Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

The aim of current study is to analyze the content of intermediate stage biology books based on multiple intelligences. To do this, the researcher used the descriptive analytical approach. To analyze the three books of the intermediate stage, the author adopted content analysis tool and area unit. They were exposed to group of experts in methods of teaching biology, and measurement and evaluation. The findings of the study have shown a significant difference between what was expected and the observation of the multiple intelligences for the three biology books excluded the (social, musical, and kinetic intelligence), and there is no significant difference between the analysis' result of the biology books and the expectations of b

This paper proposes a hybrid speech enhancement estimator that integrates the Perceptually-motivated Karhunen–Loève Transform (PKLT) with the Dual-Masking Harmonic-based (DMH) algorithm in a unified framework termed PKDMH. The main novelty lies in combining perceptual subspace projection with harmonic-residual suppression, enabling the system to jointly remove noise while preserving speech-relevant spectral cues. PKLT first performs perceptual subspace projection and suppresses inaudible components, after which DMH eliminates remaining broadband and harmonic residuals. The proposed PKDMH system was evaluated using the TIMIT dataset contaminated with five noise types: White, Pink, F16, Airport, and Car noise—across five SNR leve

Glassy polymers like Poly Mathyel Metha Acrylate are usually classified as non-porous materials; they are almost considered as fully transparent. Thin samples of these materials reflect color changing followed by porous formation and consequently cracking when exposed to certain level of ?-irradiation. The more the dose is the higher the effect have been observed. The optical microscope and UV-VIS spectroscopy have clearly approved these consequences especially for doped polymers.

 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

The aim of the current study was to evaluate the knowledge and perception of the fifth stage pharmacy students (college of pharmacy/ University of Baghdad /Iraq) regarding generic medicines. This study is a cross-sectional study carried in a college of pharmacy /University of Baghdad during the period from (November 2018- March 2019). The number of students included in the current study was 168 undergraduate stager pharmacists. A questionnaire was used to collect data of the study. Nearly 86% of the students said that they had heard of generic and brand medicines, and pharmacy was the main source of knowledge regarding generic medicines (66.7%).  About (33.3%) of the respondents agreed that generic medicines are bioequivalent to br

The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio