Monitoring of polyethylene wear in nonmetal-backed acetubular cups by digitized anteroposterior pelvic radiography

The aim of this study was to assess polyethylene wear in a total hip prosthesis by digitized radiography of the whole pelvis in the anteroposterior (AP) plane. The three-dimensional (3-D) pose of the nonmetal-backed acetubular cup, materialized by its metal ring and the femoral head made of metal or ceramic, was estimated using iterative algebraic algorithms with inner bias correction and bootstrapping for variance reduction. Points of interest were obtained by maximizing the correlation between sampled density profiles and 3-D geometric models degraded by the modulation transfer function (MTF) of the radiographic system and the film scanner. The error in the maximal correlation estimate were inferred from noise power spectra (NPS) and allowed the calculation of the point covariance matrix. Both NPS and MTF were modeled for each stage and estimated using least-square fitting of the overall NPS model to the autospectral density function calculated in stationary regions. Comparison of the radiographic time series was made possible by the high accuracy level and 3-D matching from the cup orientation. The feasibility of the full 3-D measurement, the assumption of negligible lateral wear and its influence on AP wear are discussed on simulated and real radiographic data.     

Micro-patterning of LiPON and lithium iron phosphate material deposited onto silicon nanopillars array for lithium ion solid state 3D micro-battery

The paper deals with the methodology used to form regular pattern of sputtered thin films LiPON/LiFePO₄ material acting respectively as the solid electrolyte and the positive electrode of the lithium ion solid state 3D micro-battery. The micromachining of the silicon periodic nanopillars array (negative electrode of the micro-battery) is also reported. The proposed study clearly demonstrates a breakthrough technology in the field of lithium ion micro-battery as the ecologically friendly LiFePO₄ material has never been evaluated as the positive electrode.     

Gallium nitride MEMS resonators: how residual stress impacts design and performances

Microsystem Technologies - Starting from Gallium Nitride epitaxially grown on silicon, pre-stressed micro-resonators with integrated piezoelectric transducers have been designed, fabricated, and...     

Effect of Averaging Operators in Fuzzy Optimization of Reservoir Operation

Fuzzy multiobjective decision makingmodels generally rely on the aggregation of theobjectives to form a decision function. The generalizedaveraging operator is usually adopted for aggregatingmultiple and unequal objectives because it allows trade-off amongst the objectives, and has been shown to besuitable to model human decision making behavior. In thefield of water resource management, most of the decision-making problems involving the generalized averagingoperator implicitly assume the decision maker (DM) israther optimistic. The analysis of the DM's behaviorduring the aggregation process and its impact on theperformance of the system, has therefore never beenaddressed by many researchers and decision makers. Theaim of this paper is to investigate the relationshipbetween decision makers' index of optimism and the long-term performance of a reservoir resource. Morespecifically, the generalized averaging operator, whoseparameter can be interpreted as the DM's index ofoptimism, is imbedded into a fuzzy stochastic dynamicprogram (FSDP). This approach is developed andimplemented to derive optimal operating policies for thehydroelectric complex of the Uruguay River basin inSouthern Brazil. FSDP-derived policies with differentindices of optimism are then compared with simulation. Weshow that system performance may be influenced by thedecision maker's behavior during the aggregation, andthat the optimistic assumption may not yield tosatisfactory results, especially during critical timeperiods.     

Nonsupervised ranking of different segmentation approaches: application to the estimation of the left ventricular ejection fraction from cardiac cine MRI sequences

A statistical methodology is proposed to rank several estimation methods of a relevant clinical parameter when no gold standard is available. Based on a regression without truth method, the proposed approach was applied to rank eight methods without using any a priori information regarding the reliability of each method and its degree of automation. It was only based on a prior concerning the statistical distribution of the parameter of interest in the database. The ranking of the methods relies on figures of merit derived from the regression and computed using a bootstrap process. The methodology was applied to the estimation of the left ventricular ejection fraction derived from cardiac magnetic resonance images segmented using eight approaches with different degrees of automation: three segmentations were entirely manually performed and the others were variously automated. The ranking of methods was consistent with the expected performance of the estimation methods: the most accurate estimates of the ejection fraction were obtained using manual segmentations. The robustness of the ranking was demonstrated when at least three methods were compared. These results suggest that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available.     

Electron beam nanolithography in AZnLOF 2020

We present a lithography process using electron beam lithography with an optical resist AZnLOF 2020 for pattern transfer. High-resolution 100 keV electron beam lithography in 400 nm layers of negative resist AZnLOF 2020 diluted 10:4 with PMGEA is realized. After the electron beam lithography process, the resist is used as a mask for reactive ion etching. We performed the transfer of patterns by RIE etching of the substrate allowing a final resolution of 100 nm. We demonstrate the patterning in an insulating layer, thus simplifying the fabrication process of various multilayer devices; proximity correction has been applied to improve pattern quality and also to obtain lines width according to their spacing. This negative resist is removed by wet etching or dry etching, could allow combining pattern for smallest size down to 100 nm by EBL techniques and for larger sizes by traditional lithography using photomask.     

Air-bridge interconnection and bondpad process for non-planar compound semiconductor devices

We present a versatile metallic air-bridge process that can be used either for high relief compound semiconductor devices or interconnections schemes. Our technology uses conventional contact photolithography and does not require dry-etching techniques allowing a fast fabrication time, reliable production and cost effectiveness. It is based on the use of only one photoresist and one electroplating step.     

Markov Chain Monte Carlo Modular Ensemble Tracking

Recent years have been characterized by the overgrowth of video-surveillance systems and by automation of the processing they integrate. Object Tracking has become a recurrent problem in video-surveillance and is a very important domain in computer vision. It was recently approached using classification techniques and still more recently using boosting methods.We propose in this paper a new machine learning based strategy to build the observation model of tracking systems. The global observation function results of a linear combination of several simplest observation functions so-called modules (one per visual cue). Each module is built using a Adaboost-like algorithm, derived from the Ensemble Tracking Algorithm. The importance of each module is estimated using an original probabilistic sequential filtering framework with a joint state model composed by both the spatial object parameters and the importance parameters of the observation modules.Our system is tested on challenging sequences which prove its performance for tracking and scaling on fix and mobile cameras and we compare the robustness of our algorithm with the state of the art.