Implementation of a Proposal Encryption Algorithm for Voice over Internet Protocol (VoIP)

The process of transfer a speech signal by high confidentially and as quickly as possible through the Internet needs to develop compression and encryption technology for a speech signal, so as, to reduce its size and make it understandable to persons not authorized to listen to. A system was designed to encrypt the voice over Internet Protocol (VoIP) and use compression technique for the purpose of reducing the size of data and send it over the network, (A_law PCM) algorithm was used the to compress audio data. Then algorithms of Triple Data Encryption Standard (TDES) and Advanced. Encryption Standard (AES) were applied. A new encryption algorithm was proposed based in its work on the block cipher encryption system called the Direct and Reverse algorithm, which based on three basic steps, firstly expand the initial key, secondly direct the encryption of each round in one direction, and finally substitute (Bytes) as used in the Compensation Box in AES algorithm by making it moving. In general compression ratio was calculated and it was (50%) and the results of the correlation coefficient for the proposed algorithm was compared with the results of (AES, TDES) algorithms.

Improving Decision Support Systems in Education Systems Using Data Mining and Machine Learning Techniques

Educational data mining aims to study the available data in the educational field and extract the hidden knowledge from it in order to benefit from this knowledge in enhancing the education process and making successful decisions that will improve the student’s academic performance. This study proposes the use of data mining techniques to improve student performance prediction. Three classification algorithms (Naïve Bayes,J48, Support Vector Machine) were applied to the student performance database, and then a new classifier was designed to combine the results of those individual classifiers using Voting Method. The WEKA tool was used, which supports a lot of data mining algorithms and methods. The results show that the ensemble classifier has the highest accuracy for predicting students' levels compared to other classifiers, as it has achieved a recognition accuracy of 74.8084%. The simple k-means clustering algorithm was useful in grouping similar students into separate groups, thus understanding the characteristics of each group, which helps to lead and direct each group separately.

Design a CNN network for vehicle classification

The project aims primarily to employ the benefits of artificial intelligence, specifically the characteristics of programming a neuronal network where neuronal networks, in turn, are networks that are interested in training and learning from error, and employing this error to achieve optimal results.Convolution NeuralNetworks(CNN)in particular are one of the most important neuronal networks that address classification problems and issues. Thus, this project is to design a convolution neuronal network that classifies vehicles into several types where we will design the network and train them on the database as the database includes pictures of several types of vehicles The network will classify each Image to its type, after adjusting the images, making the appropriate changes, turning them gray, and discovering the edges and lines.After the images are ready, the training process will begin, and after the training process is finished, we will produce classification results, and then we will test with a new set of images.One of the most important applications of this project is to abide by the paving places of cars, trucks, and vehicles in general, as if a picture was entered as a car for the car sample, which is a truck, for example, this will give an error where the network will discover this by examining and classifying it. As a truck, we discover that there is a violation of the paving laws

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).

Branch and Bound Optimization Algorithm

في المشكلة التي نعالجها, تحتاج شركة اتصالات إلى بناء مجموعة من الأبراج الخلوية لتوفير خدمة الاتصالات الخليوية للسكان في منطقة جغرافية. تم تحديد عدد من المواقع المحتملة لبناء الأبراج. يعتم اختيار هذه المواقع على عدة عوامل ، بما في ذلك مدى اتساق البرج مع البيئة المحيطة وارتفاع التضاريس, تتمتع الأبراج بمدى تغطية ثابت ، وبسبب قيود الميزانية ، لا يمكن بناء سوى عدد محدود منها . بالنظر إلى هذه القيود ، ترغب الشركة في توفير تغطية لأكبر قدر ممكن من السكان, والهدف هو اختيار في أي من المواقع المحتملة يجب أن تقوم الشركة ببناء الأبراج. إن المشكلة التي شرحناها يمكن نمذجتها لتصبح أحد أمثلة مشكلة 0/1 knapsack الشهيرة لذلك شرحنا في الحلقة مفهوم مشكلة 0/1 Knapsack والطرق المستخدمة في الحل, وتوسعنا في الشرح عن خوارزمية Branch and Bound كونها تعتبر أفضلها.

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.

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.

دراسة فعالية خوارزميات اكتشاف المعرفة على قواعد البيانات غرضية التوجه

The great interest in the field of knowledge discovery in relational databases has led to the development of mathematical algorithms that have proven effective in deriving knowledge of both descriptive and predictive types. However, the great development of information technology, and the wide spread of social networks and advanced web pages, increased the use of intent database systems.

Dual Programming for finding optimal solution for transportation problems

In this paper we present mathematical models for transportation problems, primal problem and dual. First, we show how is the formulation of dual transportation problem models. Finally, As a solution to the two models lead to a solution other model, we have to dissolve the Dual transportation problem, so we relied on the least cost method in resolving the primal transportation problem.

Survey Of Traditional And Semantic Plagiarism Detection Algorithms

In this paper we review and list, the advantages and limitations of the significant effective techniques employed or developed in text plagiarism detection. It was found that many of the proposed methods for plagiarism detection have a weakness points and do not detect some types of plagiarized operations. This paper show a survey about plagiarism detection including several important subjects in plagiarism detection, which is plagiarism definition, plagiarism prevention and detection, plagiarism detection systems, plagiarism detection processes and some of the current plagiarism detection techniques. This paper compares between different plagiarism detection algorithms, and shows the points of weakness, and points of efficiency, and describe the power of semantic plagiarism detection methods, and shows its efficiency in detect plagiarism cases that another plagiarism detection algorithms don’t able to detect these cases, that semantic plagiarism detection methods are developed to get rid of traditional weakness points for all plagiarism detection methods have.