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This paper presents a modified Shuffled Frog Leaping Algorithm (SFLA) applied to the design of water distribution networks. Generally, one of the major disadvantages of the traditional SFLA is the high number of parameters that need to be calibrated for proper operation of the algorithm. A method for calibrating these parameters is presented and applied to the design of three benchmark medium-sized networks widely known in the literature (Hanoi, New York Tunnel, and GoYang). For each of the problems, over 35,000 simulations were conducted. Then, a statistical analysis was performed, and the relative importance of each of the parameters was analyzed to achieve the best possible configuration of the modified SFLA. The main conclusion from this study is that not all of the original SFL algorithm parameters are important. Thus, the fraction of frogs in the memeplex q can be eliminated, while the other parameters (number of evolutionary steps Ns, number of memeplexes m, and number of frogs n) may be set to constant values that run optimally for all medium-sized networks. Furthermore, the modified acceleration parameter C becomes the key parameter in the calibration process, vastly improving the results provided by the original SFLA.

The Storm Water Management Model (SWMM) is a dynamic simulation engine of flow in sewer systems developed by the USEPA. It has been successfully used for analyzing and designing both storm water and waste water systems. However, despite including some interfacing functions, these functions are insufficient for certain simulations. This paper describes some new functions that have been added to the existing ones to form a library of functions (Toolkit). The Toolkit presented here will allow the direct modification of network data during simulation without the need to access the input file. To support the use of this library, a testing protocol was performed in order to evaluate both calculation time and accuracy of results. Finally, a case study is presented. In this application, this library will be used for the design of a sewerage network by using a genetic algorithm based on successive iterations.

Several insect species pose a serious threat to different plant species, sometimes becoming a pest that produces significant damage to the landscape, biodiversity, and/or the economy. This is the case of Rhynchophorus ferrugineus Olivier (Coleoptera: Dryophthoridae), Semanotus laurasii Lucas (Coleoptera: Cerambycidae), and Monochamus galloprovincialis Olivier (Coleoptera: Cerambycidae), which have become serious threats to ornamental and productive trees all over the world such as palm trees, cypresses, and pines. Knowledge about their flight potential is very important for designing and applying measures targeted to reduce the negative effects from these pests. Studying the flight capability and behaviour of some insects is difficult due to their small size and the large area wherein they can fly, so we wondered how we could obtain information about their flight capabilities in a controlled environment. The answer came with the design of flight mills. Relevant data about the flight potential of these insects may be recorded and analysed by means of a flight mill. Once an insect is attached to the flight mill, it is able to fly in a circular direction without hitting walls or objects. By adding sensors to the flight mill, it is possible to record the number of revolutions and flight time. This paper presents a full description of a computer monitored flight mill. The description covers both the mechanical and the electronic parts in detail. The mill was designed to easily adapt to the anatomy of different insects and was successfully tested with individuals from three species R. ferrugineus, S. laurasii, and M. galloprovincialis.

[EN] Different Population-based Algorithms (PbAs) have been used in recent years to solve all types of optimization problems related to water resource issues. However, the performances of these techniques depend heavily on correctly setting some specific parameters that guide the search for solutions. The initial random population size P is the only parameter common to all PbAs, but this parameter has received little attention from researchers. This paper explores P behaviour in a pipe-sizing problem considering both quality and speed criteria. To relate both concepts, this study applies a method based on an efficiency ratio E. First, specific parameters in each algorithm are calibrated with a fixed P. Second, specific parameters remain fixed, and the initial population size P is modified. After more than 600,000 simulations, the influence of P on obtaining successful solutions is statistically analysed. The proposed methodology is applied to four well-known benchmark networks and four different algorithms. The main conclusion of this study is that using a small population size is more efficient above a certain minimum size. Moreover, the results ensure optimal parameter calibration in each algorithm, and they can be used to select the most appropriate algorithm depending on the complexity of the problem and the goal of optimization.

[EN] The optimal function of a water distribution network is reached when the consumer demands are satisfied using the lowest quantity of energy, maintaining the minimal pressure required at the same time. One way to achieve this is through optimization of flow rate injection based on the use of the setpoint curve concept. In order to obtain that, a methodology is proposed. It allows for the assessment of the flow rate and pressure head that each pumping station has to provide for the proper functioning of the network while the minimum power consumption is kept. The methodology can be addressed in two ways: the discrete method and the continuous method. In the first method, a finite set of combinations is evaluated between pumping stations. In the continuous method, the search for the optimal solution is performed using optimization algorithms. In this paper, Hooke Jeeves and Nelder Mead algorithms are used. Both the hydraulics and the objective function used by the optimization are solved through EPANET and its Toolkit. Two case studies are evaluated, and the results of the application of the different methods are discussed.

