225 research outputs found
Earth‐Observation Data Access: A Knowledge Discovery Concept for Payload Ground Segments
In recent years the ability to store large quantities of Earth Observation (EO) satellite images has greatly surpassed the ability to access and meaningfully extract information from it. The state-of-the-art of operational systems for Remote Sensing data access (in particular for images) allows queries by geographical location, time of acquisition or type of sensor. Nevertheless, this information is often less relevant than the content of the scene (e.g. specific scattering properties, structures, objects, etc.). Moreover, the continuous increase in the size of the archives and in the variety and complexity of EO sensors require new methodologies and tools - based on a shared knowledge - for information mining and management, in support of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In addition, the current Payload Ground Segments (PGS) are mainly designed for Long Term Data Preservation (LTDP), in this article we propose an alternative solution for enhancing the access to the data content. Our solution presents a knowledge discovery concept, whose intention is to implement a communication channel between the PGS (EO data sources) and the end-user who receives the content of the data sources coded in an understandable format associated with semantics and ready for the exploitation. The first implemented concepts were presented in Knowledge driven content based Image Information Mining (KIM) and Geospatial Information Retrieval and Indexing (GeoIRIS) system as examples of data mining systems. Our new concept is developed in a modular system composed of the following components 1) the data model generation implementing methods for extracting relevant descriptors (low-level features) of the sources (EO images), analyzing their metadata in order to complement the information, and combining with vector data sources coming from Geographical Information Systems. 2) A database management system, where the database structure supports the knowledge management, feature computation, and visualization tools because of the modules for analysis, indexing, training and retrieval are resolved into the database. 3) Data mining and knowledge discovery tools allowing the end-user to perform advanced queries and to assign semantic annotations to the image content. The low-level features are complemented with semantic annotations giving meaning to the image information. The semantic description is based on semi-supervised learning methods for spatio-temporal and contextual pattern discovery. 4) Scene understanding counting on annotation tools for helping the user to create scenarios using EO images as for example change detection analysis, etc. 5) Visual data mining providing Human-Machine Interfaces for navigating and browsing the archive using 2D or 3D representation. The visualization techniques perform an interactive loop in order to optimize the visual interaction with huge volumes of data of heterogeneous nature and the end-user
Mining Multitemporal In Situ Heterogeneous Monitoring Information for the Assurance of Recorded Land Cover Changes
We present a data mining methodology to filter and validate land cover change detections obtained from multitemporal in situ surveys. As in situ data we use the measurements from the European land use and coverage area frame survey (LUCAS), which provides images with standardized metadata about land cover and land use within the whole territory of the European Union. Multitemporal LUCAS surveys present an anomaly in the amount of land cover changes that disagree with the estimated by experts. Therefore, our methodology analyses the available data in order to explain the existing irregularities in them. The initial step of our methodology is based on database query refinements. The data mining methodology continues with an image analysis process. This analysis calculates similarity measures of the multitemporal images that are used to identify the potential misclassifications. The final step involves a geographic information system based on web technologies. By defining different color codes assigned by the similarity measures, the system represents the examined points on a digital Earth globe. There, a user can easily discriminate potentially misclassified points for subsequent detailed analysis or corrections. The final output of the methodology shows remarkable results for detecting misclassified land cover changes
Analysis of Coastal Areas Using SAR Images: A Case Study of the Dutch Wadden Sea Region
