A new homotopy perturbation method for solving systems of partial differential equations

In this paper, a new homotopy perturbation method (NHPM) is introduced for obtaining solutions of systems of non-linear partial differential equations. Theoretical considerations are discussed. To illustrate the capability and reliability of the method three examples are provided. Comparison of the results of applying NHPM with those of applying HPM reveal the effectiveness and convenience of the new technique.     

Relaxed constraints support vector machines for noisy data

Real-world data collected for computer-based applications are frequently impure. Differentiation of outliers and noisy data from normal ones is a major task in data mining applications. On the other hand, elimination of noisy and outlier data from training samples of a dataset may lead to over-fitting or information loss. A fuzzy support vector machine (FSVM) provides an effective means to deal with this problem. It reduces the effect of the noisy data and outliers by using a fuzzy membership functions. In this paper, a new formation for SVMs is introduced that considers importance degrees for training samples. The constraints of the SVM are converted to fuzzy inequalities. The proposed method, RSVM, shows better efficiency in the classification of data in different domains. Especially, using the proposed RSVM for multi-class classification of arrhythmia disease is presented at the end of this paper as a practical case study to show the effectiveness of the proposed system.     

Sense and sidedness in the graphics pipeline via a passage through a separable space

Computer graphics is ostensibly based on projective geometry. The graphics pipeline—the sequence of functions applied to 3D geometric primitives to determine a 2D image—is described in the graphics literature as taking the primitives from Euclidean to projective space, and then back to Euclidean space. This is a weak foundation for computer graphics. An instructor is at a loss: one day entering the classroom and invoking the established and venerable theory of projective geometry while asserting that projective spaces are not separable, and then entering the classroom the following week to tell the students that the standard graphics pipeline performs clipping not in Euclidean, but in projective space—precisely the operation (deciding sidedness, which depends on separability) that was deemed nonsensical. But there is no need to present Blinn and Newell’s algorithm (Comput. Graph. 12, 245–251, 1978; Commun. ACM 17, 32–42, 1974)—the crucial clipping step in the graphics pipeline and, perhaps, the most original knowledge a student learns in a fourth-year computer graphics class—as a clever trick that just works. Jorge Stolfi described in 1991 oriented projective geometry. By declaring the two vectors and distinct, Blinn and Newell were already unknowingly working in oriented projective space. This paper presents the graphics pipeline on this stronger foundation.

Energy Consumption Optimization for Mobile Robots Motion Using Predictive Control

Operation of mobile robots in off-road environment requires the attention to the torque saturation problem that occurs in the wheels DC motors while climbing hills. In the present work, off-road conditions are utilized to benefit while avoiding torque saturation. Energy optimization algorithm using predictive control is implemented on a two-DC motor-driven wheels mobile robot while crossing a ditch. The predictive control algorithm is simulated and compared with the PID control and the open-loop control. Predictive control showed more capability to avoid torque saturation and noticeable reduction in the energy consumption. Furthermore, using the wheels motors armature current instead of the supply voltage as control variable in the predictive control showed more efficient speed control. Simulation results showed that in case of known ditch dimensions ahead of time, the developed algorithm is feasible. Experimental examination of the developed energy optimization algorithm is presented. The experimental results showed a good agreement with the simulation results. The effects of the road slope and the prediction horizon length on the consumed energy are evaluated. The analytical study showed that the energy consumption is reduced by increasing the prediction horizon until it reaches a limit at which no more energy reduction is obtained. This limit is proportional to the width of the ditch in front of the mobile robot. Curve fitting is applied to the obtained results to address further the effect of the parameters on the energy consumption.     

Adaptive synchronization between two non-identical BAM neural networks with unknown parameters and time-varying delays

International Journal of Control, Automation and Systems - In this paper, the synchronization of two non-identical bidirectional associative memory (BAM) neural networks with unknown parameters and...     

Optimal shape design of functionally graded thickness inversion tubes subjected to oblique loading

This paper aims to understand and optimize the crush response of Functionally Graded Thickness (FGT) tubes with various thickness distributions subjected to oblique loading using multi-objective optimization method. Hence, finite element (FE) models are established and their results are validated by experimental tests. Two objective functions (specific energy absorption and peak load) are approximated by four different multi-objective optimization models: the weighted average, multi-design optimization (MDO) technique, constrained single-objective optimization, and geometrical average methods. The optimum design results demonstrate that the selection of appropriate inversion tube parameters such as the die radius, the coefficient of friction between the die and tube, and thickness distribution function have significant roles in the crashworthiness design. The results give new ideas to improve the crashworthiness performance of inversion tubes under oblique loading conditions.     

Arabic handwritten digit recognition

In this paper, we fill a gap in the literature by studying the problem of Arabic handwritten digit recognition. The performances of different classification and feature extraction techniques on recognizing Arabic digits are going to be reported to serve as a benchmark for future work on the problem. The performance of well known classifiers and feature extraction techniques will be reported in addition to a novel feature extraction technique we present in this paper that gives a high accuracy and competes with the state-of-the-art techniques. A total of 54 different classifier/features combinations will be evaluated on Arabic digits in terms of accuracy and classification time. The results are analyzed and the problem of the digit ‘0’ is identified with a proposed method to solve it. Moreover, we propose a strategy to select and design an optimal two-stage system out of our study and, hence, we suggest a fast two-stage classification system for Arabic digits which achieves as high accuracy as the highest classifier/features combination but with much less recognition time.     

Optical coherence tomography used for security and fingerprint-sensing applications

Optical coherence tomography (OCT) is an emerging technology for high-resolution cross-sectional imaging of three-dimensional structures. In the past, OCT systems have been used mainly for medical applications, especially ophthalmological diagnostics. As the OCT system is capable of exploring the internal features of an object, the authors apply OCT technology to document security and fingerprint-based biometrics by directly retrieving the two-dimensional information form of a multiple-layer information carrier and internal human body objects. Since a typical depth-resolution of an OCT system is of micrometre scale, an information carrier having a volume of 20 mm times 20 mm times 2 mm could contain 200 mega-pixel images. On other hand, the technologies used in conventional biometrics can be easily fooled and tampered with by using artificial dummies, because these ID features are extracted only from the surface of the skin. Hence the use of OCT to explore the internal biometrics becomes increasingly important.