Assessing spatiotemporal correlations from data for short-term traffic prediction using multi-task learning

Traffic flow prediction is a fundamental problem for efficient transportation control and management. However, most current data-driven traffic prediction work found in the literature have focused on predicting traffic from an individual task perspective, and have not fully leveraged the implicit knowledge present in a road-network through space and time correlations. Such correlations are now far easier to isolate due to the recent profusion of traffic data sources and more specifically their wide geographic spread. In this paper, we take a multi-task learning (MTL) approach whose fundamental aim is to improve the generalization performance by leveraging the domain-specific information contained in related tasks that are jointly learned. In addition, another common factor found in the literature is that a historical dataset is used for the calibration and the assessment of the proposed approach, without dealing in any explicit or implicit way with the frequent challenges found in real-time prediction. In contrast, we adopt a different approach which faces this problem from a point of view of streams of data, and thus the learning procedure is undertaken online, giving greater importance to the most recent data, making data-driven decisions online, and undoing decisions which are no longer optimal. In the experiments presented we achieve a more compact and consistent knowledge in the form of rules automatically extracted from data, while maintaining or even improving, in some cases, the performance over single-task learning (STL).Peer ReviewedPostprint (published version

La Satisfacció en l'esport depèn del gènere?

En l’actualitat es valora que un dels fruits de la nostra civilització és l’esport i es pronostica que el segle XXI serà el gran segle de l’esport. Els homes i les dones han après a utilitzar el seu cos de manera que els proporcioni el màxim de plaer, tant físic com mental, i sabem que l’esport no tan sols serveix per a millorar uns resultats o mantenir una adequada imatge física, sinó que la seva essència és la qualitat de les experiències que ens proporciona. Però encara avui és una realitat que la presència de la dona en els diferents àmbits esportius: afició, participació, competició, seguiment, implicació, direcció, etc., és menor tant qualitativament com quantitativament

Index Fund Ownership and Stock Price Efficiency: Evidence from Quarterly Earnings Seasons

While prior research argues that individual investors benefit from a switch to passive investment in index funds (French 2008, Bond and García 2022), higher levels of index fund ownership of firm shares lead to competing factors that influence a firm’s price efficiency (i.e., the speed and accuracy with which a firm’s stock price reflects investor consensus on the information provided about a firm). If relative investor sophistication increases as index fund ownership increases, there is a benefit to the firm’s price efficiency. Yet, more shares held passively limit the shares available for investors to actively incorporate firm news, adversely impacting price efficiency. In this study, I consider these two competing factors using alternative sources of firm information during its earnings season to explore the impact of index fund ownership on a firm’s stock price efficiency. I find evidence of decreased investor disagreement associated with a firm’s earnings announcement, indicating a benefit to the firm’s price efficiency. Yet, I also find the decrease in investor participation from higher levels of index fund ownership adversely affects a firm’s price efficiency when incorporating information based on investor expectations of firm performance from peer disclosures. These contextualized results provide no conclusive evidence on the total impact of index fund ownership at currently observed levels, but should continue to be studied as passive investment increases over time

Improving adaptation and interpretability of a short-term traffic forecasting system

Traffic management is being more important than ever, especially in overcrowded big cities with over-pollution problems and with new unprecedented mobility changes. In this scenario, road-traffic prediction plays a key role within Intelligent Transportation Systems, allowing traffic managers to be able to anticipate and take the proper decisions. This paper aims to analyse the situation in a commercial real-time prediction system with its current problems and limitations. The analysis unveils the trade-off between simple parsimonious models and more complex models. Finally, we propose an enriched machine learning framework, Adarules, for the traffic prediction in real-time facing the problem as continuously incoming data streams with all the commonly occurring problems in such volatile scenario, namely changes in the network infrastructure and demand, new detection stations or failure ones, among others. The framework is also able to infer automatically the most relevant features to our end-task, including the relationships within the road network. Although the intention with the proposed framework is to evolve and grow with new incoming big data, however there is no limitation in starting to use it without any prior knowledge as it can starts learning the structure and parameters automatically from data. We test this predictive system in different real-work scenarios, and evaluate its performance integrating a multi-task learning paradigm for the sake of the traffic prediction task.Peer ReviewedPostprint (published version

