The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

Abstract

In this research we study the wavelet characteristics for the important time series known as Sunspot, on the aim of verifying the periodogram that other researchers had reached by the spectral transform, and noticing the variation in the period length on one side and the shifting on another.

A continuous wavelet analysis is done for this series and the periodogram in it is marked primarily. for more accuracy, the series is partitioned to its the approximate and the details components to five levels, filtering these components by using fixed threshold on one time and independent threshold on another, finding the noise series which represents the difference between

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re