This paper investigates the simultaneous recovery for two time-dependent coefficients for heat equation under Neumann boundary condition. This problem is considered under extra conditions of nonlocal type. The main issue with this problem is the solution unstable to small contamination of noise in the input data. The Crank-Nicolson finite difference method is utilized to solve the direct problem whilst the inverse problem is viewed as nonlinear optimization problem. The later problem is solved numerically using optimization toolbox from MATLAB. We found that the numerical results are accurate and stable.

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

Prenatal markers are commonly used in practice to screen for some foetal abnormalities. They can be biochemical or ultrasonic markers in addition to the newly used cell free Deoxyribonucleic Acid (DNA) estimation. This review aimed to illustrate the applications of the prenatal screening, and the reliability of these tests in detecting the presence of abnormal chromosomes such as trisomy-21, trisomy-18, and trisomy-13 in addition to neural tube defects. Prenatal markers can also be used in the anticipation of some obstetrical complications depending on levels of these markers in the mother’s circulation. In the developed countries, prenatal screening tests are regularly used during antenatal care period. Neural tube defects, numer

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

Meerkat Clan Algorithm (MCA) that is a swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. Meerkat has some behaviour. Sentry, foraging, and baby-sitter are the behaviour used to build this algorithm through dividing the solution sets into two sets, all the operations are performed on the foraging set. The sentry presents the best solution. The Flexible Job Shop Scheduling Problem (FJSSP) is vital in the two fields of generation administration and combinatorial advancement. In any case, it is very hard to accomplish an ideal answer for this problem with customary streamlining approaches attributable to the high computational unpredictability. Most

The present study focuses on the biological strategy for treating cancer and parasitic infections, such as leishmaniasis antiparasitic activity, forthe crude alcoholic extract ofFicus leaves and their extracted total flavonoids with a comparison between their effects.The flavonoids were extracted from the leaves of the mature Ficuscaricausing the reflux extraction method. Total flavonoids were detected qualitatively by TLC techniquewhich demonstratedthat the plant was rich indifferent flavonoids, especially Rutin, Quercetin, Kaempferol, luteolin and others. Quantitatively, the plant total flavonoids content was 337.3 mg / 100 g fig leaves calculated as rutin.The biologicaleffects of the crude and purified total flavonoi

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

This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori