A computer implementation of the partition of the unity procedure and its application to arthropod population dynamics. A case study on the European grape berry moth

This paper presents a new procedure to construct families of spatial approximation-prediction functions which depend on several parameters. The method is based on partitions of the unity. In order to find optimal functions in these families we introduce a Vietoris simplicial set associated to an influence radius. We consider error estimators induced by these Vietoris simplicial sets. A computational implementation of these mathematical models has been developed to be applied to any kind of finite discrete data. Our methods provide a useful tool for the analysis of the spatial distribution of species, which is imperative for developing accurate and efficient management of endangered and invasive species, biological conservation programs, etc. We demonstrate the application of our method to the analysis of the spatial distribution of the grape moth Lobesia botrana (Lepidoptera: Tortricidae) in the vineyards of La Rioja obtaining useful results for the management of this pest.     

Multi‐agent system for knowledge‐based event recognition and composition

This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. A perception agent (plurisensory agent and visual agent)‐based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre‐defined patterns as higher‐level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge‐based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.     

A non-linear forecasting system for the Ebro River at Zaragoza,Spain

This paper addresses the problem of modelling and forecasting river flows and levels based on flood routing type models. Though this is generally considered as a non-linear problem, very often it is treated by linear models. A forecasting system is built for the level and flow measurements registered in the Ebro River at the station of Zaragoza (Spain), with the main purpose of preventing floods in an early stage of development. The model takes advantage of the wealth of data available at the Ebro Hydrographical Confederation and is non-linear in essence. The system is obtained by application of system identification tools, starting from a linear specification and relating the parameters of the model estimated to some transformation of the input in the system. Such transformation requires the application of a Kalman Filter in a particular set up and the full estimation algorithm involves an iterative procedure. The model is fully developed on a data set and is thoroughly validated on a different span of data.     

A percentile system optimization approach with and without path enumeration

In this paper we deal with the travel time reliability PUE (probabilistic user equilibrium) problem studied by Lo et al. (2006) [12] and Nie (2011) [15] and we propose an alternative model that assumes a location-scale family for the path travel times, whose means and variances are evaluated in terms of link travel times. This avoids the use of the central limit theorem and convolutions providing a flexible and simple alternative. Contrary to the most existing models that require path enumeration or an iterative method to add paths sequentially, we present a percentile system optimization in its two versions: with and without path enumeration. Two examples of applications, one of them real, are used to illustrate the power of the proposed method. The cpu times required to solve the problem seem reasonable. In addition, we answer an open question raised by Nie (2011) [15] about the permutability of percentiles and partial derivatives of route travel times with respect to route flows. A family of counterexamples is given to demonstrate that the two operations: (a) obtain percentiles and (b) partial derivation of route travel times do not commute. Finally, to reproduce the trial-and-error sequence followed by users when selecting paths, we also present an algorithm that simulates this iterative process and shows that the final long-term user behavior coincides with PUE (probabilistic user equilibrium) problem resulting from some existing models.     

Next generation session management for 3D teleimmersive interactive environments

In the recent past we have seen a boom of distributed interactive multimedia environments which use multiple correlated media sensors, multi-view displays, and advanced haptic-audio-visual user interfaces for teleimmersive gaming, business meetings and other collaborative activities. However, when we investigate the emerging teleimmersive environments closer, we realize that their overall session management, including end-to-end session setup, establishment and run-time management are not appropriate for the new demands that these environments present. These environments are cyber-physical rooms that demand (a) large scale of multi-sensory devices across geographically-distributed locations and (b) interaction with each other in synchronous and real-time manner. To deal with the new teleimmersive demands, we present a new session management design with (a) session initiation protocol(s) that understand media correlations, (b) view-based multi-stream topology establishment among multiple parties, (c) efficient, light-weight and distributed session monitoring with querying and debugging capabilities, (d) flexible view-based session adaptation with efficient topology adjustments, and (e) light-weighted and consistent session tear-down protocols. The presented design of the next generation session management protocols, services, algorithms and data structures is based on our extensive experiences with building 3D teleimmersive interactive systems, experimenting with high impact teleimmersive applications and deploying such environments at various venues.     

Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data

An experimental site was set up in a large, flat and homogeneous area of rice crops for the validation of satellite derived land surface temperature (LST). Experimental campaigns were held in the summers of 2002-2004, when rice crops show full vegetation cover. LSTs were measured radiometrically along transects covering an area of 1 km². A total number of four thermal radiometers were used, which were calibrated and inter-compared through the campaigns. Radiometric temperatures were corrected for emissivity effects using field emissivity and downwelling sky radiance measurements. A database of ground-based LSTs corresponding to morning, cloud-free overpasses of Envisat/Advanced Along-Track Scanning Radiometer (AATSR) and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. Ground LSTs ranged from 25 to 32 °C, with uncertainties between ± 0.5 and ± 0.9 °C. The largest part of these uncertainties was due to the spatial variability of surface temperature. The database was used for the validation of LSTs derived from the operational AATSR and MODIS split-window algorithms, which are currently used to generate the LST product in the L2 level data. A quadratic, emissivity dependent split-window equation applicable to both AATSR and MODIS data was checked as well. Although the number of cases analyzed is limited (five concurrences for AATSR and eleven for MODIS), it can be concluded that the split-window algorithms work well, provided that the characteristics of the area are adequately prescribed, either through the classification of the land cover type and the vegetation cover, or with the surface emissivity. In this case, the AATSR LSTs yielded an average error or bias of − 0.9 °C (ground minus algorithm), with a standard deviation of 0.9 °C. The MODIS LST product agreed well with the ground LSTs, with differences comparable or smaller than the uncertainties of the ground measurements for most of the days (bias of + 0.1 °C and standard deviation of 0.6 °C, for cloud-free cases and viewing angles smaller than 60°). The quadratic split-window algorithm resulted in small average errors (+ 0.3 °C for AATSR and 0.0 °C for MODIS), with differences not exceeding ± 1.0 °C for most of the days (standard deviation of 0.9 °C for AATSR and 0.5 °C for MODIS).     

Weak and strong basic resins for uranium recovery

Summary Resins were synthesized by crosslinking of linear polyethyleneimine and subsequent N-methylation. The retention properties of these resins, for copper (pH=0 to 4); for uranium (pH=0 to 3) and for iron (pH=0 to 2) were studied. The maximum capacity of adsorption for uranium and the elution of uranium with sulphuric acid and sodium carbonate were determined. The resins, in general, do not retain iron. The thermal stability was also studied.     

Polyethyleneimine supports for resins with retention properties for heavy metals part I

Summary Resins with retention properties for copper (II), and uranium (VI) have been synthesized by crosslinking of polyethyleneimine with 1,4-dibromo-2-butene and subsequent alkylation with dimethyl sulphate. The influence of pH on the retention, maximum capacity of load and elution assays were determined.