Search results for "Data"
showing 10 items of 12992 documents
Housing market shocks in italy: A GVAR approach
2020
Abstract In this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004 − 2016 . In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the G…
A competing risks tale on successful and unsuccessful fiscal consolidations
2019
Abstract This paper analyses the transitions out of fiscal consolidations using annual data for 17 industrial countries over the period 1975-2013 and applying a discrete-time competing risks duration model. Our approach allows us to distinguish the factors behind a successful or an unsuccessful end of fiscal consolidation episodes. The results show that economic and political factors, the size and typology of fiscal adjustments and the occurrence of crises explain the differences in the length and the success/failure of fiscal consolidations. Moreover, while fiscal adjustment programmes that end successfully display positive duration dependence, those that end in an unsuccessful manner are …
Non-parametric approaches to the impact of Holstein heifer growth from birth to insemination on their dairy performance at lactation one
2012
SUMMARYParametric approaches have been used widely to model animal growth and study the impact of growth profile on performance. Individual variation is often not considered in such approaches. However, non-parametric modelling allows this. Such an approach, based on spline functions, was used to study the importance of growth profiles from age 0 to 15 months (i.e. insemination) on milk yield and composition in primiparous cows. A dataset of 447 heifers was used for analysis of growth performance; 296 of them were also used to study impact on lactation. All of them originated from a French experimental herd and were born between 1986 and 2006. Clustering methods were also tested. Comparison…
Fostering aspects of pre-service teachers’ data literacy: Results of a randomized controlled trial
2020
Abstract The present study reports the results of a randomized controlled trial aimed at fostering specific aspects of pre-service teachers’ data literacy. The 6-h intervention focused on data types, reference norms, scale transformations, graphic displays of the properties of frequency distributions, and judgments about the magnitude of mean differences. Pretest-posttest comparisons of a data literacy test showed a large and significant effect of the intervention. Furthermore, main effects but no significant interaction effects with pretest scores were found for personal and motivational covariates (academic self-concept, value beliefs, study interest) on posttest data literacy.
A Grounded Theory of Elite Male Table Tennis Players’ Activity during Matches
2006
International audience; This article describes the main features of a collaborative project involving researchers, coaches, and elite table tennis players. The project was carried out between 1997 and 2002 with funding from the French Ministry of Youth and Sports, in response to a request by French Table Tennis Team coaches to improve the training of table tennis players. Matches were videotaped during international meets and followed by interviews during which the players described and commented on their activity as they viewed the tapes. A grounded theory of players' activity emerged from the data collected and the ensuing theoretical issues that were raised. The findings on table tennis …
Quantification and classification in education: What is at stake?
2021
Histories of statistics and quantification have demonstrated that systems of statistical knowledge participate in the construction of the objects that are measured. However, the pace, purpose, and scope of quantification in state bureaucracy have expanded greatly over the past decades, fuelled by (neoliberal) societal trends that have given the social phenomenon of quantification a central place in political discussions and in the public sphere. This is particularly the case in the field of education. In this article, we ask what is at stake in state bureaucracy, professional practice, and individual pupils as quantification increasingly permeates the education field. We call for a theoret…
Cell state prediction through distributed estimation of transmit power
2019
Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of…
Dynamic Functional Connectivity Captures Individuals’ Unique Brain Signatures
2020
Recent neuroimaging evidence suggest that there exists a unique individual-specific functional connectivity (FC) pattern consistent across tasks. The objective of our study is to utilize FC patterns to identify an individual using a supervised machine learning approach. To this end, we use two previously published data sets that comprises resting-state and task-based fMRI responses. We use static FC measures as input to a linear classifier to evaluate its performance. We additionally extend this analysis to capture dynamic FC using two approaches: the common sliding window approach and the more recent phase synchrony-based measure. We found that the classification models using dynamic FC pa…
Reverse-safe data structures for text indexing
2021
We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…
An Interactive Framework for Offline Data-Driven Multiobjective Optimization
2020
We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which introduces uncertainty. The framework incorporates preference information from a decision maker in two aspects to direct the solution process. Firstly, the decision maker can guide the optimization by providing preferences for objectives. Secondly, the framework features a novel technique for the decision maker to also express preferences related to maximum acceptable uncertainty in the solutions as preferred ranges of uncertainty. In this way, the d…