COSIMA calibration for the detection and characterization of the cometary solid organic matter

On the orbiter of the Rosetta spacecraft, the Cometary Secondary Ion Mass Analyser (COSIMA) will provide new in situ insights about the chemical composition of cometary grains all along 67P/Churyumov–Gerasimenko (67P/CG) journey until the end of December 2015 nominally. The aim of this paper is to present the pre-calibration which has already been performed as well as the different methods which have been developed in order to facilitate the interpretation of the COSIMA mass spectra and more especially of their organic content. The first step was to establish a mass spectra library in positive and negative ion mode of targeted molecules and to determine the specific features of each compound and chemical family analyzed. As the exact nature of the refractory cometary organic matter is nowadays unknown, this library is obviously not exhaustive. Therefore this library has also been the starting point for the research of indicators, which enable to highlight the presence of compounds containing specific atom or structure. These indicators correspond to the intensity ratio of specific peaks in the mass spectrum. They have allowed us to identify sample containing nitrogen atom, aliphatic chains or those containing polyaromatic hydrocarbons. From these indicators, a preliminary calibration line, from which the N/C ratio could be derived, has also been established. The research of specific mass difference could also be helpful to identify peaks related to quasi-molecular ions in an unknown mass spectrum. The Bayesian Positive Source Separation (BPSS) technique will also be very helpful for data analysis. This work is the starting point for the analysis of the cometary refractory organic matter. Nevertheless, calibration work will continue in order to reach the best possible interpretation of the COSIMA observations.

A Light-Weight On-Chip Monitoring Network for Dynamic Adaptation and Calibration

Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.

A method for Kinematic Calibration of a Parallel Robot by using one camera in hand and a spherical object

The main purpose of robot calibration is the correction of the possible errors in the robot parameters. This paper presents a method for a kinematic calibration of a parallel robot that is equipped with one camera in hand. In order to preserve the mechanical configuration of the robot, the camera is utilized to acquire incremental positions of the end effector from a spherical object that is fixed in the word reference frame. The positions of the end effector are related to incremental positions of resolvers of the motors of the robot, and a kinematic model of the robot is used to find a new group of parameters which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and improving spatial measurements. Finally, the robotic system is designed to carry out tracking tasks and the calibration of the robot is validated by means of integrating the errors of the visual controller.

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.