Federico Montesino Pouzols

European Southern Observatory | ESO · Science Operation Software Department, ALMA Computing Team, Pipeline Systems Group

Protected areas are one of the main tools for halting the continuing global biodiversity crisis caused by habitat loss, fragmentation and other anthropogenic pressures. According to the Aichi Biodiversity Target 11 adopted by the Convention on Biological Diversity, the protected area network should be expanded to at least 17% of the terrestrial wor...

We introduce a novel approach to building corridors in spatial conservation prioritization. The underlying working principle is the use of a penalty structure in an iterative algorithm used for producing a spatial priority ranking. The penalty term aims to prevent loss or degradation of structural connections, or, equivalently, to promote to a high...

Habitat restoration is increasing in importance as a conservation action, compared with more traditional establishment of conservation areas. It is applied, for example, in the context of biodiversity offsetting, in which environmental impacts of economic activity are offset by additional compensating conservation efforts. We present a publicly ava...

We develop methods for conservation resource allocation, to help with decisions about targeting of protection, habitat management, maintenance and restoration or biodiversity offsetting. We construct a framework, where conservation actions have different responses for different biodiversity features in different environments, and in which uncertain...

We propose an automatic methodology framework for short- and long-term prediction of time series by means of fuzzy inference systems. In this methodology, fuzzy techniques and statistical techniques for nonparametric residual variance estimation are combined in order to build autoregressive predictive models implemented as fuzzy inference systems....

CASA, the Common Astronomy Software Applications, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can handle data from single-dish, aperture-synthesis, and Very Long Baseline In...

The challenge of balancing biodiversity protection with economic growth is epitomized by the development of renewable and unconventional energy, whose adoption is aimed at stemming the impacts of global climate change, yet has outpaced our understanding of biodiversity impacts. We evaluated the potential conflict between biodiversity protection and...

Effective planning of a large-scale restoration project is challenging, because of the range of factors that need to be considered (e.g. restoration of multiple habitats with varying degradation levels, multiple restoration goals and limited conservation resources). Ecological restoration planning studies typically focus on biodiversity and ecosyst...

Aim To quantify and compare species coverage in priority areas for conservation identified using species richness as opposed to approaches that use individual species range maps. Location Global. Methods We compare the coverage of species when global priority areas for conservation are identified based on (1) twelve species richness maps of all a...

Several imaging instruments are currently being constructed at neutron sources around the world. The Mantid software project provides an extensible framework that supports high-performance computing for data manipulation, analysis and visualisation of scientific data. At ISIS, IMAT (Imaging and Materials Science & Engineering) will offer unique tim...

Mammalian carnivores have suffered the biggest range contraction among all biodiversity and are particularly vulnerable to habitat loss and fragmentation. Therefore, we identified priority areas for the conservation of mammalian carnivores, while accounting for species-specific requirements for connectivity and expected agricultural and urban expan...

Complementarity and cost-efficiency are widely used principles for protected area network design. Despite the wide use and robust theoretical underpinnings, their effects on the performance and patterns of priority areas are rarely studied in detail. Here we compare two approaches for identifying the management priority areas inside the global prot...

Reliance on fossil fuels is causing unprecedented climate change and is accelerating environmental degradation and global biodiversity loss. Together, climate change and biodiversity loss, if not averted urgently, may inflict severe damage on ecosystem processes, functions and services that support the welfare of modern societies. Increasing renewa...

A new neutron imaging and diffraction facility, called IMAT, is currently being commissioned at the ISIS pulsed neutron spallation source. IMAT will take advantage of neutron time-of-flight measurement techniques for flexible neutron energy selection and effective energy discrimination. The instrument will be completed and commissioned within the n...

Large-scale ecological restoration is receiving increasing attention because of its contribution to biodiversity conservation, ecosystem services provision, and climate change mitigation and adaptation. One of the biggest challenges facing large-scale restoration is to identify and prioritize restoration action/s that, if implemented, can achieve t...

Resources for conserving biodiversity are invariably insufficient. This situation creates the need for transparent, systematic frameworks to help stakeholders prioritize the allocation of resources across multiple management actions. We developed a novel framework that explicitly prioritizes actions to minimize the impacts of several threats across...

The authors regret a misprint in the citation year of Telesh I.V., Schubert H., Skarlato S.O. Publication year is 2011, not 2010. The correct citation is: Telesh I.V., Schubert H., Skarlato S.O., 2011. Revisiting Remane’s concept: evidence for high plankton diversity and a protistan species maximum in the horohalinicum of the Baltic Sea. Mar. Ecol...

