Exchange of information through the channels of communication can be unsafe. Communication media are not safe to send sensitive information so it is necessary to provide the protection of information from disclosure to unauthorized persons. This research presented the method to information security is done through information hiding into the cover image using a least significant bit (LSB) technique, where a text file is encrypted using a secret sharing scheme. Then, generating positions to hiding information in a random manner of cover image, which is difficult to predict hiding in the image-by-image analysis or statistical analyzes. Where it provides two levels of information security through encryption of a text file using the secret sha

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

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Some problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) bi-orthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used t

Different solvents (light naphtha, n-heptane, and n-hexane) are used to treat Iraqi Atmospheric oil residue by the deasphalting process. Oil residue from Al-Dura refinery with specific gravity 0.9705, API 14.9, and 0.5 wt. % sulfur content was used. Deasphalting oil (DAO) was examined on a laboratory scale by using solvents with different operation conditions (temperature, concentration of solvent, solvent to oil ratio, and duration time). This study investigates the effects of these parameters on asphaltene yield. The results show that an increase in temperature for all solvents increases the extraction of asphaltene yield. The higher reduction in asphaltene content is obtained with hexane solvent at operating conditions of (90 °C

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Gypsum Plaster is an important building materials, and because of the availabilty of its raw materials. In this research the effect of various additives on the properties of plaster was studied , like Polyvinyl Acetate, Furfural, Fumed Silica at different rate of addition and two types of fibers, Carbon Fiber and Polypropylene Fiber to the plaster at a different volumetric rate. It was found that after analysis of the results the use of Furfural as an additive to plaster by 2.5% is the optimum ratio of addition to that it improved the flexural Strength by 3.18%.
When using Polyvinyl Acetate it was found that the ratio of the additive 2% is the optimum ratio of addition to the plaster, because it improved the value of the flexural stre

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima