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Impact of COVID-19 on Information Technology Sector in Egypt

Pandemics raise huge challenges yet brought several opportunities. The sudden attack of COVID-19 revealed the importance of the information technology (IT) applications. The Reliance on the IT sector has become imperative to ensure sustainability and to raise most sectors' performance efficiency, especially the services' ones. This study applied PESTEL analysis to evaluate the current status of IT in Egypt. SWOT analysis was performed to explore points of strength, weakness, opportunities, and threats that face the IT sector in Egypt as a result of the COVID19 attack. The process of foreseeing

Artificial Intelligence

Fault-Recovery and Robust Deadlock Control of Reconfigurable Multi-Unit Resource Allocation Systems Using Siphons

A multi-unit resource allocation system usually contains several processes and a number of resources with multiple units. Due to the competition for shared resources in these systems, deadlocks may occur. Recently, researchers have shown an increased awareness in deadlock control strategies for such a kind of systems without considering the dynamic changes such as processing failures and rework by using the Petri net paradigm. This article reports a new strategy for deadlock analysis and control in reconfigurable multi-unit resource systems (MRSs). We discuss a generalized class of Petri nets

Artificial Intelligence
Software and Communications

Security Perspective in RAMI 4.0

Cloud Computing, Internet of Things (IoT) are the main technologies contributing to the adoption of the fourth revolution in manufacturing, Industry 4.0 also known as smart manufacturing or digital manufacturing. Smart manufacturing facilitates and accelerates the process of manufacturing with the connection of all the systems related to the manufacturing process starting with the Enterprise Resource Planning (ERP) systems, the Industrial Control Systems (ICSs) which control the production line and the Cyber Physical Systems (CPSs). Before the emerging of web applications, cloud applications

Artificial Intelligence
Software and Communications

Code Smells and Detection Techniques: A Survey

Design and code smells are characteristics in the software source code that might indicate a deeper design problem. Code smells can lead to costly maintenance and quality problems, to remove these code smells, the software engineers should follow the best practices, which are the set of correct techniques which improve the software quality. Refactoring is an adequate technique to fix code smells, software refactoring modifies the internal code structure without changing its functionality and suggests the best redesign changes to be performed. Developers who apply correct refactoring sequences

Artificial Intelligence
Software and Communications

Convergence study of IPv6 tunneling techniques

IPv4 address exhaustion pushed IETF to create IPv6, the improved substitute of IPv4. The Internet complexity and its enormous size prolong the transition from IPv4 to IPv6 process. This means that both versions will necessarily co-exist. Meanwhile, tunneling appears as a solution trend. The tunneling is a transition technique that is considered temporary till all ISPs would support IPv6. At this paper, we compare the routing convergence of two tunnel types, 6to4 and Manually Configured versus the conventional IPv4 and IPv6 protocols. We analyze the network resources consumed during cold start

Artificial Intelligence
Software and Communications

Novel computational apoptosis-neurogenesis model for multi-abstraction level perception

artificial neural network provides a cybernetic model that is similar to human intelligence in terms of parallel processing, generalization and memory stacking on the same neural network. From the era of neurogenesis, research models expect the rules that govern new neuron to depend on old mature circuitry. Other research models show the existence of catastrophic interference associated with new neurons if species is exposed to variable information content environment. In this work, the model developed provides a theoretical framework for a novel attention sensitive neural network as well as

Artificial Intelligence

Detecting and Integrating Multiword Expression into English-Arabic Statistical Machine Translation

In this paper we introduce a new method for detecting a type of English Multiword Expressions (MWEs), which is phrasal verbs, into an English-Arabic phrase-based statistical machine translation (PBSMT) system. The detection starts with parsing the English side of the parallel corpus, detecting various linguistic patterns for phrasal verbs and finally integrate them into the En-Ar PBSMT system. In addition, the paper explores the effect of cliticizing specific words in English that have no Arabic equivalent. The results, which reported with the BLEU scores, showed that some patterns achieved

Artificial Intelligence

NileTMRG at SemEval-2016 task 5: Deep convolutional neural networks for aspect category and sentiment extraction

This paper describes our participation in the SemEval-2016 task 5, Aspect Based Sentiment Analysis (ABSA). We participated in two slots in the sentence level ABSA (Subtask 1) namely: aspect category extraction (Slot 1) and sentiment polarity extraction (Slot 3) in English Restaurants and Laptops reviews. For Slot 1, we applied different models for each domain. In the restaurants domain, we used an ensemble classifier for each aspect which is a combination of a Convolutional Neural Network (CNN) classifier initialized with pretrained word vectors, and a Support Vector Machine (SVM) classifier

Artificial Intelligence

NileTMRG at SemEval-2016 Task 7: Deriving prior polarities for Arabic sentiment terms

This paper presents a model that was developed to address SemEval Task 7: "Determining Sentiment Intensity of English and Arabic Phrases", with focus on 'Arabic Phrases'. The goal of this task is to determine the degree to which some given term is associated with positive sentiment. The underlying premise behind the model that we have adopted is that determining the context (positive or negative) in which a term usually occurs can determine its strength. Since the focus is on Twitter terms, Twitter was used to collect tweets for each term for which a strength value was to be derived. An Arabic

Artificial Intelligence

Ultrafast optic disc localization using projection of image features

Optic Disc (OD) localization is a fundamental step in developing computer-assisted diagnostics. In this work, an ultrafast method to locate the OD in retinal fundus images is presented. The proposed method is based on transforming the localization problem into two 1D problems by projecting the image features onto two perpendicular directions. Image features such as the directionality of the retinal vessels, the brightness and the size of the OD have been used in the current method. Two publicly available databases were used to evaluate the accuracy and the computation time of the proposed

Artificial Intelligence