[EN] The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving increasing attention as less expensive and more power efficient alternatives to fully digital precoding schemes. Despite their proven good performance in simple setups, their suitability for realistic cellular systems with many interfering base stations and users is still unclear. Furthermore, the performance of massive MIMO beamforming and precoding methods are in practice also affected by practical limitations and hardware constraints. In this sense, this paper assesses the performance of digital precoding and analog beamforming in an urban cellular system with an accurate mmW channel model under both ideal and realistic assumptions. The results show that analog beamforming can reach the performance of fully digital maximum ratio transmission under line of sight conditions and with a sufficient number of parallel radio-frequency (RF) chains, especially when the practical limitations of outdated channel information and per antenna power constraints are considered. This work also shows the impact of the phase shifter errors and combiner losses introduced by real phase shifter and combiner implementations over analog beamforming, where the former ones have minor impact on the performance, while the latter ones determine the optimum number of RF chains to be used in practice.

[EN] Water scarcity is a critical environmental issue worldwide, especially in arid and semiarid regions. In those regions, climate change projections suggest further reductions in freshwater supplies and increases of the recurrence, longevity and intensity of drought events. At present, one important question for policy debate is the identification of water policies that could address the mounting water scarcity problems. Suitable policies should improve economic efficiency, achieve environmental sustainability, and meet equity needs. This paper develops and applies an integrated hydro-economic model that links hydrological, economic and environmental elements to such issues. The model is used to conduct a direct comparison of water markets, water pricing and institutional cooperation, based on their economic, environmental and equity outcomes. The analysis is performed in the Jucar Basin of Spain, which is a good natural experiment for studying water scarcity and climate change policies. Results indicate that both institutional and water market policies are high performing instruments to limit the economic damage costs of droughts, achieving almost the same social benefits. However, the environmental effects of water markets are worrying. Another important finding is that water pricing is a poor policy option not only in terms of private and environmental benefits but also in terms of equity. Guardar / Salir Siguiente >

[EN] The optimal function of a water distribution network is reached when the consumer demands are satisfied using the lowest quantity of energy, maintaining the minimal pressure required at the same time. One way to achieve this is through optimization of flow rate injection based on the use of the setpoint curve concept. In order to obtain that, a methodology is proposed. It allows for the assessment of the flow rate and pressure head that each pumping station has to provide for the proper functioning of the network while the minimum power consumption is kept. The methodology can be addressed in two ways: the discrete method and the continuous method. In the first method, a finite set of combinations is evaluated between pumping stations. In the continuous method, the search for the optimal solution is performed using optimization algorithms. In this paper, Hooke Jeeves and Nelder Mead algorithms are used. Both the hydraulics and the objective function used by the optimization are solved through EPANET and its Toolkit. Two case studies are evaluated, and the results of the application of the different methods are discussed.

Waste heat recovery (WHR) in exhaust gas flow of automotive engines has proved to be a useful path to increase the overall efficiency of internal combustion engines (ICE). Recovery potentials of up to 7% are shown in several works in the literature. However, most of them are theoretical estimations. Some present results from prototypes fed by steady flows generated in an auxiliary gas tank and not with actual engine exhaust gases. This paper deals with the modeling and experimental validation of an organic Rankine cycle (ORC) with a swash-plate expander integrated in a 2 L turbocharged petrol engine using ethanol as working fluid. A global simulation model of the ORC was developed with a maximum difference of 5%, validated with experimental results. Considering the swash-plate as the main limiting factor, an additional specific submodel was implemented to model the physical phenomena in this element. This model allows simulating the fluid dynamic behavior of the swash-plate expander using a 0D model (Amesim). Differences up to 10.5% between tests and model results were found.

[EN] The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving increasing attention as less expensive and more power efficient alternatives to fully digital precoding schemes. Despite their proven good performance in simple setups, their suitability for realistic cellular systems with many interfering base stations and users is still unclear. Furthermore, the performance of massive MIMO beamforming and precoding methods are in practice also affected by practical limitations and hardware constraints. In this sense, this paper assesses the performance of digital precoding and analog beamforming in an urban cellular system with an accurate mmW channel model under both ideal and realistic assumptions. The results show that analog beamforming can reach the performance of fully digital maximum ratio transmission under line of sight conditions and with a sufficient number of parallel radio-frequency (RF) chains, especially when the practical limitations of outdated channel information and per antenna power constraints are considered. This work also shows the impact of the phase shifter errors and combiner losses introduced by real phase shifter and combiner implementations over analog beamforming, where the former ones have minor impact on the performance, while the latter ones determine the optimum number of RF chains to be used in practice.