The increased availability of civil synthetic aperture radar (SAR) satellite images with different resolution allows us to compare the imaging capabilities of these instruments, to assess the quality of the available data and to investigate different areas (e.g., the Wadden Sea region). In our investigation, we propose to explore the content of TerraSAR-X and Sentinel-1A satellite images via a data mining approach in which the main steps are patch tiling, feature extraction, classification, semantic annotation and visual-statistical analytics. Once all the extracted categories are mapped and quantified, then the next step is to interpret them from an environmental point of view. The objective of our study is the application of semi-automated SAR image interpretation. Its novelty is the automated multiclass categorisation of coastal areas. We found out that the north-west of the Netherlands can be interpreted routinely as land surfaces by our satellite image analyses, while for the Wadden Sea, we can discriminate the different water levels and their impact on the visibility of the tidal flats. This necessitates a selection of time series data spanning a full tidal cycle
Very-High-Resolution SAR Images and Linked Open Data Analytics Based on Ontologies
In this paper, we deal with the integration of multiple sources of information such as Earth observation (EO) synthetic aperture radar (SAR) images and their metadata, semantic descriptors of the image content, as well as other publicly available geospatial data sources expressed as linked open data for posing complex queries in order to support geospatial data analytics. Our approach lays the foundations for the development of richer tools and applications that focus on EO image analytics using ontologies and linked open data. We introduce a system architecture where a common satellite image product is transformed from its initial format into to actionable intelligence information, which includes image descriptors, metadata, image tiles, and semantic labels resulting in an EO-data model. We also create a SAR image ontology based on our EO-data model and a two-level taxonomy classification scheme of the image content. We demonstrate our approach by linking high-resolution TerraSAR-X images with information from CORINE Land Cover (CLC), Urban Atlas (UA), GeoNames, and OpenStreetMap (OSM), which are represented in the standard triple model of the resource description frameworks (RDFs)
The Digital Earth Observation Librarian: A Data Mining Approach for Large Satellite Images Archives
Throughout the years, various Earth Observation (EO) satellites have generated huge amounts of data. The extraction of latent information in the data repositories is not a trivial task. New methodologies and tools, being capable of handling the size, complexity and variety of data, are required. Data scientists require support for the data manipulation, labeling and information extraction processes. This paper presents our Earth Observation Image Librarian (EOLib), a modular software framework which offers innovative image data mining capabilities for TerraSAR-X and EO image data, in general. The main goal of EOLib is to reduce the time needed to bring information to end-users from Payload Ground Segments (PGS). EOLib is composed of several modules which offer functionalities such as data ingestion, feature extraction from SAR (Synthetic Aperture Radar) data, meta-data extraction, semantic definition of the image content through machine learning and data mining methods, advanced querying of the image archives based on content, meta-data and semantic categories, as well as 3-D visualization of the processed images. EOLib is operated by DLR’s (German Aerospace Center’s) Multi-Mission Payload Ground Segment of its Remote Sensing Data Center at Oberpfaffenhofen, Germany
Identificación de blancos terapéuticos putativos en Caligus rogercresseyi utilizando bases de datos de transcriptómica del parásito
86 p.Caligus rogercresseyi es un ectoparásito que afecta en gran medida la producción de salmónidos en Chile. Se estima que las pérdidas directas e indirectas asociadas a Caligus en el año 2013 fueron de alrededor de US 700 millones, lo que indica la gran importancia de estudiar mecanismos de control de este parásito. En la actualidad se ha experimentado un evidente desarrollo de resistencias de C. rogercresseyi frente a los distintos tratamientos aplicados. Dentro de los principales factores que influyeron en esta pérdida de eficacia (resistencia) se menciona el uso exclusivo y continuado del producto por más de 7 años. Para este trabajo contamos con un set de datos transcriptómicos del parasito, es decir, secuencias obtenidas a partir de RNA. Las ventajas que tiene analizar el RNA o transcriptoma de un organismo, es el poder identificar cambios de expresión génica en determinado momento celular de un tratamiento, con respecto a un control, es decir, obtenemos una imagen temporal del panorama celular asociado a los RNAs, con respecto al panorama del tratamiento, haciendo comparables y evaluables los niveles de expresión en ambas condiciones mediante algoritmos estadísticos. En este contexto, la bioinformática juega un papel fundamental, como una disciplina integrativa que se ha convertido en un componente intrínseco en esta nueva fase de estudios moleculares a gran escala, pues provee herramientas para el manejo, análisis y manipulación de grandes cantidades de datos. Durante los últimos años, se ha logrado obtener información del RNA de variados organismos, los cuales son sujetos de investigación. Es por esto que técnicas de secuenciación de RNA (bajo el protocolo de secuenciación RNA-seq) han demostrado ser una herramienta de gran alcance y con una gama muy diversa de aplicaciones.
