Multifunctional cement composites strain and damage sensors applied on reinforced concrete (RC) structural elements

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions (in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse.

Control framework for dexterous manipulation using dynamic visual servoing and tactile sensors’ feedback

Tactile sensors play an important role in robotics manipulation to perform dexterous and complex tasks. This paper presents a novel control framework to perform dexterous manipulation with multi-fingered robotic hands using feedback data from tactile and visual sensors. This control framework permits the definition of new visual controllers which allow the path tracking of the object motion taking into account both the dynamics model of the robot hand and the grasping force of the fingertips under a hybrid control scheme. In addition, the proposed general method employs optimal control to obtain the desired behaviour in the joint space of the fingers based on an indicated cost function which determines how the control effort is distributed over the joints of the robotic hand. Finally, authors show experimental verifications on a real robotic manipulation system for some of the controllers derived from the control framework.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Fire-resistance, physical, and mechanical characterization of particleboard containing Oceanic Posidonia waste

In this work, particleboards manufactured with Oceanic Posidonia waste and bonded with cement are investigated. The particleboards are made with 3/1.5/0.5 parts of cement per part of Posidonia waste. The physical properties of bulk density, swelling, surface absorption, and dimensional changes due to relative humidity as well as the mechanical properties of modulus of elasticity, bending strength, surface soundness, perpendicular tensile strength and impact resistance are studied. In terms of the above properties, the best results were obtained for particleboards with high cement content and when the waste “leaves” are treated (crushed) before board fabrication, due to internal changes to the board structure under these conditions. Based on the results of fire tests, the particleboard is non-flammable without any fire-resistant treatment.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Plant regeneration functional groups modulate the response to fire of soil enzyme activities in a Mediterranean shrubland

Soil enzymes are critical to soil nutrient cycling function but knowledge on the factors that control their response to major disturbances such as wildfires remains very limited. We evaluated the effect of fire-related plant functional traits (resprouting and seeding) on the resistance and resilience to fire of two soil enzyme activities involved in phosphorus and carbon cycling (acid phosphatase and β-glucosidase) in a Mediterranean shrublands in SE Spain. Using experimental fires, we compared four types of shrubland microsites: SS (vegetation patches dominated by seeder species), RR (patches dominated by resprouter species), SR (patches co-dominated by seeder and resprouter species), and IP (shrub interpatches). We assessed pre- and post-fire activities of the target soil enzymes, available P, soil organic C, and plant cover dynamics over three years after the fire. Post-fire regeneration functional groups (resprouter, seeder) modulated both pre- and post-fire activity of acid phosphatase and β-glucosidase, with higher activity in RR and SR patches than in SS patches and IP. However, we found no major differences in enzyme resistance and resilience between microsite types, except for a trend towards less resilience in SS patches. Fire similarly reduced the activity of both enzymes. However, acid phosphatase and β-glucosidase showed contrasting post-fire dynamics. While β-glucosidase proved to be rather resilient to fire, fully recovering three years after fire, acid phosphatase showed no signs of recovery in that period. Overall, the results indicate a positive influence of resprouter species on soil enzyme activity that is very resistant to fire. Long-lasting decrease in acid phosphatase activity probably resulted from the combined effect of P availability and post-fire drought. Our results provide insights on how plant functional traits modulate soil biochemical and microbiological response to fire in Mediterranean fire-prone shrublands.

Evaluating the Effectiveness of Post Fire Emergency Rehabilitation Treatments on Soil Degradation and Erosion Control in Semi-Arid Mediterranean Areas of the Spanish South East

In this study, we seeded a native plant species and applied a mulch of chopped wood originating from the same burned area to avoid the establishment of invasive species. We evaluated four treatments: (1) seeding, (2) mulch, (3) seeding and mulch, and (4) control. Our objective was to increase plant recovery and to minimize the soil erosion and degradation. The study was conducted in Alicante, Spain in Torremanzanas forest of the semi-arid Mediterranean bioclimatic area after the wildfire of November, 2002. During three years of monitoring, we find that combined treatment: seeding and mulch increased the post fire plant recovery 20% approximately more than the rest of treatments and the control plots. We also found that seven months after treating mulch and seeding and mulch treatments presented a gain of soil: +5.18 to + 5.24 mm while the seeding treatment and control plots presented soil loss rates of: −0.48 to −0.49 mm. In addition, mulch treatment significantly decreased soil compaction to the half, and increased the infiltration capacity to 40 ml.mn−1 more than in plots without mulch, as well as increased the soil respiration to the double compared with no mulch plots. Work in progress confirms the positive effect of chopped wood as mulching treatment with or without seeding on the soil protection against soil erosion, and the amelioration of bio-physical properties after wildfires in the Mediterranean semi-arid burned areas.