Video surveillance is needed to control many activities performed in underwater environments. The use of wired media can be a problem since the material specially designed for underwater environments is very expensive. In order to transmit the images and videos wirelessly under water, three main technologies can be used: acoustic waves, which do not provide high bandwidth, optical signals, although the effect of light dispersion in water severely penalizes the transmitted signals and therefore, despite offering high transfer rates, the maximum distance is very small, and electromagnetic (EM) waves, which can provide enough bandwidth for video delivery. In the cases where the distance between transmitter and receiver is short, the use of EM waves would be an interesting option since they provide high enough data transfer rates to transmit videos with high resolution. This paper presents a practical study of the behavior of EM waves at 2.4 GHz in freshwater underwater environments. First, we discuss the minimum requirements of a network to allow video delivery. From these results, we measure the maximum distance between nodes and the round trip time (RTT) value depending on several parameters such as data transfer rate, signal modulations, working frequency, and water temperature. The results are statistically analyzed to determine their relation. Finally, the EM waves behavior is modeled by a set of equations. The results show that there are some combinations of working frequency, modulation, transfer rate and temperature that offer better results than others. Our work shows that short communication distances with high data transfer rates is feasible.

Whole-body 123I-Metaiodobenzylguanidine (mIBG) scintigraphy is used as primary image modality to visualize neuroblastoma tumours and metastases because it is the most sensitive and specific radioactive tracer in staging the disease and evaluating the response to treatment. However, especially in paediatric neuroblastoma, information from mIBG scans is difficult to extract because of acquisition difficulties that produce low definition images, with poor contours, resolution and contrast. These problems limit physician assessment. Current oncological guidelines are based on qualitative observer-dependant analysis. This makes comparing results taken at different moments of therapy, or in different institutions, difficult. In this paper, we present a computerized method that processes an image and calculates a quantitative measurement considered as its entropy, suitable for the identification of abnormal uptake regions, for which there is enough suspicion that they may be a tumour or metastatic site. This measurement can also be compared with future scintigraphies of the same patient. Over 46 scintigraphies of 22 anonymous patients were tested; the procedure identified 96.7% of regions of abnormal uptake and it showed a low overall false negative rate of 3.3%. This method provides assistance to physicians in diagnosing tumours and also allows the monitoring of patients’ evolution.

[EN] The main objective of this paper is to generalize the Extended Irreversible Thermodynamics in order to include the anomalous transport in systems in non-equilibrium conditions. Considering the generalized entropy, the corresponding flux and entropy production, and using the time fractional derivative, we have derived a space-time generalized telegrapher's equation with a fractional nested hierarchy which can be used in separate developments for the mass transport, for the heat conduction and for the flux of ions. We have obtained a new formalism which includes the contribution of fast of higher-order fluxes in the mesoscopic and inhomogeneous media. The results take the form of continued fraction expansions. The balance equations are used in a scheme of continued fractions, and they appear as a closure condition. In this way the transport equation and its corresponding wave number-frequency relation are obtained, both of them in the mathematical structure of the continued fraction scheme. Numerical examples are included to show the dispersive nature of the solutions, and the generalized fractional transport equation in the same mathematical form, which can be applied to the mass transport, the heat conduction and the flux of ions.

[EN] Water scarcity is a critical environmental issue worldwide, especially in arid and semiarid regions. In those regions, climate change projections suggest further reductions in freshwater supplies and increases of the recurrence, longevity and intensity of drought events. At present, one important question for policy debate is the identification of water policies that could address the mounting water scarcity problems. Suitable policies should improve economic efficiency, achieve environmental sustainability, and meet equity needs. This paper develops and applies an integrated hydro-economic model that links hydrological, economic and environmental elements to such issues. The model is used to conduct a direct comparison of water markets, water pricing and institutional cooperation, based on their economic, environmental and equity outcomes. The analysis is performed in the Jucar Basin of Spain, which is a good natural experiment for studying water scarcity and climate change policies. Results indicate that both institutional and water market policies are high performing instruments to limit the economic damage costs of droughts, achieving almost the same social benefits. However, the environmental effects of water markets are worrying. Another important finding is that water pricing is a poor policy option not only in terms of private and environmental benefits but also in terms of equity. Guardar / Salir Siguiente >

