Search results for "Mach"
showing 10 items of 3360 documents
BED: A new dataset for EEG-based biometrics
2021
Various recent research works have focused on the use of electroencephalography (EEG) signals in the field of biometrics. However, advances in this area have somehow been limited by the absence of a common testbed that would make it possible to easily compare the performance of different proposals. In this work, we present a data set that has been specifically designed to allow researchers to attempt new biometric approaches that use EEG signals captured by using relatively inexpensive consumer-grade devices. The proposed data set has been made publicly accessible and can be downloaded from https://doi.org/10.5281/zenodo.4309471 . It contains EEG recordings and responses from 21 individuals…
Temperature-induced microstructural changes in shells of laboratory-grown Arctica islandica (Bivalvia).
2021
Bivalve shells are increasingly used as archives for high-resolution paleoclimate analyses. However, there is still an urgent need for quantitative temperature proxies that work without knowledge of the water chemistry–as is required for δ18O-based paleothermometry–and can better withstand diagenetic overprint. Recently, microstructural properties have been identified as a potential candidate fulfilling these requirements. So far, only few different microstructure categories (nacreous, prismatic and crossed-lamellar) of some short-lived species have been studied in detail, and in all such studies, the size and/or shape of individual biomineral units was found to increase with water temperat…
Sparse Deconvolution Using Support Vector Machines
2008
Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution problems. Here, a sparse deconvolution algorithm based on the SVM framework for signal processing is presented and analyzed, including comparative evaluations of its performance from the points of view of estimation and detection capabilities, and of robustness with respect to non-Gaussian additive noise. Publicado
On the decomposition of prefix codes
2017
Abstract In this paper we focus on the decomposition of rational and maximal prefix codes. We present an effective procedure that allows us to decide whether such a code is decomposable. In this case, the procedure also produces the factors of some of its decompositions. We also give partial results on the problem of deciding whether a rational maximal prefix code decomposes over a finite prefix code.
Production of bone mineral material and BMP-2 in osteoblasts cultured on double acid-etched titanium
2017
Background: The study of osteoblasts and their osteogenic functions is essential in order to understand them and their applications in implantology. In this sense, this study try to study BMP-2 production and bone matrix deposition, in addition to other biological variables, in osteoblasts cultured on a rough double acid-etched titanium surface (Osseotite®, Biomet 3i, Palm Beach Garden, Florida, USA) in comparison to a smooth titanium surface (machined) and a control Petri dish. Material and Methods: An in vitro prospective study. NHOst human osteoblasts from the femur were cultured on three different surfaces: Control group: 25-mm methacrylate dish (n = 6); Machined group: titanium discs w…
Overexpression of bone morphogenetic protein-6 (BMP-6) in the epidermis of transgenic mice: inhibition or stimulation of proliferation depending on t…
1996
Bone morphogenetic protein-6 (BMP-6) belongs to the family of TGF-beta-related growth factors. In the developing epidermis, expression of BMP-6 coincides with the onset of stratification. Expression persists perinatally but declines after day 6 postpartum, although it can still be detected in adult skin by reverse transcriptase-polymerase chain reaction (RT-PCR) analysis. We constitutively overexpressed BMP-6 in suprabasal layers of interfollicular epidermis in transgenic mice using a keratin 10 promoter. All mice expressing the transgene developed abnormalities in the skin, indicating an active transgene-derived factor. Depending on the pattern of transgene expression, the effects on proli…
Processing of rock core microtomography images: Using seven different machine learning algorithms
2016
The abilities of machine learning algorithms to process X-ray microtomographic rock images were determined. The study focused on the use of unsupervised, supervised, and ensemble clustering techniques, to segment X-ray computer microtomography rock images and to estimate the pore spaces and pore size diameters in the rocks. The unsupervised k-means technique gave the fastest processing time and the supervised least squares support vector machine technique gave the slowest processing time. Multiphase assemblages of solid phases (minerals and finely grained minerals) and the pore phase were found on visual inspection of the images. In general, the accuracy in terms of porosity values and pore…
Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study
2014
International audience; Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of a fall detection system based on such a smart camera, which allows to reduce the development time compared to standard approaches. Founded on a supervised classification approach, we propose a HW/SW implementation to detect falls in a home environment using a single camera and an optimized descriptor adapted to real-time t…
Alternating model trees
2015
Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose a method for growing alternating model trees, a form of option tree for regression problems. The motivation is that alternating decision trees achieve high accuracy in classification problems because they represent an ensemble classifier as a single tree structure. As in alternating decision trees for classification, our alternating model trees for regression contain splitter and prediction nodes, but we use simple linear regression functions as opposed to constant predicto…
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
2012
During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…