50 research outputs found
Selective Oxidation of Furfural at Room Temperature on a TiO2-Supported Ag Catalyst
No full textInternational audienceThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC B
Short-term Euro-Dollar exchange rate forecasting using regression models
No full textIn this project, our goal is to investigate mathematical and statistical models to forecast the short-term exchange rate. Notably, we are considering the 15-minutes time frame Euro-Dollar (EUR/USD) currency pair as the object of the project.
There are several different major currency pair such as EUR/USD USD/JPY, GBP/USD, USD/CHF, AUD/USD, and USD/CAD.
We chose EUR/USD since it is the most traded currency pair in the market; however, most of our work can be applied to other currency pair with some modifications.
In addition, we will also focus on polynomial regression models, which we hypothesized to be a better fit given the non-linear nature of the data
Ni-Fe alloying enhances the efficiency of the maltose hydrogenation process: The role of surface species and kinetic study
No full textInternational audienceUnlike the conversion of monosaccharides to the corresponding polyols, the production of maltitol by hydrogenation of maltose has been seldom investigated in the literature, despite its industrial importance. Monometallic Ni catalysts are known for their lack of stability, and the objective of the present paper is to determine through a kinetic study, to what extent a Ni-Fe/SiO 2 bimetallic catalyst would outperform a Ni/SiO 2 catalyst in the aqueous phase hydrogenation of maltose, as they have been reported to do for monosaccharides. The effect of reaction parameters (T = 80-150 °C, P H2 = 20-40 bar, maltose mass fraction in water = 4.4-17.5 wt.%) on activity, selectivity, and stability was examined. In all cases, maltitol was the major product, with a carbon balance higher than 98%, but maltose hydrolysis to glucose occurred in the upper range of temperature. In order to preserve both the catalyst selectivity and stability, a temperature of 80 °C was selected for the kinetic study. A first order model including an inhibiting term based on maltose concentration could fit the evolution of the conversion of maltose as a function of time. The adsorption constant of maltose and the apparent hydrogenation rate constant for the Ni-Fe catalyst were both larger by a factor 2 to 3 compared with the Ni catalyst, indicating a stronger interaction of maltose with the Ni-Fe surface. Another major difference was a reaction order of 0.5 with respect to the hydrogen pressure on Ni-Fe/SiO 2 compared with a near zero-order on Ni/SiO 2 , stressing significant differences in coverage of the bimetallic surface. The activity of the Ni-Fe catalyst remained constant for three runs of reaction without major structural changes, while the Ni catalyst deactivated by transforming to a phyllosilicate phase. As far as activity, selectivity and stability are concerned; Ni-Fe/SiO 2 appeared as a better suited catalyst than Ni/SiO 2 for the aqueous phase hydrogenation of maltose at 80 °C, with a more pronounced benefit than formerly reported for xylose on the same catalysts
The effects of normal mixtures and autocorrelation on the fraction non-conforming
No full textIn this article the effects of mixtures of two normal distributions on the fraction nonconforming are studied in the context of capability analysis. When the output from several processes is mixed, the quality characteristic variables of the resulting mix may result in a normal mixture distribution. This can happen in cases such as monitoring an output from several suppliers, several machines, or several workers. This study considered the independence case and autocorrelated processes for a mixture of two normal distributions, using a autoregressive
model of order one, AR(1). It is shown that the true attained process fraction nonconforming (corresponding to specific values for some capability index) can be very different from what is expected when the data are independent normal random variables.Journal ArticleAuthor's accepted manuscrip
A bibliometrics-enhanced, PAGER-Compliant scoping review of the literature on paralympic powerlifting. Insights for practices and future research
No full textParalympic powerlifting (PP), formerly known as “International Paralympic Committee”
(IPC) powerlifting, is the format of powerlifting adapted for athletes with disabilities, and it differs
from the version for able-bodied athletes in that it consists of bench press only. According to the
mandate of the IPC, PP athletes should be enabled to achieve sporting excellence. As such, rigorous
evidence is needed. However, to the best of our knowledge, there exists no systematic assessment
of the body of scholarly evidence in the field of PP. Therefore, the present study was conducted to
fill in this gap of knowledge, by conducting a scoping review of the literature enhanced by a
bibliometrics analysis and by mining two major scholarly databases (MEDLINE via PubMed and
Scopus). The aim was to provide a review/summary of the findings to date to help practitioners and
athletes. Thirty-seven studies were retained in the present study. These covered the following
thematic areas: (i) warm-up strategies (n = 2); (ii) aspects of training (n = 2); (iii) physiological aspects
and responses (n = 2); (iv) psychological aspects and responses (n = 2); (v) biomechanics of bench
press (n = 8); (vi) recovery strategy (n = 5); (vii) impact of the disability and type of disability (n = 4);
(viii) epidemiology of PP (n = 6); and (ix) new analytical/statistical approaches for kinematics
assessments, internal load monitoring, and predictions of mechanical outputs in strength exercises
and in PP (n = 6). Bibliometrics analysis of the PP-related scientific output revealed that, despite
having already become a paralympic sports discipline in 1984, only in the last few years, PP has
been attracting a lot of interest from the community of researchers, with the first scholarly
