Criminal justice in France after September 11: Has the balance between liberty and security been disturbed?

This is the abstract of the conference paper delivered at the Ninth Biennial International Conference - Societies in Transition: Balancing Security, Social Justice and Tradition in 2010

Stochastic effects on the dynamics of a resonant MEMS magnetometer: a Monte Carlo investigation

In the design of Lorentz force MEMS magnetometers, the coupled thermo-electro-magneto-mechanical fields governing the dynamics of the relevant compliant structures can be appropriately exploited to enhance their performances. In recent works, we showed that reduced-order models for the dynamics of the said movable structures can be recast in the form of the Duffing equation, where nonlinear terms arise from the multi-physics governing the problem. As stochastic effects may play a role due to the micrometric dimensions of the device, an investigation of the link between the statistics of sensor imperfections and output is here carried out. The said imperfections at the microscopic length-scale are modeled in terms of: overetch thickness, assumed to feature a uniform distribution in a proper interval matching available experimental data; and elastic properties of the vibrating polycrystalline silicon film, as obtained through a numerical homogenization procedure over a representative film volume. To get insights into the effects of the parameters governing the nonlinear dynamics of the resonant structure, a Monte Carlo analysis is adopted

The Entropy Conundrum: A Solution Proposal

In 2004, physicist Mark Newman, along with biologist Michael Lachmann and computer scientist Cristopher Moore, showed that if electromagnetic radiation is used as a transmission medium, the most information-efficient format for a given 1-D signal is indistinguishable from blackbody radiation. Since many natural processes maximize the Gibbs-Boltzmann entropy, they should give rise to spectra indistinguishable from optimally efficient transmission. In 2008, computer scientist C.S. Calude and physicist K. Svozil proved that "Quantum Randomness" is not Turing computable. In 2013, academic scientist R.A. Fiorini confirmed Newman, Lachmann and Moore's result, creating analogous example for 2-D signal (image), as an application of CICT in pattern recognition and image analysis. Paradoxically if you don’t know the code used for the message you can’t tell the difference between an information-rich message and a random jumble of letters. This is an entropy conundrum to solve. Even the most sophisticated instrumentation system is completely unable to reliably discriminate so called "random noise" from any combinatorically optimized encoded message, which CICT called "deterministic noise". Entropy fundamental concept crosses so many scientific and research areas, but, unfortunately, even across so many different disciplines, scientists have not yet worked out a definitive solution to the fundamental problem of the logical relationship between human experience and knowledge extraction. So, both classic concept of entropy and system random noise should be revisited deeply at theoretical and operational level. A convenient CICT solution proposal will be presented

Cosmic rays: direct measurements

This paper is based on the rapporteur talk given at the 34$^{th}$ International Cosmic Ray Conference (ICRC), on August 6$^{th}$, 2015. The purpose of the talk and paper is to provide a summary of the most recent results from balloon-borne and space-based experiments presented at the conference, and give an overview of the future missions and developments foreseen in this field.Comment: Write-up of the rapporteur talk given at the 34th International Cosmic Ray Conference, 30 July-6 August, 2015, The Hague, The Netherlands. 24 pages , 11 figure

Hybrid reduced-order modeling and particle-Kalman filtering for the health monitoring of flexible structures

MEMS-based, surface-mounted structural health monitoring systems were recently proposed to locate possible damage events in lightweight composite structures. To track the structural dynamics induced by the external actions and identify in real-time the inception of drifts from the virgin, or undamaged state, recursive Bayesian filters are here adopted. As the main drawback of any on-line identification method might be linked to the excessive computational costs, two solutions are jointly enforced: an order-reduction of the numerical model used to track the structural behavior, through the proper orthogonal decomposition in its snapshot-based version; an improved particle filtering strategy, which features an extended Kalman updating of each evolving particle before the resampling stage. While the former method alone can reduce the number of effective degrees-of-freedom of the structure to a few only (depending on the excitation), the latter allows to track the evolution of damage and also locate it thanks to an intricate formulation. To assess the proposed procedure, the case of a thin plate subject to bending is investigated; it is shown that, when the procedure is fed by measurements gathered by a network of inertial MEMS sensors appropriately deployed over the plate, damage is efficiently and accurately estimated and located

Comparison of distance metrics for hierarchical data in medical databases

Distance metrics are broadly used in different research areas and applications, such as bio- informatics, data mining and many other fields. However, there are some metrics, like pq-gram and Edit Distance used specifically for data with a hierarchical structure. Other metrics used for non- hierarchical data are the geometric and Hamming metrics. We have applied these metrics to The Health Improvement Network (THIN) database which has some hierarchical data. The THIN data has to be converted into a tree-like structure for the first group of metrics. For the second group of metrics, the data are converted into a frequency table or matrix, then for all metrics, all distances are found and normalised. Based on this particular data set, our research question: which of these metrics is useful for THIN data? This paper compares the metrics, particularly the pqgram metric on finding the similarities of patients’ data. It also investigates the similar patients who have the same close distances as well as the metrics suitability for clustering the whole patient population. Our results show that the two groups of metrics perform differently as they represent different structures of the data. Nevertheless, all the metrics could represent some similar data of patients as well as discriminate sufficiently well in clustering the patient population using k-means clustering algorithm