CATARINA 2012-Leg 1 - CTD-O2 Data report

The CATARINA Leg1 cruise was carried out from June 22 to July 24 2012 on board the B/O Sarmiento de Gamboa, under the scientific supervision of Aida Rios (CSIC-IIM). It included the occurrence of the OVIDE hydrological section that was performed in June 2002, 2004, 2006, 2008 and 2010, as part of the CLIVAR program (name A25) ), and under the supervision of Herlé Mercier (CNRSLPO). This section begins near Lisbon (Portugal), runs through the West European Basin and the Iceland Basin, crosses the Reykjanes Ridge (300 miles north of Charlie-Gibbs Fracture Zone, and ends at Cape Hoppe (southeast tip of Greenland). The objective of this repeated hydrological section is to monitor the variability of water mass properties and main current transports in the basin, complementing the international observation array relevant for climate studies. In addition, the Labrador Sea was partly sampled (stations 101-108) between Greenland and Newfoundland, but heavy weather conditions prevented the achievement of the section south of 53°40’N. The quality of CTD data is essential to reach the first objective of the CATARINA project, i.e. to quantify the Meridional Overturning Circulation and water mass ventilation changes and their effect on the changes in the anthropogenic carbon ocean uptake and storage capacity. The CATARINA project was mainly funded by the Spanish Ministry of Sciences and Innovation and co-funded by the Fondo Europeo de Desarrollo Regional. The hydrological OVIDE section includes 95 surface-bottom stations from coast to coast, collecting profiles of temperature, salinity, oxygen and currents, spaced by 2 to 25 Nm depending on the steepness of the topography. The position of the stations closely follows that of OVIDE 2002. In addition, 8 stations were carried out in the Labrador Sea. From the 24 bottles closed at various depth at each stations, samples of sea water are used for salinity and oxygen calibration, and for measurements of biogeochemical components that are not reported here. The data were acquired with a Seabird CTD (SBE911+) and an SBE43 for the dissolved oxygen, belonging to the Spanish UTM group. The software SBE data processing was used after decoding and cleaning the raw data. Then, the LPO matlab toolbox was used to calibrate and bin the data as it was done for the previous OVIDE cruises, using on the one hand pre and post-cruise calibration results for the pressure and temperature sensors (done at Ifremer) and on the other hand the water samples of the 24 bottles of the rosette at each station for the salinity and dissolved oxygen data. A final accuracy of 0.002°C, 0.002 psu and 0.04 ml/l (2.3 umol/kg) was obtained on final profiles of temperature, salinity and dissolved oxygen, compatible with international requirements issued from the WOCE program.

Sistema integrado de generación de mapas de profundidad para videoconferencia 3D en tiempo real

This paper presents the implementation of a high quality real-time 3D video system intended for 3D videoconferencing -- Basically, the system is able to extract depth information from a pair of images coming from a short-baseline camera setup -- The system is based on the use of a variant of the adaptive support-weight algorithm to be applied on GPU-based architectures -- The reason to do it is to get real-time results without compromising accuracy and also to reduce costs by using commodity hardware -- The complete system runs over the GStreamer multimedia software platform to make it even more flexible -- Moreover, an autoestereoscopic display has been used as the end-up terminal for 3D content visualization

Falcon herramientas de software para el procesamiento aerofotogramétrico

En el área de Aerofotogrametría Digital, el software comercial prevalente para postproceso presenta limitaciones debido a dos factores: (i) las legislaciones de cada país o región requieren diferentes convenciones, y (ii) las necesidades de las empresas son tan cambiantes que no justifican la compra de software de alto rendimiento, que puede quedar sin utilizar debido a un viraje del mercado -- El presente proyecto se ha desarrollado para atender necesidades de procesamiento automático de planos (partición, detección y corrección de errores, etc.), así como módulos de importación – exportación paquete a paquete, trazado de rutas e interacción con GPS -- Este artículo informa de los dos últimos aspectos -- Debido a necesidades de los clientes, los archivos entregados deben llevar un formato comercial (DWG, DXF), pero el procesamiento de los archivos debe ser hecho en paquetes y formatos diversos (DGN) -- Por lo tanto, fue necesario diseñar e implementar un formato acompañante que permitió llevar la información que se pierde al usar filtros comerciales (DGN a DXF/DWG) -- Asimismo se crearon módulos de importación y exportación redundantes, que hicieron efectivos dichos atributos -- En el aspecto de generación de rutas de vuelo, se reportan en este artículo la aplicación de algoritmos tradicionales de barrido (peinado) de áreas 2D, a los cuales se agregaron restricciones geométricas (puntos fijos, offsets, orden de los barridos de acuerdo a coordenadas del sitio de partida, etc.) -- Debido a los altos costos de equipos equivalentes, se decidió desarrollar software para traducción de rutas entre formatos GPS y formatos geográficos locales al país -- Ello permite la eliminación de fuentes de error y además facilita la carga del plan de vuelo, a costos mucho menores a los del hardware / software comercial

