Tourism carrying capacity of Mar Chiquita beaches, Buenos Aires, Argentina

La zona costera del Partido de Mar Chiquita presenta playas cuya geomorfología y nivel de antropización es diversa. De sur a norte, incluye los barrios costeros de Playa Dorada, Santa Elena, Santa Clara del Mar, Camet Norte, La Caleta, Mar de Cobo y Balneario Parque Mar Chiquita. Es uno de los sectores de la provincia de Buenos Aires más afectados por los procesos de erosión costera. Esta erosión es originada principalmente por tormentas sudestadas y por la incesante modificación del paisaje ribereño causada por la urbanización y las obras de defensa costera. Planificar la capacidad máxima soportable de un determinado espacio, en conjunto con una ordenación ambiental del territorio, contribuye a que dicho fenómeno no se vea incrementado. El presente trabajo se enfocó en determinar la Capacidad de Carga Turística (CCT) para las playas del Partido de Mar Chiquita, mediante el empleo de fotografías aéreas e imágenes satelitales, con el fin de determinar la carga máxima de personas que podrán acceder a dicho recurso sin representar un detrimento de la calidad de este y también analizar la evolución de la gestión municipal en relación con el manejo del turismo costero. La CCT para el área de estudio arrojó un valor de 1 887.07 visitantes/día para el año 2011, comparado con los 943.55 que se obtuvieron para el año 1955.Mar Chiquita beaches’ geomorphology and anthropization is diverse. From south to north, this area inclu-des the following coastal areas: Playa Dorada, Santa Elena, Santa Clara del Mar, Camet Norte, La Caleta, Mar de Cobo and Balneario Parque Mar Chiquita. This section is one of the most affected areas by erosion in the Buenos Aires Province. Erosion here is caused mainly by southerly storms and constant changes in the coastal landscape resulting from urbanization and the coastal defense work. Planning the maximum tolerable capacity for a given space and environmental land management help this phenomenon not to in-crease. This study was focused on determining the Tourism Carrying Capacity (TCC) for the Mar Chiquita beaches by using aerial photographs and satellite images in order to determinate the maximum amount of visitors in this resource without affecting its quality and analyze the evolution of municipal management in relation to coastal tourism management. TCC for the studied area was stated at 1,887.07 visitors/day in 2011, compared to 943.55 visitors for 1955.Fil: Fernández, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Bertola, German Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentin

Early forest fire detection by vision-enabled wireless sensor networks

Wireless sensor networks constitute a powerful technology particularly suitable for environmental monitoring. With regard to wildfires, they enable low-cost fine-grained surveillance of hazardous locations like wildland-urban interfaces. This paper presents work developed during the last 4 years targeting a vision-enabled wireless sensor network node for the reliable, early on-site detection of forest fires. The tasks carried out ranged from devising a robust vision algorithm for smoke detection to the design and physical implementation of a power-efficient smart imager tailored to the characteristics of such an algorithm. By integrating this smart imager with a commercial wireless platform, we endowed the resulting system with vision capabilities and radio communication. Numerous tests were arranged in different natural scenarios in order to progressively tune all the parameters involved in the autonomous operation of this prototype node. The last test carried out, involving the prescribed burning of a 95 x 20-m shrub plot, confirmed the high degree of reliability of our approach in terms of both successful early detection and a very low false-alarm rate. Journal compilationMinisterio de Ciencia e Innovación TEC2009-11812, IPT-2011-1625-430000Office of Naval Research (USA) N000141110312Centro para el Desarrollo Tecnológico e Industrial IPC-2011100

Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm

n this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.This research was partially funded by Ministerio de Economía, Industria y Competitividad, project number TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P, and by the Comunidad Autónoma de Madrid, project number S2013ICE-2933_02

Modelling consumer credit risk via survival analysis

Credit risk models are used by financial companies to evaluate in advance the insolvency risk caused by credits that enter into default. Many models for credit risk have been developed over the past few decades. In this paper, we focus on those models that can be formulated in terms of the probability of default by using survival analysis techniques. With this objective three different mechanisms are proposed based on the key idea of writing the default probability in terms of the conditional distribution function of the time to default. The first method is based on a Cox’s regression model, the second approach uses generalized linear models under censoring and the third one is based on nonparametric kernel estimation, using the product-limit conditional distribution function estimator by Beran. The resulting nonparametric estimator of the default probability is proved to be consistent and asymptotically normal. An empirical study, based on modified real data, illustrates the three methods.Peer Reviewe

CMOS Vision Sensors: Embedding Computer Vision at Imaging Front-Ends

CMOS Image Sensors (CIS) are key for imaging technol-ogies. These chips are conceived for capturing opticalscenes focused on their surface, and for delivering elec-trical images, commonly in digital format. CISs may incor-porate intelligence; however, their smartness basicallyconcerns calibration, error correction and other similartasks. The term CVISs (CMOS VIsion Sensors) definesother class of sensor front-ends which are aimed at per-forming vision tasks right at the focal plane. They havebeen running under names such as computational imagesensors, vision sensors and silicon retinas, among others. CVIS and CISs are similar regarding physical imple-mentation. However, while inputs of both CIS and CVISare images captured by photo-sensors placed at thefocal-plane, CVISs primary outputs may not be imagesbut either image features or even decisions based on thespatial-temporal analysis of the scenes. We may hencestate that CVISs are more “intelligent” than CISs as theyfocus on information instead of on raw data. Actually,CVIS architectures capable of extracting and interpretingthe information contained in images, and prompting reac-tion commands thereof, have been explored for years inacademia, and industrial applications are recently ramp-ing up.One of the challenges of CVISs architects is incorporat-ing computer vision concepts into the design flow. Theendeavor is ambitious because imaging and computervision communities are rather disjoint groups talking dif-ferent languages. The Cellular Nonlinear Network Univer-sal Machine (CNNUM) paradigm, proposed by Profs.Chua and Roska, defined an adequate framework forsuch conciliation as it is particularly well suited for hard-ware-software co-design [1]-[4]. This paper overviewsCVISs chips that were conceived and prototyped at IMSEVision Lab over the past twenty years. Some of them fitthe CNNUM paradigm while others are tangential to it. Allthem employ per-pixel mixed-signal processing circuitryto achieve sensor-processing concurrency in the quest offast operation with reduced energy budget.Junta de Andalucía TIC 2012-2338Ministerio de Economía y Competitividad TEC 2015-66878-C3-1-R y TEC 2015-66878-C3-3-

In the quest of vision-sensors-on-chip: Pre-processing sensors for data reduction

This paper shows that the implementation of vision systems benefits from the usage of sensing front-end chips with embedded pre-processing capabilities - called CVIS. Such embedded pre-processors reduce the number of data to be delivered for ulterior processing. This strategy, which is also adopted by natural vision systems, relaxes system-level requirements regarding data storage and communications and enables highly compact and fast vision systems. The paper includes several proof-o-concept CVIS chips with embedded pre-processing and illustrate their potential advantages. © 2017, Society for Imaging Science and Technology.Office of Naval Research (USA) N00014-14-1-0355Ministerio de Economía y Competitiviad TEC2015-66878-C3-1-R, TEC2015-66878-C3-3-RJunta de Andalucía 2012 TIC 233

Theorical quantification of emissions produced in the use of explosives in large mining in Colombia

Una cuantificación de las emisiones y sustancias generadas para los productos es una herramienta útil para reducir y anticiparse a impactos que pueda afectar nuestro entorno. En el caso de explosivos civiles, los cuales son utilizados en infraestructura (vial y energética) y minería, permite conocer de primera mano las etapas en las cuales los impactos y sus efectos pueden ser reducidos a partir de optimización logística, selección de materias primas y formulaciones que aprovechen mejor la energía mediante un enfoque de balance de oxígeno, a fin de disminuir la huella de carbono global. Los resultados principales muestran que los mayores impactos son causados por el nitrato de amonio en la eutrificación del agua y en los kilogramos dióxido de carbono equivalente producto de la reacción. Las comparaciones de cinco emulsiones muestran que la inclusión de aceite usado proveniente de otros procesos conlleva una reducción de impactos ambientales.A quantification of emissions and substances generated for products is a useful tool to reduce and anticipate impacts that may affect our environment. In the case of civil explosives, which are used in infrastructure (vial and energy) and mining, it allows us to know first-hand the stages in which the impacts and their effects can be reduced from logistics optimization, selection of raw materials and formulations that make better use of it. energy using an oxygen balance approach, in order to decrease the global carbon footprint. The main results show that the greatest impacts are caused by ammonium nitrate in the eutrophication of the water and in the kilograms of carbon dioxide equivalent product of the reaction. Comparisons of five emulsions show that the inclusion of used oil from other processes leads to a reduction in environmental impacts.Especializació

System based on inertial sensors for behavioral monitoring of wildlife

Sensors Network is an integration of multiples sensors in a system to collect information about different environment variables. Monitoring systems allow us to determine the current state, to know its behavior and sometimes to predict what it is going to happen. This work presents a monitoring system for semi-wild animals that get their actions using an IMU (inertial measure unit) and a sensor fusion algorithm. Based on an ARM-CortexM4 microcontroller this system sends data using ZigBee technology of different sensor axis in two different operations modes: RAW (logging all information into a SD card) or RT (real-time operation). The sensor fusion algorithm improves both the precision and noise interferences.Junta de Andalucía P12-TIC-130