Big IoT data mining for real-time energy disaggregation in buildings (extended abstract)

In the smart grid context, the identification and prediction of building energy flexibility is a challenging open question. In this paper, we propose a hybrid approach to address this problem. It combines sparse smart meters with deep learning methods, e.g. Factored Four-Way Conditional Restricted Boltzmann Machines (FFW-CRBMs), to accurately predict and identify the energy flexibility of buildings unequipped with smart meters, starting from their aggregated energy values. The proposed approach was validated on a real database, namely the Reference Energy Disaggregation Dataset

On Some Geometric Properties of Slice Regular Functions of a Quaternion Variable

The goal of this paper is to introduce and study some geometric properties of slice regular functions of quaternion variable like univalence, subordination, starlikeness, convexity and spirallikeness in the unit ball. We prove a number of results, among which an Area-type Theorem, Rogosinski inequality, and a Bieberbach-de Branges Theorem for a subclass of slice regular functions. We also discuss some geometric and algebraic interpretations of our results in terms of maps from $\mathbb R^4$ to itself. As a tool for subordination we define a suitable notion of composition of slice regular functions which is of independent interest

Big IoT data mining for real-time energy disaggregation in buildings (extended abstract)

In the smart grid context, the identification and prediction of building energy flexibility is a challenging open question. In this paper, we propose a hybrid approach to address this problem. It combines sparse smart meters with deep learning methods, e.g. Factored Four-Way Conditional Restricted Boltzmann Machines (FFW-CRBMs), to accurately predict and identify the energy flexibility of buildings unequipped with smart meters, starting from their aggregated energy values. The proposed approach was validated on a real database, namely the Reference Energy Disaggregation Dataset

Crowdsourcing Dialect Characterization through Twitter

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.Comment: 10 pages, 5 figure

Disclosure Style and Its Determinants in Integrated Reports

Integrated Reporting promotes a more cohesive and efficient approach to corporate reporting and aims to improve the quality of information available to providers of financial capital. The purpose of this paper was to investigate the determinants of readability and optimism which build the disclosure style of integrated reports. Our research draws on impression management theory and legitimacy theory, while also taking into consideration the cultural system of Hofstede with its further developments by Gray. Our sample consisted of 30 annual reports, extracted randomly from the Integrated Reporting examples database set up by the International Integrated Reporting Council. For the purposes of our investigation, we have carried out a multivariate regression analysis. Firstly, our results show that the higher the revenues of the reporting company, the more balanced their integrated reports, while younger companies use a more optimistic tone when reporting. Additionally, optimism seems to be inversely correlated with the length of the reports. Secondly, entities based in countries with a stronger tendency towards transparency surprisingly provide less readable integrated reports. It was also revealed that companies operating in non-environmentally sensitive industries, as well as International Financial Reporting Standards adopters deliver foggier and thus less readable integrated reports

Extragalactic Millimeter-wave Point-source Catalog, Number Counts and Statistics from 771 deg^2 of the SPT-SZ Survey

We present a point-source catalog from 771 deg^2 of the South Pole Telescope Sunyaev-Zel'dovich survey at 95, 150, and 220 GHz. We detect 1545 sources above 4.5σ significance in at least one band. Based on their relative brightness between survey bands, we classify the sources into two populations, one dominated by synchrotron emission from active galactic nuclei, and one dominated by thermal emission from dust-enshrouded star-forming galaxies. We find 1238 synchrotron and 307 dusty sources. We cross-match all sources against external catalogs and find 189 unidentified synchrotron sources and 189 unidentified dusty sources. The dusty sources without counterparts are good candidates for high-redshift, strongly lensed submillimeter galaxies. We derive number counts for each population from 1 Jy down to roughly 11, 4, and 11 mJy at 95, 150, and 220 GHz. We compare these counts with galaxy population models and find that none of the models we consider for either population provide a good fit to the measured counts in all three bands. The disparities imply that these measurements will be an important input to the next generation of millimeter-wave extragalactic source population models

Deep learning methods for on-line flexibility prediction and optimal resource allocation in smart buildings

Unprecedented high volume of data is available with the upward growth of the advanced metering infrastructure. Because the built environment is the largest user of electricity, a deeper look at building energy consumption holds promise for helping to achieve overall optimization of the energy system. Yet, a knowledge transfer from the fusion of extensive data is under development. To overcome this limitation, in the big data era, more and more machine learning methods appear to be suitable to automatically extract, predict and optimized building electrical patterns by performing successive transformation of the data. More recently, there has been a revival of interest in deep learning methods as the most advance on-line solutions for large-scale and real databases. Enabling real-time applications from the high level of aggregation in the smart grid will put end-users in position to change their consumption patterns, offering useful benefits for the system as a whole.<br/

Failure to protect the myocardium against ischemia/reperfusion injury after chronic atorvastatin treatment is recaptured by acute atorvastatin treatment A potential role for phosphatase and tensin homolog deleted on chromosome ten?

ObjectivesWe sought to ascertain whether chronic oral therapy with atorvastatin protects against ischemia/reperfusion (I/R) injury.BackgroundWe have recently shown that acute atorvastatin treatment protects against reperfusion-induced injury by activating the PI3K/Akt/eNOS pathway. However, many patients are on chronic statin therapy, and it is necessary to investigate whether this, in itself, provides a therapeutic advantage.MethodsSprague-Dawley rats were orally treated for one day, three days, one week, or two weeks with 20 mg/kg of atorvastatin or vehicle, after which the hearts underwent 35 min of ischemia and 120 min reperfusion (IR). Two additional groups were treated for one or two weeks with atorvastatin and then received a supplementary dose of 40 mg/kg before IR. The risk zone was determined using Evans blue and infarct size (IR%) using triphenyltetrazolium chloride staining.ResultsTreatment with atorvastatin for one and three days significantly reduced infarct size versus controls (38.9 ± 3.1% vs. 56.4 ± 2.3%; 39.3 ± 2.4% vs. 61.3 ± 3.8%, respectively). However, after one or two weeks of treatment, no protection was observed (52.6 ± 3.8% vs. 58.6 ± 4.3%; 58.3 ± 2.7% vs. 52.4 ± 5.7%, respectively). Surprisingly, a supplementary dose of atorvastatin recaptured the protection in the groups treated chronically (36.2 ± 2.8% vs. 58.6 ± 4.3%; 26.8 ± 1.5% vs. 51.2 ± 6.7%, at one and two weeks, respectively). Interestingly, we observed an increased level of phosphatase and tensin homolog deleted on chromosome ten (PTEN), the phosphatidylinositol-3 kinase inhibitor, in the chronic treated hearts.ConclusionsIn conclusion, atorvastatin appears to have an acute protective effect that wanes with time associated with an increase in PTEN levels. This waning protection can be recaptured by an acute high dose given immediately before IR. These results may have protential clinical relevance