The coupling between form and forces, their structural morphology, is a key point for tensegrity systems. In the first part of this paper we describe the design process of the simplest tensegrity system which was achieved by Kenneth Snelson. Some other simple cells are presented and tensypolyhedra are defined as tensegrity systems which meet polyhedra geometry in a stable equilibrium state. A numerical model giving access to more complex systems, in terms of number of components and geometrical properties, is then evoked. The third part is devoted to linear assemblies of annular cells which can be folded.Some experimental models of the tensegrity ring which is the basic component of this “hollow rope” have been realized and are examined.

1. IntroductionSpace structures are mostly interested for their lightness. one of the recent branches of space structures are called tensegrity structures. These structures are composed of compression bars and prestressed cables. There are not sufficient works about dynamic characteristics and behavior of these structures. Sultan et al carried out some research on nonlinear dynamic behavior of these structures [1]. Ben Kahla and Moussa studied the dynamic effects of rupture of a cable in an expanded tetrahedron [2]. Ben Kahla also has carried out a numerical analysis study of seismic behavior of a tensegrity frame [3]. Following these studies, in this research a set of tensegrity barrel vaults are considered and their seismic behavior is studied.

The word tensegrity is a contraction of tensional integrity. In simple structural terms, tensegrity systems are self-stressed pin-jointed networks. Each node receives at least one strut compression member) and three cables (tension members). Tension members are thus prestressed against adjoining compression members. This is a pure form of tensegrity where only compression and tension members co-exist to form free-standing structures requiring minimum anchorage system compared with conventional types of structures. Double layer tensegrity systems are interesting because the compression members are relatively short, making the network quite rigid and compact. In the non-prestressed state, the system could be easily deployed. The present paper reviews limited research so far conducted at Coventry University on double layer tensegrity networks. It also reviews future directions in research into this fascinating field that has yet to be fully explored and exploited to find proper applications for it in the civil engineering discipline.      

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With the widespread use of Android smartphones, the Android platform has become an attractive target for cybersecurity attackers and malware authors. Meanwhile, the growing emergence of zero-day malware has long been a major concern for cybersecurity researchers. This is because malware that has not been seen before often exhibits new or unknown behaviors, and there is no documented defense against it. In recent years, deep learning has become the dominant machine learning technique for malware detection and could achieve outstanding achievements. Currently, most deep malware detection techniques are supervised in nature and require training on large datasets of benign and malicious samples. However, supervised techniques usually do not perform well against zero-day malware. Semi-supervised and unsupervised deep malware detection techniques have more potential to detect previously unseen malware. In this paper, we present MalGAE, a novel end-to-end deep malware detection technique that leverages one-Class graph neural networks to detect Android malware in a semi-supervised manner. MalGAE represents each Android application with an attributed function call graph (AFCG) to benefit the ability of graphs to model complex relationships between data. It builds a deep one-Class Classifier by training a stacked graph autoencoder with graph convolutional layers on benign AFCGs. Experimental results show that MalGAE can achieve good detection performance in terms of different evaluation measures.