Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...

  Background :Cell proliferation is one of the most critical factors in metastasis and prognosis of the malignant tumors.Recent investigations show that the eosinophil granolosytes have an important role in developing of malignant tumors. The relation between cell proliferation and eosinophilic infiltration in oral squamous cell carcinoma (OSCS) with prognosis is unclear.The aim of this study w...

Uterine leiomyoma is the most common benign tumor of genital tract. The etiology of myomas is unknown. Leiomyoma shows a broad spectrum of radiographic appearances depending on the number, size, and location of the tumor. The diagnostic method for uterine leiomyomas is based primarily on the clinical situation. Despite of the varied diagnostic options such as; transvaginal sonography, sonohyste...

background : wilson disease (wd) is an autosomal recessive progressive degeneration of hepatolenticular tissue that causes the increase of copper deposition in the liver and other organs, with resultant hepatic, neurologic and psychological manifestations. wd is fatal if left untreated. the aim of the current study was to evaluate the clinical and para-clinical findings in children with wd in s...

In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

High dimensional microarray datasets are difficult to classify since they have many features with small number ofinstances and imbalanced distribution of classes. This paper proposes a filter-based feature selection method to improvethe classification performance of microarray datasets by selecting the significant features. Combining the concepts ofrough sets, weighted rough set, fuzzy rough se...

Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operat...