Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si
... Show MoreSpeech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreThis paper displays the effect of uncoated and coated chopped carbon fibers with alumina Al2O3 or Tri calcium phosphate (TCP) on the impact strength of acrylic poly methyl methacrylate (PMMA) denture base resin. To improve bonding between carbon fibers and coating materials powders, the surface of carbon fibers has been treated with Para amino benzoic acid (C9H10N2O3) and poly vinyl alcohol (PVA) was also used. The morphology of the coating layers has been examined by field emission scanning electron microscope (FE-SEM). From the results, PMMA reinforced with uncoated chopped carbon fiber has high impact strength value but still have bad aesthetic. Samples prepared b
... Show MoreFlexible pavement design and analysis were carried out in the past with semi-experimental methods, using elastic characteristics of pavement layers. Due to the complex interferences between various layers and their time consumption, the traditional pavement analysis, and design methods were replaced with fast and powerful methods including the Finite Element Method (FEM) and the Discrete Element Method (DEM). FEM requires less computational power and is more appropriate for continuous environments. In this study, flexible pavement consisting of 5 layers (surface, binder, base, subbase, and subgrade) had been analyzed using FEM. The ABAQUS (6.14-2) software had been utilized to investigate the influence of the base layer depth on ver
... Show MoreThe 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
... Show MoreLowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.