Substantial ecological changes occurred in the 1970s in the Northern Baltic during a temporary period of low salinity (S). This period was preceded by an episodic increase in the rainfall over the Baltic Sea watershed area. Several climate models, both global and regional, project an increase in the runoff of the Northern latitudes due to proceedin...

Mantid: A high performance framework for the reduction and analysis of muon spin resonance and neutron scattering data.

Mantid: A high performance framework for the reduction and analysis of muon spin resonance and neutron scattering data.

Mantid: A high performance framework for the reduction and analysis of muon spin resonance and neutron scattering data.

Excel spreadsheet tool for calculating minimum offset multipliers.

Between 1990 and 2007, 15 southern white (Ceratotherium simum simum) and black (Diceros bicornis) rhinoceroses on average were killed illegally every year in South Africa. Since 2007 illegal killing of southern white rhinoceros for their horn has escalated to >950 individuals/year in 2013. We conducted an ecological–economic analysis to determine w...

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Biodiversity offsetting, which means compensation for ecological and environmental damage caused by development activity, has recently been gaining strong political support around the world. One common criticism levelled at offsets is that they exchange certain and almost immediate losses for uncertain future gains. In the case of restoration offse...

Aim Global conservation policies, such as the Convention on Biological Diversity ( CBD ) decision to aim for the protection of 17% of the area of terrestrial ecosystems by 2020, are typically realized at national levels. We investigate the difference between continentally coordinated conservation versus nationally devolved conservation, in a manner...

Deep learning has proven to be beneficial for complex tasks such as classifying images. However, this approach has been mostly applied to static datasets. The analysis of non-stationary (e.g., concept drift) streams of data involves specific issues connected with the temporal and changing nature of the data. In this paper, we propose a proof-of-con...

A method for performing kernel smoothing regression in an incremental, adaptive manner is described. A simple and fast combination of incremental vector quantization with kernel smoothing regression using adaptive bandwidth is shown to be effective for online modeling of environmental datasets. The approach proposed is to apply kernel smoothing reg...

Soft computing techniques and particularly fuzzy inference systems are gaining momentum as tools for network traffic modeling, analysis and control. Efficient hardware implementations of these techniques that can achieve real-time operation in high-speed networking equipment as well as other highly time-constrained application fields is however an...

A method for performing kernel smoothing regression in an online adaptive manner is presented. The approach proposed is to apply kernel smoothing regression on an incremental estimation of the (evolving) probability distribution of the incoming data stream rather than the sequence of observations. This is achieved by performing vector quantization...

The structure and behavior of packet switched networks is difficult to model in a way comparable to many natural and artificial systems. Nonetheless, the Internet is an outstanding and challenging case because of its incredibly fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core co...

This chapter looks into the practical implementation of some of the fuzzy inference systems proposed in previous chapters. Both architectural and operational constraints are considered. The focus is on an open FPGA-based hardware platform for the implementation of efficient fuzzy inference systems for solving problems in high-performance packet swi...

Current network measurement systems are becoming highly sophisticated, producing huge amounts of convoluted measurement data and statistics. As a very common case, those networks implementing statistics reporting based on the NetFlow [15] technology can generate several GBs of data on a daily basis. In addition, these measurements are often very ha...

In this chapter, we focus on long-term modeling and prediction of univariate nonlinear time series. First, a method for long-term time series prediction by means of fuzzy inference systems combined with residual variance estimation techniques is developed and validated through a number of time series prediction benchmarks. This method provides an a...

This chapter deals with control of network traffic in routers as well as end-to-end flows. First it is proposed an scheme for implementing end-to-end traffic control mechanisms through fuzzy inference systems. A comparative evaluation of simulation and implementation results from the fuzzy rate controler as compared to that of traditional TCP flow...

Understanding the dynamics and performance of packet switched networks on the basis of measurements enables practitioners to optimize resources. As network measurement research further advances and new measurement tools and infrastructures are available, the task of network operation becomes more and more complex. In this chapter we apply the metho...

As other complex systems in social and natural sciences as well as in engineering, the Internet is hard to understand from a technical point of view. Packet switched networks defy analytical modeling. The Internet is an outstanding and challenging case because of its fast development, unparalleled heterogeneity and the inherent lack of measurement...

This paper proposes a method for the identification of evolving fuzzy Takagi-Sugeno systems based on the Optimally-Pruned Extreme Learning Machine (OP-ELM) methodology. We describe ELM which is a simple yet accurate and fast learning algorithm for training single-hidden layer feed-forward artificial neural networks (SLFNs) with random hidden neuron...