Con respecto a éste trabajo de memoria de título, el objetivo principal se basa en identificar secuencias aminoacídicas deducidas, asociadas a posibles proteínas o péptidos vinculados con resistencia farmacológica y/o como blancos terapéuticos putativos a través del análisis de las bases de datos transcriptómicas de Caligus rogercresseyi. Para lograr lo anterior, se realizó un análisis de las bases de datos transcriptómicas de Caligus rogercresseyi a partir de un ensamble de novo del transcriptoma del parásito, para luego lograr identificar a través de expresión diferencial los distintos niveles de expresión existentes con tratamientos de Emamectina y Deltametrina en C.rogercresseyi. Se utilizó un protocolo de RNA-seq, en conjunto con otras herramientas bioinformáticas, con las cuales se buscó encontrar blancos terapéuticos putativos, que permitan desarrollar futuros estudios para combatir con éxito a este parásito y, de esta manera a largo plazo, lograr disminuir de las pérdidas económicas causadas por Caligus. Y desde otra perspectiva, que en ningún caso es menos importante, la generación de este conocimiento posibilitará contribuir en una posible disminución de la contaminación ambiental asociada a los tratamientos químicos, como los realizados hoy en día./
ABSTRACT: Caligus rogercresseyi is an ectoparasite that greatly affects the production of salmonids in Chile. It is estimated that the direct and indirect losses associated with sea lice in 2013 were about US 700 million, which indicates the great importance of studying mechanisms controlling this pest. Today it has experienced an obvious development of resistance of C. rogercresseyi against the various treatments applied. Among the main factors influencing this efficiency loss (resistance) mentioned the exclusive and continuous use of the product for more than 7 years.For this study we have a set of the parasite transcriptome data, that is to say sequences obtained from RNA. The advantages analyze the RNA or transcriptome of an organism, in order to identify gene expression changes in certain cells during a treatment, with respect to control, that is to say, obtain a temporary image cell panorama of associated RNAs, with respect to the treatment panorama, making comparable and evaluable expression levels in both conditions using statistical algorithms. In this context, bioinformatics plays a key role as an integrative discipline that has become an intrinsic component in this new phase of molecular-scale studies, it provides tools for operation, analysis and handling of large amounts of data. In recent years, it has been possible to obtain information of various organisms RNA, which are subject to research. That is why RNA sequencing techniques (under the protocol sequencing RNA-seq) have proven to be a powerful tool with a very diverse range of applications. With respect to this thesis, the main objective is based on identifying amino acid sequences deduced, associated with possible proteins or peptides associated with drug resistance and / or as therapeutic targets putative through the analysis of the basis of transcriptomic data Caligus rogercresseyi. To achieve this, an analysis of the basis of transcriptomic data Caligus rogercresseyi was performed from an ensemble de novo transcriptome parasite, and then be able to identify through differential expressions, different levels of existing expression treatments Emamectin and deltamethrin in C. rogercresseyi.
IX A protocol of RNA-seq was used in conjunction with other bioinformatics tools, with which they seek to find putative therapeutic targets, in order to develop future studies to successfully combat this parasite and thus long-term, achieve the decrease of economic losses caused by sea lice. And from another perspective, that in no case is less important, the generation of this knowledge will enable a contribution to a possible reduction of environmental pollution associated with chemical treatments, such as those made today
5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica
El V Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2019, realizado del 6 al 8 de febrero de 2019 y organizado por la Universidad Politécnica Salesiana, ofreció a la comunidad académica nacional e internacional una plataforma de comunicación unificada, dirigida a cubrir los problemas teóricos y prácticos de mayor impacto en la sociedad moderna desde la ingeniería.
En esta edición, dedicada a los 25 años de vida de la UPS, los ejes temáticos estuvieron relacionados con la aplicación de la ciencia, el desarrollo tecnológico y la innovación en cinco pilares fundamentales de nuestra sociedad: la industria, la movilidad, la sostenibilidad ambiental, la información y las telecomunicaciones.
El comité científico estuvo conformado formado por 48 investigadores procedentes de diez países: España, Reino Unido, Italia, Bélgica, México, Venezuela, Colombia, Brasil, Estados Unidos y Ecuador.
