Samir Abou El-Seoud

Cloud Computing Based E-Learning System

Cloud computing technologies although in their early stages, have managed to change the way applications are going to be developed and accessed. These technologies are aimed at running applications as services over the internet on a flexible infrastructure. Microsoft office applications, such as word processing, excel spreadsheet, access database and many more can be accessed through the internet, even though the files and applications are housed in the cloud. Cloud computing provides a low cost solution to academic institutions for their researchers, faculty and students. This setup provides an additional benefit because all these browser-based applications can also be accessed through mobile devices in addition to being available to a variety of laptop and desk top computers, provided internet access is available. In this paper we present a solution that is based on cloud computing and can be used for building a virtual environment both for teaching and learning. We present an interactive tool that can be used for science education; we combined various technologies to achieve this goal. The environment and the design proposed can also be used as a platform for exploring and sharing new ideas as well as for designing, modifying and monitoring educational or course contents. In our design under the same environment we also allow integration of different pedagogical approaches to both learning and teaching.

Collaborating and learning a second language in a Wireless Virtual Reality Environment

Virtual Reality (VR), a computer-generated 3D space that is multisensorial, interactive and engaging, is today one of the new frontiers in Computer-Assisted Language Learning (CALL). VR can be used to promote language learning and practice as it simulates reality, while offering a stimuli-rich environment for language students. The purpose of this paper is twofold: To provide an introduction to VR applications in CALL, and to describe the implementation of a Collaborative Virtual Reality Environment (CVRE) running on a wireless network, which is currently being assessed by Mexican Engineering students for listening comprehension practice of the English language.

An Assistive Computerized System for Children with Intellectual and Learning Disabilities

This work proposes an assistive computerized system using the Arabic language for children with intellectual and learning disabilities (ILD) who are resident at Shafallah Center in Doha, Qatar. The system is flexible and can be used by parents, children and teachers, where they can employ the materials according to specific needs. The contents are developed with the help of special education instructors. The tutorials cover a range of topics on basic concepts of living including simple mathematics and sciences. The animated images used in the tutorials are taken from the childrens environment, so they can feel more comfortable when using the system. After studying the tutorials, children can solve puzzles based on the topics they learned. A simple intelligent greedy algorithm is used to guide children to a solution. Concept analysis are used to extract the main ideas of electronic texts and dialogues, link them with images, sounds and clips, and present them to the children with ILD.

Mobile Learning Platform Connected to Moodle Using J2ME

This paper presents a mobile learning platform (MLP) connected to a Moodle course management system build, using the Java2 Micro Edition (J2ME), developed in our Mobile Multimedia and Wireless Communication Lab (MMWCL). The MLP uses wireless communications (Bluetooth, WI-FI, WIMAX) to connect with the Moodle server. Later, after the connection is established with the server, the J2ME application will be able to provide the user with a bundle of services. These services include grades, course schedules, attendance records, course announcements, and university activities, as well as quality assessments.

Geometry Compression for 3D Polygonal Models using a Neural Network

ABSTRACT Three dimensional models are commonly used in computer graphics and 3D modeling characters in animation movies and games. 3D objects are more complex to handle than other multimedia data due to the fact that various representations exist for the same object, yielding a number of difficulties, among of which are the distinct sources of 3D data. Research work in the field of three dimensional environments is represented by a broad spectrum of applications. In this paper we restrict ourselves only on how to do compression using a neural network in order to minimize the size of 3D models for making transmission over networks much faster. The main objective behind this compression is to simplify the 3D model and make handling the large size of 3d objects much easier for other processes. Even the process of rendering , digital watermarking, etc., will be faster and more efficient. Keywords Geometry Compression, Artificial Intelligent, Genetic Algorithm, Neural Network, Multilayer feed forward.

The Impact of XML Databases Normalization on Design and Usability of Internet Applications

Database normalization is a process which eliminates redundancy, organizes data efficiently and improves data consistency. Functional, multivalued, and join dependencies (FDs, MVDs, and JDs) play fundamental roles in relational databases where they provide semantics for the data and at the same time are the foundations for database design. In this study we investigate the issue of defining functional, multivalued and join dependencies and their normal forms in XML database model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain dependencies among paths in the document. Our goal is to find a way for converting an arbitrary XML Schema to a well-designed one that avoids these problems. We extend the notion of tuple for relational databases to the XML model. We show that an XML tree can be represented as a set of tree tuples. We introduce the definitions of FD, MVD, and JD and new Normal Forms of XML Schema that based on these dependencies (X-1NF, X-2NF, X-3NF, X-BCNF, X-4NF, and X-5NF). We show that our proposed normal forms are necessary and sufficient to ensure all conforming XML documents have no redundancies.

Robust Digital Watermarking for Compressed 3D Models based on Polygonal Representation

ABSTRACT Multimedia has recently played an increasingly important role in various domains, including Web applications, movies, video game and medical visualization. The rapid growth of digital media data over the Internet, on the other hand, makes it easy for anyone to access, copy, edit and distribute digital contents such as electronic documents, images, sounds and videos. Motivated by this, much research work has been dedicated to develop methods for digital data copyright protection, tracing the ownership, and preventing illegal duplication or tampering. This paper introduces a methodology of robust digital watermarking based on a well-known spherical wavelet transformation, applied to 3D compressed model based on polygonal representation using a neural network. It will be demonstrated in this work that applying a watermarking algorithm on a compressed domain of a 3D object is more effective, efficient, and robust than when applied on a normal domain.

Schema Design and Normalization Algorithm for XML Databases Model

In this paper we study the problem of schema design and normalization in XML databases model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain functional dependencies among paths in the document. Based on our research works, in which we presented the functional dependencies and normal forms of XML Schema, we present the decomposition algorithm for converting any XML Schema into normalized one, that satisfies X-BCNF.

Image Denoising Technique for CT Dose Modulation

Low-dose computed tomography (LDCT) imaging is considerably recommended for use in clinical CT scanning because of growing fears over excessive radiation exposure. Automatic exposure control (AEC) is one of the methods used in dose reduction techniques that have been implemented clinically comprise showing significant decrease scan range. The quality of some images may be roughly degraded with noise and streak artifacts due to x-ray flux, based on modulating radiation dose in the angular and slice directions. In 2005, the nonlocal means (NLM) algorithm showed high performance in denoising images corrupted by LDCT. The proposed method incorporates a prior knowledge obtained from previous high-quality CT slices to improve low-quality CT slice during the filtering process because of the anatomical similarity between the arranged image slices of the scans. The proposed method is evaluated using real data and CT image quality is notably improved.

An interactive augmented reality imaging system for minimally invasive orthopedic surgery

In orthopedic surgery, it is important for physicians to completely understand the three-dimensional bone structure for several procedures. To achieve this goal, it is required to image the patient several times using C-arm scanner from different positions during the surgery. This procedure is time consuming and increase the x-ray dose given to both patient and physician. In this paper, we propose an augmented reality imaging system for minimally invasive orthopedic surgery. The system is based on mapping the x-ray image to the real object such that the number of x-ray shots during the surgery can be significantly reduced. We consider two imaging scenarios that can fit with different cases. Results obtained through clinical data indicate that the proposed approach has a potential usefulness in real applications.