A syntactic approach to combining functional notation, lazy evaluation, and higher-order in LP systems

Nondeterminism and partially instantiated data structures give logic programming expressive power beyond that of functional programming. However, functional programming often provides convenient syntactic features, such as having a designated implicit output argument, which allow function cali nesting and sometimes results in more compact code. Functional programming also sometimes allows a more direct encoding of lazy evaluation, with its ability to deal with infinite data structures. We present a syntactic functional extensión, used in the Ciao system, which can be implemented in ISO-standard Prolog systems and covers function application, predefined evaluable functors, functional definitions, quoting, and lazy evaluation. The extensión is also composable with higher-order features and can be combined with other extensions to ISO-Prolog such as constraints. We also highlight the features of the Ciao system which help implementation and present some data on the overhead of using lazy evaluation with respect to eager evaluation.

The role of cover crops in irrigated systems: water balance, nitrate leaching and soil mineral nitrogen accumulation

Soil salinity and salt leaching are a risk for sustainable agricultural production in many irrigated areas. This study was conducted over 3.5 years to determine how replacing the usual winter fallow with a cover crop (CC) affects soil salt accumulation and salt leaching in irrigated systems. Treatments studied during the period between summer crops were: barley (Hordeum vulgare L.), vetch (Vicia villosa L.) and fallow. Soil water content was monitored daily to a depth of 1.3 m and used with the numerical model WAVE to calculate drainage. Electrical conductivity (EC) was measured in soil solutions periodically, and in the soil saturated paste extracts before sowing CC and maize. Salt leaching was calculated multiplying drainage by total dissolved salts in the soil solution, and use to obtain a salt balance. Total salt leaching over the four winter fallow periods was 26 Mg ha−1, whereas less than 18 Mg ha−1 in the presence of a CC. Periods of salt gain occurred more often in the CC than in the fallow. By the end of the experiment, net salt losses occurred in all treatments, owing to occasional periods of heavy rainfall. The CC were more prone than the fallow to reduce soil salt accumulation during the early growth stages of the subsequent cash crop.

The role of cover crops in irrigated systems: Soil salinity and salt leaching

Soil salinity and salt leaching are a risk for sustainable agricultural production in many irrigated areas. This study was conducted over 3.5 years to determine how replacing the usual winter fallow with a cover crop (CC) affects soil salt accumulation and salt leaching in irrigated systems. Treatments studied during the period between summer crops were: barley (Hordeum vulgare L.), vetch (Vicia villosa L.) and fallow. Soil water content was monitored daily to a depth of 1.3 m and used with the numerical model WAVE to calculate drainage. Electrical conductivity (EC) was measured in soil solutions periodically, and in the soil saturated paste extracts before sowing CC and maize. Salt leaching was calculated multiplying drainage by total dissolved salts in the soil solution, and use to obtain a salt balance. Total salt leaching over the four winter fallow periods was 26 Mg ha−1, whereas less than 18 Mg ha−1 in the presence of a CC. Periods of salt gain occurred more often in the CC than in the fallow. By the end of the experiment, net salt losses occurred in all treatments, owing to occasional periods of heavy rainfall. The CC were more prone than the fallow to reduce soil salt accumulation during the early growth stages of the subsequent cash crop.

A second order in time modified Lagrange-Galerkin finite element method for the incompressible Navier-Stokes equations

We introduce a second order in time modified Lagrange--Galerkin (MLG) method for the time dependent incompressible Navier--Stokes equations. The main ingredient of the new method is the scheme proposed to calculate in a more efficient manner the Galerkin projection of the functions transported along the characteristic curves of the transport operator. We present error estimates for velocity and pressure in the framework of mixed finite elements when either the mini-element or the $P2/P1$ Taylor--Hood element are used.

Integration of Correlation Processes in Design Systems.