[EN] This paper presents a new application of photogrammetric techniques for protecting cultural heritage. The accuracy of the method and the fact that it can be used to carry out different tests without contact between the sample and the instruments can make this technique very useful for authenticating and cataloging artworks. The application focuses on the field of pictorial artworks, and wooden panel paintings in particular. In these works, the orography formed by the brushstrokes can be easily digitalized using a photogrammetric technique, called Structured Light System, with submillimeter accuracy. Thus, some of the physical characteristics of the brushstrokes, like minimum and maximum heights or slopes become a fingerprint of the painting. We explain in detail the general principles of the Structured Light System Technique and the specific characteristics of the commercial set-up used in this work. Some experiments are carried out on a sample painted by us to check the accuracy limits of the technique and to propose some tests that can help to stablish a methodology for authentication purposes. Finally, some preliminary results obtained on a real pictorial artwork are presented, providing geometrical information of its metric features as an example of the possibilities of this application

The Internet of Things (IoT) is, at this moment, one of the most promising technologies that has arisen for decades. Wireless Sensor Networks (WSNs) are one of the main pillars for many IoT applications, insofar as they require to obtain context-awareness information. The bibliography shows many difficulties in their real implementation that have prevented its massive deployment. Additionally, in IoT environments where data producers and data consumers are not directly related, compatibility and certification issues become fundamental. Both problems would profit from accurate knowledge of the internal behavior of WSNs that must be obtained by the utilization of appropriate tools. There are many ad-hoc proposals with no common structure or methodology, and intended to monitor a particular WSN. To overcome this problem, this paper proposes a structured three -layer reference model for WSN Monitoring Platforms (WSN-MP), which offers a standard environment for the design of new monitoring platforms to debug, verify and certify a WSN's behavior and performance, and applicable to every WSN. This model also allows the comparative analysis of the current proposals for monitoring the operation of WSNs. Following this methodology, it is possible to achieve a standardization of WSN-MP, promoting new research areas in order to solve the problems of each layer.

The Storm Water Management Model (SWMM) is a dynamic simulation engine of flow in sewer systems developed by the USEPA. It has been successfully used for analyzing and designing both storm water and waste water systems. However, despite including some interfacing functions, these functions are insufficient for certain simulations. This paper describes some new functions that have been added to the existing ones to form a library of functions (Toolkit). The Toolkit presented here will allow the direct modification of network data during simulation without the need to access the input file. To support the use of this library, a testing protocol was performed in order to evaluate both calculation time and accuracy of results. Finally, a case study is presented. In this application, this library will be used for the design of a sewerage network by using a genetic algorithm based on successive iterations.

This paper presents a modified Shuffled Frog Leaping Algorithm (SFLA) applied to the design of water distribution networks. Generally, one of the major disadvantages of the traditional SFLA is the high number of parameters that need to be calibrated for proper operation of the algorithm. A method for calibrating these parameters is presented and applied to the design of three benchmark medium-sized networks widely known in the literature (Hanoi, New York Tunnel, and GoYang). For each of the problems, over 35,000 simulations were conducted. Then, a statistical analysis was performed, and the relative importance of each of the parameters was analyzed to achieve the best possible configuration of the modified SFLA. The main conclusion from this study is that not all of the original SFL algorithm parameters are important. Thus, the fraction of frogs in the memeplex q can be eliminated, while the other parameters (number of evolutionary steps Ns, number of memeplexes m, and number of frogs n) may be set to constant values that run optimally for all medium-sized networks. Furthermore, the modified acceleration parameter C becomes the key parameter in the calibration process, vastly improving the results provided by the original SFLA.

In this paper, the dynamical behavior of different optimal iterative schemes for solving nonlinear equations with increasing order, is studied. The tendency of the complexity of the Julia set is analyzed and referred to the fractal dimension. In fact, this fractal dimension can be shown to be a powerful tool to compare iterative schemes that estimate the solution of a nonlinear equation. Based on the box-counting algorithm, several iterative derivative-free methods of different convergence orders are compared.

An off-line simulator based on Excel used to evaluate the operation of four-wire delta (4WD) services as well as the effects of reactive and imbalance compensators in sinusoidal steady-state conditions is described in this paper. Voltages, currents and powers in the primary and secondary windings of the transformer as well as in the high voltage (HV) and low voltage (LV) lines and in the loads are calculated through that simulator. The apparent powers in the mains, transformer and loads are determined applying Buchholz¿s and unified power measurement (UPM) formulations in both scalar and vector notations. The effects of the neutral current are especially examined, in order to minimize them, and the optimal wye load distribution is determined by the simulator. The simulator provides the necessary elements of passive reactive and unbalanced compensators that optimize the 4WD transformer operation too. Those compensators are determined for each load, and they can be separately selected and included in the simulation process or not. An application example is finally used to step by step explain how the simulator runs.

