Network-coding based event diffusion for wireless networks using semi-broadcasting

Publish/subscribe is a well known and powerful distributed programming paradigm with many potential applications. Publish/subscribe content dissemination techniques based on opportunistic networking and network coding-based epidemic routing are key techniques for optimizing network resources, simplifying network architecture, and providing a platform for realizing innovative networking applications and service.In this paper we consider the central problem of any pub/sub implementation, namely the problem of event dissemination, in the case of a wireless mesh network. We propose a new dissemination strategy based on the notion of semi-broadcast. In a semi-broadcast based protocol the actual content is disseminated in two phases. In the first phase only a fraction of the content is broadcasted (pushed) over the network and stored inside any node, whereas in the second phase the missed part is retried (pulled) on demand from other nodes. Thanks to network coding the partial content stored in each node at the end of the first phase is a set of random linear combinations over the whole content. This allows a very efficient recovery strategy as the missed part is found in nearby nodes with a high probability.The benefit of this approach is that only the interested subscribers, which can vary in number and position over time, can engage the pulling phase.We propose several protocols based on non-trivial forwarding mechanisms that employ network coding as a central tool for supporting adaptive event dissemination while exploiting the broadcast nature of wireless transmissions and guided to the semi-broadcast principle. We show a considerable enhancement in term of total flooding costs and full decoding rates by a self parameter control deployment during the dissemination procedure.     

Scale effect and two-phase flow in a thin hydrophobic porous layer. Application to water transport in gas diffusion layers of proton exchange membrane fuel cells

Pore network simulations are performed to study water transport in gas diffusion layers (GDLs) of polymer electrolyte membrane fuel cells (PEMFCs). The transport and equilibrium properties are shown to be scale dependent in a thin system like a GDL. A distinguishing feature of such a thin system is the lack of length scale separation between the system size and the size of the representative elementary volume (REV) over which are supposed to be defined the macroscopic properties within the framework of the continuum approach to porous media. Owing to the lack of length scale separation, two-phase flow traditional continuum models are expected to offer poor predictions of water distribution in a GDL. This is illustrated through comparisons with results from the pore network model. The influence of inlet boundary conditions on invasion patterns is studied and shown to affect greatly the saturation profiles. The effects of GDL differential compression and partial coverage of outlet surface are also investigated.     

Fusion of thermal infrared and visible spectra for robust moving object detection

The detection of moving objects is a crucial step for many video surveillance applications whether using a visible camera (VIS) or an infrared (IR) one. In order to profit from both types, several fusion methods were proposed in the literature: low-level fusion, medium-level fusion and high-level fusion. The first one is the most used for moving objects’ detection in IR and VIS spectra. In this paper, we present an overview of the different moving object detection methods in IR and VIS spectra and a state of the art of the low-level fusion techniques. Moreover, we propose a new method for moving object detection using low-level fusion of IR and VIS spectra. In order to evaluate quantitatively and qualitatively our proposed method, three series of experiments were carried out using two well-known datasets namely “OSU Color-Thermal Database” and “INO-Database”; the results of these evaluations show promising results and demonstrate the effectiveness of the proposed method.     

Deep multilayer multiple kernel learning

Multiple kernel learning (MKL) approach has been proposed for kernel methods and has shown high performance for solving some real-world applications. It consists on learning the optimal kernel from one layer of multiple predefined kernels. Unfortunately, this approach is not rich enough to solve relatively complex problems. With the emergence and the success of the deep learning concept, multilayer of multiple kernel learning (MLMKL) methods were inspired by the idea of deep architecture. They are introduced in order to improve the conventional MKL methods. Such architectures tend to learn deep kernel machines by exploring the combinations of multiple kernels in a multilayer structure. However, existing MLMKL methods often have trouble with the optimization of the network for two or more layers. Additionally, they do not always outperform the simplest method of combining multiple kernels (i.e., MKL). In order to improve the effectiveness of MKL approaches, we introduce, in this paper, a novel backpropagation MLMKL framework. Specifically, we propose to optimize the network over an adaptive backpropagation algorithm. We use the gradient ascent method instead of dual objective function, or the estimation of the leave-one-out error. We test our proposed method through a large set of experiments on a variety of benchmark data sets. We have successfully optimized the system over many layers. Empirical results over an extensive set of experiments show that our algorithm achieves high performance compared to the traditional MKL approach and existing MLMKL methods.     

