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The wave concept iterative procedure (WCIP) is a powerful tool dedicated to the numerical analysis of RF circuits. The big problem of this method is that the required calculation time becomes higher when the circuit’s complexity increases, that’s to say for circuits with huge mesh surface. In this paper, we use a fast WCIP method based on 2D Discrete Wavelet Transform (2D DWT) to study a frequency selective surface, FSS, having a U-geometry. This 2D DWT technique is used to optimize the amount of information manipulated by the iterative process in order to get a fast convergence time.

Due to its global nature and highly dynamic and competitive environment, supply chain arguably is more exposed to disruptions. As supply chains continue to grow in scale and complexity, inventory management in a dynamic business environment is a challenging task. The aim of this paper is to propose a multi-agent approach to quantify the impact of inventory disruptions. Our objective is to analyze the capacities of supply chains to cope with disruptions before and after stockouts by including (proactive) mitigation strategies and reactive strategies. The proposed system allows providing advice to human users in the form of decision support. A prototype system is built and validated, which demonstrates the feasibility of the proposed approach. The experiments show that the implementation of multi-agent technology makes the system much more flexible to make the final decision.

Geographic and climate parameters influence the epidemiology of Respiratory Syncytial Virus (RSV). In Tunisia, information about the impact of environment factors on RSV infection is not well established. The objective is to predict the onset of RSV season based on meteorological parameters by investigating the association between RSV bronchiolitis and climate factors.

In this paper, we propose a novel approach for finding correspondence between three-dimensional shapes undergoing non-rigid transformations. Our proposal is based on the computation of the mean of curvature fields values on a local parametrization constructed around interest points on the surface. This local parametrization corresponds to the Darcyan coordinates system. Thereafter, correspondence is found by measuring the \(L_{2}\) distance between obtained descriptors. We conduct the experimentation on the full objects of the Tosca database which contains a set of 3D objects with non-rigid deformations. The obtained results show the performance of the proposed approach.

The development of context aware UIs has become a major requirement to ensure their efficiency and improve their usability, thus inducing many variations of the same UI depending on the constraints imposed by the context of use. To address this challenge, many works decided to rely on the Software Product Line Engineering (SPLE) paradigm. Software product lines (SPLs) were widely used due to their advantages, such as, but not limited to: the reuse of shared artifacts, the generation of specific products from shared artifacts, the reduction in time, effort and cost of development. Others works have relied on Dynamic Software Product Line (DSPL) approaches to develop a family of adaptive UIs. The DSPL exploits the knowledge acquired in SPLE to develop systems that can be context-aware, post-deployment reconfigurable, or adaptable at run-time. In order to address the challenge of context awareness, this paper presents an overview of UI-(D)SPL approaches which specifically focus on context-aware adaptation of user interfaces.

Natural disasters have reached unpredictable intensity around the world during the last two decades. Therefore, rapid response to the urgent relief in an efficient way is necessary for alleviation of disaster impact in the affected areas. Humanitarian Supply Chain Management plays a crucial role for disaster response management. Warehouse and inventory management is a key activity. Its effectiveness and efficiency are challenging issues during emergency response. In fact, by ensuring appropriate fast and well organized distribution of emergency relief supplies, damages would be mitigated and more lives saved. This paper draws first a literature review to better define humanitarian supply chain management and highlight inventory management characteristics and needs in a post-disasters context. An agent-based model and a simulator are developed in order to enable decision makers find efficient scenarios to respond effectively to urgent requests following a disaster. First simulation results are discussed.

We study the impact of multiple relays on the primary user (PU) and secondary user (SU) rates of underlay MIMO cognitive radio. Both users exploit amplify-and-forward relays to communicate with the destination. A space alignment technique and a special linear precoding and decoding scheme are applied to allow the SU to use the resulting free eigenmodes. In addition, the SU can communicate over the used eigenmodes under the condition of respecting an interference constraint tolerated by the PU. At the destination, a successive interference cancellation (SIC) is performed to estimate the secondary signal. We present the explicit expressions of the optimal PU and SU powers that maximize their achievable rates. In the numerical results, we show that our scheme provides cognitive rate gain even in absence of tolerated interference. In addition, we show that increasing the number of relays enhances the PU and SU rates at low power regime and/or when the relays power is sufficiently high.

Due to the enormous amount of data stored in spatial multidimensional databases (also called spatial datacubes) and the complexity of multidimensional structures, extracting interesting information by exploiting spatial data cubes becomes more and more difficult. Users might overlook what part of the cube contains the relevant information and what the next query should be. This could affect their exploitation of spatial datacubes.