Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

The research problem is clearly deficient suffered by the internal audit function in all institutions of Iraq, as a result of the lack of sponsor organizations for this profession and there is no law or local legislation determine its powers and its responsibilities and scope of work As well as the lack of interest of senior management in economic units that function, as it focuses its work on the scope of financial and accounting matters only So required to rebuild this function in line with the current developments as well as the lack of a framework that defines the strategy of this function, and it came the idea of research to find out how to create a regulatory method for re-strategic construction of the internal audit function depen

The city has normal natural state, and the man has a usual movement, change and search for the new .Also, the city has a usual change and transform in its time, place and quality (sizes)structures. The city has a solid memory diving into the past and the future and reflects The real present, and this memory has a timing layers change into real materialistic place making the city has accumulated overlapping circles which is hard to break u , and it broadcasts the lockup timing density ,in which there is no visual record precisely, it is just like((the social record)) that evaluates the un visual relationships between the components and parts of the city (community and form) in a visual quiet exhibition and transform change inside.

Five samples of the ternary alloy Ge-S-Cd were created using the melting point method, and the effects of partially substituting cadmium for germanium were determined. and partial substitution of germanium by cadmium was used to study the change in electrical conductivity. Electrical experiments were performed on Ge_35-xS₆₅Cd_xternary alloy with x = 0, 5, 10, 15, and 20. It was discovered that the conductivity (σ_dc) rises with rising temperature in all samples under experiment. This confirms that the samples have semiconductor behavior. It has been observed that there are three regions of electrical conductivity in the electrical conductivity curve at low, moderate, and high temperatures. The pr

The main goal of this paper is to study and discuss a new class of meromorphici "functions[ which are multivalent defined by [fractional  calculus operators. Coefficients iestimates , radiisi of satarlikeness , convexityi and closed-to-iconvexity are studied. Also distortion iand closure theorems for the classi" ,  are considered.

this study aimed to study the effect of Cordia myxa extract on the growth and activities of the following types of bacteria : Escherichia coli , Pseudomonas aeruginosa, Proteus Spp., Klebsiella pneumoniae , Staphylococcus aureus, Streptococcus pyogenes , Bacillus subtilus, and the yeast Candida albicans .the results showed an inhibitory effect of the methanol extract on both the growth and activity of the tested microbes .this was reflected by the minimum inhibitory concentration ( MIC ) of different type of bacteria and the yeast.

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

We focus on studying the dynamics of bulk semiconductor optical amplifiers and their effects on the saturation region for short pulse that differ, however there is the same unsaturated gain for both dynamics. Parameters like current injection, fast dynamics present by carrier heating (CH), and spectra hole burning (SHB) are studied for regions that occur a response to certain dynamics. The behavior of the saturation region is found to be responsible for phenomena such as recovery time and chirp for the pulse under study.

     This paper is concerned with preliminary test double stage shrinkage estimators to estimate the variance (s²) of normal distribution when a prior estimate  of the actual value (s²) is a available when the mean is unknown  , using specifying shrinkage weight factors y(×) in addition to pre-test region (R).

      Expressions for the Bias, Mean squared error [MSE (×)], Relative Efficiency [R.EFF (×)], Expected sample size [E(n/s²)] and percentage of overall sample saved of proposed estimator were derived. Numerical results (using MathCAD program) and conclusions are drawn about selection of different constants including in the me