Self-Organized Monitoring in Ad-Hoc Networks

We propose in this paper a self-organized monitoring architecture for mobile ad-hoc networks based on a selective scheme where subsets of nodes are managed. These nodes are determined based on their network behavior in order to favor subsets of well-connected nodes. The key idea is to relax the requirements of the management plane, and to use these manageable subsets to monitor the performance of the overall network. We therefore propose a new performance metric to be monitored, in order to estimate the capability of ad-hoc nodes to communicate end-to-end in the network. Extensive simulations show how different parameters affect this metric.     

Time-varying analysis methods and models for the respiratory and cardiac system coupling in graded exercise

The analysis of heart period series is a difficult task especially under graded exercise conditions. From all the information present in these series, we are the most interested in the coupling between respiratory and cardiac systems, known as respiratory sinus arrythmia. In this paper, we show that precise patterns concerning the respiratory frequency can be extracted from the heart period series. An evolutive model is introduced in order to achieve tracking of the main respiratory-related frequencies and their time-varying amplitudes. Since respiration acts to modulate the sinus rhythm, we relate the frequencies and amplitudes to this modulation by analyzing in detail its nonlinear transformation giving the heart period signal. This analysis is performed assuming stationary conditions but also in the realistic case where the mean heart period, the amplitude, and the frequency of the respiration are time-varying. Since this paper is devoted to the theoretical and complete presentation of the method used in a physiological study published elsewhere, the capabilities of our method will be illustrated in a realistic simulated case.     

选择正确的PFC解决方案

本文用一种创新的方法提出了四种功率因数校正(PFC)电路设计。两种临界导通模式(CRM)升压．一种连续导通模式(CCM)升压和一种CCM单段回扫，并且推荐了基于功率要求、效率、失真程度、电路板空间和成本限制的解决方案。     

A pseudojoint estimation of time delay and scale factor for M-wave analysis

A pseudojoint estimation of time scale and time delay between an unknown deterministic transient type signal and a reference signal is proposed. The method is based on the separation between the estimations of the two dependent parameters. The time autocorrelation function (TACF) preserves the time scale and is invariant with respect to the time delay between the signals. The time scale factor can, thus, be estimated independently from time delay using the TACFs of the two signals. After estimating the time scale factor, the signal can be scaled by the estimated amount. The time delay is then estimated without bias due to the time scale factor. To obtain high resolution joint estimates, the time scale factor is estimated in the scale domain from the scale transforms of the TACFs of the two signals. The proposed method has low computational cost. Moreover, the results on synthetic signals show good performance of the method with respect to the Cramér-Rao Lower Bound and the joint Maximum Likelihood Estimation. A possible application of the technique to the analysis of electromyogram (EMG) signals detected during electrically elicited contractions is also presented. In a few representative cases, it is shown that the time scale estimate reveals myoelectric manifestations of muscle fatigue and is less affected by M-wave truncation than spectral EMG attributes.     

A Photoaddressable Liquid Crystalline Phase Transition in Graphene Oxide Nanocomposites

The multifunctionality of graphene has the potential to unlock important developments in nanocomposite science. However, the manipulation of graphene without interfering with its unique properties and while controlling its spatial organization remains challenging. Here, the formation of a photoaddressable liquid crystalline (LC) solution through the stabilization of graphene oxide (GO) with photocleavable brushes is described. The LC behavior leads to the thermodynamic entrapment of GO into low aspect ratio domains that fail to display the properties typically predicted for graphene nanocomposites. The morphology and structural and electronic performance of these nanocomposites are regenerated through the brush cleavage, which controls the phase transition of the LC phase. These results show that kinetic control of graphene assembly can be an attractive tool toward the dynamic regulation of processable sol states and structured percolated networks for rational composite manufacturing.     

B-spline explicit active surfaces: an efficient framework for real-time 3-D region-based segmentation

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.     

A cross validation study of deep brain stimulation targeting: from experts to atlas-based, segmentation-based and automatic registration algorithms

Validation of image registration algorithms is a difficult task and open-ended problem, usually application-dependent. In this paper, we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and essential tremor. DBS involves implantation of an electrode deep inside the brain to electrically stimulate specific areas shutting down the disease's symptoms. The subthalamic nucleus (STN) has turned out to be the optimal target for this kind of surgery. Unfortunately, the STN is in general not clearly distinguishable in common medical imaging modalities. Usual techniques to infer its location are the use of anatomical atlases and visible surrounding landmarks. Surgeons have to adjust the electrode intraoperatively using electrophysiological recordings and macrostimulation tests. We constructed a ground truth derived from specific patients whose STNs are clearly visible on magnetic resonance (MR) T2-weighted images. A patient is chosen as atlas both for the right and left sides. Then, by registering each patient with the atlas using different methods, several estimations of the STN location are obtained. Two studies are driven using our proposed validation scheme. First, a comparison between different atlas-based and nonrigid registration algorithms with a evaluation of their performance and usability to locate the STN automatically. Second, a study of which visible surrounding structures influence the STN location. The two studies are cross validated between them and against expert's variability. Using this scheme, we evaluated the expert's ability against the estimation error provided by the tested algorithms and we demonstrated that automatic STN targeting is possible and as accurate as the expert-driven techniques currently used. We also show which structures have to be taken into account to accurately estimate the STN location.     

Ligand‐Free Synthesis of Aluminum‐Doped Zinc Oxide Nanocrystals and their Use as Optical Spacers in Color‐Tuned Highly Efficient Organic Solar Cells

The color of polymer solar cells using an opaque electrode is given by the reflected light, which depends on the composition and thickness of each layer of the device. Metal‐oxide‐based optical spacers are intensively studied in polymer solar cells aiming to optimize the light absorption. However, the low conductivity of materials such as ZnO and TiO₂ limits the thickness of such optical spacers to tenths of nanometers. A novel synthesis route of cluster‐free Al‐doped ZnO (AZO) nanocrystals (NCs) is presented for solution processing of highly conductive layers without the need of temperature annealing, including thick optical spacers on top of polymer blends. The processing of 80 nm thick optical spacers based on AZO nanocrystal solutions on top of 200 nm thick polymer blend layer is demonstrated leading to improved photocurrent density of 17% compared to solar cells using standard active layers of 90 nm in combination with thin ZnO‐based optical spacers. These AZO NCs also open new opportunities for the processing of high‐efficiency color tuned solar cells. For the first time, it is shown that applying solution‐processed thick optical spacer with polymer blends of different thicknesses can process solar cells of similar efficiency over 7% but of different colors.