A Computational Architecture Based on RFID Sensors for Traceability in Smart Cities

Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

Methodology based on registration techniques for representing subjects and their deformations acquired from general purpose 3D sensors

In this thesis a methodology for representing 3D subjects and their deformations in adverse situations is studied. The study is focused in providing methods based on registration techniques to improve the data in situations where the sensor is working in the limit of its sensitivity. In order to do this, it is proposed two methods to overcome the problems which can difficult the process in these conditions. First a rigid registration based on model registration is presented, where the model of 3D planar markers is used. This model is estimated using a proposed method which improves its quality by taking into account prior knowledge of the marker. To study the deformations, it is proposed a framework to combine multiple spaces in a non-rigid registration technique. This proposal improves the quality of the alignment with a more robust matching process that makes use of all available input data. Moreover, this framework allows the registration of multiple spaces simultaneously providing a more general technique. Concretely, it is instantiated using colour and location in the matching process for 3D location registration.

Successional stage after land abandonment modulates fire severity and post-fire recovery in a Mediterranean mountain landscape

This study analyses the effect of successional stage after farmland terrace abandonment on post-fire plant recovery in a Mediterranean landscape. Specific objectives of the study were to (1) compare fuel characteristics and fire severity in three successional stages after farmland abandonment – dry grassland, dense shrubland and pine stands; (2) analyse the effect of pre-fire successional stage and fire severity on vegetation recovery and (3) analyse the relative vulnerability (i.e. potential for ecosystem shift and soil degradation) to wildfires of the successional stages. We assessed 30 abandoned terraces (15 unburned and 15 burned), with diverse successional stages, on the Xortà Range (south-east Spain). Post-fire recovery was measured 1, 4 and 7 years after fire. The successional stages varied in aboveground biomass, litter amount, vertical structure and continuity of plant cover, and flammability. Dry grassland showed the lowest fire severity, whereas no differences in severity were found between shrubland and pine stands. One year after fire, plant cover was inversely related to fire severity; this relationship attenuated with time after fire. Post-fire recovery of pine stands and shrubland led in both cases to shrublands, contributing to landscape homogenisation. The pine stands showed the largest changes in composition due to fire and the lowest post-fire plant recovery – a sign of high vulnerability to fire.

How can an invasive grass affect fire behavior in a tropical savanna? A community and individual plant level approach

Some invasive grasses have been reported to change fire behavior in invaded plant communities. Urochloa brizantha is an aggressive invasive grass in the Brazilian Cerrado, an ecosystem where fire is a common disturbance. We investigated the effects of U. brizantha on fire behavior in an open Cerrado physiognomy in Central Brazil. Using experimental burnings we compared fire behavior at both the community and the individual plant level in invaded (UJ) and non-invaded (NJ) areas burned in July. We also assessed the effect of fire season in invaded areas by comparing July (UJ) and October (UO) burnings. We evaluated the following variables: fuel load, fuel moisture, combustion efficiency, maximum fire temperature, flame height, and fire intensity. Additionally, we evaluated the temperatures reached under invasive and native grass tussocks in both seasons. Fuel load, combustion efficiency, and fire intensity were higher in NJ than in UJ, whilst flame height showed the opposite trend. Fuel amount and fire intensity were higher in October than in July. At the individual plant level, U. brizantha moisture was higher than that of native species, however, temperatures reaching ≥600 °C at ground level were more frequent under U. brizantha tussocks than under native grasses. At the community level, the invasive grass modified fire behavior towards lower intensity, lower burning efficiency, and higher flame height. These results provide essential information for the planning of prescribed burnings in invaded Cerrado areas.

Compressive behaviour of a tire recycled steel and textil fiber concrete subjected to fire

The use of rubber aggregates, steel and textile fibres recycled from tires in concrete is a solution that it is being studied by several authors around the world. A few works have been carried out at room temperature but very scarce at high temperatures. This paper presents the results of a research with the aim to evaluate the behaviour at high temperatures of a concrete made with different amounts of recycled textile and steel fibres from tires. The study considered five concrete compositions, with the same water/cement ratio (W/C=0.43), differing only in the type and quantity of fibers incorporated in the mixture. Thus, a reference composition (0% fiber), two compositions with 30 and 70kg/m3 of steel fibers and a composition with 2 and 4kg/m3 of textile fibers from tires were tested. The concrete was tested for a load level of 0.5fcd and different maximum temperature levels (20, 300, 500 and 700ºC).