Analysis of non ambiguous BOC signal acquisition performance Acquisition

The Binary Offset Carrier planned for future GNSS signal, including several GALILEO Signals as well as GPS M-code, presents a high degree of spectral separation from conventional signals. It also greatly improves positioning accuracy and enhances multipath rejection. However, with such a modulation, the acquisition process is made more complex. Specific techniques must be employed in order to avoid unacceptable errors. This paper assesses the performance of three method allowing to acquire and track BOC signal unambiguously : The Bump-jumping technique, The "BPSK-like" technique and the subcarrier Phase cancellation technique

The Dynamics of Innovation Networks

We analyse the changing contribution of networks to the innovative performance of 30 pharmaceutical companies from 1989 to 1997. Count data models show that collaborations with universities and biotechnology companies are important determinants of the firms' innovative performance, but their respective contributions diverge when industry matures. Larger firms enjoy a significant size advantage and in-house research activities are highly significant. Returns to scale in research are decreasing over time while the size advantage is increasing. The changing contribution of networks to knowledge production suggests that these are phase-specific, which has substantial managerial and policy implications.pharmaceutical industry, biotechnology, innovative processes, networks

Privacy-preserving Publication of Mobility Data with High Utility

An increasing amount of mobility data is being collected every day by different means, e.g., by mobile phone operators. This data is sometimes published after the application of simple anonymization techniques, which might lead to severe privacy threats. We propose in this paper a new solution whose novelty is twofold. Firstly, we introduce an algorithm designed to hide places where a user stops during her journey (namely points of interest), by enforcing a constant speed along her trajectory. Secondly, we leverage places where users meet to take a chance to swap their trajectories and therefore confuse an attacker.Comment: 2015 35th IEEE International Conference on Distributed Computed System

Time Distortion Anonymization for the Publication of Mobility Data with High Utility

An increasing amount of mobility data is being collected every day by different means, such as mobile applications or crowd-sensing campaigns. This data is sometimes published after the application of simple anonymization techniques (e.g., putting an identifier instead of the users' names), which might lead to severe threats to the privacy of the participating users. Literature contains more sophisticated anonymization techniques, often based on adding noise to the spatial data. However, these techniques either compromise the privacy if the added noise is too little or the utility of the data if the added noise is too strong. We investigate in this paper an alternative solution, which builds on time distortion instead of spatial distortion. Specifically, our contribution lies in (1) the introduction of the concept of time distortion to anonymize mobility datasets (2) Promesse, a protection mechanism implementing this concept (3) a practical study of Promesse compared to two representative spatial distortion mechanisms, namely Wait For Me, which enforces k-anonymity, and Geo-Indistinguishability, which enforces differential privacy. We evaluate our mechanism practically using three real-life datasets. Our results show that time distortion reduces the number of points of interest that can be retrieved by an adversary to under 3 %, while the introduced spatial error is almost null and the distortion introduced on the results of range queries is kept under 13 % on average.Comment: in 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Aug 2015, Helsinki, Finlan

Influence of material removal on the dynamic behavior of thin-walled structures in peripheral milling

Machining is a material removal process that alters the dynamic properties during machining operations. The peripheral milling of a thin-walled structure generates vibration of the workpiece and this influences the quality of the machined surface. A reduction of tool life and spindle life can also be experienced when machining is subjected to vibration. In this paper, the linearized stability lobes theory allows us to determine critical and optimal cutting conditions for which vibration is not appar- ent in the milling of thin-walled workpieces. The evolution of the mechanical parameters of the cut- ting tool, machine tool and workpiece during the milling operation are not taken into account. The critical and optimal cutting conditions depend on dynamic properties of the workpiece. It is illustrated how the stability lobes theory is used to evaluate the variation of the dynamic properties of the thin- walled workpiece. We use both modal measurement and finite element method to establish a 3D rep- resentation of stability lobes. The 3D representation allows us to identify spindle speed values at which the variation of spindle speed is initiated to improve the surface finish of the workpiece

Integration of dynamic behaviour variations in the stability lobes method: 3D lobes construction and application to thin-walled structure milling

Vibratory problems occurring during peripheral milling of thin-walled structures affect the quality of the fin- ished part and, to a lesser extent, the tool life and the spindle life. Therefore, it is necessary to be able to limit these problems with a suitable choice of cutting conditions. The stability lobes theory makes it possible to choose the appropriate cutting con- ditions according to the dynamical behaviour of the tool or the part. We introduce the dynamical behaviour variation of the part with respect to the tool position in order to determine optimal cutting conditions during the machining process. This general- ization of the classical lobes diagram leads us to a 3D lobes diagram construction. These computed results are compared with real experiments of down-milling of thin-walled structures