[EN] Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.

An off-line simulator based on Excel used to evaluate the operation of four-wire delta (4WD) services as well as the effects of reactive and imbalance compensators in sinusoidal steady-state conditions is described in this paper. Voltages, currents and powers in the primary and secondary windings of the transformer as well as in the high voltage (HV) and low voltage (LV) lines and in the loads are calculated through that simulator. The apparent powers in the mains, transformer and loads are determined applying Buchholz¿s and unified power measurement (UPM) formulations in both scalar and vector notations. The effects of the neutral current are especially examined, in order to minimize them, and the optimal wye load distribution is determined by the simulator. The simulator provides the necessary elements of passive reactive and unbalanced compensators that optimize the 4WD transformer operation too. Those compensators are determined for each load, and they can be separately selected and included in the simulation process or not. An application example is finally used to step by step explain how the simulator runs.

[EN] Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.

[EN] The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015.

Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking) in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 +/- 0.417 cm) while the electromagnetic device provided the most inaccurate results (11.027 +/- 2.364 cm). However, this tracking solution provided the best jitter values (0.324 +/- 0.093 cm), in contrast to the skeleton tracking, which had the worst results (1.522 +/- 0.858 cm). Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order). Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system.

The main aim of smart cities is achieving sustainable resources. In order to make a correct use of resources, an accurate monitoring and management of them are needed. In some places, like underground aquifers, the access for monitoring can be hard therefore the use of sensors can be a good solution. The groundwater is very important as a water resource, just in USA, aquifers suppose the water resource for 50% of population. However, its importance aquifers are endangered due to the contamination. One of the most important parameters to monitor in groundwater is the salinity. High salinity level indicates groundwater salinization. In this paper we present a specific sensor for groundwater salinization monitoring. The sensor is able to measure the electric conductivity of water, i.e., higher electric conductivity means higher water salinization. The sensor, which is composed of two copper coils, measures the alterations in magnetic fields due to the presence of electric charges in water. Different salinities in water generate different alterations. Our sensor is undergone to several tests performed in order to obtain a conductivity sensor with enough accuracy. First, several prototypes are tested and are compared with the purpose of choosing the best coils combination. When the best prototype is selected, it is calibrated using up to 30 different samples. Our Conductivity sensor presents an operational range from 0.585 mS/cm to 73.8 mS/cm, which is wide enough to cover the needs. With this work, we have demonstrated that it is feasible of measuring water conductivity using solenoids coils and its application for groundwater monitoring.

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

[EN] The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015.

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

Preventive conservation represents a working method and combination of techniques which helps in determining and controlling the deterioration process of cultural heritage in order to take the necessary actions before it occurs. It is acknowledged as important, both in terms of preserving and also reducing the cost of future conservation measures. Therefore, long-term monitoring of physical parameters influencing cultural heritage is necessary. In the context of Smart Cities, monitoring of cultural heritage is of interest in order to perform future comparative studies and load information into the cloud that will be useful for the conservation of other heritage sites. In this paper the development of an economical and appropriate acquisition data system combining wired and wireless communication, as well as third party hardware for increased versatility, is presented. The device allows monitoring a complex network of points with high sampling frequency, with wired sensors in a 1-wire bus and a wireless centralized system recording data for monitoring of physical parameters, as well as the future possibility of attaching an alarm system or sending data over the Internet. This has been possible with the development of three board's designs and more than 5000 algorithm lines. System tests have shown an adequate system operation.

Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking) in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 +/- 0.417 cm) while the electromagnetic device provided the most inaccurate results (11.027 +/- 2.364 cm). However, this tracking solution provided the best jitter values (0.324 +/- 0.093 cm), in contrast to the skeleton tracking, which had the worst results (1.522 +/- 0.858 cm). Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order). Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system.

[EN] Failure analysis of the dam-foundation interface in concrete dams is characterized by complexity, uncertainties on models and parameters, and a strong non-linear softening behavior. In practice, these uncertainties are dealt with a well-structured mixture of experience, best practices and prudent, conservative design approaches based on the safety factor concept. Yet, a sound, deep knowledge of some aspects of this failure mode remain unveiled, as they have been offset in practical applications by the use of this conservative approach. In this paper we show a strategy to analyse this failure mode under a reliability-based approach. The proposed methodology of analysis integrates epistemic uncertainty on spatial variability of strength parameters and data from dam monitoring. The purpose is to produce meaningful and useful information regarding the probability of occurrence of this failure mode that can be incorporated in risk-informed dam safety reviews. In addition, relationships between probability of failure and factors of safety are obtained. This research is supported by a more than a decade of intensive professional practice on real world cases and its final purpose is to bring some clarity, guidance and to contribute to the improvement of current knowledge and best practices on such an important dam safety concern.

