In this paper, a description of a design for new DES block cipher, namely DES64X and DES128X. The goals of this design, a part of its security level, are large implementation flexibility on various operating systems as well as high performances. The high level structure is based on the principle of DES and Feistel schema, and proposes the design of an efficient key-schedule algorithm which will output pseudorandomsequences of subkeys. The main goal is to reach the highest possible flexibility, in terms of round numbers, key size, and block size. A comparison of the proposed systems on 32-bit, 64-bit operating system, using 32-bit and 64-bit Java Virtual Machine (JVM), showed that the latter has much better performance than the former.

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

Can not reach a comprehensive concept for interior design through the use of Harmonization term according transformations experienced by the terms of the variables associated with the backlog of cultures that characterize concepts according to the nature of the users of the spaces in the design output, which necessitates the meaning of the combination of knowledge, art, science, such as the type of perceptions design the Harmonization cognitive science with art to create products of the use of design configurations that help the designer to put such a product within the reality and like the fact that reliable, as well as the rational knowledge tend somehow to the objective specifically in facilitating the substance subject to perceptible

The limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

يسعى المجتمع من خلال الوحدات الإقتصادية إلى الوصول إلى تحقيق أفضل الإنجازات التي لا تتمثل بالسلع والخدمات حسب وإنما بما يتحقق من مردود لكافة الاطراف المعنية بالوحدات الإقتصادية على ان لايتم ذلك على حساب قيم المجتمع وأخلاقياته وآدابه العامة. وعليه تصبح الوحدات الإقتصادية مسرحاً لصراعات قوى متعددة كل منها له قيمه الأخلاقية سواء كان فرداً أومجموعة افراد أو وحدة إقتصادية أو أي جهة أُخرى، وبحكم مسؤولياته