LFI 30 and 44 GHz receivers Back-End Modules

The 30 and 44 GHz Back End Modules (BEM) for the Planck Low Frequency Instrument are broadband receivers (20% relative bandwidth) working at room temperature. The signals coming from the Front End Module are amplified, band pass filtered and finally converted to DC by a detector diode. Each receiver has two identical branches following the differential scheme of the Planck radiometers. The BEM design is based on MMIC Low Noise Amplifiers using GaAs P-HEMT devices, microstrip filters and Schottky diode detectors. Their manufacturing development has included elegant breadboard prototypes and finally qualification and flight model units. Electrical, mechanical and environmental tests were carried out for the characterization and verification of the manufactured BEMs. A description of the 30 and 44 GHz Back End Modules of Planck-LFI radiometers is given, with details of the tests done to determine their electrical and environmental performances. The electrical performances of the 30 and 44 GHz Back End Modules: frequency response, effective bandwidth, equivalent noise temperature, 1/f noise and linearity are presented

Synchronization of stochastic hybrid oscillators driven by a common switching environment

Many systems in biology, physics and chemistry can be modeled through ordinary differential equations, which are piecewise smooth, but switch between different states according to a Markov jump process. In the fast switching limit, the dynamics converges to a deterministic ODE. In this paper we suppose that this limit ODE supports a stable limit cycle. We demonstrate that a set of such oscillators can synchronize when they are uncoupled, but they share the same switching Markov jump process. The latter is taken to represent the effect of a common randomly switching environment. We determine the leading order of the Lyapunov coefficient governing the rate of decay of the phase difference in the fast switching limit. The analysis bears some similarities to the classical analysis of synchronization of stochastic oscillators subject to common white noise. However the discrete nature of the Markov jump process raises some difficulties: in fact we find that the Lyapunov coefficient from the quasi-steady-state approximation differs from the Lyapunov coefficient one obtains from a second order perturbation expansion in the waiting time between jumps. Finally, we demonstrate synchronization numerically in the radial isochron clock model and show that the latter Lyapinov exponent is more accurate

How is Gaze Influenced by Image Transformations? Dataset and Model

Data size is the bottleneck for developing deep saliency models, because collecting eye-movement data is very time consuming and expensive. Most of current studies on human attention and saliency modeling have used high quality stereotype stimuli. In real world, however, captured images undergo various types of transformations. Can we use these transformations to augment existing saliency datasets? Here, we first create a novel saliency dataset including fixations of 10 observers over 1900 images degraded by 19 types of transformations. Second, by analyzing eye movements, we find that observers look at different locations over transformed versus original images. Third, we utilize the new data over transformed images, called data augmentation transformation (DAT), to train deep saliency models. We find that label preserving DATs with negligible impact on human gaze boost saliency prediction, whereas some other DATs that severely impact human gaze degrade the performance. These label preserving valid augmentation transformations provide a solution to enlarge existing saliency datasets. Finally, we introduce a novel saliency model based on generative adversarial network (dubbed GazeGAN). A modified UNet is proposed as the generator of the GazeGAN, which combines classic skip connections with a novel center-surround connection (CSC), in order to leverage multi level features. We also propose a histogram loss based on Alternative Chi Square Distance (ACS HistLoss) to refine the saliency map in terms of luminance distribution. Extensive experiments and comparisons over 3 datasets indicate that GazeGAN achieves the best performance in terms of popular saliency evaluation metrics, and is more robust to various perturbations. Our code and data are available at: https://github.com/CZHQuality/Sal-CFS-GAN

A Communication Monitor for Wireless Sensor Networks Based on Software Defined Radio

Link quality estimation of reliability-crucial wireless sensor networks (WSNs) is often limited by the observability and testability of single-chip radio transceivers. The estimation is often based on collection of packer-level statistics, including packet reception rate, or vendor-specific registers, such as CC2420's Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI). The speed or accuracy of such metrics limits the performance of reliability mechanisms built in wireless sensor networks. To improve link quality estimation in WSNs, we designed a powerful wireless communication monitor based on Software Defined Radio (SDR). We studied the relations between three implemented link quality metrics and packet reception rate under different channel conditions. Based on a comparison of the metrics' relative advantages, we proposed using a combination of them for fast and accurate estimation of a sensor network link

Photonic microwave harmonic generator driven by an optoelectronic ring oscillator

We describe a new architecture to generate microwave signals by optical means. Our system combines the advantages of two techniques: frequency multipliers and loop oscillators. A frequency multiplier allows to obtain high frequencies using frequency harmonic generation, nevertheless, a very good quality reference signal is necessary to drive the system. In our setup, this reference signal is obtained using a loop oscillator. Optoelectronic loop oscillators generate signals with good performance in terms of phase noise and linewidth. We present the theory related to those techniques and the experimental data obtained

Projection image-to-image translation in hybrid X-ray/MR imaging

The potential benefit of hybrid X-ray and MR imaging in the interventional environment is large due to the combination of fast imaging with high contrast variety. However, a vast amount of existing image enhancement methods requires the image information of both modalities to be present in the same domain. To unlock this potential, we present a solution to image-to-image translation from MR projections to corresponding X-ray projection images. The approach is based on a state-of-the-art image generator network that is modified to fit the specific application. Furthermore, we propose the inclusion of a gradient map in the loss function to allow the network to emphasize high-frequency details in image generation. Our approach is capable of creating X-ray projection images with natural appearance. Additionally, our extensions show clear improvement compared to the baseline method.Comment: In proceedings of SPIE Medical Imaging 201