Requirements definition and testing of the new version of multi-mission generic monitoring system (GEMS) v 4.4 for operations at Eumetsat

EUMETSAT (www.eumetsat.int) e’ l’agenzia europea per operazioni su satelliti per monitorare clima, meteo e ambiente terrestre. Dal centro operativo situato a Darmstadt (Germania), si controllano satelliti meteorologici su orbite geostazionarie e polari che raccolgono dati per l’osservazione dell’atmosfera, degli oceani e della superficie terrestre per un servizio continuo di 24/7. Un sistema di monitoraggio centralizzato per programmi diversi all’interno dell’ambiente operazionale di EUMETSAT, e’ dato da GEMS (Generic Event Monitoring System). Il software garantisce il controllo di diverse piattaforme, cross-monitoring di diverse sezioni operative, ed ha le caratteristiche per potere essere esteso a future missioni. L’attuale versione della GEMS MMI (Multi Media Interface), v. 3.6, utilizza standard Java Server Pages (JSP) e fa uso pesante di codici Java; utilizza inoltre files ASCII per filtri e display dei dati. Conseguenza diretta e’ ad esempio, il fatto che le informazioni non sono automaticamente aggiornate, ma hanno bisogno di ricaricare la pagina. Ulteriori inputs per una nuova versione della GEMS MMI vengono da diversi comportamenti anomali riportati durante l’uso quotidiano del software. La tesi si concentra sulla definizione di nuovi requisiti per una nuova versione della GEMS MMI (v. 4.4) da parte della divisione ingegneristica e di manutenzione di operazioni di EUMETSAT. Per le attivita’ di supporto, i test sono stati condotti presso Solenix. Il nuovo software permettera’ una migliore applicazione web, con tempi di risposta piu’ rapidi, aggiornamento delle informazioni automatico, utilizzo totale del database di GEMS e le capacita’ di filtri, insieme ad applicazioni per telefoni cellulari per il supporto delle attivita’ di reperibilita’. La nuova versione di GEMS avra’ una nuova Graphical User Interface (GUI) che utilizza tecnologie moderne. Per un ambiente di operazioni come e’ quello di EUMETSAT, dove l’affidabilita’ delle tecnologie e la longevita’ dell’approccio scelto sono di vitale importanza, non tutti gli attuali strumenti a disposizione sono adatti e hanno bisogno di essere migliorati. Allo stesso tempo, un’ interfaccia moderna, in termini di visual design, interattivita’ e funzionalita’, e’ importante per la nuova GEMS MMI.

The CIAO Multi-Dialect Compiler and System: An Experimentation Workbench for Future (C)LP Systems

CIAO is an advanced programming environment supporting Logic and Constraint programming. It offers a simple concurrent kernel on top of which declarative and non-declarative extensions are added via librarles. Librarles are available for supporting the ISOProlog standard, several constraint domains, functional and higher order programming, concurrent and distributed programming, internet programming, and others. The source language allows declaring properties of predicates via assertions, including types and modes. Such properties are checked at compile-time or at run-time. The compiler and system architecture are designed to natively support modular global analysis, with the two objectives of proving properties in assertions and performing program optimizations, including transparently exploiting parallelism in programs. The purpose of this paper is to report on recent progress made in the context of the CIAO system, with special emphasis on the capabilities of the compiler, the techniques used for supporting such capabilities, and the results in the áreas of program analysis and transformation already obtained with the system.

The CIAO multi-dialect compiler and system: An experimentation workbench for future (C)LP systems

Abstract is not available.

The CIAO multi-dialect compiler and system: A demo and status report

Abstract is not available

An online failure prediction system for private IaaS platforms

The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines di_erent types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments.

Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots

Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

Development of the infrastructure for a multi-agent traffic management system simulation

This document contains detailed description of the design and the implementation of a multi-agent application controlling traffic lights in a city together with a system for simulating traffic and testing. The goal of this thesis is to design and build a simplified intelligent and distributed solution to the problem with the traffic in the big cities following different good practices in order to allow future refining of the model of the real world. The problem of the traffic in the big cities is still a problem that cannot be solved. Not only is the increasing number of cars a reason for the traffic jams, but also the way the traffic is organized. Usually, the intersections with traffic lights are replaced by roundabouts or interchanges to increase the number of cars that can cross the intersection in certain time. But still there are places where the infrastructure cannot be changed and the traffic light semaphores are the only way to control the car flows. In real life, the traffic lights have a predefined plan for change or they receive information from a centralized system when and how they have to change. But what if the traffic lights can cooperate and decide on their own when and how to change? Using this problem, the purpose of the thesis is to explore different agent-based software engineering approaches to design and build a non-conventional distributed system. From the software engineering point of view, the goal of the thesis is to apply the knowledge and use the skills, acquired during the various courses of the master program in Software Engineering, while solving a practical and complex problem such as the traffic in the cities.

Power-Aware Multi-Objective Evolvable Hardware System on an FPGA

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

The design and implementation of a multi-task batch operating system and paging interpreter for the PDP-II /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

Development of a multi-tiered speech annotation system for accented English

This paper discusses methodological issues in the development of a multitiered, phonetic annotation system, intended to capture pronunciation variation in the speech of second language learners and to serve in construction of a data base for training ASR models to recognize major pronunciation variants in the assessment of accented English.

Breakdown of hydrostatic balance at convective scales in the forecast errors in the Met Office Unified Model

For data assimilation in numerical weather prediction, the initial forecast-error covariance matrix Pf is required. For variational assimilation it is particularly important to prescribe an accurate initial matrix Pf, since Pf is either static (in the 3D-Var case) or constant at the beginning of each assimilation window (in the 4D-Var case). At large scales the atmospheric flow is well approximated by hydrostatic balance and this balance is strongly enforced in the initial matrix Pf used in operational variational assimilation systems such as that of the Met Office. However, at convective scales this balance does not necessarily hold any more. Here we examine the extent to which hydrostatic balance is valid in the vertical forecast-error covariances for high-resolution models in order to determine whether there is a need to relax this balance constraint in convective-scale data assimilation. We use the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and a 1.5 km resolution version of the Unified Model for a case study characterized by the presence of convective activity. An ensemble of high-resolution forecasts valid up to three hours after the onset of convection is produced. We show that at 1.5 km resolution hydrostatic balance does not hold for forecast errors in regions of convection. This indicates that in the presence of convection hydrostatic balance should not be enforced in the covariance matrix used for variational data assimilation at this scale. The results show the need to investigate covariance models that may be better suited for convective-scale data assimilation. Finally, we give a measure of the balance present in the forecast perturbations as a function of the horizontal scale (from 3–90 km) using a set of diagnostics. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office