[EN] The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015.

Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

[EN] The environment in livestock buildings must be controlled to ensure the health and welfare of both workers and animals, as well as to restrict the emission of pollutants to the atmosphere. Among the pollutants generated inside these premises, carbon dioxide (CO2) is of great interest in terms of animal welfare and ventilation control. The use of inexpensive sensors means that complete systems can be designed with a number of sensors located around the building. This paper describes a study of the suitability of multipoint simultaneous CO2 sensors operating in a wireless sensor network, which was found to operate satisfactorily under laboratory conditions and was found to be the best alternative for these applications. The sensors showed a highly linear response to CO2 concentrations, ranging from 500 to 5000 ppm. However, individual sensor response was found to differ, which made it necessary to calibrate each one separately. Sensor precision ranged between 80 and 110 ppm CO2, and sensor response to register a 95% change in concentration was estimated at around 5 min. These features mean this type of sensor network can be used to monitor animal welfare and also for environmental control in poorly ventilated livestock premises. According to the tests conducted in this study, a temporal drift may occur and therefore a regular calibration of sensors would be needed.

[EN] The environment in livestock buildings must be controlled to ensure the health and welfare of both workers and animals, as well as to restrict the emission of pollutants to the atmosphere. Among the pollutants generated inside these premises, carbon dioxide (CO2) is of great interest in terms of animal welfare and ventilation control. The use of inexpensive sensors means that complete systems can be designed with a number of sensors located around the building. This paper describes a study of the suitability of multipoint simultaneous CO2 sensors operating in a wireless sensor network, which was found to operate satisfactorily under laboratory conditions and was found to be the best alternative for these applications. The sensors showed a highly linear response to CO2 concentrations, ranging from 500 to 5000 ppm. However, individual sensor response was found to differ, which made it necessary to calibrate each one separately. Sensor precision ranged between 80 and 110 ppm CO2, and sensor response to register a 95% change in concentration was estimated at around 5 min. These features mean this type of sensor network can be used to monitor animal welfare and also for environmental control in poorly ventilated livestock premises. According to the tests conducted in this study, a temporal drift may occur and therefore a regular calibration of sensors would be needed.

[EN] This paper presents an application of the Analytical Hierarchy Process (AHP) by integrating a Delphi process for selecting the best sustainable disinfection technique for wastewater reuse projects. The proposed methodology provides project managers a tool to evaluate problems with multiple criteria and multiple alternatives which involve non-commeasurable decision criteria, with expert opinions playing a major role in the selection of these treatment technologies. Five disinfection techniques for wastewater reuse have been evaluated for each of the nine criteria weighted according to the opinions of consulted experts. Finally, the VIKOR method has been applied to determine a compromise solution, and to establish the stability of the results. Therefore, the expert system proposed to select the optimal disinfection alternative is a hybrid method combining the AHP with the Delphi method and the VIKOR technique, which is shown to be appropriate in realistic scenarios where multiple stakeholders are involved in the selection of a sustainable disinfection technique for wastewater reuse projects.

The new paradigms and latest developments in the Electrical Grid are based on the introduction of distributed intelligence at several stages of its physical layer, giving birth to concepts such as Smart Grids, Virtual Power Plants, microgrids, Smart Buildings and Smart Environments. Distributed Generation (DG) is a philosophy in which energy is no longer produced exclusively in huge centralized plants, but also in smaller premises which take advantage of local conditions in order to minimize transmission losses and optimize production and consumption. This represents a new opportunity for renewable energy, because small elements such as solar panels and wind turbines are expected to be scattered along the grid, feeding local installations or selling energy to the grid depending on their local generation/consumption conditions. The introduction of these highly dynamic elements will lead to a substantial change in the curves of demanded energy. The aim of this paper is to apply Short-Term Load Forecasting (STLF) in microgrid environments with curves and similar behaviours, using two different data sets: the first one packing electricity consumption information during four years and six months in a microgrid along with calendar data, while the second one will be just four months of the previous parameters along with the solar radiation from the site. For the first set of data different STLF models will be discussed, studying the effect of each variable, in order to identify the best one. That model will be employed with the second set of data, in order to make a comparison with a new model that takes into account the solar radiation, since the photovoltaic installations of the microgrid will cause the power demand to fluctuate depending on the solar radiation.

