Search results for "reduction"
showing 10 items of 2058 documents
Analysis of stamping performances of dual phase steels: A multi-objective approach to reduce springback and thinning failure
2009
The industrial interest on light weight components has contributed in the last years to a significant research effort on new materials able to guarantee high mechanical properties, good formability and reasonable costs together with reduced weights when compared to traditional mild steels. Among such materials advanced high strength steels (AHSS) such as transformations induced plasticity (TRIP) and dual phase (DP), and light weight alloys proved their usefulness in stamping of automotive components. As AHSS are concerned, one of the main drawbacks is related to springback occurrence. Many aspects have to be taken into account when springback reduction is investigated: material behavior iss…
Electron transfer mechanism in Shewanella loihica PV-4 biofilms formed at graphite electrode
2012
Abstract Electron transfer mechanisms in Shewanella loihica PV-4 viable biofilms formed at graphite electrodes were investigated in potentiostat-controlled electrochemical cells poised at oxidative potentials (0.2 V vs. Ag/AgCl). Chronoamperometry (CA) showed a repeatable biofilm growth of S. loihica PV-4 on graphite electrode. CA, cyclic voltammetry (CV) and its first derivative shows that both direct electron transfer (DET) mediated electron transfer (MET) mechanism contributes to the overall anodic (oxidation) current. The maximum anodic current density recorded on graphite was 90 μA cm − 2 . Fluorescence emission spectra shows increased concentration of quinone derivatives and riboflavi…
Parameter tuning for nacelle-based passive structural control of a spar-type floating wind turbine
2013
This paper deals with the modeling and parameter tuning of a spar-type floating wind turbine with a tuned mass damper (TMD) installed in nacelle. Firstly, a mathematical model for the system surge-heave-pitch motion is established based on first principles. Secondly, different parameter tuning methods are adopted to find the optimal TMD parameters for load reduction. Thirdly, nonlinear wind turbine simulations with different designs are conducted under different wind and wave conditions. The results show that TMD with small spring and damping coefficients will help to produce much load reduction in above rated condition. However, it may deteriorate system performance when the turbine is wor…
Multi-temporal and Multi-source Remote Sensing Image Classification by Nonlinear Relative Normalization
2016
Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corres…
A Spatial-Temporal Correlation Approach for Data Reduction in Cluster-Based Sensor Networks
2019
International audience; In a resource-constrained Wireless Sensor Networks (WSNs), the optimization of the sampling and the transmission rates of each individual node is a crucial issue. A high volume of redundant data transmitted through the network will result in collisions, data loss, and energy dissipation. This paper proposes a novel data reduction scheme, that exploits the spatial-temporal correlation among sensor data in order to determine the optimal sampling strategy for the deployed sensor nodes. This strategy reduces the overall sampling/transmission rates while preserving the quality of the data. Moreover, a back-end reconstruction algorithm is deployed on the workstation (Sink)…
Spatial noise-aware temperature retrieval from infrared sounder data
2020
In this paper we present a combined strategy for the retrieval of atmospheric profiles from infrared sounders. The approach considers the spatial information and a noise-dependent dimensionality reduction approach. The extracted features are fed into a canonical linear regression. We compare Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) for dimensionality reduction, and study the compactness and information content of the extracted features. Assessment of the results is done on a big dataset covering many spatial and temporal situations. PCA is widely used for these purposes but our analysis shows that one can gain significant improvements of the error rates when using…
Adaptive-threshold neural spike detection by noise-envelope tracking
2007
A new method for adaptive threshold setting is implemented and used in two threshold-based spike detectors: simple threshold and nonlinear energy operator. Detection quality assessment is performed using both a set of artificially generated signals and a real neural recording. Receiver operating curves are obtained and results show that, compared to fix threshold, adaptive threshold setting yields performance improvement.
Neural cell pattern formation on glass and oxidized silicon surfaces modified with poly(N-isopropylacrylamide)
1996
Control over the adsorption of proteins and over the adsorption and spatial orientation of mammalian cells onto surfaces has been achieved by modification of glass and other silicon oxide substrates with poly(N-isopropylacrylamide) (PNIPAM). The functionalization of the substrates was achieved either by a polymer-analogous reaction of aminosilanes with reactive N-(isopropylacrylamide) (NIPAM)-copolymers and by copolymerization of NIPAM with surface-bound methacrylsilane. The obtained coatings were characterized by FT-1R, ellipsometry, and surface plasmon resonance measurements. The adsorption of two proteins-fibrinogen and ribonuclease A-on these surfaces was studied in situ by real time su…
Bioprospective of Sorbus aucuparia leaf extract in development of silver and gold nanocolloids
2010
At the present time the bioprospective field is a dynamic area of research. The rapid biosynthesis of silver and gold nanoparticles without using toxic chemicals is reported here. Sorbus aucuparia is omnipresent in Europe. The aqueous leaves extract of the plant were used as reducing agent for the synthesis of silver and gold nanoparticles from their salt solutions. The synthesized nanoparticles were spherical, triangular and hexagonal in shape with an average size of 16 and 18nm for silver and gold, respectively. Different extract quantities, metal concentrations, temperatures and contact times were investigated to find their effect on nanoparticles synthesis. The resulting silver and gold…
Protocol for development of various plants leaves extract in single-pot synthesis of metal nanoparticles
2012
This article is aimed to extend a simple protocol for preparation of various plant leaves extract and their application to green synthesis of the metallic nanoparticles. Five plant leaves extract showed mild reduction and stabilization ability for silver and gold nanoparticles (AgNPs and AuNPs) at room temperature. The particle size range varied from 25 to 42 nm and 21 to 47 nm for AgNPs and AuNPs, respectively. Plant leaves extract-mediated nanoparticles were characterized to confirm the shape, size, crystallinity, and content using different spectroscopic investigations. Differences in stability of nanoparticles at different pH were also measured by zeta potential.