Interleaving Gains for Receive Diversity Schemes of Distributed Turbo Codes in Wireless Half–Duplex Relay Channels

This paper proposes the interleaving gain in two different distributed turbo-coding schemes: Distributed Turbo Codes (DTC) and Distributed Multiple Turbo Codes (DMTC) for half-duplex relay system as an extension of our previous work on turbo coding interleaver design for direct communication channel. For these schemes with half-duplex constraint, the source node transmits its information with the parity bit sequence(s) to both the relay and the destination nodes during the first phase. The relay received the data from the source and process it by using decode and forward protocol. For the second transmission period, the decoded systematic data at relay is interleaved and re-encoded by a Recursive Systematic Convolutional (RSC) encoder and forwarded to the destination. At destination node, the signals received from the source and relay are processed by using turbo log-MAP iterative decoding for retrieving the original information bits. We demonstrate via simulations that the interleaving gain has a large effect with DTC scheme when we use only one RSC encoder at both the source and relay with best performance when using Modified Matched S-Random (MMSR) interleaver. Furthermore, by designing a Chaotic Pseudo Random Interleaver (CPRI) as an outer interleaver at the source node instead of classical interleavers, our scheme can add more secure channel conditions

Terrorism in the Middle East: Implications on Egyptian Travel and Tourism

This paper attempts to shed the light on challenging issues affecting travel and tourism industry especially in the Middle East such as political, socio-economic and security instability. Due to its geopolitical and historical importance, the paper focuses on the situation in Egypt as a descriptive case study. The methodology relies on historical review and impact assessment to understand the roots and extended branches of instability in the Middle East that led to the Arab Spring, by focusing on the Egyptian case in the last half century. The assessment explains the negative effect of Western and Egyptian policy on extending the contemporary Middle East crisis by using militarization over sustainability. The assessment not only shows the consequences and risks for the local population and visitors, but also suggests potential corrective actions

Wrinkling, creasing, and folding in fiber-reinforced soft tissues

Many biological tissues develop elaborate folds during growth and development. The onset of this folding is often understood in relation to the creasing and wrinkling of a thin elastic layer that grows whilst attached to a large elastic foundation. In reality, many biological tissues are reinforced by fibres and so are intrinsically anisotropic. However, the correlation between the fiber directions and the pattern formed during growth is not well understood. Here, we consider the stability of a two-layer tissue composed of a thin hyperelastic strip adhered to an elastic half-space in which are embedded elastic fibers. The combined object is subject to a uniform compression and, at a critical value of this compression, buckles out of the plane — it wrinkles. We characterize the wrinkle wavelength at onset as a function of the fiber orientation both computationally and analytically and show that the onset of surface instability can be either promoted or inhibited as the fiber stiffness increases, depending on the fibre angle. However, we find that the structure of the resulting folds is approximately independent of the fiber orientation. We also explore numerically the formation of large creases in fiber-reinforced tissue in the post-buckling regime

Characterization of Vehicle Behavior with Information Theory

This work proposes the use of Information Theory for the characterization of vehicles behavior through their velocities. Three public data sets were used: i.Mobile Century data set collected on Highway I-880, near Union City, California; ii.Borl\"ange GPS data set collected in the Swedish city of Borl\"ange; and iii.Beijing taxicabs data set collected in Beijing, China, where each vehicle speed is stored as a time series. The Bandt-Pompe methodology combined with the Complexity-Entropy plane were used to identify different regimes and behaviors. The global velocity is compatible with a correlated noise with f^{-k} Power Spectrum with k >= 0. With this we identify traffic behaviors as, for instance, random velocities (k aprox. 0) when there is congestion, and more correlated velocities (k aprox. 3) in the presence of free traffic flow

Bott--Kitaev periodic table and index theory

We consider topological insulators and superconductors with discrete symmetries and clarify the relevant index theory behind the periodic table proposed by Kitaev. An effective Hamiltonian determines the analytical index, which can be computed by a topological index. We focus on the spatial dimensions one, two and three, and only consider the bulk theory. In two dimensions, the $\mathbb{Z}$-valued invariants are given by the first Chern number. Meanwhile, $\mathbb{Z}_2$-valued invariants can be computed by the odd topological index and its variations. The Bott-Kitaev periodic table is well-known in the physics literature, we organize the topological invariants in the framework of KR-theory.Comment: 37 page

Online and Offline Dynamic Influence Maximization Games Over Social Networks

In this work, we consider dynamic influence maximization games over social networks with multiple players (influencers). The goal of each influencer is to maximize their own reward subject to their limited total budget rate constraints. Thus, influencers need to carefully design their investment policies considering individuals' opinion dynamics and other influencers' investment strategies, leading to a dynamic game problem. We first consider the case of a single influencer who wants to maximize its utility subject to a total budget rate constraint. We study both offline and online versions of the problem where the opinion dynamics are either known or not known a priori. In the singe-influencer case, we propose an online no-regret algorithm, meaning that as the number of campaign opportunities grows, the average utilities obtained by the offline and online solutions converge. Then, we consider the game formulation with multiple influencers in offline and online settings. For the offline setting, we show that the dynamic game admits a unique Nash equilibrium policy and provide a method to compute it. For the online setting and with two influencers, we show that if each influencer applies the same no-regret online algorithm proposed for the single-influencer maximization problem, they will converge to the set of $\epsilon$-Nash equilibrium policies where $\epsilon=O(\frac{1}{\sqrt{K}})$ scales in average inversely with the number of campaign times $K$ considering the average utilities of the influencers. Moreover, we extend this result to any finite number of influencers under more strict requirements on the information structure. Finally, we provide numerical analysis to validate our results under various settings.Comment: This work has been submitted to IEEE for possible publicatio