Artworks are a valuable part of the World s cultural and historical heritage. Conservation and authentication of authorship are important aspects to consider in the protection of cultural patrimony. In this paper we present a novel application of a well-known method based on the phase-shift analysis of an ultrasonic signal, providing an integrated encoding system that enables authentication of the authorship of wooden panel paintings. The method has been evaluated in comparison with optical analysis and shows promising results. The proposed method provides an integrated fingerprint of the artwork, and could be used to enrich the cataloging and protection of artworks. Other advantages that make particularly attractive the proposed technique are its robustness and the use of low-cost sensors.

Entropy estimation metrics have become a widely used method to identify subtle changes or hidden features in biomedical records. These methods have been more effective than conventional linear techniques in a number of signal classification applications, specially the healthy pathological segmentation dichotomy. Nevertheless, a thorough characterization of these measures, namely, how to match metric and signal features, is still lacking. This paper studies a specific characterization problem: the influence of missing samples in biomedical records. The assessment is conducted using four of the most popular entropy metrics: Approximate Entropy, Sample Entropy, Fuzzy Entropy, and Detrended Fluctuation Analysis. The rationale of this study is that missing samples are a signal disturbance that can arise in many cases: signal compression, non-uniform sampling, or data transmission stages. It is of great interest to determine if these real situations can impair the capability of segmenting signal classes using such metrics. The experiments employed several biosignals: electroencephalograms, gait records, and RR time series. Samples of these signals were systematically removed, and the entropy computed for each case. The results showed that these metrics are robust against missing samples: With a data loss percentage of 50% or even higher, the methods were still able to distinguish among signal classes.

[EN] The use of methods based on measuring electrical conductivity to assess pozzolanic activity has recently been used primarily in aqueous suspensions of pozzolan: calcium hydroxide. However, the use of similar methods in suspensions of cement with pozzolans has not been widely studied. This paper proposes a new method for rapid assessment of the pozzolanic activity of mineral admixtures in aqueous cement suspensions. In this study, the conditions for the application of the method were optimized, such as time, temperature, w/c ratio and dosage procedure. Finally, results are presented from the application of this method for characterizing the pozzolanic activity of the spent catalytic cracking catalyst. These results corroborate as previously reported, namely the high reactivity of this pozzolan obtained by other methods, such as thermogravimetry or evolution of the mechanical strength. In addition, the pozzolanic activity of the catalyst was compared with other pozzolans such as metakaolin and silica fume.

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime.

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime.

[EN] This paper presents an application of the Analytical Hierarchy Process (AHP) by integrating a Delphi process for selecting the best sustainable disinfection technique for wastewater reuse projects. The proposed methodology provides project managers a tool to evaluate problems with multiple criteria and multiple alternatives which involve non-commeasurable decision criteria, with expert opinions playing a major role in the selection of these treatment technologies. Five disinfection techniques for wastewater reuse have been evaluated for each of the nine criteria weighted according to the opinions of consulted experts. Finally, the VIKOR method has been applied to determine a compromise solution, and to establish the stability of the results. Therefore, the expert system proposed to select the optimal disinfection alternative is a hybrid method combining the AHP with the Delphi method and the VIKOR technique, which is shown to be appropriate in realistic scenarios where multiple stakeholders are involved in the selection of a sustainable disinfection technique for wastewater reuse projects.

Artworks are a valuable part of the World s cultural and historical heritage. Conservation and authentication of authorship are important aspects to consider in the protection of cultural patrimony. In this paper we present a novel application of a well-known method based on the phase-shift analysis of an ultrasonic signal, providing an integrated encoding system that enables authentication of the authorship of wooden panel paintings. The method has been evaluated in comparison with optical analysis and shows promising results. The proposed method provides an integrated fingerprint of the artwork, and could be used to enrich the cataloging and protection of artworks. Other advantages that make particularly attractive the proposed technique are its robustness and the use of low-cost sensors.

