Quantum abstract detecting systems

Quantum Information Processing - Gaussian Boson Sampling (GBS) is a model of photonic quantum computing where single-mode squeezed states are sent through linear-optical interferometers and...     

A survey on the service interoperability in cloud computing: Client-centric and provider-centric perspectives

The vendor lock-in is a prominent issue in cloud computing. It is caused by cloud providers who offer proprietary services, which hinders the cloud interoperability. Client-centric interoperability enables the migration of the data and applications across clouds; it gives the clients control over their workloads and a wider range of service choices. Whereas, provider-centric interoperability allows the providers to collaborate. Thus, providers, who have spare resources, can lend them to other providers who lack computational or storage capabilities to overcome the limitations of their local resources. In this article, we conduct a survey to differentiate between client- and provider-centric interoperability solutions. We aim to provide an up-to-date analysis of the current tendencies and the neglected areas of the cloud interoperability field. Thus, we study the cloud service interoperability evolution through the years. Furthermore, we propose definitions for the intra-cloud and inter-cloud interoperability. Moreover, we propose a taxonomy to classify the cloud interoperability approaches into client-centric and provider-centric categories. Then, for each category, we classify the approaches based on their interoperability environment into single cloud or interconnected clouds. Finally, we analyze and compare the approaches based on multiple criteria. The study reveals the focus on the client-centric solutions and the interoperability in interconnected clouds. We notice more interest in the data and application levels interoperability, mainly, in infrastructure as a service model. We also find that client-centric solutions are, mostly, semantic technologies and brokers. However, provider-centric solutions are middleware, protocols, and standards. We conclude that a generic cloud service interoperability model is needed.     

An Improved Chaotic Cryptosystem for Image Encryption and Digital Watermarking

Wireless Personal Communications - In this article, enhanced chaotic range map is used for data hiding and multimedia security. By using complex properties of improved chaotic logistic map that...     

Synthesis and Characterizations of p-Type Kesterite Ag 2 ZnSnS 4 Thin Films Deposited by Spray Pyrolysis

The fabrication of absorber materials based on kesterite materials has attracted considerable attention in recent articles owing to their excellent optical and electrical properties. In this work, we present the synthesis of Ag2ZnSnS4 films with different thicknesses using a cost-effective spray pyrolysis method. X-ray diffraction was used to check the tetragonal phase and the highly oriented nature of the Ag2ZnSnS4 films. Optical data analysis indicates that a direct allowed transition has appeared in the Ag2ZnSnS4 thin films. The optical results reveal that the energy gap decreases from 1.5 eV to 1.23 eV via enlarging the film thickness of the Ag2ZnSnS4 thin films. Moreover, the dispersion parameters obtained via the Wemple–DiDomenico model and the nonlinear optical parameters of the Ag2ZnSnS4 samples were computed and analyzed.     

Predicting muscle forces measurements from kinematics data using kinect in stroke rehabilitation

Muscle strength is mostly measured by wearable devices. However, wearing such devices is a tedious, unpleasant, and sometimes impossible task for stroke patients. In this paper, a mathematical model is proposed to estimate the strength of the upper limb muscles of a stroke patient by using Microsoft Kinect sensor. A prototype exergame is designed and developed to mimic real post-stroke rehabilitation exercises. Least-square regression matrix is used to find the relation between the kinematics of the upper limb and the strength of the corresponding muscles. Kinect sensor is used along with a force sensing resistors (FSR) glove and two straps to collect both, real-time upper limb joints data and the strength of muscles of the subjects while they are performing the exercises. The prototype of this system is tested on five stroke patients and eight healthy subjects. Results show that there is no statistically significant difference between the measured and the estimated values of the upper-limb muscles of the stroke patients. Thus, the proposed method is useful in estimating the strength of the muscles of stroke patient without the need to wear any devices.     

Radial invariant of 2D and 3D Racah moments

In this paper, we introduce new sets of 2D and 3D rotation, scaling and translation invariants based on orthogonal radial Racah moments. We also provide theoretical mathematics to derive them. Thus, this work proposes in the first case a new 2D radial Racah moments based on polar representation of an object by one-dimensional orthogonal discrete Racah polynomials on non-uniform lattice, and a circular function. In the second case, we present new 3D radial Racah moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Racah polynomials and a spherical function. Further 2D and 3D invariants are extracted from the proposed 2D and 3D radial Racah moments respectively will appear in the third case. To validate the proposed approach, we have resolved three problems. The 2D/ 3D image reconstruction, the invariance of 2D/3D rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Racah moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges rapidly to the original image using 2D and 3D radial Racah moments, and the test 2D/3D images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and PSB database for 3D image.     

GPU fuzzy c-means algorithm implementations: performance analysis on medical image segmentation

Multimedia Tools and Applications - Image segmentation in the medical imagery such as MRI, is an essential step to the sensitive analysis of human tissues lesions with the objective to improve the...     

The Impact of Social Media on Consumers’ Acculturation and Purchase Intentions

Social media has emerged as a significant and effective means of assisting and endorsing activities and communications among peers, consumers and organizations that outdo the restrictions of time and space. While the previous studies acknowledge the role of agents of culture change, it largely remains silent on the role of social media in influencing acculturation outcomes and consumption choices. This study uses self-administered questionnaire to collect data from 514 Turkish-Dutch respondents and examines how their use of social media affects their acculturation and consumption choices. This research makes a significant contribution to consumer acculturation research by showing that social media is a vital means of culture change and a driver of acculturation strategies and consumption choices. This study is the first to investigate the role of social media as an agent of culture change in terms of how it impacts acculturation and consumption. The paper discusses implications for theory development and for practice.     

Energy efficient teaching-learning-based optimization for the discrete routing problem in wireless sensor networks

Wireless sensor networks (WSNs) are composed of sensor nodes, having limited energy resources and low processing capability. Accordingly, major challenges are involved in WSNs Routing. Thus, in many use cases, routing is considered as an NP-hard optimization problem. Many routing protocols are based on metaheuristics, such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Despite the fact that metaheuristics have provided elegant solutions, they still suffer from complexity concerns and difficulty of parameter tuning. In this paper, we propose a new routing approach based on Teaching Learning Based Optimization (TLBO) which is a recent and robust method, consisting on two essential phases: Teacher and Learner. As TLBO was proposed for continuous optimization problems, this work presents the first use of TLBO for the discrete problem of WSN routing. The approach is well founded theoretically as well as detailed algorithmically. Experimental results show that our approach allows obtaining lower energy consumption which leads to a better WSN lifetime. Our method is also compared to some typical routing methods; PSO approach, advanced ACO approach, Improved Harmony based approach (IHSBEER) and Ad-hoc On-demand Distance Vector (AODV) routing protocol, to illustrate TLBO’s routing efficiency.     

Discrete kinetic theory for 2D modeling of a moving crowd: Application to the evacuation of a non-connected bounded domain

This paper concerns the mathematical modeling of the motion of a crowd in a non connected bounded domain, based on kinetic and stochastic game theories. The proposed model is a mesoscopic probabilistic approach that retains features obtained from both micro- and macro-scale representations; pedestrian interactions with various obstacles being managed from a probabilistic perspective. A proof of the existence and uniqueness of the proposed mathematical model’s solution is given for large times. A numerical resolution scheme based on the splitting method is implemented and then applied to crowd evacuation in a non connected bounded domain with one rectangular obstacle. The evacuation time of the room is then calculated by our technique, according to the dimensions and position of a square-shaped obstacle, and finally compared to the time obtained by a deterministic approach by means of randomly varying some of its parameters.