Run-time defragmentation for dynamically reconfigurable hardware

Reconfigurable computing experienced a considerable expansion in the last few years, due in part to the fast run-time partial reconfiguration features offered by recent SRAM-based Field Programmable Gate Arrays (FPGAs), which allowed the implementation in real-time of dynamic resource allocation strategies, with multiple independent functions from different applications sharing the same logic resources in the space and temporal domains. However, when the sequence of reconfigurations to be performed is not predictable, the efficient management of the logic space available becomes the greatest challenge posed to these systems. Resource allocation decisions have to be made concurrently with system operation, taking into account function priorities and optimizing the space currently available. As a consequence of the unpredictability of this allocation procedure, the logic space becomes fragmented, with many small areas of free resources failing to satisfy most requests and so remaining unused. A rearrangement of the currently running functions is therefore necessary, so as to obtain enough contiguous space to implement incoming functions, avoiding the spreading of their components and the resulting degradation of system performance. A novel active relocation procedure for Configurable Logic Blocks (CLBs) is herein presented, able to carry out online rearrangements, defragmenting the available FPGA resources without disturbing functions currently running.

Comparative analysis of time-frequency methods estimating the time-varying microstructure of sleep EEG spindles

Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006

Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles

Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon, France August 23-26, 2007

Real Time Internet DGPS Service

The accuracy of the Navigation Satellite Timing and Ranging (NAVSTAR) Global Positioning System (GPS) measurements is insufficient for many outdoor navigation tasks. As a result, in the late nineties, a new methodology – the Differential GPS (DGPS) – was developed. The differential approach is based on the calculation and dissemination of the range errors of the GPS satellites received. GPS/DGPS receivers correlate the broadcasted GPS data with the DGPS corrections, granting users increased accuracy. DGPS data can be disseminated using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to provide mobile platforms within our campus with DGPS data for precise outdoor navigation. To achieve this objective, we designed and implemented a three-tier client/server distributed system that establishes Internet links with remote DGPS sources and performs campus-wide dissemination of the obtained data. The Internet links are established between data servers connected to remote DGPS sources and the client, which is the data input module of the campus-wide DGPS data provider. The campus DGPS data provider allows the establishment of both Intranet and wireless links within the campus. This distributed system is expected to provide adequate support for accurate (submetric) outdoor navigation tasks.

Pliocene-quaternary upwelling in the SoutheasternAtlantic may reflect changes in water mass production

Proceedings of tile 1" R.C.A.N.S. Congress, Lisboa, October 1992

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Real-time scheduling with resource sharing on heterogeneous multiprocessors

Consider the problem of scheduling a task set τ of implicit-deadline sporadic tasks to meet all deadlines on a t-type heterogeneous multiprocessor platform where tasks may access multiple shared resources. The multiprocessor platform has m k processors of type-k, where k∈{1,2,…,t}. The execution time of a task depends on the type of processor on which it executes. The set of shared resources is denoted by R. For each task τ i , there is a resource set R i ⊆R such that for each job of τ i , during one phase of its execution, the job requests to hold the resource set R i exclusively with the interpretation that (i) the job makes a single request to hold all the resources in the resource set R i and (ii) at all times, when a job of τ i holds R i , no other job holds any resource in R i . Each job of task τ i may request the resource set R i at most once during its execution. A job is allowed to migrate when it requests a resource set and when it releases the resource set but a job is not allowed to migrate at other times. Our goal is to design a scheduling algorithm for this problem and prove its performance. We propose an algorithm, LP-EE-vpr, which offers the guarantee that if an implicit-deadline sporadic task set is schedulable on a t-type heterogeneous multiprocessor platform by an optimal scheduling algorithm that allows a job to migrate only when it requests or releases a resource set, then our algorithm also meets the deadlines with the same restriction on job migration, if given processors 4×(1+MAXP×⌈|P|×MAXPmin{m1,m2,…,mt}⌉) times as fast. (Here MAXP and |P| are computed based on the resource sets that tasks request.) For the special case that each task requests at most one resource, the bound of LP-EE-vpr collapses to 4×(1+⌈|R|min{m1,m2,…,mt}⌉). To the best of our knowledge, LP-EE-vpr is the first algorithm with proven performance guarantee for real-time scheduling of sporadic tasks with resource sharing on t-type heterogeneous multiprocessors.

Efficient schedulability tests for real-time embedded systems with urgent routines

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.

Juggling time concepts: complex metanarrative in Alejandro González Iñárritu’s 21 Grams

ABSTRACT - Starting with the explanation of metanarrative as a sort of self-reflexive storytelling (as defended by Kenneth Weaver Hope in his unpublished PhD. thesis), I propose to talk about enunciative practices that stress the telling more than the told. In line with some metaficcional practices applied to cinema, such as the ‘mindfuck’ film (Jonathan Eig, 2003), the ‘psychological puzzle film’ (Elliot Panek, 2003) and the ‘mind-game film’ (Thomas Elsaesser, 2009), I will address the manipulations that a narrative film endures in order to produce a more fruitful and complex experience for the viewer. I will particularly concentrate on the misrepresentation of time as a way to produce a labyrinthine work of fiction where the linear description of events is replaced by a game of time disclosure. The viewer is thus called upon to reconstruct the order of the various situations portrayed in a process that I call ‘temporal mapping’. However, as the viewer attempts to do this, the film, ironically, because of the intricate nature of the plot and the uncertain status of the characters, resists the attempt. There is a sort of teasing taking place between the film and its spectator: an invitation of decoding that is half-denied until the end, where the puzzle is finally solved. I will use three of Alejandro Iñárritu’s films to better convey my point: Amores perros (2000), 21 Grams (2003) and Babel (2006). I will consider Iñárritu’s methods to produce a non-linear storytelling as a way to stress the importance of time and its validity as one of the elements that make up for a metanarrative experience in films. I will focus especially on 21 Grams, which I consider to be a paragon of the labyrinth.

Maximum level and time to peak of dam-break waves on mobile horizontal bed

Journal of Hydraulic Engineering, Vol. 135, No. 11, November 1, 2009

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Sonographic features of portal hypertension in Schistosomiasis Mansoni

The diagnostic value of real-time sonography in the study of portal hypertension was assessed in 66 patients with hepatosplenic schistosomiasis mansoni, all with Symmers's fibrosis and esophageal varices. Seventy-one individuals without schistosomiasis were selected as controls. The inner diameters of the portal vessels were measured by sonography in all patients and controls: splenoportography was also performed in the schistosomal group. Intra-splenic pressure was over 30 cm of water in 44 of 60 patients with schistosomiasis. The upper limit of normality for portal vessel diameters was set through receiver operating characteristic curve at 12 mm for portal vein, 9 mm for splenic vein at splenic hilus, and 9 mm for superior mesenteric vein. The best discriminative vein for the diagnosis of portal hypertension was the splenic vein followed by the portal vein. A direct correlation was observed between the diameter of the splenic vein, measured by sonography, and the intra-splenic pressure. Except for the paraumbilical and mesenteric veins, more frequently identified by sonography, there was no statistical difference in the frequency of visualization of splanchnic vessels by sonography or splenoportography.

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.