The new paradigms and latest developments in the Electrical Grid are based on the introduction of distributed intelligence at several stages of its physical layer, giving birth to concepts such as Smart Grids, Virtual Power Plants, microgrids, Smart Buildings and Smart Environments. Distributed Generation (DG) is a philosophy in which energy is no longer produced exclusively in huge centralized plants, but also in smaller premises which take advantage of local conditions in order to minimize transmission losses and optimize production and consumption. This represents a new opportunity for renewable energy, because small elements such as solar panels and wind turbines are expected to be scattered along the grid, feeding local installations or selling energy to the grid depending on their local generation/consumption conditions. The introduction of these highly dynamic elements will lead to a substantial change in the curves of demanded energy. The aim of this paper is to apply Short-Term Load Forecasting (STLF) in microgrid environments with curves and similar behaviours, using two different data sets: the first one packing electricity consumption information during four years and six months in a microgrid along with calendar data, while the second one will be just four months of the previous parameters along with the solar radiation from the site. For the first set of data different STLF models will be discussed, studying the effect of each variable, in order to identify the best one. That model will be employed with the second set of data, in order to make a comparison with a new model that takes into account the solar radiation, since the photovoltaic installations of the microgrid will cause the power demand to fluctuate depending on the solar radiation.

Entropy estimation metrics have become a widely used method to identify subtle changes or hidden features in biomedical records. These methods have been more effective than conventional linear techniques in a number of signal classification applications, specially the healthy pathological segmentation dichotomy. Nevertheless, a thorough characterization of these measures, namely, how to match metric and signal features, is still lacking. This paper studies a specific characterization problem: the influence of missing samples in biomedical records. The assessment is conducted using four of the most popular entropy metrics: Approximate Entropy, Sample Entropy, Fuzzy Entropy, and Detrended Fluctuation Analysis. The rationale of this study is that missing samples are a signal disturbance that can arise in many cases: signal compression, non-uniform sampling, or data transmission stages. It is of great interest to determine if these real situations can impair the capability of segmenting signal classes using such metrics. The experiments employed several biosignals: electroencephalograms, gait records, and RR time series. Samples of these signals were systematically removed, and the entropy computed for each case. The results showed that these metrics are robust against missing samples: With a data loss percentage of 50% or even higher, the methods were still able to distinguish among signal classes.

[EN] The use of methods based on measuring electrical conductivity to assess pozzolanic activity has recently been used primarily in aqueous suspensions of pozzolan: calcium hydroxide. However, the use of similar methods in suspensions of cement with pozzolans has not been widely studied. This paper proposes a new method for rapid assessment of the pozzolanic activity of mineral admixtures in aqueous cement suspensions. In this study, the conditions for the application of the method were optimized, such as time, temperature, w/c ratio and dosage procedure. Finally, results are presented from the application of this method for characterizing the pozzolanic activity of the spent catalytic cracking catalyst. These results corroborate as previously reported, namely the high reactivity of this pozzolan obtained by other methods, such as thermogravimetry or evolution of the mechanical strength. In addition, the pozzolanic activity of the catalyst was compared with other pozzolans such as metakaolin and silica fume.

[EN] Plants have developed versatile strategies to deal with the great variety of challenging conditions they are exposed to. Among them, the regulation of translation is a common target to finely modulate gene expression both under biotic and abiotic stress situations. Upon environmental challenges, translation is regulated to reduce the consumption of energy and to selectively synthesize proteins involved in the proper establishment of the tolerance response. In the case of viral infections, the situation is more complex, as viruses have evolved unconventional mechanisms to regulate translation in order to ensure the production of the viral encoded proteins using the plant machinery. Although the final purpose is different, in some cases, both plants and viruses share common mechanisms to modulate translation. In others, the mechanisms leading to the control of translation are viral- or stress-specific. In this paper, we review the different mechanisms involved in the regulation of translation initiation under virus infection and under environmental stress in plants. In addition, we describe the main features within the viral RNAs and the cellular mRNAs that promote their selective translation in plants undergoing biotic and abiotic stress situations.

Regenerated Fibre Bragg Gratings have the potential for high-temperature monitoring. In this paper, the inscription of Fibre Bragg Gratings (FBGs) and the later regeneration process to obtain Regenerated Fiber Bragg Gratings (RFBGs) in high-birefringence optical fiber is reported. The obtained RFBGs show two Bragg resonances corresponding to the slow and fast axis that are characterized in temperature terms. As the temperature increases the separation between the two Bragg resonances is reduced, which can be used for low cost interrogation. The proposed interrogation setup is based in the use of optical filters in order to convert the wavelength shift of each of the Bragg resonances into optical power changes. The design of the optical filters is also studied in this article. In first place, the ideal filter is calculated using a recursive method and defining the boundary conditions. This ideal filter linearizes the output of the interrogation setup but is limited by the large wavelength shift of the RFBG with temperature and the maximum attenuation. The response of modal interferometers as optical filters is also analyzed. They can be easily tuned shifting the optical spectrum. The output of the proposed interrogation scheme is simulated in these conditions improving the sensitivity.