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Consistency Analysis of Madd rules in the Holy Quran

A consistency analysis is performed for one of the famous Tajweed rules in the Holy Quran - Madd rules. They are tested on records of one of the famous reference reciters - Sheikh El-Hosary-to find a consistent boundaries and to evaluate the performance of other new learners. A vowel detection algorithm is used to detect the duration of the detected Madd patterns. This algorithm was applied on a dataset of 105 minutes of Quranic records of Sheikh El-Hosary. The consistency result is found to be normally distributed with a mean of 0.379 second of one movement time of Madd and standard deviation

Artificial Intelligence

Trans-Compiler based Mobile Applications code converter: Swift to java

Numerous commercial tools like Xamarin, React Native and PhoneGap utilize the concept of cross-platform mobile applications development that builds applications once and runs it everywhere opposed to native mobile app development that writes in a specific programming language for every platform. These commercial tools are not very efficient for native developers as mobile applications must be written in specific language and they need the usage of specific frameworks. In this paper, a suggested approach in TCAIOSC tool to convert mobile applications from Android to iOS is used to develop the

Artificial Intelligence
Circuit Theory and Applications
Software and Communications
Innovation, Entrepreneurship and Competitiveness

VoIP performance evaluation over IPv4-6 and manually configured tunnels

IPv4 address space is exhausted. Internet Engineering Task Force (IETF) developed IPv6 -the upgrade of IPv4- to satisfy the continual increase of the IP address needs. The Internet is so ramified and enormous that the complete transition from IPv4 to IPv6 is slow. Therefore, their coexistence is inevitable. Manually configured tunnels are an important solution to allow this co-existence that allows transmitting native IPv6 packets over IPv4 networks. Meanwhile, VoIP is also gaining momentum with expectation to occupy considerable percentage of Internet traffic. In this paper, we compare the

Artificial Intelligence

Performance evaluation and comparison of the top market virtualization hypervisors

The virtualization of IT infrastructure enables the consolidation and pooling of IT resources so that they can be shared over diverse applications to offset the limitation of shrinking resources and growing business needs. It provides a logical abstraction of physical computing resources and creates computing environments that are not restricted by physical configuration or implementation. Virtualization is very important for cloud computing because the delivery of services is simplified by providing a platform for optimizing complex IT resources in a scalable manner, which makes cloud

Artificial Intelligence

Robust autonomous visual detection and tracking of moving targets in UAV imagery

The use of Unmanned Aerial Vehicles (UAVs) for reconnaissance and surveillance applications has been steadily growing over the past few years. The operations of such largely autonomous systems rely primarily on the automatic detection and tracking of targets of interest. This paper presents a novel automatic multiple moving target detection and tracking framework that executes in real-time and is suitable for UAV imagery. The framework is based on image feature processing and projective geometry and is carried out on the following stages. First, outlier image features are computed with least

Artificial Intelligence

Scale-adaptive object tracking with diverse ensembles

Tracking by detection techniques have recently been gaining increased attention in visual object tracking due to their promising results in applications such as robotics, surveillance, traffic monitoring, to name a few. These techniques often employ semi-supervised appearance model where a set of samples are continuously extracted around the object to train a discriminant classifier between the object and the background whereas real-time performance is attained by using reduced object representations as in the case of the compressive tracking algorithm. However, because they rely on self

Artificial Intelligence

Towards cloud customers self-monitoring and availability-monitoring

As an attractive IT environment, Cloud Computing represents a good enough paradigm which governments, national entities, small/medium/large organizations and companies want to migrate to. In fact, outsourcing IT related services to Cloud technology, needs monitoring and controlling mechanisms. However, Cloud Customers cannot fully rely on the Cloud Providers measurements, reports and figures. In this book chapter, we cover the two Cloud Computing operation sides. For the first operation side, we provide advices and guidelines for Cloud layers which can be under Cloud Customer control, to allow

Artificial Intelligence

5G and Satellite Network Convergence: Survey for Opportunities, Challenges and Enabler Technologies

Development of 5G system as a global telecommunication infrastructure is accelerating to realize the concept of a unified network infrastructure incorporating all access technologies. The potential of Low Earth Orbit (LEO) constellation systems has emerged to support wide range of services. This could help to achieve 5G key service requirements for enhanced Mobile Broadband (eMBB), Massive Machine-Type Communications (mMTC), and Ultra-Reliable Low-Latency Communication (URLLC). The integration of satellite communications with the 5G New Radio (NR) is stimulated by technology advancement to

Artificial Intelligence

Vision capabilities for a humanoid robot tutoring biology

Robots are expected to be the future solution in various fields. One of these fields is education. Teachers, students and robots have to work together to make this assumption true. For this, robots must have the adequate capabilities that can help them succeed. Vision of the robot is an essential tool that the robot uses to perform several tasks. Hence, it has to be taken into consideration, the steps and the expectations for this robot vision system to surpass at least the very basic skills. Detection, recognition, and localization are the basic skills that we are implementing in our

Artificial Intelligence

Optical character recognition using deep recurrent attention model

We address the problem of recognizing multi-digit numbers in optical character images. Classical approaches to solve this problem include separate localization, segmentation and recognition steps. In this paper, an integrated approach to multi-digit recognition from raw pixels to ultimate multi class labeling is proposed by using recurrent attention model based on a spatial transformer model equipped with LSTM to localize digits individually and a subsequent deep convolutional neural network for actual recognition. The proposed method is evaluated on the publicly available SVHN dataset where

Artificial Intelligence