Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are Z_H (9.2-13.8) m, Z_d (4.3-8.1) m and Z_o (0.24-0.48) m.

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Natural frequency under initial stresses for simply supported cross-ply composite laminated plates (E glass- fiber) are obtained using Refind theory (RPT). This theory accounts for parabolic distribution of the transverse shear strain through the plate thickness and satisfies the zero traction boundary conditions on the surfaces of the plate without using shear correction factors. The governing equations for Eigen value problem under initial stress are derived using Hamilton’s principle and solved using Navier solution for simply supported cross-ply symmetric and antisymmetric laminated plates. The effect of many design factors such as modulus ratio, thickness ratio and number of laminates on the Natural frequency and buckling stresses

Colloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO₃ (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be

In this paper, Touchard polynomials (TPs) are presented for solving Linear Volterra integral equations of the second kind (LVIEs-2k) and the first kind (LVIEs-1k) besides, the singular kernel type of this equation. Illustrative examples show the efficiency of the presented method, and the approximate numerical (AN) solutions are compared with one another method in some examples. All calculations and graphs are performed by program MATLAB2018b.

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

Sensitive information of any multimedia must be encrypted before transmission. The dual chaotic algorithm is a good option to encrypt sensitive information by using different parameters and different initial conditions for two chaotic maps. A dual chaotic framework creates a complex chaotic trajectory to prevent the illegal use of information from eavesdroppers. Limited precisions of a single chaotic map cause a degradation in the dynamical behavior of the communication system. To overcome this degradation issue in, a novel form of dual chaos map algorithm is analyzed. To maintain the stability of the dynamical system, the Lyapunov Exponent (LE) is determined for the single and dual maps. In this paper, the LE of the single and dual maps

This study was performed on the Tigris River (Baghdad city section) during the period between December 2016 and December 2018 to assess seasonal variation in water quality using the Overall Index of Pollution (OIP). The OIP is one of the reliable tools for the assessment of surface water quality. To calculate OIP-values, eight parameters were measured ( pH, Dissolved Oxygen "DO", Biological Oxygen Demand "BOD", Total Dissolved Solid "TDS", Total Hardness "TH", calcium "Ca", Sulphate "SO4" and Alkalinity). The results showed the anthropogenic activities impact of Baghdad population that directly discharge of "inadequate treated" waste water to the river.  OIP values were acceptable (1˃OIP˃ 1.7) in 2011, 2012, 2013 and 2018. However, in

       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor