Fast template tracking in video sequences

Tracking of poorly defined, rotating and/or distorted objects in a video sequence poses significant problems especially in medical diagnostics including ultrasound (sonographic) video used for examination and diagnosis of internal movement of tissue or muscle and nerve action. Cross-correlation techniques have been successful in retrieving dynamic information directly from ultrasound video data. We outline a fast implementation of tracking based on normalized cross-correlation using an adaptive template and present results from our application, developed in MATLAB?, which successfully tracks arbitrarily selected objects in deformed or severely compromised images. Common ultrasound image evaluation is qualitative but there is need to retrieve quantitative dynamic information such as the trajectory or velocity of selected areas. Our approach uses normalized two-dimensional cross-correlation to find the position of an initially selected template enclosing the feature of interest and map its trajectory frame-by-frame to produce displacement and velocity plots. We illustrate operation of the application using routine ultrasound data and demonstrate its performance using test video of objects rotating full circle and rolling down a ramp. We analyse errors associated with sampling to compare performance of our implementation with a more rigorous but tedious and computationally expensive correlation of a resampled, rotated, and shifted template.     

Dielectrophoresis‐Assisted Integration of 1024 Carbon Nanotube Sensors into a CMOS Microsystem

Carbon‐nanotube (CNT)‐based sensors offer the potential to detect single‐molecule events and picomolar analyte concentrations. An important step toward applications of such nanosensors is their integration in large arrays. The availability of large arrays would enable multiplexed and parallel sensing, and the simultaneously obtained sensor signals would facilitate statistical analysis. A reliable method to fabricate an array of 1024 CNT‐based sensors on a fully processed complementary‐metal‐oxide‐semiconductor microsystem is presented. A high‐yield process for the deposition of CNTs from a suspension by means of liquid‐coupled floating‐electrode dielectrophoresis (DEP), which yielded 80% of the sensor devices featuring between one and five CNTs, is developed. The mechanism of floating‐electrode DEP on full arrays and individual devices to understand its self‐limiting behavior is studied. The resistance distributions across the array of CNT devices with respect to different DEP parameters are characterized. The CNT devices are then operated as liquid‐gated CNT field‐effect‐transistors (LG‐CNTFET) in liquid environment. Current dependency to the gate voltage of up to two orders of magnitude is recorded. Finally, the sensors are validated by studying the pH dependency of the LG‐CNTFET conductance and it is demonstrated that 73% of the CNT sensors of a given microsystem show a resistance decrease upon increasing the pH value.     

Système de protection contre les erreurs pour la liaison ionosphérique

This paper presents an error correcting system designed for a 1 200 bit/s self adaptative modem operating on the HF channel. An analysis of error statistics has been made simulating a specific link whose characteristics had been measured beforehand by a HF backscattering probe. The coding system which has been chosen consists of a cascade of two cyclic codes. One corrects long bursts of errors (Kasami code), the other corrects single errors and small bursts (Reed Solomon code). Both codes are interleaved. The overall rate is 50 %. An error correction simulation has shown that in most of the cases studied, with a ber of 10^?4 a coding gain of at least 10^?2 has been achieved.     

L’optimisation des réseaux cellulaires assistée par ordinateur: le logiciel RNO (Radio Network Optimisation)

Quality of service has become today a major concern for operators of mobile communication networks. The massive development of networks and strong competition between operators has lead to the necessary and daily follow-up of network quality of service, a key factor for its subscriber’s fidelity. This article aims at presenting the optimization methodology and proposes its illustration with a case of RNO (Radio Network Optimisation) software usage, one of the Alcatel optimization toolchain component. After a short presentation of cellular network, the optimization basic principles are described. RNO software and its main functionnalities are then detailed before a last part dedicated to a real case of optimization done with RNO software.     

Microtentacle Actuators Based on Shape Memory Alloy Smart Soft Composite

Recent advances in miniature robotics have brought promising improvements in performance by leveraging the latest developments in soft materials, new fabrication schemes, and continuum actuation. Such devices can be used for applications that need delicate manipulation such as microsurgery or investigation of small‐scale biological samples. The shape memory effect of certain alloys is one of the promising actuation mechanisms at small scales because of its high work density and simple actuation mechanism. However, for sub‐millimeter devices, it is difficult to achieve complex and large displacement with shape memory alloy actuators because of the limitation in the fabrication process. Herein, a fabrication scheme for miniaturized smart soft composite actuator is proposed by utilizing two‐photon polymerization. The morphing modes are varied by changing the direction of the scaffold lamination. In addition, the actuation is controlled via local resistive heating of a carbon nanotube layer deposited inside of the actuators. The proposed design can generate a 390 µN force and achieve a bending angle up to 80°. Applications of the actuators are demonstrated by grasping small and delicate objects with single and two finger devices.     

Rate of evolution of the specific surface area of surface snow layers

The snowpack can impact atmospheric chemistry by exchanging adsorbed or dissolved gases with the atmosphere. Modeling this impact requires the knowledge of the specific surface area (SSA) of snow and its variations with time. We have therefore measured the evolution of the SSA of eight recent surface snow layers in the Arctic and the French Alps, using CH4 adsorption at liquid nitrogen temperature (77 K). The SSA of fresh snow layers was found to decrease with time, from initial values in the range 613-1540 cm2/g to values as low as 257 cm2/g after 6 days. This is explained by snow metamorphism, which causes modifications in crystal shapes, here essentially crystal rounding and the disappearance of microstructures. A parametrization of the rate of SSA decrease is proposed. We fit the SSA decrease to an exponential law and find that the time constant alpha(exp) (day(-1)) depends on temperature according to alpha(exp) = 76.6 exp (-1708/7), with Tin kelvin. Our parametrization predicts that the SSA of a snow layer evolving at -40 degrees C will decrease by a factor of 2 after 14 days, while a similar decrease at -1 degrees C will only require 5 days. Wind was found to increase the rate of SSA decrease, but insufficient data did not allow a parametrization of this effect.