Hyperspectral subspace identification

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

C3G - A portuguese collaboration for geology, geodesy and geophysics

Portugal joined the effort to create the EPOS infrastructure in 2008, and it became immediately apparent that a national network of Earth Sciences infrastructures was required to participate in the initiative. At that time, FCT was promoting the creation of a national infrastructure called RNG - Rede Nacional de Geofísica (National Geophysics Network). A memorandum of understanding had been agreed upon, and it seemed therefore straightforward to use RNG (enlarged to include relevant participants that were not RNG members) as the Portuguese partner to EPOS-PP. However, at the time of signature of the EPOS-PP contract with the European Commission (November 2010), RNG had not gained formal identity yet, and IST (one of the participants) signed the grant agreement on behalf of the Portuguese consortium. During 2011 no progress was made towards the formal creation of RNG, and the composition of the network – based on proposals submitted to a call issued in 2002 – had by then become obsolete. On February 2012, the EPOS national contact point was mandated by the representatives of the participating national infrastructures to request from FCT the recognition of a new consortium - C3G, Collaboratory for Geology, Geodesy and Geophysics - as the Portuguese partner to EPOS-PP. This request was supported by formal letters from the following institutions: ‐ LNEG. Laboratório Nacional de Energia e Geologia (National Geological Survey); ‐ IGP ‐ Instituto Geográfico Português (National Geographic Institute); ‐ IDL, Instituto Dom Luiz – Laboratório Associado ‐ CGE, Centro de Geofísica de Évora; ‐ FCTUC, Faculdade de Ciências e Tecnologia da Universidade de Coimbra; ‐ Instituto Superior de Engenharia de Lisboa; ‐ Instituto Superior Técnico; ‐ Universidade da Beira Interior. While Instituto de Meteorologia (Meteorological Institute, in charge of the national seismographic network) actively supports the national participation in EPOS, a letter of support was not feasible in view of the organic changes underway at the time. C3G aims at the integration and coordination, at national level, of existing Earth Sciences infrastructures, namely: ‐ seismic and geodetic networks (IM, IST, IDL, CGE); ‐ rock physics laboratories (ISEL); ‐ geophysical laboratories dedicated to natural resources and environmental studies; ‐ geological and geophysical data repositories; ‐ facilities for data storage and computing resources. The C3G - Collaboratory for Geology, Geodesy and Geophysics will be coordinated by Universidade da Beira Interior, whose Department of Informatics will host the C3G infrastructure.

Unsupervised hyperspectral signal subspace identification

Hyperspectral imaging sensors provide image data containing both spectral and spatial information from the Earth surface. The huge data volumes produced by these sensors put stringent requirements on communications, storage, and processing. This paper presents a method, termed hyperspectral signal subspace identification by minimum error (HySime), that infer the signal subspace and determines its dimensionality without any prior knowledge. The identification of this subspace enables a correct dimensionality reduction yielding gains in algorithm performance and complexity and in data storage. HySime method is unsupervised and fully-automatic, i.e., it does not depend on any tuning parameters. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

Signal subspace identification in hyperspectral imagery

Terrestrial remote sensing imagery involves the acquisition of information from the Earth's surface without physical contact with the area under study. Among the remote sensing modalities, hyperspectral imaging has recently emerged as a powerful passive technology. This technology has been widely used in the fields of urban and regional planning, water resource management, environmental monitoring, food safety, counterfeit drugs detection, oil spill and other types of chemical contamination detection, biological hazards prevention, and target detection for military and security purposes [2-9]. Hyperspectral sensors sample the reflected solar radiation from the Earth surface in the portion of the spectrum extending from the visible region through the near-infrared and mid-infrared (wavelengths between 0.3 and 2.5 µm) in hundreds of narrow (of the order of 10 nm) contiguous bands [10]. This high spectral resolution can be used for object detection and for discriminating between different objects based on their spectral xharacteristics [6]. However, this huge spectral resolution yields large amounts of data to be processed. For example, the Airbone Visible/Infrared Imaging Spectrometer (AVIRIS) [11] collects a 512 (along track) X 614 (across track) X 224 (bands) X 12 (bits) data cube in 5 s, corresponding to about 140 MBs. Similar data collection ratios are achieved by other spectrometers [12]. Such huge data volumes put stringent requirements on communications, storage, and processing. The problem of signal sbspace identification of hyperspectral data represents a crucial first step in many hypersctral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction (DR) yelding gains in data storage and retrieval and in computational time and complexity. Additionally, DR may also improve algorithms performance since it reduce data dimensionality without losses in the useful signal components. The computation of statistical estimates is a relevant example of the advantages of DR, since the number of samples required to obtain accurate estimates increases drastically with the dimmensionality of the data (Hughes phnomenon) [13].

