Sadat Academy for Management Sciences

About: Sadat Academy for Management Sciences is a education organization based out in Cairo, Egypt. It is known for research contribution in the topics: Cloud computing & Population. The organization has 76 authors who have published 106 publications receiving 871 citations.

Intelligent cross road traffic management system (ICRTMS)

Abstract: The aim of this research is to provide a design of an integrated intelligent system for management and controlling traffic lights based on distributed long range Photoelectric Sensors in distances prior to and after the traffic lights The appropriate distances for sensors are chosen by the traffic management department so that they can monitor cars that are moving towards a specific traffic and then transfer this data to the intelligent software that are installed in the traffic control cabinet, which can control the traffic lights according to the measures that the sensors have read, and applying a proposed algorithm based on the total calculated relative weight of each road Accordingly, the system will open the traffic that are overcrowded and give it a longer time larger than the given time for other traffics that their measures proved that their traffic density is less This system can be programmed with very important criteria that enable it to take decisions for intelligent automatic control of traffic lights Also the proposed system is designed to accept information about any emergency case through an active RFID based technology Emergency cases such as the passing of presidents, ministries and ambulances vehicles that require immediate opening for the traffic automatically The system has the ability to open a complete path for such emergency cases from the next traffic until reaching the target destination (end of the path) As a result the system will guarantee the fluency of traffic for such emergency cases or for the main vital streets and paths that require the fluent traffic all the time, without affecting the fluency of traffic generally at normal streets according to the time of the day and the traffic density Also the proposed system can be tuned to run automatically without any human intervention or can be tuned to allow human intervention at certain circumstances

NoSQL Injection Attack Detection in Web Applications Using RESTful Service

Abstract: Despite the extensive research of using web services for security purposes, there is a big challenge towards finding a no radical solution for NoSQL injection attack. This paper presents an independent RESTful web service in a layered approach to detect NoSQL injection attacks in web applications. The proposed method is named DNIARS. DNIARS depends on comparing the generated patterns from NoSQL statement structure in static code state and dynamic state. Accordingly, the DNIARS can respond to the web application with the possibility of NoSQL injection attack. The proposed DNIARS was implemented in PHP plain code and can be considered as an independent framework that has the ability for responding to different requests formats like JSON, XML. To evaluate its performance, DNIARS was tested using the most common testing tools for RESTful web service. According to the results, DNIARS can work in real environments where the error rate did not exceed 1%.

A proposed PCNN features quality optimization technique for pose-invariant 3D Arabic sign language recognition

Abstract: This paper proposes a novel technique to deal with pose variations in 3D object recognition. This technique uses pulse-coupled neural network (PCNN) for image features generation from two different viewing angles. These signatures qualities are then evaluated, using a proposed fitness function. The features evaluation step is taken before any classification steps are performed. The evaluation results dynamic weighting factors for each camera express the features quality from the current viewing angles. The proposed technique uses the two 2D image features and their corresponding calculated weighting factors to construct optimized quality 3D features. An experiment was conducted in Arabic sign language recognition application which multiple views are necessary to distinguish some signs. The proposed technique obtained a 96% recognition accuracy for pose-invariant restrictions with a degree of freedom from 0 to 90.