
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

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

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

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

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

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

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

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

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

Behaviorally-Based Textual Similarity Engine for Matching Job-Seekers with Jobs
Understanding both of job-seekers and employers behavior in addition to analyzing the text of job-seekers and job profiles are two important missions for the e-recruitment industry. They are important tasks for matching job-seekers with jobs to find the top relevant suggestions for each job-seeker. Recommender systems, information retrieval and text mining are originally targeted to assist users and provide them with useful information, which makes human-computer interaction plays a fundamental role in the users’ acceptance of the produced suggestions. We introduce our intelligent framework to
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