Herramientas automáticas de diagnóstico y corrección para aerofotogrametría

En Aerofotogrametría, el proceso de restitución (paso de imagen a formato electrónico vectorizado) es realizado por un operador humano, con asistencia de hardware y Software especializado -- Dicho proceso implica la traducción de accidentes geográficos, detalles topográficos, etc., la cual conlleva errores tanto geométricos (precisión) como topológicos (conectividad) de los datos digitales vectorizados -- Adicionalmente, aun si la vectorizacion es perfecta, los editores en etapas subsecuentes deben realizar tareas repetitivas: formateo, marcado, ajuste de convenciones, etc., que por el tamaño de los archivos de datos se hacen prolongadas y propensas al error -- Tanto los procesos de corrección como de formateo y marcado requieren además la ejecución de entradas / salidas con el usuario en el computador, proceso que es particularmente lento -- Esta investigación presenta el desarrollo de herramientas automáticas de (i) detección y corrección de errores comunes en los planos restituidos, (ii) partición y re-agrupación inteligentes de planos grandes, y (iii) formateo y marcado automático -- El desarrollo de software se hace usando el standard AIS (Application Interface Specification), lo que lo hace portable a los modeladores cuya interface AIS haya sido implementada -- El proyecto se desarrolla para la firma AeroEstudios LTDA de Colombia, la cual lo ha incorporado a sus herramientas de procesamiento de información digital

Hints on building a church /

Includes bibliographical references (p. 191-194) and index.

Smart mail – a smart platform for mail management

Email is a key communication format in a digital world, both for professional and/or personal usage. Exchanged messages (both human and automatically generated) have reached such a volume that processing them can be a great challenge for human users that try to do it on a daily basis and in an efficient manner. In fact, a significant amount of their time is spent searching and getting context information (normally historic information) in order to prepare a reply message or to take a decision/action, when compared to the actual time required for writing a reply. Therefore, it is of utmost importance for this process to use both automatic and semi-automatic mechanisms that allow to put email messages into context. Since context information is given, not only by historical email messages but also inferred from the relationship between contacts and/or organizations present in the messages, the existence of navigation mechanisms (and even exploration ones) between contacts and entities associated to email messages, is of fundamental importance. This is the main purpose of the SMART Mail prototype, which architecture, data visualization and exploration components and AI algorithms, are presented throughout this paper.

Data protection by design in the e-health care sector: theoretical and applied perspectives

In the digital age, e-health technologies play a pivotal role in the processing of medical information. As personal health data represents sensitive information concerning a data subject, enhancing data protection and security of systems and practices has become a primary concern. In recent years, there has been an increasing interest in the concept of Privacy by Design, which aims at developing a product or a service in a way that it supports privacy principles and rules. In the EU, Article 25 of the General Data Protection Regulation provides a binding obligation of implementing Data Protection by Design technical and organisational measures. This thesis explores how an e-health system could be developed and how data processing activities could be carried out to apply data protection principles and requirements from the design stage. The research attempts to bridge the gap between the legal and technical disciplines on DPbD by providing a set of guidelines for the implementation of the principle. The work is based on literature review, legal and comparative analysis, and investigation of the existing technical solutions and engineering methodologies. The work can be differentiated by theoretical and applied perspectives. First, it critically conducts a legal analysis on the principle of PbD and it studies the DPbD legal obligation and the related provisions. Later, the research contextualises the rule in the health care field by investigating the applicable legal framework for personal health data processing. Moreover, the research focuses on the US legal system by conducting a comparative analysis. Adopting an applied perspective, the research investigates the existing technical methodologies and tools to design data protection and it proposes a set of comprehensive DPbD organisational and technical guidelines for a crucial case study, that is an Electronic Health Record system.

Data analysis of collapse mechanisms of a 3D printed groin vault in shaking table testing

The aim of this novel experimental study is to investigate the behaviour of a 2m x 2m model of a masonry groin vault, which is built by the assembly of blocks made of a 3D-printed plastic skin filled with mortar. The choice of the groin vault is due to the large presence of this vulnerable roofing system in the historical heritage. Experimental tests on the shaking table are carried out to explore the vault response on two support boundary conditions, involving four lateral confinement modes. The data processing of markers displacement has allowed to examine the collapse mechanisms of the vault, based on the arches deformed shapes. There then follows a numerical evaluation, to provide the orders of magnitude of the displacements associated to the previous mechanisms. Given that these displacements are related to the arches shortening and elongation, the last objective is the definition of a critical elongation between two diagonal bricks and consequently of a diagonal portion. This study aims to continue the previous work and to take another step forward in the research of ground motion effects on masonry structures.

Machine learning as a service for high energy physics (MLaaS4HEP): a service for ML-based data analyses

With the CERN LHC program underway, there has been an acceleration of data growth in the High Energy Physics (HEP) field and the usage of Machine Learning (ML) in HEP will be critical during the HL-LHC program when the data that will be produced will reach the exascale. ML techniques have been successfully used in many areas of HEP nevertheless, the development of a ML project and its implementation for production use is a highly time-consuming task and requires specific skills. Complicating this scenario is the fact that HEP data is stored in ROOT data format, which is mostly unknown outside of the HEP community. The work presented in this thesis is focused on the development of a ML as a Service (MLaaS) solution for HEP, aiming to provide a cloud service that allows HEP users to run ML pipelines via HTTP calls. These pipelines are executed by using the MLaaS4HEP framework, which allows reading data, processing data, and training ML models directly using ROOT files of arbitrary size from local or distributed data sources. Such a solution provides HEP users non-expert in ML with a tool that allows them to apply ML techniques in their analyses in a streamlined manner. Over the years the MLaaS4HEP framework has been developed, validated, and tested and new features have been added. A first MLaaS solution has been developed by automatizing the deployment of a platform equipped with the MLaaS4HEP framework. Then, a service with APIs has been developed, so that a user after being authenticated and authorized can submit MLaaS4HEP workflows producing trained ML models ready for the inference phase. A working prototype of this service is currently running on a virtual machine of INFN-Cloud and is compliant to be added to the INFN Cloud portfolio of services.

Big data analysis systems in IoE environments for managing privacy and data protection: pseudonymity, de-anonymization and the right to be forgotten

The thesis represents the conclusive outcome of the European Joint Doctorate programmein Law, Science & Technology funded by the European Commission with the instrument Marie Skłodowska-Curie Innovative Training Networks actions inside of the H2020, grantagreement n. 814177. The tension between data protection and privacy from one side, and the need of granting further uses of processed personal datails is investigated, drawing the lines of the technological development of the de-anonymization/re-identification risk with an explorative survey. After acknowledging its span, it is questioned whether a certain degree of anonymity can still be granted focusing on a double perspective: an objective and a subjective perspective. The objective perspective focuses on the data processing models per se, while the subjective perspective investigates whether the distribution of roles and responsibilities among stakeholders can ensure data anonymity.

Governing algorithms in the big data era for balancing new digital rights - designing GDPR compliant and trustworthy XAI systems

This thesis investigates the legal, ethical, technical, and psychological issues of general data processing and artificial intelligence practices and the explainability of AI systems. It consists of two main parts. In the initial section, we provide a comprehensive overview of the big data processing ecosystem and the main challenges we face today. We then evaluate the GDPR’s data privacy framework in the European Union. The Trustworthy AI Framework proposed by the EU’s High-Level Expert Group on AI (AI HLEG) is examined in detail. The ethical principles for the foundation and realization of Trustworthy AI are analyzed along with the assessment list prepared by the AI HLEG. Then, we list the main big data challenges the European researchers and institutions identified and provide a literature review on the technical and organizational measures to address these challenges. A quantitative analysis is conducted on the identified big data challenges and the measures to address them, which leads to practical recommendations for better data processing and AI practices in the EU. In the subsequent part, we concentrate on the explainability of AI systems. We clarify the terminology and list the goals aimed at the explainability of AI systems. We identify the reasons for the explainability-accuracy trade-off and how we can address it. We conduct a comparative cognitive analysis between human reasoning and machine-generated explanations with the aim of understanding how explainable AI can contribute to human reasoning. We then focus on the technical and legal responses to remedy the explainability problem. In this part, GDPR’s right to explanation framework and safeguards are analyzed in-depth with their contribution to the realization of Trustworthy AI. Then, we analyze the explanation techniques applicable at different stages of machine learning and propose several recommendations in chronological order to develop GDPR-compliant and Trustworthy XAI systems.

6G enabled IoV scenarios with distributed intelligence mechanisms

The Internet of Vehicles (IoV) paradigm has emerged in recent times, where with the support of technologies like the Internet of Things and V2X , Vehicular Users (VUs) can access different services through internet connectivity. With the support of 6G technology, the IoV paradigm will evolve further and converge into a fully connected and intelligent vehicular system. However, this brings new challenges over dynamic and resource-constrained vehicular systems, and advanced solutions are demanded. This dissertation analyzes the future 6G enabled IoV systems demands, corresponding challenges, and provides various solutions to address them. The vehicular services and application requests demands proper data processing solutions with the support of distributed computing environments such as Vehicular Edge Computing (VEC). While analyzing the performance of VEC systems it is important to take into account the limited resources, coverage, and vehicular mobility into account. Recently, Non terrestrial Networks (NTN) have gained huge popularity for boosting the coverage and capacity of terrestrial wireless networks. Integrating such NTN facilities into the terrestrial VEC system can address the above mentioned challenges. Additionally, such integrated Terrestrial and Non-terrestrial networks (T-NTN) can also be considered to provide advanced intelligent solutions with the support of the edge intelligence paradigm. In this dissertation, we proposed an edge computing-enabled joint T-NTN-based vehicular system architecture to serve VUs. Next, we analyze the terrestrial VEC systems performance for VUs data processing problems and propose solutions to improve the performance in terms of latency and energy costs. Next, we extend the scenario toward the joint T-NTN system and address the problem of distributed data processing through ML-based solutions. We also proposed advanced distributed learning frameworks with the support of a joint T-NTN framework with edge computing facilities. In the end, proper conclusive remarks and several future directions are provided for the proposed solutions.

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

In Vivo Determination Of The Volatile Metabolites Of Saprotroph Fungi By Comprehensive Two-dimensional Gas Chromatography.

In this work, we discuss the use of multi-way principal component analysis combined with comprehensive two-dimensional gas chromatography to study the volatile metabolites of the saprophytic fungus Memnoniella sp. isolated in vivo by headspace solid-phase microextraction. This fungus has been identified as having the ability to induce plant resistance against pathogens, possibly through its volatile metabolites. Adequate culture media was inoculated, and its headspace was then sampled with a solid-phase microextraction fiber and chromatographed every 24 h over seven days. The raw chromatogram processing using multi-way principal component analysis allowed the determination of the inoculation period, during which the concentration of volatile metabolites was maximized, as well as the discrimination of the appropriate peaks from the complex culture media background. Several volatile metabolites not previously described in the literature on biocontrol fungi were observed, as well as sesquiterpenes and aliphatic alcohols. These results stress that, due to the complexity of multidimensional chromatographic data, multivariate tools might be mandatory even for apparently trivial tasks, such as the determination of the temporal profile of metabolite production and extinction. However, when compared with conventional gas chromatography, the complex data processing yields a considerable improvement in the information obtained from the samples. This article is protected by copyright. All rights reserved.

Analise cinematica da movimentação dos membros superiores e inferiores, tronco e cabeça durante a marcha de hemipareticos

Universidade Estadual de Campinas . Faculdade de Educação Física