Archive of the PASATA (PASsive Acoustic Tracking of Antarctic marine mammals) field documentation

Recordings from the PerenniAL Acoustic Observatory in the Antarctic ocean (PALAOA) show seasonal acoustic presence of 4 Antarctic ice-breeding seal species (Ross seal, Ommatophoca rossii, Weddell seal, Leptonychotes weddellii, crabeater, Lobodon carcinophaga, and leopard seal, Hydrurga leptonyx). Apart from Weddell seals, inhabiting the fast-ice in Atka Bay, the other three (pack-ice) species however have to date never (Ross and leopard seal) or only very rarely (crabeater seals) been sighted in the Atka Bay region. The aim of the PASATA project is twofold: the large passive acoustic hydrophone array (hereafter referred to as large array) aims to localize calling pack-ice pinniped species to obtain information on their location and hence the ice habitat they occupy. This large array consists of four autonomous passive acoustic recorders with a hydrophone sensor deployed through a drilled hole in the sea ice. The PASATA recordings are time-stamped and can therefore be coupled to the PALAOA recordings so that the hydrophone array spans the bay almost entirely from east to west. The second, smaller hydrophone array (hereafter referred to as small array), also consists of four autonomous passive acoustic recorders with hydrophone sensors deployed through drilled holes in the sea ice. The smaller array was deployed within a Weddell seal breeding colony, located further south in the bay, just off the ice shelf. Male Weddell seals are thought to defend underwater territories around or near tide cracks and breathing holes used by females. Vocal activity increases strongly during the breeding season and vocalizations are thought to be used underwater by males for the purpose of territorial defense and advertisement. With the smaller hydrophone array we aim to investigate underwater behaviour of vocalizing male and female Weddell seals to provide further information on underwater movement patterns in relation to the location of tide cracks and breathing holes. As a pilot project, one on-ice and three underwater camera systems have been deployed near breathing holes to obtain additional visual information on Weddell seal behavioural activity. Upon each visit in the breeding colony, a census of colony composition on the ice (number of animals, sex, presence of dependent pups, presence and severity of injuries-indicative of competition intensity) as well as GPS readings of breathing holes and positions of hauled out Weddell seals are taken.

Land Surface Temperature continuous time series from SSM/I passive microwave radiometers, over northern latitudes (Latitudes > 45°N), during summer snow free period (2000-2011), with links to NetCDF files

Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.

A characterisation of passive and active interactions and their influence on student's achievement using Moodle LMS Logs

During the last years, there has been much concern about learning management systems' (LMS) effectiveness when compared to traditional learning and about how to assess students' participation during the course. The tracking and monitoring capabilities of most recent LMS have made it possible to analyse every interaction in the system. The issues addressed on this study are: a) Is LMS student's interaction an indicator of academic performance?; b) Are different results in performance expected between distance and in-class LMS-supported education?; c) How can LMS interactions from logs be categorised?; d) May this categorisation detect 'learning witnesses'? To answer these questions, a set of interaction types from Moodle LMS activity record logs has been analysed during two years in online and in-class Master's degrees at the UPM. The results show partial or no evidence of influence between interaction indicators and academic performance, although the proposed categorisation may help detect learning witnesses.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Dual-Band Tunable Recursive Active Filter

This letter presents a novel recursive active filter topology that provides dual-band performance, with independent tuning capability in both bands. The dual-band operation is achieved by using two independent feedback lines. Additionally, linear phase shifters based on left-handed cells are included in these two branches in order to tune the center frequency of both pass bands.

From irradiance to output power fluctuations: the pv plant as a low pass filter

The power generated by large grid-connected photovoltaic (PV) plants depends greatly on the solar irradiance. This paper studies the effects of the solar irradiance variability analyzing experimental 1-s data collected throughout a year at six PV plants, totaling 18 MWp. Each PV plant was modeled as a first order filter function based on an analysis in the frequency domain of the irradiance data and the output power signals. An empiric expression which relates the filter parameters and the PV plant size has been proposed. This simple model has been successfully validated precisely determining the daily maximum output power fluctuation from incident irradiance measurements.

Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter

When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this regard, this paper presents the application of extended Kalman filter for the parametric adaptation of a fuzzy model

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process

A Novel Scalable Deblocking-Filter Architecture for H.264/AVC and SVC Video Codecs

A highly parallel and scalable Deblocking Filter (DF) hardware architecture for H.264/AVC and SVC video codecs is presented in this paper. The proposed architecture mainly consists on a coarse grain systolic array obtained by replicating a unique and homogeneous Functional Unit (FU), in which a whole Deblocking-Filter unit is implemented. The proposal is also based on a novel macroblock-level parallelization strategy of the filtering algorithm which improves the final performance by exploiting specific data dependences. This way communication overhead is reduced and a more intensive parallelism in comparison with the existing state-of-the-art solutions is obtained. Furthermore, the architecture is completely flexible, since the level of parallelism can be changed, according to the application requirements. The design has been implemented in a Virtex-5 FPGA, and it allows filtering 4CIF (704 × 576 pixels @30 fps) video sequences in real-time at frequencies lower than 10.16 Mhz.

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.