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Intercept algorithm for maneuvering targets based on differential geometry and lyapunov theory

Nowadays, the homing guidance is utilized in the existed and under development air defense systems (ADS) to effectively intercept the targets. The targets became smarter and capable to fly and maneuver professionally and the tendency to design missile with a small warhead became greater, then there is a pressure to produce a more precise and accurate missile guidance system based on intelligent algorithms to ensure effective interception of highly maneuverable targets. The aim of this paper is to present an intelligent guidance algorithm that effectively and precisely intercept the

Artificial Intelligence
Innovation, Entrepreneurship and Competitiveness

NileULex: A phrase and word level sentiment lexicon for Egyptian and modern standard Arabic

This paper presents NileULex, which is an Arabic sentiment lexicon containing close to six thousands Arabic words and compound phrases. Forty five percent of the terms and expressions in the lexicon are Egyptian or colloquial while fifty five percent are Modern Standard Arabic. The development of the presented lexicon has taken place over the past two years. While the collection of many of the terms included in the lexicon was done automatically, the actual addition of any term was done manually. One of the important criterions for adding terms to the lexicon, was that they be as unambiguous

Artificial Intelligence

Guava Trees Disease Monitoring Using the Integration of Machine Learning and Predictive Analytics

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical sensors and data analysis methods that are able to cope with the resolution, size and complexity of the signals from these sensors. In this paper, several methods of machine learning have been utilized

Artificial Intelligence
Energy and Water
Software and Communications
Agriculture and Crops

Highly efficient human action recognition using compact 2DPCA-based descriptors in the spatial and transform domains

Human action recognition is considered as a challenging problem in the field of computer vision. Most of the reported algorithms are computationally expensive. In this paper, a novel system for human action recognition based on Two-Dimensional Principal Component Analysis (2DPCA) is presented. This method works directly on the optical flow and / or silhouette extracted from the input video in both the spatial domain and the transform domain. The algorithm reduces the computational complexity and storage requirements, while achieving high recognition accuracy, compared with the most recent

Artificial Intelligence

Intelligent Arabic-Based Healthcare Assistant

Text classification has been one of the most common natural language processing (NLP) objectives in recent years. Compared to other languages, this mission with Arabic is relatively restricted and in its early stages, and this combination in the medical application area is rare. This paper builds an Arabic health care assistant, specifically a pediatrician that supports Arabic dialects, especially Egyptian accents. The proposed application is a chatbot based on Artificial Intelligence (AI) models after experimenting with Two Bidirectional Encoder Representations from Transformers (BERT) models

Artificial Intelligence
Healthcare
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Evaluating the Modsecurity Web Application Firewall against SQL Injection Attacks

SQL injection attacks target databases of web servers. The ability to modify, update, retrieve and delete database contents imposes a high risk on any website in different sectors. In this paper, we investigate the efforts done in the literature to detect and prevent the SQL injection attacks. We also assess the efficiency of the Modsecurity web application firewall in preventing SQL injection attacks. © 2020 IEEE.

Artificial Intelligence
Software and Communications

A secure and privacy-preserving event reporting scheme for vehicular Ad Hoc networks

In vehicular ad hoc networks, vehicles should report events to warn the drivers of unexpected hazards on the roads. While these reports can contribute to safer driving, vehicular ad hoc networks suffer from various security threats; a major one is Sybil attacks. In these attacks, an individual attacker can pretend as several vehicles that report a false event. In this paper, we propose a secure event-reporting scheme that is resilient to Sybil attacks and preserves the privacy of drivers. Instead of using asymmetric key cryptography, we use symmetric key cryptography to decrease the

Artificial Intelligence
Software and Communications

Cloud computing privacy issues, challenges and solutions

There are many cloud computing initiatives that represent a lot of benefit to enterprise customers. However, there are a lot of challenges and concerns regarding the security and the privacy of the customer data that is hosted on the cloud. We explore in this paper the various aspects of cloud computing regarding data life cycle and its security and privacy challenges along with the devised methodology to address those challenges. We mention some of the regulations and law requirements in place to ensure cloud customer data privacy. © 2017 IEEE.

Artificial Intelligence
Software and Communications

Segmented OTA Platform Over ICN Vehicular Networks

The Internet Protocol (IP) architecture could not fully satisfy the Vehicular Ad-hoc Networks (VANETs) needed efficiency, due to their dynamic topology and high mobility. This paper presents a technique that updates the software of Electronic Control Units (ECUs) in vehicles using segmented Over The Air (OTA) platform over Information-Centric Network (ICN) architecture. In VANET, the amount of time for active vehicles’ connectivity varies due to the vehicular network’s dynamic topologies. The importance of Flashing Over The Air (FOTA) has been illustrated as well as the impact of applying the

Artificial Intelligence
Software and Communications

Detection and Countermeasures of DDoS Attacks in Cloud Computing

Greater portions of the world are moving to cloud computing because of its advantages However, due to its distributed nature, it can be easily exploited by Distributed Denial of Service (DDoS) attacks. In distributed DDoS attacks, legitimate users are prevented from using cloud resources. In this paper, the various DDoS detection and defenses mechanisms cloud computing are reviewed. We propose a new technique based on Remote Triggered Black Hole (RTBH) to prevent DDoS attacks before it target to cloud resources. © 2018 IEEE.

Artificial Intelligence
Software and Communications