Som graminívors els humans? Una aproximació paremiològica a la qüestió

Els humans som clarament graminívors, però no d?ençà de l?aparició de la nostre espècie, ara fa uns dos-cents mil anys, sinó d?ençà de la revolució neolítica, fa tan sols uns deu mil anys, amb el sorgiment de l?agricultura. Som també graminívors segons la parla popular? Per mitjà de la paremiologia quantitativa, és a dir, de la categorització i quantificació sistemàtica dels proverbis es demostra que el nostre llenguatge conté un nombre dominant d?expressions populars referides als cereals i especialment al pa. A més, es detecta una correlació significativa entre els refranys i la composició dietètica de la cuina mediterrània catalana.Today humans are clearly graminivorous, but 200,000 years ago, when our species first appeared, this was not the case. In fact it wasn?t until the Neolithic revolution and the discovery of agriculture, 10,000 years ago, that this came to be. But are we also graminivorous when it comes to popular figures of speech? Quantitative paremiology (the categorisation and systematic quantification of proverbs) demonstrates that the Catalan language contains a dominant number of expressions about cereals and especially about bread. In addition, the study has detected a significant correlation between the proverbs and the dietary composition of Mediterranean Catalan cuisine

Index Fund Ownership and Stock Price Efficiency: Evidence from Quarterly Earnings Seasons

While prior research argues that individual investors benefit from a switch to passive investment in index funds (French 2008, Bond and García 2022), higher levels of index fund ownership of firm shares lead to competing factors that influence a firm’s price efficiency (i.e., the speed and accuracy with which a firm’s stock price reflects investor consensus on the information provided about a firm). If relative investor sophistication increases as index fund ownership increases, there is a benefit to the firm’s price efficiency. Yet, more shares held passively limit the shares available for investors to actively incorporate firm news, adversely impacting price efficiency. In this study, I consider these two competing factors using alternative sources of firm information during its earnings season to explore the impact of index fund ownership on a firm’s stock price efficiency. I find evidence of decreased investor disagreement associated with a firm’s earnings announcement, indicating a benefit to the firm’s price efficiency. Yet, I also find the decrease in investor participation from higher levels of index fund ownership adversely affects a firm’s price efficiency when incorporating information based on investor expectations of firm performance from peer disclosures. These contextualized results provide no conclusive evidence on the total impact of index fund ownership at currently observed levels, but should continue to be studied as passive investment increases over time

Dense and Warm Molecular Gas and Warm Dust in Nearby Galaxies

We performed 12CO(1-0), 13CO(1-0), and HCN(1-0) single-dish observations (beam size ~14"-18") toward nearby starburst and non-starburst galaxies using the Nobeyama 45 m telescope. The 13CO(1-0) and HCN(1-0) emissions were detected from all the seven starburst galaxies, with the intensities of both lines being similar (i.e., the ratios are around unity). On the other hand, for case of the non-starburst galaxies, the 13CO(1-0) emission was detected from all three galaxies, while the HCN(1-0) emission was weakly or not detected in past observations. This result indicates that the HCN/13CO intensity ratios are significantly larger (~1.15+-0.32) in the starburst galaxy samples than the non-starburst galaxy samples (<0.31+-0.14). The large-velocity-gradient model suggests that the molecular gas in the starburst galaxies have warmer and denser conditions than that in the non-starburst galaxies, and the photon-dominated-region model suggests that the denser molecular gas is irradiated by stronger interstellar radiation field in the starburst galaxies than that in the non-starburst galaxies. In addition, HCN/13CO in our sample galaxies exhibit strong correlations with the IRAS 25 micron flux ratios. It is a well established fact that there exists a strong correlation between dense molecular gas and star formation activities, but our results suggest that molecular gas temperature is also an important parameter.Comment: 14 pages, 6 figures. Accepted for publication in PAS