Mobile device-to-device distributed computing using data sets

The rapidly increasing computing power, available storage and communication capabilities of mobile devices makes it possible to start processing and storing data locally, rather than offloading it to remote servers; allowing scenarios of mobile clouds without infrastructure dependency. We can now aim at connecting neighboring mobile devices, creating a local mobile cloud that provides storage and computing services on local generated data. In this paper, we describe an early overview of a distributed mobile system that allows accessing and processing of data distributed across mobile devices without an external communication infrastructure. Copyright © 2015 ICST.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

On the Suitability of Suffix Arrays for Lempel-Ziv Data Compression

Lossless compression algorithms of the Lempel-Ziv (LZ) family are widely used nowadays. Regarding time and memory requirements, LZ encoding is much more demanding than decoding. In order to speed up the encoding process, efficient data structures, like suffix trees, have been used. In this paper, we explore the use of suffix arrays to hold the dictionary of the LZ encoder, and propose an algorithm to search over it. We show that the resulting encoder attains roughly the same compression ratios as those based on suffix trees. However, the amount of memory required by the suffix array is fixed, and much lower than the variable amount of memory used by encoders based on suffix trees (which depends on the text to encode). We conclude that suffix arrays, when compared to suffix trees in terms of the trade-off among time, memory, and compression ratio, may be preferable in scenarios (e.g., embedded systems) where memory is at a premium and high speed is not critical.

Automatic assignment of absolute configuration from 1D NMR data

Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding 1H NMR chemical shifts and the other with 94 13C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r2 0.936 for the test set between the predicted and experimental values.

Lightning Data Observed With Lightning Location System in Portugal

This paper presents an investigation into cloud-to-ground lightning activity over the continental territory of Portugal with data collected by the national Lightning Location System. The Lightning Location System in Portugal is first presented. Analyses about geographical, seasonal, and polarity distribution of cloud-to-ground lightning activity and cumulative probability of peak current are carried out. An overall ground flash density map is constructed from the database, which contains the information of more than five years and almost four million records. This map is compared with the thunderstorm days map, produced by the Portuguese Institute of Meteorology, and with the orographic map of Portugal. Finally, conclusions are duly drawn.

Multi-stage evolution of a sub-aerial volcanic ridge over the last 1.3 Myr: S. Jorge Island, Azores Triple Junction

New K/Ar dating and geochemical analyses have been carried out on the WNW-ESE elongated oceanic island of S. Jorge to reconstruct the volcanic evolution of a linear ridge developed close to the Azores triple junction. We show that S. Jorge sub-aerial construction encompasses the last 1.3 Myr, a time interval far much longer than previously reported. The early development of the ridge involved a sub-aerial building phase exposed in the southeast end of the island and now constrained between 1.32 +/- 0.02 and 1.21 +/- 0.02 Ma. Basic lavas from this older stage are alkaline and enriched in incompatible elements, reflecting partial melting of an enriched mantle source. At least three differentiation cycles from alkaline basalts to mugearites are documented within this stage. The successive episodes of magma rising, storage and evolution suggest an intermittent reopening of the magma feeding system, possibly due to recurrent tensional or trans-tensional tectonic events. Present data show a gap in sub-aerial volcanism before a second main ongoing building phase starting at about 750 ka. Sub-aerial construction of the S. Jorge ridge migrated progressively towards the west, but involved several overlapping volcanic episodes constrained along the main WNW-ESE structural axis of the island. Malic magmas erupted during the second phase have been also generated by partial melting of an enriched mantle source. Trace element data suggest, however, variable and lower degrees of partial melting of a shallower mantle domain, which is interpreted as an increasing control of lithospheric deformation on the genesis and extraction of primitive melts during the last 750 kyr. The multi-stage development of the S. Jorge volcanic ridge over the last 1.3 Myr has most likely been greatly influenced by regional tectonics, controlled by deformation along the diffuse boundary between the Nubian and the Eurasian plates, and the increasing effect of sea-floor spreading at the Mid-Atlantic Ridge.

