Abstract

               The main problem of the study lies in the lack of a clear perception among the study sample about the impact of digital marketing tools on legal liquidity. Legal) of the International Development Bank for Investment and Finance and to achieve the objectives of the research, the method of observation and survey was used in measuring the dimensions of digital marketing. As for banking liquidity, the reports and financial statements of the bank were used as the research sample, as well as the use of the statistical analysis program SPSS in the statement of the relationship The study concluded, in summary, the following: Mar

Background: Squamous cell carcinoma is a disease of elderly peopleand it is uncommon in people with less than 40 years old; however many literatures revealed that tumor developing in patients younger than forty years appears more aggressive at the time of diagnosis. The purpose of the present study was to focus on the clincopathological features of the oral SCC in different age groups. Material and methods: In this study thirty five cases of paraffin embedded tissue blocks of oral squamous cell carcinoma were studied. The age range was from 16 to 80 years. The clinicopathological data were recorded for evaluating the tumor characters according to age of patients. Results : The age was not significantly correlated to the clinicopathological

The term ‘photometry’ refers to the accurate determination of the apparent brightness of an astronomical object. Until roughly 1980, nearly all astronomical photometry was done by means of analog measurements of photographic plates, or by analog or digital (photon-counting) techniques with photomultipliers. These photometers produced brightness readings which were typically displayed on dials, plotted on strip charts or printed on strips of paper, and it was often quite practical to analyse these raw data with pencil, paper and a slide rule or table of logarithms. However, during the late 1970s electronic area detectors for astronomy became more advanced: first, for a brief period, television-type cameras were employed, but these were s

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

The subject of an valuation of quality of construction projects is one of the topics which it becomes necessary of the absence of the quantity standards in measuring the control works and the quality valuation standards in constructional projects. In the time being it depends on the experience of the workers which leads to an apparent differences in the valuation.

The idea of this research came to put the standards to evaluate the quality of the projects in a special system depending on quantity scale nor quality specifying in order to prepare an expert system “ Crystal “ to apply this special system to able the engineers to valuate the quality of their projects easily and in more accurate ways.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and