One of the main purposes of the semantic Web is to improve the retrieval performance of search systems. Unlike keyword based search systems, the semantic search systems aim to discover pages related to the query's concepts rather than merely collecting all pages instantiating its keywords. To that end, the concepts must be defined to be used as a semantic index instead of the traditional lexical one. In fact, The Arabic language is still far from being semantically searchable. Therefore, this paper proposed a model that exploits the Universal Word Net ontology for producing an Arabic Concepts-Space to be used as the index of Semantic Vector Space Model. The Vector Space Model is one of the most common information retrieval models due to its capability of expressing the documents' structure. However, like all keyword-based search systems, its sensitivity to the query's keywords reduces its retrieval effectiveness. The proposed model allows the VSM to represent Arabic documents by their topic, and thus classify them semantically. This, consequently, enhances the retrieval effectiveness of the search system.

An Artificial Neural Network (ANN) model was developed to predict the pressure drop of titanium dioxide-water (TiO2-water). The model was developed based on experimentally measured data. Experimental measurements of fully developed turbulent flow in pipe at different particle volumetric concentrations, nanoparticle diameters, nanofluid temperature and Reynolds number were used to construct the proposed model. The ANN model was validated by comparing the predicted results with the experimental measured data at different experimental conditions. It was shown that, the present ANN model performed well in predicting the pressure drop of TiO2-water nanofluid under different flow conditions with a high degree of accuracy.

The hybrid architecture of Terrestrial and Satellite networks discussed in this paper utilizes frequency reuse. However, at the same time the frequency reuse results in Co-Channel Interference (CCI). The CCI is caused by the mobile users to the satellite end because of the strong receiver on the satellite end. Mainly, this paper will focus on to tone down the CCI and would also show that how the OFDM based adaptive beamforming can be employed to mitigate this interference. The technique which is being used to mitigate this interference is Pre-FFT adaptive beamforming also called as time domain beamforming. In this paper, main task is to mitigate the CCI which is induced by the mobile users to the satellite end and will be considered that there are J users. Out of these J users there is one desired user and rest are interferers. When the interfered data is received at the satellite end, the Pre-FFT adaptive beamforming extracts the desired user data from the interferers by applying the complex weights to the received symbol. The weight for the next symbol is then updated by Least Mean Square (LMS) algorithm and then is applied to it. This process is carried out till all the desired user data is extracted from the interference signal.

Cat Swarm Optimization (CSO) is one of the new swarm intelligence algorithms for finding the best global solution. Because of complexity, sometimes the pure CSO takes a long time to converge and cannot achieve the accurate solution. For solving this problem and improving the convergence accuracy level, we propose a new improved CSO namely ‘Adaptive Dynamic Cat Swarm Optimization’. First, we add a new adaptive inertia weight to velocity equation and then use an adaptive acceleration coefficient. Second, by using the information of two previous/next dimensions and applying a new factor, we reach to a new position update equation composing the average of position and velocity information. Experimental results for six test functions show that in comparison with the pure CSO, the proposed CSO can takes a less time to converge and can find the best solution in less iteration.

One of the most important techniques for improving the performance of web based applications is web proxy caching Technique. It is used for several purposes such as reduce network traffic, server load, and user perceived retrieval delays by replicating popular content on proxy caches that are strategically placed within the network. The use of web proxy caching is important and useful in the government organizations that provides services to citizens and has many branches all over the country where it is beneficial to improve the efficiency of the computer networks performance, especially remote areas which suffer from the problem of poor network communication. Using of proxy caches provides all users in the government computer networks by reducing the amount of redundant traffic that circulates through the network. It also provides them by getting quicker access to documents that are cached. In addition, there are a lot of benefits we can obtain from the using of proxy caches but we will address them later. In this research, we will use web proxy caching to provide all of the above benefits that we are mentioned above and to overcome on the problem of poor network communication in ENR (Egyptian National Railways). We are going to use a scheme to achieve the integration of forward web proxy caching and reverse proxy caching.

Due to the time-varying nature of the wireless channel and presence of limited resources for the signal transmission, which faces various detrimental effects such as path-loss, delay spread, Doppler spread, shadowing and interference make it very difficult to achieve sufficient data rates. To combat the effect of multi-path fading in the wireless communication system, the diversity combining mechanism has been introduced. In this paper, we have developed an algorithm for the performance evaluation of various spatial diversity combing techniques by using Matlab simulation. The developed new algorithm combine all three diversity techniques such as maximal ratio combining (MRC), selection combining (SC) and equal gain combing (EGC) techniques The combined diversity techniques algorithm computes and compares the MRC, SC, and EGC combing techniques theoretically by using the Matlab simulation.