This paper proposes an approach to the identification of evolving fuzzy Takagi–Sugeno systems based on the optimally pruned extreme learning machine (OP-ELM) methodology. First, we describe ELM, a simple yet accurate learning algorithm for training single-hidden layer feed-forward artificial neural networks with random hidden neurons. We then descr...

This paper analyzes the impact of different detrending approaches on the performance of a variety of computational intelligence (CI) models. Three approaches are compared: Linear, nonlinear detrending (based on empirical mode decomposition) and first-differencing. Five representative CI methods are evaluated: Dynamic evolving neural-fuzzy inference...

We analyze the use of clustering methods for the automatic identification of fuzzy inference models for autoregressive prediction of time series. A methodology that combines fuzzy methods and residual variance estimation techniques is followed. A nonparametric residual variance estimator is used for a priori input and model selection. A simple sche...

A new software tool for time series prediction by means of fuzzy inference systems is reported. This tool, named xftsp, implements a novel methodology for time series prediction based on methods for automatic fuzzy systems identification and supervised learning combined with statistical methods for nonparametric residual variance estimation. xftsp...

We address, by means of fuzzy linguistic summaries, two related problems: summarizing network flow statistics and making these statistics human-readable. Two complementary summarization methods are developed. First, a fixed set of protoforms of interest is defined, and the ones with a higher truth value are shown to the user as simple on-line summa...

We apply fuzzy techniques for system identification and supervised learning in order to develop fuzzy inference based autoregressors for time series prediction. An automatic methodology framework that combines fuzzy techniques and statistical techniques for nonparametric residual variance estimation is proposed. Identification is performed through...

End-to-end Internet packet dynamics is a complex problem for which models available to date are at best incomplete. A major research problem in Internet transport layer protocols is the development of rate control mechanisms that can cope with the requirements of a growing diversity of technologies, applications and services. This paper describes n...

Resumen Los sistemas de medida y estimación activa de prestaciones de redes se basan en la medida de la respuesta de la red frente a tráfico de prueba transmitido entre nodos de extremo a extremo. En esta ponencia presentamos un entorno integrado de medida y estimación activa de prestaciones. El entorno generaliza, unifica y amplía el conjunto de t...

In this communication we present the activities related to the development of fuzzy logic based systems at the Microelectronics Institute of Seville (Spain). These activities regard with the design of circuits and systems that operate in fuzzy logic, the development of CAD tools for fuzzy logic and the accomplishment of applications that use fuzzy...

A comparative analysis of state-of-the-art active probing tools for bandwidth estimation is outlined. Techniques and tools for capacity, available bandwidth and bulk transfer capacity estimation are simul- taneously assessed. First, a generic framework for the design of active bandwidth estimation tools is proposed as a result of our analysis of th...

El IETF ha desarrollado un conjunto de protocolos y tecnologías para el transporte de datos y señalización en tiempo real, así como para la descripción de sesiones multimedia y negociación de capacidades de los participantes. Estos protocolos, apoyados por otros servicios ya existentes, como los de directorio o el DNS, constituyen un modelo abierto...

Soft computing techniques are gaining momentum as tools for network traffic modeling, analysis and control. Effi-cient hardware implementations of these techniques that can achieve real-time operation in high-speed communications equipment is however an open problem. This paper describes a platform for the development of fuzzy systems with appli-ca...

Recent research results propose and show the usefulness of a fuzzy control based approach to the development of intelligent systems for congestion control in Internet routers. However, adoption of this new technology is handicapped because of operational requirements, mostly in terms of inference speed, a hard constrain on the practical implementat...

Proc. Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU 2006), Paris, July. 2-7, 2006. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expecte...

Summary Network performance active measurement and estimation systems are based on the response to test traffic between two end-points in the network. This paper presents an integrated environment for the active measurement and estimation of network performance. The environment has been conceived as a generalization, unification and extension to th...

A major research problem in In- ternet transport and network lay- ers is the development of trac reg- ulation mechanisms that can cope with the requirements of a grow- ing diversity of technologies, ap- plications and services. This pa- per presents novel mechanisms for intelligent trac scheduling in In- ternet routers by means of fuzzy logic based...

In the context of a previously proposed methodology frame- work for time series prediction, we use a clustering technique in order to identify fuzzy inference systems for the regressive modeling of time series. We propose a modified version of the method for the identification of fuzzy rules based on the subtractive clustering method proposed by Ch...