Tracking animal life in the natural reserves by using hybrid wireless sensors networks

The great development of mobile wireless sensor networks has many very important applications. One of the most important applications that has attracted scientists' attention recently is to track animals in their homes to follow the behavior and lives of some endangered animals, but monitoring animals activities in the forest is a very difficult task, especially if the animals to be monitored are teeny, therefore we cannot use the traditional tracking systems ) like GPS, As well as the harsh and dangerous nature of the forest make the use of wireless sensor networks the best solution, especially that sensors are low-cost, small size, which made them suitable for such tasks, in this research we will study new way to track a group of partridge where sensors are placed on these birds to observe their life and behavior ,The important challenge in this research is to know the location of these mobile birds to be able to the help them in appropriate time , so will introduce a new method that provides us with acceptable accuracy, a simple, easy, inexpensive and low energy consumption compared with other methods of animals tracking ,based on a set of predefined reference nodes, where sensors information is sent to a gathering center through these reference nodes ,then Analyze it and use it to the approximate location of the animals. We will evaluate this method using Network Simulator (NS2).

Optimal Strengthening Design Of Reinforced Concrete Frames Using Steel Jacket Technique

This research investigates the behavior of RC frames strengthened using steel jacket technique and the impact of using this technique on the frame specifications was examined in terms of rigidity, ductility and resistance.

New Hybrid Evolutionary Algorithm for Solving Multi-Objective Optimization Problems

Multi-objective evolutionary algorithms are used in a wide range of fields to solve the issues of optimization, which require several conflicting objectives to be considered together. Basic evolutionary algorithm algorithms have several drawbacks, such as lack of a good criterion for termination, and lack of evidence of good convergence. A multi-objective hybrid evolutionary algorithm is often used to overcome these defects.

Mobile Robot Motion Planning using Bug Algorithms

Motion Planning is an important and potential issue in Robotics, because it gives the robot the ability to reach its target automatically with collision free, which increase the robot performance and reduce its operational cost. The robot motion planning is commonly divide into two approaches: finding the appropriate path and making the robot tracking this path until it reaches its goal. This research depends on one of the most common obstacles avoidance path planningtechniques (Bug algorithms) to find global path of robot. And make the Boe-Bot robot (differential drive robot) tracking the paths generated by these algorithms in a certain environment.

Increasing Input Block and Encryption Efficiency by Mixing BBM & IDEA

We take an IDEA Algorithm and add to it some stages depend on BBM to get an Enhanced Algorithm, which had 3keys, 128-bit input block.

Rainfall-Runoff Modeling by Using Hybrid System of Artificial Neural Network and Genetic Algorithm

This study has reached to that ANN (5-9-1) (five neurons in input layer_nine neurons in hidden layer _ one neuron in output layer) is the optimum artificial network that hybrid system has reached to it with mean squared error equals (1*10^-4) (0.7 m3/sec), where this software has summed up millions of experiments in one step and in limited time, it has also given a zero value of a number of network connections, such as some connections related of relative humidity input because of the lake of impact this parameter on the runoff when other parameters are avaliable. This study recommend to use this technique in forecasting of evaporation and other climatic elements.

Enhancing the Quality of Service for Real Time and non-Real Time Application via Internet Network

Services that demanded by users via internet network are classified in two main kinds, Services work in real time such as video and voice in real time and use UDP protocol, and other services that work in non-real time such as web browsing (HTTP) and file transfer (FTP) which use TCP Protocol. In this research, we study and analyze algorithms that enhance the quality of service for various applications. For real time application, we use queues disciplines, which gives high priority for these services and achieves minimum delay. For non-real time application, we study congestion control algorithms, which achieve best performance for reliable transfer process with existing the congestion in the network. We used OPNET 14.5 program for simulating various services via internet network. Simulation results show achieving minimum delay for voice service, and achieving high transmission rate for FTP application with existing of packets loss in the network.

A Study of QoS in Long Term Evolution Networks "LTE"

Long Term Evolution “LTE” is considered to be one of the most important and latest communication technologies falling under the fourth generation of cellular communications technology 4G. LTE supports high-speed and large bandwidth which makes it a great candidate to providing the potential to improve the Quality of Service "QoS" associated with specific types of data transfer. As a consequence, researchers have paid their attentions to this type of networks. In fact, it was a great challenge for researchers to achieve a good level of QoS for all users as the LTE provides Audio and Data transmission to users at the same time.

Quasi-Optimal Stepsize Strategy for Givens Parameterized Independent Component Analysis

In this paper, we propose an efficient strategy for calculating quasi-optimal stepsizes for the Givens-parameterized deflationary ICA algorithm, DelLR.

Classification Of Arabic Texts Using Object Properties In Databases

In our research we offer detailed study of one of the data mining functions within the text data using the object properties in databases. It studies the possibility of applying this function on the Arabic texts. We use procedural query language PL / SQL that deals with the object of Oracle databases. Data mining model Has been built. It works on classification of Arabic texts documents using SVM algorithm for indexing of texts and texts preparation, Naïve Bayes algorithm to classify data after transformation it into nested tables. So we made an evaluation of the obtained results and conclusions.