A new multipath mitigation method for GNSS receivers based on antenna array

the potential of small antenna array for multipath mitigation in GNSS systems is considered in this paper. To discriminate the different incoming signals (Line of sight and multipaths), a new implementation of the well known SAGE algorithm is proposed. This allows a significant complexity reduction and it is fully compatible with conventional GNSS receivers. Theoretical study thanks to the Cramer Rao Bound derivation and tracking simulation results (in static and dynamic scenarios) show that the proposed method is a very promising approach for the multipath mitigation problem in GNSS receivers

A new tracking approach for multipath mitigation based on antenna array

In Global Navigation Satellites Systems (GNSS), multipaths (MP) are still one of the major error sources. The additional signal replica due to reflection will introduce a bias in conventional Delay Lock Loops (DLL) which will finally cause a strong positioning error. Several techniques, based on Maximum Likelihood estimation (ML), have been developed for multipaths mitigation/estimation such as the Narrow correlator spacing [1] or the Multipath Estimating Delay-Lock-Loop (MEDLL) [2] algorithm. These techniques try to discriminate the MP from the Line Of Sight Signal (LOSS) on the time and frequency domains and thus, short delay multipaths (<0.1Chips) can not be completely mitigated. Antenna array perform a spatial sampling of the wave front what makes possible the discrimination of the sources on the space domain (azimuth and elevation). As the time-delay domain and space domain can be assumed independent, we can expect to mitigate/estimate very short delay MP by using an antenna array. However, we don't want to increase too much the size, the complexity and the cost of the receivers and thus, we focus our study on small arrays with a small number of antennas: typically a square 2x2 array. Consequently, conventional beamforming (space Fast Fourier Transform) is not directive enough to assure the mitigation of the multipaths, and then this first class of solutions was rejected. In order to improve the resolution, adaptive beamformers have also been tested. However, the LOSS and the MP signal are strongly correlated and thus, classical adaptive algorithms [3] are not able to discriminate the sources. These preliminary studies have shown that the mitigation/estimation of multipaths based on the space domain will exhibit limited performances in presence of close sources. Then, in order to propose robust algorithms, we decided to investigate a space-time-frequency estimation of the sources. Space Alternating Generalized Expectation maximisation (SAGE) algorithm [4], which is a low-complexity generalization of the Expectation Maximisation (EM) algorithm, has been considered. The basic concept of the SAGE algorithm is the hidden data space [4]. Instead of estimating the parameters of all impinging waves in parallel in one iteration step as done by the EM algorithm, the SAGE algorithm estimates the parameters of each signal sequentially. Moreover, SAGE algorithm breaks down the multi-dimensional optimization problem into several smaller problems. In [5], it can be seen that SAGE algorithm is efficient for any multipaths configurations (small relative delays, close DOAs) and space-time-frequency approach is clearly outperforming classical time-frequency approaches. Notwithstanding, SAGE algorithm is a post processing algorithm. Thus, it's necessary to memorise in the receiver the incoming signal in order to apply SAGE estimation. For example, if we want to process 10ms of signal with a 10MHz sampling rate, we need to store a matrix of m*105 with m the number of antennas. In such condition, we can understand than SAGE algorithm is hardly implemented in real time. The challenge is then to find a new type of algorithms that reach the efficiency of the SAGE algorithms, but with a reduced complexity in order to enable real time processing. Furthermore, the implementation should be compatible with conventional GNSS tracking loops (DLL and PLL). To cope with these two constraints, we propose to apply the SAGE algorithm on the post-correlated signal. Indeed, the correlation step can be seen as a compression step and thus, the size of the studied signal is strongly reduced. In such a way, SAGE algorithm is able to provide estimates of the relative delay and Doppler of the received signals with respect to the local replicas. Thus, a post correlation implementation of SAGE can be seen as a discriminator for both the DLL and the PLL

Exports and sectoral financial dependence: evidence on French firms during the great global crisis

The unprecedented drop in international trade during the last quarter of 2008 and the first quarter of 2009 has mainly been analysed at the macroeconomic or sectoral level. However, exporters who are heterogeneous in terms of productivity, size or external financial dependence should be heterogeneously affected by the crisis. This issue is examined in this paper by using data on monthly exports at the product and destination level for some 100,000 individual French exporters, up to 2009M4. We show that the drop in French exports is mainly due to the intensive margin of large exporters. Small and large exporters are evenly affected when sectoral and geographical specialisations are controlled for. Lastly, exporters (small and large) in sectors structurally more dependent on external finance are the most affected by the crisis. JEL Classification: F02, F10, G01financial crisis, firms’ heterogeneity, intensive and extensive margins, international trade