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

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

This research was aimed to study the efficiency of microfiltration membranes for the treatment of oily wastewater and the factors affecting the performance of the microfiltration membranes experimental work were includes operating the microfiltration process using polypropylene membrane (1 micron) and ceramic membrane (0.5 micron) constructed as candle; two methods of operation were examined: dead end and cross flow. The oil emulsion was prepared using two types of oils: vegetable oil and motor oil (classic oil 20W-50). The operating parameters studied are: feed oil concentration 50 – 800 mg/l, feed flow rate 10 – 40 l/h, and temperature 30 – 50 oC, for dead end and cross flow microfiltration.
It was found that water flux decrea

     Estimating multivariate location and scatter with both affine equivariance and positive break down has always been difficult. Awell-known estimator which satisfies both properties is the Minimum volume Ellipsoid Estimator (MVE) Computing the exact (MVE) is often not feasible, so one usually resorts to an approximate Algorithm. In the regression setup, algorithm for positive-break down estimators like Least Median of squares typically recomputed the intercept at each step, to improve the result. This approach is called intercept adjustment. In this paper we show that a similar technique, called location adjustment, Can be applied to the (MVE). For this purpose we use the Minimum Volume Ball (MVB). In order

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.

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative