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Optical information security is one of the most important research directions in information science and technology, especially in the copyright protection, confidential information transmission/storage and military remote sensing. Since double random phase encoding technology (DRPE) was proposed, optical image encryption technology has become the main topic of optical information security and it has been developed and studied deeply. Much significant research and investigation on optical image encryption have been presented based on DRPE or further optical operation, such as digital holography, and Fresnel transform, gyrator transform. In this paper, the optical encryption system for gray image and color image is reviewed.

The performance of marine seismic sources (air guns) is of great importance to achieve high resolution images of the seabed and subsurface. In challenging offshore conditions, mechanical or electrical failures within the air gun assembly can cause insufficient performance. Air leaks result in pressure drops and are currently recognised as one of the major issues causing downtime and data degradation, often requiring repeating survey lines. As the number of air guns involved in modern surveys increases, it becomes harder to identify potential air leaks in time, increasing the cost of such failures significantly.To address this issue, this paper presents a monitoring framework for real-time and fast fault detection on individual operating air guns, based on Principal Component Analysis (PCA) and Gaussian Mixture Models (GMMs). For this purpose, we use the output data typically recorded by source controllers employed for air gun synchronisation. The framework exploits the potential of timing sensor measurements not used in seismic post-processing, to develop a robust diagnostic approach. It is successfully benchmarked against data from two types of surveys (dual and triple source). The present approach can be used to identify normal operation and early faults occurring in air guns without requiring a large database of historic data. It can be effectively applied for air gun monitoring during seismic surveying, enhancing online Quality Control (QC).

International audience; This paper is about the collaborative use of a far-infrared spectrum human detector and a visible spectrum human detector; the idea is to make collaborate these two detectors of different nature to automatically adapt the human detection whatever the luminosity changes and whatever the infrared emission changes of the scene. Our collaborative approach of detection handles: 1) gradual luminosity changes due, for instance, to the passage from night to day (and vice-versa), 2) sudden luminosity changes due, for instance, to navigation in a forest (when going through a glade in a forest), 3) infrared emission saturation when the global temperature of the scene is very high and does not permit to distinguish human people in infrared. Our approach of detection permits to detect people 24 hours a day and regardless the weather conditions. Furthermore, the proposed approach is relatively fast: it is practically as fast as using one detector alone whereas two are used in the same time.

Studies on [Pt(II)(di-tert-butylSalophen)] which is thermally stable (Td = 390°C) and displays a deep-red emission (Imax = 660 nm) are presented. Based on efficient energy transfer, this Pt(II) complex was used as a probe for exciton formation in organic light-emitting diodes (OLEDs). Electrical characterisation of host-guest system based devices showed that the presence of the Pt(II) complex within Tris-(8-hydroxyquinoline)aluminium matrix emissive layer, led to electrically active states. Upon electrical driving stress, modulation of the charge transport properties in devices was highlighted. Negative Differential Resistance (NDR) was observed and interpreted in terms of space charge effect. A figure of merit higher than 103 was achieved. Aging investigations showed a reversible electrical degradation and suggested that the Pt(II) complex would stabilise OLEDs performance. Moreover, internal electric field model was proposed to explain the observed polarisation/depolarisation phenomena.

Seismic sources are routinely employed by the oil and gas industry to identify hydrocarbon reserves beneath the seabed, and by researchers to image the sub-seabed for geophysics and to identify geo-hazards such as tsunami-generating areas. For mitigation purposes, it is paramount to identify animals in the water column, but they can be missed by surface observations (if they are diving or in bad weather) or by Passive Acoustic Monitoring (if they remain silent). For operational reasons, it is also important to know about any other sizeable objects below the water surface. Seismic sources emit high-amplitude broadband sounds, typically below 300 Hz, directed toward the seabed. They can also radiate energy up to 20 kHz into the water column, and it can be used as a “source of opportunity”. We use these higher frequencies (between 500 Hz to 20 kHz) to investigate their potential in identifying a variety of mid-water targets, with data from surveys conducted in challenging environments (two in shallow waters, 7–25 m deep, one in deep water, >1,500 m deep) with seismic sources up to 4,500 cubic inches in volume. The shallow-water surveys used a fixed source and freely drifting buoys, whereas the deep-water survey used a towed source with passive acoustic monitoring (PAM) vessel closely follow the seismic vessel to record data. The time spreads of individual shots recorded and the SNR at frequencies between 20 Hz – 20 kHz were compared between the surveys. Based on target strengths of potential targets at different ranges, and on benchmarked models of acoustic propagation, 2-D plots of measured vs. expected levels can be used to detect “hidden” targets of different sizes (from 0.5 to 20 m). The analyses suggest that, at 500 Hz, it is possible to confidently detect mid-water targets within the exclusion zone, and potentially going much further, to as deep as 2 km and as far as 2 km from the source. This has important implications for real-time mitigation and protection of marine mammals, which can be detected even if they are submerged and silent.

The Direct-Lead-Bonding (DLB) interconnection appears to be a promising technology for power-module (PM). Nevertheless, the absence of wire-fuse-effect in case of extreme failure, compared to classical wire-bonding, leads authors to rethink fail-safe and fault-tolerant strategies for critical converter. Therefore, this paper will provide a comparative study between these two designs in terms of failure-mode and post-fault high-current capability.

Marine renewable energy (MRE) is an emerging technology and at present there are an increasing number of MRE prototypes and full-scale devices deployed. The future commercialization in the near future may contribute to the mitigation of carbon emissions and diversify the renewable electricity generation portfolio. Because of the high costs of marine intervention, it is important to establish reliable, remote monitoring techniques. The underwater sound around MRE devices is often monitored for environmental impact assessments. This approach can also be potentially utilized to monitor the engineering health of MRE devices. This is the objective of the project AEMORE (Acoustic Emission technology for environmental and engineering health Monitoring of Offshore Renewable Energy), jointly conducted by the Universities of Exeter and Bath, with J+S Ltd. Acoustic Emission (AE) monitoring is already used for Structural Health Monitoring (SHM) of land-based structures and devices such as wind turbines. AE allows faults and defects to be detected early in a device's lifetime, providing more time to plan and implement necessary maintenance and repair procedures to avoid catastrophic failure. This is highly desirable for MRE structures, which operate in energetic seas with tight weather access windows. This paper explores the remit for AE monitoring to SHM and maintenance planning for MRE devices and demonstrates that this novel application is principally feasible. A brief review of the state of the art of AE for land-based systems aids to illustrate how its techniques can be applied to underwater environments and MRE components. This literature review will inform a classification system that relates likely failure modes to their expected acoustic emissions. The results from previous underwater environmental studies are used to evaluate their potential for SHM of MRE structures. AE environmental data collected during the operation of the Fred Olsen Lifesaver wave energy converter at the Falmouth Bay Test site (FaBTest, SW UK) is used to demonstrate this novel application. The case study provides proof that this concept is valid for underwater SHM of marine renewable structures.

The drive towards sustainable energy has seen rapid development of marine renewable energy devices, and current efforts are focusing on wave and tidal stream energy. The NERC/DEFRA collaboration FLOWBEC-4D (Flow, Water column & Benthic Ecology 4D) is addressing the lack of knowledge of the environmental and ecological effects of installing and operating large arrays of wave and tidal energy devices. The FLOWBEC sonar platform combines a number of instruments to record information at a range of physical and multi-trophic levels. Data are recorded at a resolution of several measurements per second, for durations of 2 weeks to capture an entire spring-neap tidal cycle. An upward-facing multifrequency Simrad EK60 echosounder (38, 120 and 200 kHz) is synchronized with an upward-facing Imagenex 837B Delta T multibeam sonar (120° × 20° beamwidth, 260 kHz) aligned with the tidal flow. An ADV is used for local current measurements and a fluorometer is used to measure chlorophyll (as a proxy for plankton) and turbidity. The platform is self-contained with no cables or anchors, facilitating rapid deployment and recovery in high-energy sites and flexibility in allowing baseline data to be gathered. Five 2-week deployments were completed in 2012 and 2013 at wave and tidal energy sites, both in the presence and absence of renewable energy structures. These surveys were conducted at the European Marine Energy Centre, Orkney, UK. Algorithms for noise removal, target detection and target tracking have been written using a combination of LabVIEW, MATLAB and Echoview. Target morphology, behavior and frequency response are used to aid target classification, with concurrent shore-based seabird observations used to ground truth the acoustic data. Using this information, the depth preference and interactions of birds, fish schools and marine mammals with renewable energy structures can be tracked. Seabird and mammal dive profiles, predator-prey interactions and the effect of hydrodynamic processes during foraging events throughout the water column can also be analyzed. These datasets offer insights into how fish, seabirds and marine mammals successfully forage within dynamic marine habitats and also whether individuals face collision risks with tidal stream turbines. Measurements from the subsea platform are complemented by 3D hydrodynamic model data and concurrent shore-based marine X-band radar. This range of concurrent fine-scale information across physical and trophic levels will improve our understanding of how the fine-scale physical influence of currents, waves and turbulence at tidal and wave energy sites affect the behavior of marine wildlife, and how tidal and wave energy devices might alter the behavior of such wildlife. Together, the results from these deployments increase our environmental understanding of the physical and ecological effects of installing and operating marine renewable energy devices. These results can be used to guide marine spatial planning, device design, licensing and operation, as individual devices are scaled up to arrays and new sites are considered. The combination of our current technology and analytical approach can help to de-risk the licensing process by providing a higher level of certainty about the behavior of a range of mobile marine species in high energy environments. It is likely that this approach will lead to greater mechanistic understanding of how and why mobile predators use these high energy areas for foraging. If a fuller understanding and quantification can be achieved at single demonstration scales, and these are found to be similar, then the predictive power of the outcomes might lead to a wider strategic approach to monitoring and possibly lead to a reduction in the level of monitoring required at each commercial site.

Dual decomposition methods are the current state-of-the-art for training multiclass formulations of Support Vector Machines (SVMs). At every iteration, dual decomposition methods update a small subset of dual variables by solving a restricted optimization problem. In this paper, we propose an exact and efficient method for solving the restricted problem. In our method, the restricted problem is reduced to the well-known problem of Euclidean projection onto the positive simplex, which we can solve exactly in expected O(k) time, where k is the number of classes. We demonstrate that our method empirically achieves state-of-the-art convergence on several large-scale high-dimensional datasets.

International audience; In white light cystoscopy, bladder images are characterized by a strong texture and scene illumination variability which complicates image mosaicing. State-of-art methods exhibit high image registration accuracy at the expense of computational time.We propose an algorithm which selects either a feature based method or an optical flow method according to the image texture ; for fast and accurate bladder wall mosaicing. Total variation (TV) optical flow method (deduced by duality) guarantees robust registration of poorly textured images. Realistic phantom images are registered with subpixel accuracy with a processing speed-up by a factor of 8 and 16 for two reference methods. Patient data results also illustrate the performance of the algorithm.

We study the computational complexity of a general consensus problem for switched systems. A set of n × n stochastic matrices {P 1 , …, P k } is a consensus set if for every switching map τ : ℕ → {1, …, k} and for every initial state x(0), the sequence of states defined by x(t + 1) = P τ(t) x(t) converges to a state whose entries are all identical. We show in this paper that, unless P = NP, the problem of determining if a set of matrices is a consensus set cannot be decided in polynomial-time. As a consequence, unless P = NP, it is not possible to give efficiently checkable necessary and sufficient conditions for consensus. This provides a possible explanation for the absence of such conditions in the current literature on consensus. On the positive side, we provide a simple algorithm which checks whether {P 1 , …, P k } is a consensus set in a number of operations which scales as a doubly exponential in n.

Caliste HD is the last member of the Caliste family of Cd(Zn)Te micro-cameras for space applications. This hybrid component is made of the assembly of one 16 × 16 pixel Cd(Zn)Te detector and eight analog front-end ASIC named IDeF-X HD equipped with 32 spectroscopic channels. The pixels are 625 µm pitch and are surrounded by a 20 µm wide guard ring. The new generation of ASIC has the advantage of having a power consumption 4 times lower as the previous version (0.2 W for the full device) and offers the possibility to extend the dynamic range from 250 keV to 1 MeV. The technology is fully compliant with operation in space (tolerant to radiation, thermal and mechanical constraints). This paper presents the preliminary spectroscopic results obtained with the samples produced so far. At −16°C the sum spectrum built with all single events of the 1 mm-thick Al Schottky detector show an energy resolution of 0.82 keV FWHM at 14 keV and 0.92 keV FWHM at 60 keV. A good uniformity in gain and in noise is measured over the 256 pixels; the low level-threshold is lower than 2 keV for all pixels.

The paper deals with the thermal behavior for paralleled MOSFET's module during accelerated cycling burn-in test in harsh ambient and current conditions. The aim of the work is to optimize the key parameters acting on the self-heating in order to avoid undesirable failures resulting from overheating. An electro-thermal model is developed to simulate the device temperature during the test. Well calibrated to the experimental data for R on and avalanche phases, our model allowed realistic thermal prediction. The impact of gate bias, pulse time, as well as disparities of breakdown voltage between the FETs was analyzed and the test conditions were optimized.

We study a simple continuous-time multi-agent system related to Krause's model of opinion dynamics: each agent holds a real value, and this value is continuously attracted by every other value differing from it by less than 1, with an intensity proportional to the difference.

Traditionally, HMM-based approaches to online Kanji handwriting recognition have relied on a hand-made dictionary, mapping characters to primitives such as strokes or substrokes. We present an unsupervised way to learn a stroke tagger from data, which we eventually use to automatically generate such a dictionary. In addition to not requiring a prior hand-made dictionary, our approach can improve the recognition accuracy by exploiting unlabeled data when the amount of labeled data is limited.

This paper presents a general class of gossip-based averaging algorithms, which are inspired from Uniform Gossip [1]. While Uniform Gossip works synchronously on complete graphs, weighted gossip algorithms allow asynchronous rounds and converge on any connected, directed or undirected graph. Unlike most previous gossip algorithms [2]–[6], Weighted Gossip admits stochastic update matrices which need not be doubly stochastic. Double-stochasticity being very restrictive in a distributed setting [7], this novel degree of freedom is essential and it opens the perspective of designing a large number of new gossip-based algorithms. To give an example, we present one of these algorithms, which we call One-Way Averaging. It is based on random geographic routing, just like Path Averaging [5], except that routes are one way instead of round trip. Hence in this example, getting rid of double stochasticity allows us to add robustness to Path Averaging.

Today, the demand for uninterrupted power supply for Telecommunication and Internet services increases drastically. Following the same trend, cooling demand explodes. Supplying sufficient power with extremely high reliability becomes even more challenging.

The MICE experiment is being commissioned at RAL to study the feasibility of a Neutrino Factory: muons are cooled by a dedicated system based on radiofrequency while the particle ID is performed by a KLOE-light detector followed by EMR (Electron Muon Ranger), a fully active tracker-calorimeter positioned at the end of the beamline. EMR consists of 48 planes of 59 1.1 m long scintillator bars with a triangular section. The light in each bar is collected by one 1.2 mm WLS fiber and is readout by a single PMT (Philips XP2972) on one side to provide the information on the charge deposit in the plane and a 64 channel multianode PMT (Hamamatsu) on the other one to digitize the trigger output of each single bar. The single PMT is readout by a CAEN V1731 Waveform Digitizer, while the frontend electronics to treat the multianode signals is organized in two near-detector boards: a FEB (FrontEnd Board) and a buffer board. The FEB hosts a dedicated socket for the MAPMT, the frontend ASIC and two control FPGAs (Altera CYCLONE II) while the buffer board stores the data during the spill. The PMT is connected to the FEB through a flexible multilayer kapton cable. The 64 MAPMT signals are pre-amplified, shaped and discriminated by the MAROC-2 (Omega, LAL), a low noise single power rail ASIC with multiplexed analog and parallel digital outputs. The experiment foresees one event every 5 µs during a spill of 1 ms every 1 s. The 64 discriminated signals are sampled with a 400 MHz clock and in presence of the experiment trigger, the above threshold bars numbers are stored together with a timestamp in the buffer board to be sent to the VME DAQ system during the interspill. The communication is based on the TLK1501 Gigabit link: 6 buffer boards are daisy chained for a total of 8 VME control boards. A configuration board completes the DAQ and is responsible of the configuration of the frontend and of the distribution of the trigger and synchronization clock signals. This paper presents the tests of the electronics and its performance both with a small EMR prototype with square bars and in the test system for the mass production of the final modules.

The capability of 20V trench power MOSFETs to withstand high current repetitive avalanche events has been investigated. Automotive standard 20V BVdss rated MOSFETs with active area of 21mm2 have been successfully subjected with up to 300 million 59µs duration avalanche events at peak currents up to 135A whilst held at an average junction temperature of 150°C. The effect of cell pitch on parameter shifts has been investigated by applying avalanche currents up to 200A (9.5A/mm2). It has been found that reduced cell pitch increases the stability of threshold voltage and on-state resistance whilst suffering from increased drain-source leakage.

Odontocetes use active sonar for echolocation, navigation and socialisation. Their sonar is characterised by narrow transmission and reception directivity patterns, over a variety of ranges and frequencies. Typical echolocation clicks of bottlenose dolphins (Tursiops truncatus) last between 50–200 µs, with a broad frequency range of ∼100–170 kHz depending on circumstances. These characteristics are very attractive for the design of bio-inspired sonars, but the actual mechanisms of sound reception are not well understood. Physiological and behavioural evidence suggests that dolphins hear the echoes of their high-frequency clicks through their lower jaws. The angular precision predicted by this theory is however much less than dolphins have been observed to display. A recent hypothesis is that the teeth also play a part in sound reception, acting as a passive beam-forming structure. This paper presents 2-D models of acoustic propagation in a dolphin jaw, based on real measurements, and shows the importance of multiple scattering between teeth, potential masking effects, and the match between theoretical directivity and that observed in the field. We use these results to look at the implications for realistic biosonar design.

Researchers have been unable to predict the large-scale features of aggregate social networks. We analyze the anonymous communications patterns of 2.5 million customers of a Belgian mobile phone operator. With these communications, we construct the social network of the customers, that we call microscopic network. Grouping customers together by billing address city, we obtain a social network of cities, which we call the macroscopic network, is built from 571 towns and cities in Belgium. Using the mobile phone network, we are able to show that the macroscopic network has both a degree distribution and edge weight distribution with lognormal characteristics. We find that inter-city communications can be characterized by a gravity model: the intensity of communication between two cities is proportional to the product of the two populations divided by the square of the distance between them. Furthermore, we observe that intra-urban communications scale superlinearly with city population.

We consider a simple dynamical model of agents distributed on the real line. The agents have a limited vision range and they synchronously update their positions by moving to the average position of the agents that are within their vision range. This dynamical model was initially introduced in the social science literature as a model of opinion dynamics and is known there as the “Krause model”. It gives rise to surprising and partly unexplained dynamics that we describe and discuss in this paper. One of the central observations is the 2R-conjecture: when sufficiently many agents are distributed on the real line and have their position evolve according to the above dynamics, the agents eventually merge into clusters that have inter-cluster distances roughly equal to 2R (R is the vision range of the agents). This observation is supported by extensive numerical evidence and is robust under various modifications of the model. It is easy to see that clusters need to be separated by at least R. On the other hand, the unproved bound 2R that is observed in practice can probably only be obtained by taking into account the specifics of the model's dynamics. In this paper, we study these dynamics and consider a number of issues related to the 2R conjecture that explicitly uses the model's dynamics. In particular, we provide bounds for the vision range that lead all agents to merge into only one cluster, we analyze the relations between agents on finite and infinite intervals, and we introduce a notion of equilibrium stability for which clusters of equal weights need to be separated by at least 2R to be stable. These results, however, do not prove the conjecture. To understand the system behavior for a large agent density, we also consider a version of the model that involves a continuum of agents. We study properties of this continuous model and of its equilibria, and investigate the connections between the discrete and continuous versions.

Motivated by [1], [2] and [3], we consider here formations of autonomous agents in a 2-dimensional space. Each agent tries to maintain its distances toward a pre-specified group of other agents constant, and the problem is to determine if one can guarantee that the structure of the formation will persist, i.e., if the distance between any pair of agents will remain constant. A natural way to represent such a formation is to use a directed graph. We provide a theoretical framework for this problem, and give a formal definition of persistent graphs (a graph is persistent if almost all corresponding agents formations persist). Note that although persistence is related to rigidity (concerning which much is known [4]), these are two distinct notions. We then derive various properties of persistent graphs, and give a combinatorial criterion to decide persistence. We also define the notion of minimal persistence (persistence with least number of edges), and eventually, we apply these notion to the interesting special case of cycle-free graphs.

We discuss an old distributed algorithm for reaching consensus that has received a fair amount of recent attention. In this algorithm, a number of agents exchange their values asynchronously and form weighted averages with (possibly outdated) values possessed by their neighbors. We overview existing convergence results, and establish some new ones, for the case of unbounded intercommunication intervals.

The evolution of the CdTe detector properties (leakage current, capacitance, and geometry) requires a continuous improvement of the electronic frond-end in terms of geometry, noise, and power consumption. This is why our group is working on a new modular spectro-imaging system based on CdTe detectors coupled to dedicated full custom readout ASICs, named IDeF-X for imaging detector front-end. We present the most recent version of IDeF-X which is a sixteen-channel analogue readout chip for hard X-ray spectroscopy. It has been processed with the standard AMS 0.35 /spl mu/m CMOS technology. Each channel consists of a charge sensitive preamplifier, a pole zero cancellation stage, a variable peaking time filter and an output buffer. IDeF-X is designed to be DC coupled to detectors having a low dark current at room temperature and is optimized for input capacitance ranging from 2 to 5 pF.