Today’s technology prediction of a heart disease using intelligent system is a real challenge to modern technology. In this paper different membership functions using a fuzzy rule based system for the diagnosis of the heart disease has been presented. The system has seven inputs .These are Chest pain type, resting blood pressure in mm(Trestbps),Serum cholesterol in mg(Chol),numbers of years as a smoker(years), fasting of blood sugar(fbs), maximum heart rate achieved(thalrest), resting blood rate(tpeakbps). The angiographic disease status of heart of patients has been recorded as an output. It is to mention that the diagnosis of heart disease by angiographic disease status is assigned by a number between 0 to 1,that number indicates whether the heart attack is mild or massive. Here an effort has been made to decide suitable membership function for proper diagnosis of heart disease.Different membership functions used are triangular, trapezoidal, Gaussian ,Z shaped, bell shaped ,sigmoid based ,Gaussians combination membership functions. Based on the minimum value of absolute residual the particular membership function can be decided using the fuzzy rule base system for the proper diagnosis heart disease status of a patient.

The performance of one-bit hard combination decision scheme for cooperative spectrum sensing in cognitive radio has been studied in this paper. Energy detector model is used to observe the presence of primary user signal. Simulation result shows that the probability of missed detection is decreasing for both conventional hard combination and one-bit hard combination with OR rule according to the increasing of probability of false alarm. It also has demonstrated that one-bit hard combination decision scheme exhibits comparable performance with the conventional scheme and thus achieves a good tradeoff between performance and complexity.

Addition forms the basic structure for many processing operations like counting, multiplication, filtering etc. Adder circuits that add two binary numbers are of great interest for many designers. The simplest approach to design an adder is to implement gates to yield the required logic function. Carry-look ahead adder is a major functional block in arithmetic logic unit due to its high speed operation. The arithmetic logic unit has been widely used in microprocessor systems and mostly in processing modules of embedded systems. Therefore, it is of interest to study the functional behavior and power consumption carry-look ahead adder. In this project, the adder is implemented using 180 nm CMOS technology on bulk substrate. Two logic families i.e. static CMOS and adiabatic logic have been analyzed and implemented to study the transient characteristics of the adder. Finally the power consumption is estimated and compared. From the results it has been found that the static CMOS logic offers low delay whereas the adiabatic logic consumes low power.

The brain signal or Electroencephalogram (EEG) has been proved as one of the most important bio-signal that deals with a number of problems and disorders related to the human being. Epilepsy is one of the most commonly known disorders found in humans. The application of EEG in epilepsy related research and treatment is now a very common practice. Variety of smart tools and algorithms exist to assist the experts in taking decision related to the treatment to be provided to an epileptic patient. However, web based applications or tools are still needed that can assist those doctors and experts, who are not having such existing smart tools for EEG analysis with them. In the current work, a web based system named WEBspike has been proposed that breaks the geographical boundary in assisting doctors in taking proper and fast decision regarding the treatment of epileptic patient. The proposed system receives the EEG data from various users through internet and processes it for Epileptic Spike (ES) patterns present in it. It sends back a report to the user regarding the appearance of ES pattern present in the submitted EEG data. The average spike recognition rate obtained by the system with the test files, was 99.09% on an average.

Cognitive radio is a technology initiated by many research organizations and academic institutions to raise the spectrum utilization of underutilized channels in order to alleviate spectrum scarcity problem to a larger extent. Spectrum handoff is initiated due to appearance of primary user (PU) on the channels occupied by the secondary user (SU) at that time and location or interference to the PU exceeds the certain threshold. In this paper, we propose a novel spectrum handoff algorithm using fuzzy logic based approach that does two important functions: 1) adjusts transmission power of SU intelligently in order to avoid handoff by reducing harmful interference to PUs and 2) takes handoff decisions intelligently in the light of new parameter such as expected holding time (HT) of the channel as one of its antecedent. Simulated results show impact analysis of selection of the channel in the light of HT information and the comparison with random selection algorithm demonstrates that there is considerable reduction in handoff rate of SU.

In this paper, a PD-serial fuzzy based robust nonlinear estimator for a robot manipulator is proposed by using robust factorization approach. That is, considering the uncertainties of dynamic model consisting of measurement error and disturbances, a PD with fuzzy estimator variable structure nonlinear feedback control scheme is designed to reduce effect of uncertainties. This research aims to design a new methodology to fix the position in robot manipulator. PD method is a linear methodology which can be used for highly nonlinear system’s (e.g., robot manipulator). To estimate this method, new serial fuzzy variable structure method (PD.FVSM) is used. This estimator can estimate the parameters to have the best performance.