With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

Objective: To compare the efficacy and safety of isosorbide mononitrate (IMN) versus misoprostol used to induce labour for overdue pregnancy.
Setting: A prospective randomized clinical study conducted at AL-Elwiya Maternity Teaching Hospital in Baghdad from Jan. 2008 to Dec. 2008.
Method: One hundred and fifty women with over due pregnancy (past date and posterm pregnancy) referred for induction of labour with Bishop scores <_ 5 were randomly allocated to receive either forty mg isosorbide mononitrate (IMN) tablet as a single vaginal dose (n=75) or fifty mcg misoprostol vaginally (n=75) every six hrs for a maximum of three doses. Amniotomy and/or oxytocin infusion is considered when Bishop scores frankly progressed (augmentation

Electronic Commerce (EC) is an important field due to the many advantages it involves. This study aims to discuss the constraints surrounding educated Iraqi women which results overall lack of entering the EC and to give us additional insight into why they are avoiding entering this world. Results reveal that lack of awareness, lack of government policy and support, language, security and trust are the most important factors that contributes to EC adoption in addition to many other factors

Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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This research including, CO3O4 was prepared by the chemical spry pyrolysis, deposited film acceptable to assess film properties and applications as photodetector devise, studying the optical and optoelectronics properties of Cobalt Oxide and effect of different doping ratios with Br (2, 5, 8)%. the optical energy gap for direct transition were evaluated and it decreases as the percentage Br increase, Hall measurements showed that all the films are p-type, the current–voltage characteristic of Br:CO3O4 /Si Heterojunction show change forward current at dark varies with applied voltage, high spectral response, specific detectivity and quantum efficiency of CO3O4 /Si detector with 8% of Br ,was deliberate, extreme value with 673nm.

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

The method of operational matrices based on different types of polynomials such as Bernstein, shifted Legendre and Bernoulli polynomials will be presented and implemented to solve the nonlinear Blasius equations approximately. The nonlinear differential equation will be converted into a system of nonlinear algebraic equations that can be solved using Mathematica®12. The efficiency of these methods has been studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as the polynomial degree (n) increases, since the errors decrease. Moreover, the approximate solutions obtained by the proposed methods are compared with the solution of the 4th order Runge-Kutta method (RK4), which gives very