Fueron recibidas un centenar de contribuciones, de las cuales 39 fueron aprobadas en forma de ponencias y 15 en formato poster. Estas contribuciones fueron presentadas de forma oral ante toda la comunidad académica que se dio cita en el Congreso, quienes desde el aula magna, el auditorio y la sala de usos múltiples de la Universidad Politécnica Salesiana, cumplieron respetuosamente la responsabilidad de representar a toda la sociedad en la revisión, aceptación y validación del conocimiento nuevo que fue presentado en cada exposición por los investigadores.
Paralelo a las sesiones técnicas, el Congreso contó con espacios de presentación de posters científicos y cinco workshops en temáticas de vanguardia que cautivaron la atención de nuestros docentes y estudiantes. También en el marco del evento se impartieron un total de ocho conferencias magistrales en temas tan actuales como la gestión del conocimiento en la universidad-ecosistema, los retos y oportunidades de la industria 4.0, los avances de la investigación básica y aplicada en mecatrónica para el estudio de robots de nueva generación, la optimización en ingeniería con técnicas multi-objetivo, el desarrollo de las redes avanzadas en Latinoamérica y los mundos, la contaminación del aire debido al tránsito vehicular, el radón y los riesgos que representa este gas radiactivo para la salud humana, entre otros
A communal catalogue reveals Earth's multiscale microbial diversity
Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe
A communal catalogue reveals Earth’s multiscale microbial diversity
Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity
Worldwide comparison of survival from childhood leukaemia for 1995–2009, by subtype, age, and sex (CONCORD-2): a population-based study of individual data for 89 828 children from 198 registries in 53 countries
Background Global inequalities in access to health care are reflected in differences in cancer survival. The CONCORD programme was designed to assess worldwide differences and trends in population-based cancer survival. In this population-based study, we aimed to estimate survival inequalities globally for several subtypes of childhood leukaemia.
Methods Cancer registries participating in CONCORD were asked to submit tumour registrations for all children aged 0-14 years who were diagnosed with leukaemia between Jan 1, 1995, and Dec 31, 2009, and followed up until Dec 31, 2009. Haematological malignancies were defined by morphology codes in the International Classification of Diseases for Oncology, third revision. We excluded data from registries from which the data were judged to be less reliable, or included only lymphomas, and data from countries in which data for fewer than ten children were available for analysis. We also excluded records because of a missing date of birth, diagnosis, or last known vital status. We estimated 5-year net survival (ie, the probability of surviving at least 5 years after diagnosis, after controlling for deaths from other causes [background mortality]) for children by calendar period of diagnosis (1995-99, 2000-04, and 2005-09), sex, and age at diagnosis (< 1, 1-4, 5-9, and 10-14 years, inclusive) using appropriate life tables. We estimated age-standardised net survival for international comparison of survival trends for precursor-cell acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML).
Findings We analysed data from 89 828 children from 198 registries in 53 countries. During 1995-99, 5-year agestandardised net survival for all lymphoid leukaemias combined ranged from 10.6% (95% CI 3.1-18.2) in the Chinese registries to 86.8% (81.6-92.0) in Austria. International differences in 5-year survival for childhood leukaemia were still large as recently as 2005-09, when age-standardised survival for lymphoid leukaemias ranged from 52.4% (95% CI 42.8-61.9) in Cali, Colombia, to 91.6% (89.5-93.6) in the German registries, and for AML ranged from 33.3% (18.9-47.7) in Bulgaria to 78.2% (72.0-84.3) in German registries. Survival from precursor-cell ALL was very close to that of all lymphoid leukaemias combined, with similar variation. In most countries, survival from AML improved more than survival from ALL between 2000-04 and 2005-09. Survival for each type of leukaemia varied markedly with age: survival was highest for children aged 1-4 and 5-9 years, and lowest for infants (younger than 1 year). There was no systematic difference in survival between boys and girls.
Interpretation Global inequalities in survival from childhood leukaemia have narrowed with time but remain very wide for both ALL and AML. These results provide useful information for health policy makers on the effectiveness of health-care systems and for cancer policy makers to reduce inequalities in childhood survival
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