3HA: Hybrid Hole Healing Algorithm in a Wireless Sensor Networks

In wireless sensor networks (WSNs), the appearance of coverage holes over a large target field is mostly possible. Those holes reduce network performance and may affect the network efficiency. Several approaches were proposed to heal coverage holes in WSNs, but they still suffer from some weaknesses. In this paper we suggest a distributed algorithm, named hybrid hole healing algorithm (3HA), to find the minimum effective patching positions to deploy additional nodes to cover the holes. A hole manager node of each hole is responsible for operating the 3HA algorithm which requires two phases. The first phase finds all candidate patching positions using a Voronoi diagram. It takes all Voronoi vertices within the hole as the initial patching positions list. The second phase reduces as much as possible this list based on integer linear programming and on a probabilistic sensor model. The 3HA algorithm repeats the above phases in rounds, until all Voronoi vertices are covered. Simulation results show that our solution offers a high coverage ratio for various forms and sizes of holes and reduces the number of additional sensors when compared to some algorithms like the Perimeter-based, the Delaunay triangulation-based, the Voronoi-based, and the Trees-based coverage hole healing methods.

     

Graphic approach for the determination of the existence of sequences guaranteeing observability of switched linear systems

This paper deals with the design of sequences allowing the observability of the state of a switched linear system. The proposed method, based on a graph-theoretic approach, needs only the knowledge of the system’s structure. The necessary and sufficient conditions for the existence of at least one switching sequence guaranteeing the observability of a switched structured system are provided. Such conditions are particularly intuitive and they can be implemented with classic algorithms of the graph theory.     

Virtual-water content of agricultural production and food trade balance of Tunisia

This article is devoted to the assessment of Tunisian agricultural production and food trade balance water-equivalent. A linear regression model relating annual rainfall to crop yields is developed to estimate the agricultural production water-equivalent. Its implementation is based on national data for crop and animal production, leading to food demand water-equivalent quantification. Results highlight the relationship between agricultural and water policies and provide a picture of food security in the country in relation to local agricultural production, and to virtual water fluxes related to foodstuffs trade balance.     

Data Security Model for Cloud Computing

From the perspective of data security, which has always been an important aspect of quality of service, cloud computing focuses a new challenging security threats. Therefore, a data security model must solve the most challenges of cloud computing security. The proposed data security model provides a single default gateway as a platform. It used to secure sensitive user data across multiple public and private cloud applications, including Salesforce, Chatter, Gmail, and Amazon Web Services, without influencing functionality or performance. Default gateway platform encrypts sensitive data automatically in a real time before sending to the cloud storage without breaking cloud application. It did not effect on user functionality and visibility. If an unauthorized person gets data from cloud storage, he only sees encrypted data. If authorized person accesses successfully in his cloud, the data is decrypted in real time for your use. The default gateway platform must contain strong and fast encryption algorithm, file integrity, malware detection, firewall, tokenization and more. This paper interested about authentication, stronger and faster encryption algorithm, and file integrity.     

First-Principle Study of Electronic and Half-Metallic Ferromagnetic Properties of Vanadium (V)-Doped Cubic BP and InP

In this study, we use the first-principle calculations of density functional theory with gradient generalized approximation of Wu–Cohen to investigate the doping effect of vanadium impurity on structural, electronic and magnetic properties of In_1?x V _x P and B_1?x V _x P alloys at various concentrations x = 0.0625, 0.125 and 0.25. Owing to the metallic nature of majority spin and semiconducting minority spin, the In_1?x V _x P compounds exhibit a half-metallic character with total magnetic moments of 2 μ _B, while the B_1?x V _x P has metallic nature for all concentrations. The results of exchange parameters revealed that exchange coupling between vanadium atoms and the conduction band is ferromagnetic, confirming the magnetic feature of In_1?x V _x P and B_1?x V _x P. From our findings, we have predicted that the In_1?x V _x P alloys seem to be potential materials for spintronics.     

Observability of switching structured linear systems with unknown input. A graph-theoretic approach

This paper deals with the observability of the discrete mode, the internal state and the input of switching structured linear systems with unknown input. The proposed method, based on a graph-theoretic approach, assumes only the knowledge of the system’s structure. We express, in graphical terms, necessary and sufficient conditions for the generic observability of the discrete mode, the continuous internal state and the input of a switching structured linear system. These conditions can be implemented by classical graph theory algorithms based on finding particular paths and cycles in a digraph.     

A Hybrid Virtual Cloud Learning Model during the COVID-19 Pandemic

The COVID-19 pandemic has affected the educational systems worldwide, leading to the near-total closures of schools, universities, and colleges. Universities need to adapt to changes to face this crisis without negatively affecting students’ performance. Accordingly, the purpose of this study is to identify and help solve to critical challenges and factors that influence the e-learning system for Computer Maintenance courses during the COVID-19 pandemic. The paper examines the effect of a hybrid modeling approach that uses Cloud Computing Services (CCS) and Virtual Reality (VR) in a Virtual Cloud Learning Environment (VCLE) system. The VCLE system provides students with various utilities and educational services such as presentation slides/text, data sharing, assignments, quizzes/tests, and chatrooms. In addition, learning through VR enables the students to simulate physical presence, and they respond well to VR environments that are closer to reality as they feel that they are an integral part of the environment. Also, the research presents a rubric assessment that the students can use to reflect on the skills they used during the course. The research findings offer useful suggestions for enabling students to become acquainted with the proposed system’s usage, especially during the COVID-19 pandemic, and for improving student achievement more than the traditional methods of learning.     

Reliability Prediction of Composite Tubular Structure Under Mechanical Loading by Finite Element Method

The diversified use of filamentary composites in harsh marine environments, recorded in recent years, has prompted researchers to focus their work on the reliability prediction. Through failure criteria, Tsai–Wu and the maximum stress, the reliability of multilayer tubular structures under mechanical loading is the subject of this paper, where Monte Carlo method estimated the failure probability. A sensitivity analysis was performed in order to identify the influence of the different parameters, such as materials’ properties, geometry, manufacturing and loading, on the reliability of the composite cylindrical structure studied. To achieve a high accuracy of the results, we have carried out 105 simulations. The results showed great influence on pressure loading, ply thickness and finally winding angle of filament composite.