Overheating caused by passive solar elements in Tunis. Effectiveness of some ways to prevent it

Although Tunisian winters are mild compared with northern regions, there are heating requirements; their limited level suggests that passive solar energy would probably be able to meet them. However, the summer is hot enough, and one may wonder whether a solar design oriented toward the cold season would not induce severe overheating. Numerous studies have dealt with the heating performance of passive solar elements, but very little has been done to analyze their behavior in hot climatic conditions. The National School for Engineers of Tunis has built a passive solar pavilion which has been carefully instrumented. Special care has been devoted to the summer behavior of the pavilion. In this paper we describe some of the actions taken to prevent overheating, and we investigate their efficacy both by analysis of recorded measurements and by simulation. It is found that night ventilation is the most responsible action in decreasing room temperature, and that Trombe wall screening is more efficient than operating the walls as a solar chimney; overhangs are of valuable aid, and shuttering of the direct gain element also helps against overheating. The high thermal capacity results in a very stable room temperature, and plays an essential role for cooling when coupled with night ventilation. Finally, it is found that if appropriate action is taken in the hot season, a house equipped with passive solar heating elements can reach a very acceptable level of comfort in summer time.     

Clogging modeling in pleated filters for gas filtration

A model of clogging of a pleated filter in gas filtration is presented. The model is obtained by combining a semi-analytical model of the flow in a pleated filter and an empirical model of clogging of the planar filter medium applied locally along the pleated filter channels. The model takes into account the formation of a filtration cake of variable thickness at the porous wall of the pleated filter entrance channels and the resulting evolution of the entrance channels aperture distribution during the filtration/clogging process. Based on the numerical predictions, two main clogging scenarios are identified and analyzed. The optimum pleat density, defined as the pleat density maximizing the filter capacity, is determined and shown to be greater than the pleat density minimizing the pressure drop for a clean filter. Predictions of the evolution of overall pressure drop across the pleated filter due to clogging are compared with experimental data.     

Nonlinear dynamic of the renewable energy cycle transition in Tunisia: Evidence from smooth transition autoregressive models

In this paper, we focus on the problem of the energy transition in Tunisia were we suggest to study and modeling the nonlinear dynamic of the endogenous renewable energy cycle.As today the socioeconomic development in Tunisia is too complicated and dependent on the adopted energetic strategy. Our contribution consists on recognizing exactly the main bases of this correlative development.In this context, we try to provide some theoretical and empirical studies for renewable energy politics especially under the chaotic transition in the post revolution period in Tunisia.All this work will be based on the application of the univariate STAR (smooth transition autoregressive) method composed by two transition process types the logistic STAR model (LSTAR) and the exponential STAR model (ESTAR). As results we found that the LSTAR process is more adequate for asymmetric data for our case. In this regard, our results indicated that the renewable energy can not only work as a possible factor for energetic strategy transition in Tunisia, but also, is a promising candidate for stability and socioeconomic development.     

Mixed Cartesian feedback for Zero-IF WCDMA transmitter

In this paper, a new adaptive power amplifier (PA) linearization technique is presented. The idea is to consider a classic WCDMA zero-intermediate frequency (Zero-IF) transmitter with a modified Cartesian feedback (CFB) loop. The new transmitter architecture consists of an analog stage including forward I/Q modulator and feedback I/Q demodulator, and a digital stage adjusting the phase rotation around the loop. The whole system consumes 500 and 2.94 mW, respectively, for the analog and the digital part. System level simulation gave a maximum improvement of 35 dBc at 5 MHz from the carrier for the W-CDMA signal.     

An Overview of the Authentication of Olive Tree and Oil

Adulteration of virgin olive oil with less expensive oils is a serious problem for the public and quality control evaluators of olive oil. That is why olive oil authenticity has become a major issue for producers, consumers, and policy makers. In order to avoid fraud to consumers, it is crucial to study the traceability of olive oil. This review covers 2 important techniques, analytical, and molecular methods, used to characterize olive oil and detect possible adulteration. Several analytical techniques are discussed for the detection of olive oil adulteration by analyzing minor and major compounds of olive oil. However, the chemical composition of olive oil can dramatically change due to the environmental and processing conditions. For this reason, the DNA‐based technologies are gaining greater attention now because they are not influenced by environmental conditions and provide an opportunity for direct comparison of different genetic materials. In this review, we emphasize the great potential of different authenticity methods and discuss their practical implementation in olive oil traceability.