The integration of correlation processes in design systems has as a target measurements in 3D directly and according to the users criteria in order to generate the required database for the development of the project. In the phase of photogrammetric works, internal and external orientation parameters are calculated and stereo models are created from standard images. The aforementioned are integrated in the system where the measurement of the selected items is done by applying developed correlation algorithms. The processing period has the tools to carry out the calculations in an easy and automatic way, as well as image measurement techniques to acquire the most correct information. The proposed software development is done on Visual Studio platforms for PC, applying the most apt codes and symbols according to the terms of reference required for the design. The results of generating the data base in an interactive way with the geometric study of the structures, facilitates and improves the quality of the works in the projects.

Effect of soiling in CPV systems

The effect of soiling in flat PV modules has been already studied, causing a reduction of the electrical output of 4% on average. For CPV's, as far as soiling produces light scattering at the optical collector surface, the scattered rays should be definitively lost because they cannot be focused onto the receivers again. While the theoretical study becomes difficult because soiling is variable at different sites, it becomes easier to begin the monitoring of the real field performance of concentrators and then raise the following question: how much does the soiling affect to PV concentrators in comparison with flat panels?? The answers allow to predict the PV concentrator electrical performance and to establish a pattern of cleaning frequency. Some experiments have been conducted at the IES-UPM and CSES-ANU sites, consisting in linear reflective concentration systems, a point focus refractive concentrator and a flat module. All the systems have been measured when soiled and then after cleaning, achieving different increases of ISC. In general, results show that CPV systems are more sensitive to soiling than flat panels, accumulating losses in ISC of about 14% on average in three different tests conducted at IESUPM and CSES-ANU test sites in Madrid (Spain) and Canberra (Australia). Some concentrators can reach losses up to 26% when the system is soiled for 4 months of exposure.

Non-Maxwellian electron distributions in time-dependent simulations of low-Z materials illuminated by a high-intensity X-ray laser

The interaction of high intensity X-ray lasers with matter is modeled. A collisional-radiative timedependent module is implemented to study radiation transport in matter from ultrashort and ultraintense X-ray bursts. Inverse bremsstrahlung absorption by free electrons, electron conduction or hydrodynamic effects are not considered. The collisional-radiative system is coupled with the electron distribution evolution treated with a Fokker-Planck approach with additional inelastic terms. The model includes spontaneous emission, resonant photoabsorption, collisional excitation and de-excitation, radiative recombination, photoionization, collisional ionization, three-body recombination, autoionization and dielectronic capture. It is found that for high densities, but still below solid, collisions play an important role and thermalization times are not short enough to ensure a thermal electron distribution. At these densities Maxwellian and non-Maxwellian electron distribution models yield substantial differences in collisional rates, modifying the atomic population dynamics.

A fuzzy approach to risk analysis in information systems

Assets are interrelated in risk analysis methodologies for information systems promoted by international standards. This means that an attack on one asset can be propagated through the network and threaten an organization's most valuable assets. It is necessary to valuate all assets, the direct and indirect asset dependencies, as well as the probability of threats and the resulting asset degradation. These methodologies do not, however, consider uncertain valuations and use precise values on different scales, usually percentages. Linguistic terms are used by the experts to represent assets values, dependencies and frequency and asset degradation associated with possible threats. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms.

A fuzzy extension of MAGERIT methodology for risk analysis in information systems

We propose a fuzzy approach to deal with risk analysis for information systems. We extend MAGERIT methodology that valuates the asset dependencies to a fuzzy framework adding fuzzy linguistic terms to valuate the different elements (terminal asset values, asset dependencies as well as the probability of threats and the resulting asset degradation) in risk analysis. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms and, finally, the results of these operations are translated into a linguistic term by means of a similarity function.

