of 97.50%, specificity of 82.86% and accuracy of 94.3% for clinical Brain MRI database. This outcome proofs that the presented algorithm is robust and effective compared with other recent techniques.
Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth
... Show MoreA number of aqueous samples were collected from river Tigris in Baghdad city, enriched ~1000 times using solid phase extraction (SPE), then extracted the trace concentrations of some polychlorinated biphenyls (PCB) using an aqueous two-phase system (ATPS) composed of 1Methylpyridinium chloride [MePy]Cl and KH2PO4 salt. High performance liquid chromatography technique coupled with ultraviolet (HPLC-UV) is used for the quantification. Extraction under the optimized conditions of pH, solvent composition, duration and temperature has given with a yield of PCB about 91%. The limit of detection (LOD) and limit of quantification (LOQ) for analyses are 0.11-0.62 µg.L−1 and 2.67–3.43 µg.L−1 respectively with relative stan
... Show MoreThe presented work includes the Homotopy Transforms of Analysis Method (HTAM). By this method, the approximate solution of nonlinear Navier- Stokes equations of fractional order derivative was obtained. The Caputo's derivative was used in the proposed method. The desired solution was calculated by using the convergent power series to the components. The obtained results are demonstrated by comparison with the results of Adomain decomposition method, Homotopy Analysis method and exact solution, as explained in examples (4.1) and (4.2). The comparison shows that the used method is powerful and efficient.
This paper introduces the Multistep Modified Reduced Differential Transform Method (MMRDTM). It is applied to approximate the solution for Nonlinear Schrodinger Equations (NLSEs) of power law nonlinearity. The proposed method has some advantages. An analytical approximation can be generated in a fast converging series by applying the proposed approach. On top of that, the number of computed terms is also significantly reduced. Compared to the RDTM, the nonlinear term in this method is replaced by related Adomian polynomials prior to the implementation of a multistep approach. As a consequence, only a smaller number of NLSE computed terms are required in the attained approximation. Moreover, the approximation also converges rapidly over a
... Show MoreDetecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated und
... Show MoreThe DEM (Digital elevation model) means that the topography of the earth's surface (such as; Terrain relief and ocean floors), can be described mathematically by elevations as functions of three positions either in geographical coordinates, (Lat. Long. System) or in rectangular coordinates systems (X, Y, Z). Therefore, a DEM is an array number that represents spatial distributions of terrain characteristics. In this paper, the contour lines with different interval of high-resolution digital elevation model (1m) for AL-khamisah, The Qar Government was obtained. The altitudes ranging is between 1 m – 8.5 m, so characterized by varying heights within a small spatial region because it represents in multiple spots with flat surfaces.
This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s
This paper examines the change in planning pattern In Lebanon, which relies on vehicles as a semi-single mode of transport, and directing it towards re-shaping the city and introducing concepts of "smooth or flexible" mobility in its schemes; the concept of a "compact city" with an infrastructure based on a flexible mobility culture. Taking into consideration environmental, economical and health risks of the existing model, the paper focuses on the four foundations of the concepts of "city based on culture flexible mobility, "and provides a SWOT analysis to encourage for a shift in the planning methodology.
Abstract
Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance. This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS). Simulatio
... Show MoreThe essential objective of this paper is to introduce new notions of fibrewise topological spaces on D that are named to be upper perfect topological spaces, lower perfect topological spaces, multi-perfect topological spaces, fibrewise upper perfect topological spaces, and fibrewise lower perfect topological spaces. fibrewise multi-perfect topological spaces, filter base, contact point, rigid, multi-rigid, multi-rigid, fibrewise upper weakly closed, fibrewise lower weakly closed, fibrewise multi-weakly closed, set, almost upper perfect, almost lower perfect, almost multi-perfect, fibrewise almost upper perfect, fibrewise almost lower perfect, fibrewise almost multi-perfect, upper* continuous fibrewise upper∗ topol
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