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.

Vibrations loads in the process of designing scientific spacecraft payloads

Scientific missions constitute fundamental cornerstones of space agencies such as ESA and NASA. Modern astronomy could not be understood without the data provided by these missions. Scientists need to design very carefully onboard instruments. Payloads have to survive the crucial launch moment and later perform well in the really harsh space environ-ment. It is very important that the instrument conceptual idea can be engineered to sustain all those loads

QKD in dense WDM passive optical networks

Quantum cryptography in communications networks

A review of load models for the prediction of footfall-induced vibration in structures

Crowd induced dynamic loading in large structures, such as gymnasiums or stadium, is usually modelled as a series of harmonic loads which are defined in terms of their Fourier coefficients. Different values of these coefficients that were obtained from full scale measurements can be found in codes. Recently, an alternative has been proposed, based on random generation of load time histories that take into account phase lag among individuals inside the crowd. This paper presents the testing done on a structure designed to be a gymnasium. Two series of dynamic test were performed on the gym slab. For the first test an electrodynamic shaker was placed at several locations and during the second one people located inside a marked area bounced and jumped guided by different metronome rates. A finite element model (FEM) is presented and a comparison of numerically predicted and experimentally observed vibration modes and frequencies has been used to assess its validity. The second group of measurements will be compared with predictions made using the FEM model and three alternatives for crowd induced load modelling.

Effects of traffic loads on reinforced concrete railroad culverts

In the context of the present conference paper culverts are defined as an opening or conduit passing through an embankment usually for the purpose of conveying water or providing safe pedestrian and animal crossings under rail infrastructure. The clear opening of culverts may reach values of up to 12m however, values around 3m are encountered much more frequently. Depending on the topography, the number of culverts is about 10 times that of bridges. In spite of this, their dynamic behavior has received far less attention than that of bridges. The fundamental frequency of culverts is considerably higher than that of bridges even in the case of short span bridges. As the operational speed of modern high-speed passenger rail systems rises, higher frequencies are excited and thus more energy is encountered in frequency bands where the fundamental frequency of box culverts is located. Many research efforts have been spent on the subject of ballast instability due to bridge resonance, since it was first observed when high-speed trains were introduced to the Paris/Lyon rail line. To prevent this phenomenon from occurring, design codes establish a limit value for the vertical deck acceleration. Obviously one needs some sort of numerical model in order to estimate this acceleration level and at that point things get quite complicated. Not only acceleration but also displacement values are of interest e.g. to estimate the impact factor. According to design manuals the structural design should consider the depth of cover, trench width and condition, bedding type, backfill material, and compaction. The same applies to the numerical model however, the question is: What type of model is appropriate for this job? A 3D model including the embankment and an important part of the soil underneath the culvert is computationally very expensive and hard to justify taking into account the associated costs. Consequently, there is a clear need for simplified models and design rules in order to achieve reasonable costs. This paper will describe the results obtained from a 2D finite element model which has been calibrated by means of a 3D model and experimental data obtained at culverts that belong to the high-speed railway line that links the two towns of Segovia and Valladolid in Spain

Crop rotation and residues influence N2O emission and N efficiency rather than tillage under a rainfed Mediterranean agroecosystem

Conservation tillage and crop rotation have spread during the last decades because promotes several positive effects (increase of soil organic content, reduction of soil erosion, and enhancement of carbon sequestration) (Six et al., 2004). However, these benefits could be partly counterbalanced by negative effects on the release of nitrous oxide (N2O) (Linn and Doran, 1984). There is a lack of data on long-term tillage system study, particularly in Mediterranean agro-ecosystems. The aim of this study was to evaluate the effects of long-term (>17 year) tillage systems (no tillage (NT), minimum tillage (MT) and conventional tillage (CT)); and crop rotation (wheat (W)-vetch (V)-barley (B)) versus wheat monoculture (M) on N2O emissions. Additionally, Yield-scaled N2O emissions (YSNE) and N uptake efficiency (NUpE) were assessed for each treatment.

Influence of Tillage and Liming on N2O emission from a rainfed crop

Nitrous oxide (N2O) is the main greenhouse gas (GHG) produced by agricultural soils due to microbial processes. The application of N fertilizers is associated with an increase of N2O losses. However, it is possible to mitigate these emissions by the introduction of adequate management practices (Snyder et al., 2009). Soil conservation practices (i.e.no tillage, NT) have recently become widespread because they promote several positive effects (increases in soil organic carbonand soil fertility, reduction of soil erosion, etc). In terms of GHG emissions, there is no consensus in the literature on the effects of tillage on N2O. Several studies found that NT can produce greater (Baggs et al., 2003), lower (Malhi et al., 2006) or similar (Grandey et al., 2006) N2O emissions compared to traditional tillage (TT). This large uncertainty is associated with the duration of tillage practices and climatic variability. Liming is widely use to solve problems of soil acidity (Al toxicity, yield penalties, etc). Several studies show a decrease in N2O emissions with liming (Barton et al., 2013) whereas no significant effects or increases were observed in others (Galbally et al., 2010). The aim of this work was to evaluate the effects of tillage (NT vs TT) and liming application or not of Ca-amendment) on N2O emissions from an acid soil during a rainfed crop.

Lime rendering of the houses of historical core of Maracaibo, Venezuela

An advance of the study undertaken of the plastering of the few dwellings that still exist in the historical area of Maracaibo is presented, with a base of restoration mortar of the plastering of sandstone known as “piedra de ojo”. The mortars are made of lime with a ferruginous stone aggregate that gives them a pinkish color, with additions of ceramics, bamboo, sand, wood and straw, and kneaded with salty water from Lake Maracaibo

First 20 years of DNDC: Model evolution and GRAMP.

The DNDC (DeNitrification and DeComposition) model was first developed by Li et al. (1992) as a rain event-driven process-orientated simulation model for nitrous oxide, carbon dioxide and nitrogen gas emissions from the agricultural soils in the U.S. Over the last 20 years, the model has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. The Global Research Alliance Modelling Platform (GRAMP) is a UK-led initiative for the establishment of a purposeful and credible web-based platform initially aimed at users of the DNDC model. With the aim of improving the predictions of soil C and N cycling in the context of climate change the objectives of GRAMP are to: 1) to document the existing versions of the DNDC model; 2) to create a family tree of the individual DNDC versions; 3) to provide information on model use and development; and 4) to identify strengths, weaknesses and potential improvements for the model.

Comparison of micrometeorological techinques for estimating ammonia emission from covered slurry storage and land spreading of cattle slurry

The micrometeorological mass-balance integrated horizontal flux (IHF) technique has been commonly employed for measuring ammonia (NH3) emissions inon-field experiments. However, the inverse-dispersion modeling technique, such as the backward Lagrangian stochastic (bLS) modeling approach, is currently highlighted as offering flexibility in plot design and requiring a minimum number of samplers (Ro et al., 2013). The objective of this study was to make a comparison between the bLS technique with the IHF technique for estimating NH3 emission from flexible bag storage and following landspreading of dairy cattle slurry. Moreover, considering that NH3 emission in storage could have been non uniform, the effect on bLS estimates of a single point and multiple downwind concentration measurements was tested, as proposed by Sanz et al. (2010).

The NH3-Abating effect of Slurry Injection as Influenced by Soil Moisture in a Semiarid Arable Soil

Accumulation of large volumes of dilute slurries is considered one of the major problems related to intensive farming (Sommer et al., 2004). In the EU-27, more than half of the total N excretion is applied to croplands due to technical advantages for farmers (e.g. reuse of nutrients). However, the N use efficiency of slurries produced by livestock is low, i.e. only 20-52% of the excreted N is recovered by crops. Much of the remainder can be lost into the atmosphere as ammonia (NH3), nitrous oxide (N2O), dinitrogen (N2) and nitrogen oxides (NOx).

Autonomous Acquisition of Natural Language

An important part of human intelligence is the ability to use language. Humans learn how to use language in a society of language users, which is probably the most effective way to learn a language from the ground up. Principles that might allow an artificial agents to learn language this way are not known at present. Here we present a framework which begins to address this challenge. Our auto-catalytic, endogenous, reflective architecture (AERA) supports the creation of agents that can learn natural language by observation. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime mock television interview, using gesture and situated language. Results show that S1 can learn multimodal complex language and multimodal communicative acts, using a vocabulary of 100 words with numerous sentence formats, by observing unscripted interaction between the humans, with no grammar being provided to it a priori, and only high-level information about the format of the human interaction in the form of high-level goals of the interviewer and interviewee and a small ontology. The agent learns both the pragmatics, semantics, and syntax of complex sentences spoken by the human subjects on the topic of recycling of objects such as aluminum cans, glass bottles, plastic, and wood, as well as use of manual deictic reference and anaphora.

A proposal for an Internet of Things-based monitoring system composed by low capability, open source and open hardware devices

The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.

Ground and airborne level optical sensors: is it possible to estimate maize crop N status?

Adjusting N fertilizer application to crop requirements is a key issue to improve fertilizer efficiency, reducing unnecessary input costs to farmers and N environmental impact. Among the multiple soil and crop tests developed, optical sensors that detect crop N nutritional status may have a large potential to adjust N fertilizer recommendation (Samborski et al. 2009). Optical readings are rapid to take and non-destructive, they can be efficiently processed and combined to obtain indexes or indicators of crop status. However, other physiological stress conditions may interfere with the readings and detection of the best crop nutritional status indicators is not always and easy task. Comparison of different equipments and technologies might help to identify strengths and weakness of the application of optical sensors for N fertilizer recommendation. The aim of this study was to evaluate the potential of various ground-level optical sensors and narrow-band indices obtained from airborne hyperspectral images as tools for maize N fertilizer recommendations. Specific objectives were i) to determine which indices could detect differences in maize plants treated with different N fertilizer rates, and ii) to evaluate its ability to identify N-responsive from non-responsive sites.

Initializing the DSSAT-Century model: inverse calibration of carbon pools from apparent soil N mineralization

The CENTURY soil organic matter model was adapted for the DSSAT (Decision Support System for Agrotechnology Transfer), modular format in order to better simulate the dynamics of soil organic nutrient processes (Gijsman et al., 2002). The CENTURY model divides the soil organic carbon (SOC) into three hypothetical pools: microbial or active material (SOC1), intermediate (SOC2) and the largely inert and stable material (SOC3) (Jones et al., 2003). At the beginning of the simulation, CENTURY model needs a value of SOC3 per soil layer which can be estimated by the model (based on soil texture and management history) or given as an input. Then, the model assigns about 5% and 95% of the remaining SOC to SOC1 and SOC2, respectively. The model performance when simulating SOC and nitrogen (N) dynamics strongly depends on the initialization process. The common methods (e.g. Basso et al., 2011) to initialize SOC pools deal mostly with carbon (C) mineralization processes and less with N. Dynamics of SOM, SOC, and soil organic N are linked in the CENTURY-DSSAT model through the C/N ratio of decomposing material that determines either mineralization or immobilization of N (Gijsman et al., 2002). The aim of this study was to evaluate an alternative method to initialize the SOC pools in the DSSAT-CENTURY model from apparent soil N mineralization (Napmin) field measurements by using automatic inverse calibration (simulated annealing). The results were compared with the ones obtained by the iterative initialization procedure developed by Basso et al., 2011.