Detecting false testimonies in reputation systems using self-organizing maps

It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

Knowledge Modelling in Multiagent Systems: The Case of the Management of a National Network

This paper presents the knowledge model of a distributed decision support system, that has been designed for the management of a national network in Ukraine. It shows how advanced Artificial Intelligence techniques (multiagent systems and knowledge modelling) have been applied to solve this real-world decision support problem: on the one hand its distributed nature, implied by different loci of decision-making at the network nodes, suggested to apply a multiagent solution; on the other, due to the complexity of problem-solving for local network administration, it was useful to apply knowledge modelling techniques, in order to structure the different knowledge types and reasoning processes involved. The paper sets out from a description of our particular management problem. Subsequently, our agent model is described, pointing out the local problem-solving and coordination knowledge models. Finally, the dynamics of the approach is illustrated by an example.

Emotions and the Engineering of Adaptiveness in Complex Systems

A major challenge in the engineering of complex and critical systems is the management of change, both in the system and in its operational environment. Due to the growing of complexity in systems, new approaches on autonomy must be able to detect critical changes and avoid their progress towards undesirable states. We are searching for methods to build systems that can tune the adaptability protocols. New mechanisms that use system-wellness requirements to reduce the influence of the outer domain and transfer the control of uncertainly to the inner one. Under the view of cognitive systems, biological emotions suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories to causally connect to the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress.

Human Factor in Resilience Systems

This paper shows the importance of a holistic comprehension of the Earth as a living planet, where man inhabits and is exposed to environmental incidences of different nature. The aim of the paper here summarized is a reflection on all these concepts and scientific considerations related to the important role of men in the handling of natural hazards. Our Planet is an unstable and dynamical system highly sensitive to initial conditions, as proposed by Chaos theory (González-Miranda 2004); it is a complex organic whole, which responds to minimal variations which can affect several natural phenomena such as plate tectonics, solar flares, fluid turbulences, landscape formation, forest fires, growth and migration of populations and biological evolution. This is known as the “butterfly effect” (Lorenz 1972), which means that a small change of the system causes a chain of events leading to large-scale unpredictable consequences. The aim of this work is dwelling on the importance of the knowledge of these natural and catastrophic geological, biological and human systems so much sensible to equilibrium conditions, to prevent, avoid and mend their effects, and to face them in a resilient way

Emotions and the Engineering of Adaptiveness in Complex Systems

A major challenge in the engineering of complex and critical systems is the management of change, both in the system and in its operational environment. Due to the growing of complexity in systems, new approaches on autonomy must be able to detect critical changes and avoid their progress towards undesirable states. We are searching for methods to build systems that can tune the adaptability protocols. New mechanisms that use system-wellness requirements to reduce the influence of the outer domain and transfer the control of uncertainly to the inner one. Under the view of cognitive systems, biological emotions suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories to causally connect to the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress.

Eventual election of multiple leaders for solving consensus in anonymous systems

In classical distributed systems, each process has a unique identity. Today, new distributed systems have emerged where a unique identity is not always possible to be assigned to each process. For example, in many sensor networks a unique identity is not possible to be included in each device due to its small storage capacity, reduced computational power, or the huge number of devices to be identified. In these cases, we have to work with anonymous distributed systems where processes cannot be identified. Consensus cannot be solved in classical and anonymous asynchronous distributed systems where processes can crash. To bypass this impossibility result, failure detectors are added to these systems. It is known that ? is the weakest failure detector class for solving consensus in classical asynchronous systems when amajority of processes never crashes. Although A? was introduced as an anonymous version of ?, to find the weakest failure detector in anonymous systems to solve consensus when amajority of processes never crashes is nowadays an open question. Furthermore, A? has the important drawback that it is not implementable. Very recently, A? has been introduced as a counterpart of ? for anonymous systems. In this paper, we show that the A? failure detector class is strictly weaker than A? (i.e., A? provides less information about process crashes than A?). We also present in this paper the first implementation of A? (hence, we also show that A? is implementable), and, finally, we include the first implementation of consensus in anonymous asynchronous systems augmented with A? and where a majority of processes does not crash.