contribution dating back to 2012, and with more than one-third of the scientific output being
published this year (2022). As such, this scholarly discipline is quite recent and young. Moreover,
the community dealing with this topic is poorly interconnected, with most authors contributing to
just one article, and with one single author being a hub node of the author network. Distributions
of the number of articles and the authors/co-authors were found to be highly asymmetrical,
indicating that this research is still in its infancy and has great room as well as great potential to
grow. Reflecting this, many research topics are also overlooked and underdeveloped, with the
currently available evidence being based on a few studies
Adaptive multiscale stereo images matching based on wavelet transform modulus maxima
No full textIn this paper we propose a multiscale stereo correspondence matching method based on wavelets transform modulus maxima. Exploitation of maxima modulus chains has given us the opportunity to refine the search for corresponding. Based on the wavelet transform we construct maps of modules and phases for different scales, then extracted the maxima and then we build chains of maxima. Points constituents maxima modulus chains will be considered as points of interest in matching processes. The availability of all its multiscale information, allows searching under geometric constraints, for each point of interest in the left image corresponding one of the best points of constituent chains of the right image. The experiment results demonstrate that the number of corresponding has a very clear decrease when the scale increases. In several tests we obtained the uniqueness of the corresponding by browsing through the fine to coarse scales and calculations remain very reasonable.Journal ArticleFinal article publishe
On wavelet-based statistical process monitoring
No full textThis paper presents an overview of wavelet-based techniques for statistical process monitoring. The use of wavelet has already had an effective contribution to many applications. The increase of data availability has led to the use of wavelet analysis as a tool to reduce, denoise, and process the data before using statistical models for monitoring. The most recent review paper on wavelet-based methods for process monitoring had the goal to review the findings up to 2004. In this paper, we provide a recent reference for researchers and engineers with a different focus. We focus on: (i) wavelet statistical properties, (ii) control charts based on wavelet coefficients, and (iii) wavelet-based process monitoring methods within a machine learning framework. It is clear from the literature that wavelets are widely used with multivariate methods compared to univariate methods. We also found some potential research areas regarding the use of wavelet in image process monitoring and designing control charts based on wavelet statistics, and listed them in the paper.Journal ArticleAuthor's accepted manuscrip
Hierarchical topics in texts generated by a stream
No full textWe observe a stream of text messages, generated by Twitter or by a text file and present a tool which constructs a dynamic list of topics. Each tweet generates edges of a graph where the nodes are the tags and edges link the author of the tweet with the tags present in the tweet. We consider the large clusters of the graph and approximate the stream of edges with a Reservoir sampling. We study the giant components of the Reservoir and each large component represents a topic. The nodes of high degree and their edges provide the first layer of a topic, and the iteration over the nodes provide a hierarchical decomposition. For a standard text, we use a Weighted Reservoir sampling where the weight is the similarity between words given by Word2vec. We consider dynamic overlapping windows and provide the topicalization on each window. We compare this approach with the Word2content and LDA techniques in the case of a standard text, viewed as a stream
PIDs and HAL, the French Open Archive
No full textInternational audiencePresentation at the PIDfest Conference 2024. Lightning Talk presentation about the French multidisciplinary open archive HAL (https://hal.science/). In this presentation, we will discuss how PIDs are managed in HAL and how they contribute to quality metadata. HAL is a multidisciplinary French national open archive, published or not published, HAL contains more than 1.250.000 files of articles, preprints, conference papers, images etc… HAL is chosen by the whole French scientific and university community for the dissemination of knowledge. HAL helps and encourages its contributors to provide high quality metadata about publications, these metadata are mandatory to enhance the dissemination of the articles, to improve their discoverability and also to assist institutions toward the path of open access. HAL deposit form is quite exhaustive, in fact contributors can provide many metadata about a publication, for instance authors can be associated with many identifiers, same applies to author affiliations, journals, funding agencies.. , providing identifiers for these entities helps to avoid duplicates and to have accurate data which would require a considerable curation effort otherwise. In order to help HAL contributors and leverage the process of depositing in HAL, we use different techniques such as extracting metadata from the full-text or use metadata providers like CrossRef API , PubMed , arXiv… , the metadata for a given article is fetched using available interfaces and in case this metadata contains PIDs , for instance ORCIDs for authors, or RORs for organizations, this helps to avoid relying on approximate matching strategies which can lead to introducing (when matching fails) duplicates to HAL master data or even erroneous data, this mechanism is crucial especially to provide up to date resumes for researchers and collections for organizations