Study of the Saldanha Massif (MAR, 36 degrees 34 ' N): Constrains from rock magnetic and geophysical data

We present a study of the magnetic properties of a group of basalt samples from the Saldanha Massif (Mid-Atlantic Ridge - MAR - 36degrees 33' 54" N, 33degrees 26' W), and we set out to interpret these properties in the tectono-magmatic framework of this sector of the MAR. Most samples have low magnetic anisotropy and magnetic minerals of single domain grain size, typical of rapid cooling. The thermomagnetic study mostly shows two different susceptibility peaks. The high temperature peak is related to mineralogical alteration due to heating. The low temperature peak shows a distinction between three different stages of low temperature oxidation: the presence of titanomagnetite, titanomagnetite and titanomaghemite, and exclusively of titanomaghemite. Based on established empirical relationships between Curie temperature and degree of oxidation, the latter is tentatively deduced for all samples. Finally, swath bathymetry and sidescan sonar data combined with dive observations show that the Saldanha Massif is located over an exposed section of upper mantle rocks interpreted to be the result of detachment tectonics. Basalt samples inside the detachment zone often have higher than expected oxidation rates; this effect can be explained by the higher permeability caused by the detachment fault activity.

The source of the 1722 Algarve earthquake: evidence from MCS and tsunami data

The 27 December 1722 Algarve earthquake destroyed a large area in southern Portugal generating a local tsunami that inundated the shallow areas of Tavira. It is unclear whether its source was located onshore or offshore and, in any case, what was the tectonic source responsible for the event. We analyze available historical information concerning macroseismicity and the tsunami to discuss the most probable location of the source. We also review available seismotectonic knowledge of the offshore region close to the probable epicenter, selecting a set of four candidate sources. We simulate tsunamis produced by these candidate sources assuming that the sea bottom displacement is caused by a compressive dislocation over a rectangular fault, as given by the half-space homogeneous elastic approach, and we use numerical modeling to study wave propagation and run-up. We conclude that the 27 December 1722 Tavira earthquake and tsunami was probably generated offshore, close to 37 degrees 01'N, 7 degrees 49'W.

Extreme Value Theory versus traditional GARCH approaches applied to financial data: a comparative evaluation

Although stock prices fluctuate, the variations are relatively small and are frequently assumed to be normal distributed on a large time scale. But sometimes these fluctuations can become determinant, especially when unforeseen large drops in asset prices are observed that could result in huge losses or even in market crashes. The evidence shows that these events happen far more often than would be expected under the generalized assumption of normal distributed financial returns. Thus it is crucial to properly model the distribution tails so as to be able to predict the frequency and magnitude of extreme stock price returns. In this paper we follow the approach suggested by McNeil and Frey (2000) and combine the GARCH-type models with the Extreme Value Theory (EVT) to estimate the tails of three financial index returns DJI,FTSE 100 and NIKKEI 225 representing three important financial areas in the world. Our results indicate that EVT-based conditional quantile estimates are much more accurate than those from conventional AR-GARCH models assuming normal or Student’s t-distribution innovations when doing out-of-sample estimation (within the insample estimation, this is so for the right tail of the distribution of returns).

PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods

Background: With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it. Results: PHYLOViZ is platform independent Java software that allows the integrated analysis of sequence-based typing methods, including SNP data generated from whole genome sequence approaches, and associated epidemiological data. goeBURST and its Minimum Spanning Tree expansion are used for visualizing the possible evolutionary relationships between isolates. The results can be displayed as an annotated graph overlaying the query results of any other epidemiological data available. Conclusions: PHYLOViZ is a user-friendly software that allows the combined analysis of multiple data sources for microbial epidemiological and population studies. It is freely available at http://www.phyloviz.net.

Probing the scalar-pseudoscalar mixing in the 125 GeV Higgs particle with current data

LHC has found hints for a Higgs particle of 125 GeV. We investigate the possibility that such a particle is a mixture of scalar and pseudoscalar states. For definiteness, we concentrate on a two-Higgs doublet model with explicit CP violation and soft Z(2) violation. Including all Higgs production mechanisms, we determine the current constraints obtained by comparing h -> yy with h -> VV*, and comment on the information which can be gained by measurements of h -> b (b) over bar. We find bounds vertical bar s(2)vertical bar less than or similar to 0.83 at one sigma, where vertical bar s(2)vertical bar = 0 (vertical bar s(2)vertical bar = 1) corresponds to a pure scalar (pure pseudoscalar) state.