942 resultados para data centric research


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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.

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Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

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Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is a very important problem with wide range of implications, including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. It is therefore more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alerts with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. After misbehavior is detected, we do not revoke all the secret credentials of misbehaving nodes, as done in most schemes. Instead, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes. © 2011 IEEE.

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Unattended Wireless Sensor Networks (UWSNs) operate in autonomous or disconnected mode: sensed data is collected periodically by an itinerant sink. Between successive sink visits, sensor-collected data is subject to some unique vulnerabilities. In particular, while the network is unattended, a mobile adversary (capable of subverting up to a fraction of sensors at a time) can migrate between compromised sets of sensors and inject fraudulent data. In this paper, we provide two collaborative authentication techniques that allow an UWSN to maintain integrity and authenticity of sensor data-in the presence of a mobile adversary-until the next sink visit. Proposed schemes use simple, standard, and inexpensive symmetric cryptographic primitives, coupled with key evolution and few message exchanges. We study their security and effectiveness, both analytically and via simulations. We also assess their robustness and show how to achieve the desired trade-off between performance and security.

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A workflow-centric research object bundles a workflow, the provenance of the results obtained by its enactment, other digital objects that are relevant for the experiment (papers, datasets, etc.), and annotations that semantically describe all these objects. In this paper, we propose a model to specify workflow-centric research objects, and show how the model can be grounded using semantic technologies and existing vocabularies, in particular the Object Reuse and Exchange (ORE) model and the Annotation Ontology (AO).We describe the life-cycle of a research object, which resembles the life-cycle of a scienti?c experiment.

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In New Zealand and Australia, the BRACElet project has been investigating students' acquisition of programming skills in introductory programming courses. The project has explored students' skills in basic syntax, tracing code, understanding code, and writing code, seeking to establish the relationships between these skills. This ITiCSE working group report presents the most recent step in the BRACElet project, which includes replication of earlier analysis using a far broader pool of naturally occurring data, refinement of the SOLO taxonomy in code-explaining questions, extension of the taxonomy to code-writing questions, extension of some earlier studies on students' 'doodling' while answering exam questions, and exploration of a further theoretical basis for work that until now has been primarily empirical.

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Postprint

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The term Artificial intelligence acquired a lot of baggage since its introduction and in its current incarnation is synonymous with Deep Learning. The sudden availability of data and computing resources has opened the gates to myriads of applications. Not all are created equal though, and problems might arise especially for fields not closely related to the tasks that pertain tech companies that spearheaded DL. The perspective of practitioners seems to be changing, however. Human-Centric AI emerged in the last few years as a new way of thinking DL and AI applications from the ground up, with a special attention at their relationship with humans. The goal is designing a system that can gracefully integrate in already established workflows, as in many real-world scenarios AI may not be good enough to completely replace its humans. Often this replacement may even be unneeded or undesirable. Another important perspective comes from, Andrew Ng, a DL pioneer, who recently started shifting the focus of development from “better models” towards better, and smaller, data. He defined his approach Data-Centric AI. Without downplaying the importance of pushing the state of the art in DL, we must recognize that if the goal is creating a tool for humans to use, more raw performance may not align with more utility for the final user. A Human-Centric approach is compatible with a Data-Centric one, and we find that the two overlap nicely when human expertise is used as the driving force behind data quality. This thesis documents a series of case-studies where these approaches were employed, to different extents, to guide the design and implementation of intelligent systems. We found human expertise proved crucial in improving datasets and models. The last chapter includes a slight deviation, with studies on the pandemic, still preserving the human and data centric perspective.

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Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

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The proposal to work on this final project came after several discussions held with Dr. Elzbieta Malinowski Gadja, who in 2008 published the book entitled Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (Data-Centric Systems and Applications). The project was carried out under the technical supervision of Dr. Malinowski and the direct beneficiary was the University of Costa Rica (UCR) where Dr. Malinowski is a professor at the Department of Computer Science and Informatics. The purpose of this project was twofold: First, to translate chapter III of said book with the intention of generating educational material for the use of the UCR and, second, to venture in the field of technical translation related to data warehouse. For the first component, the goal was to generate a final product that would eventually serve as an educational tool for the post-graduate courses of the UCR. For the second component, this project allowed me to acquire new skills and put into practice techniques that have helped me not only to perfom better in my current job as an Assistant Translator of the Inter-American BAnk (IDB), but also to use them in similar projects. The process was lenggthy and required torough research and constant communication with the author. The investigation focused on the search of terms and definitions to prepare the glossary, which was the basis to start the translation project. The translation process itself was carried out by phases, so that comments and corrections by the author could be taken into account in subsequent stages. Later, based on the glossary and the translated text, illustrations had been created in the Visio software were translated. In addition to the technical revision by the author, professor Carme Mangiron was in charge of revising the non-technical text. The result was a high-quality document that is currently used as reference and study material by the Department of Computer Science and Informatics of Costa Rica.

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The constant scientific production in the universities and in the research centers makes these organizations produce and acquire a great amount of data in a short period of time. Due to the big quantity of data, the research organizations become potentially vulnerable to the impacts on information booms that may cause a chaos as far as information management is concerned. In this context, the development of data catalogues comes up as one possible solution to the problems such as (I) the organization and (II) the data management. In the scientific scope, the data catalogues are implemented with the standard for digital and geospatial metadata and are broadly utilized in the process of producing a catalogue of scientific information. The aim of this work is to present the characteristics of access and storage of metadata in databank systems in order to improve the description and dissemination of scientific data. Relevant aspects will be considered and they should be analyzed during the stage of planning, once they can determine the success of implementation. The use of data catalogues by research organizations may be a way to promote and facilitate the dissemination of scientific data, avoid the repetition of efforts while being executed, as well as incentivate the use of collected, processed an also stored.

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The proposal to work on this final project came after several discussions held with Dr. Elzbieta Malinowski Gadja, who in 2008 published the book entitled Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (Data-Centric Systems and Applications). The project was carried out under the technical supervision of Dr. Malinowski and the direct beneficiary was the University of Costa Rica (UCR) where Dr. Malinowski is a professor at the Department of Computer Science and Informatics. The purpose of this project was twofold: First, to translate chapter III of said book with the intention of generating educational material for the use of the UCR and, second, to venture in the field of technical translation related to data warehouse. For the first component, the goal was to generate a final product that would eventually serve as an educational tool for the post-graduate courses of the UCR. For the second component, this project allowed me to acquire new skills and put into practice techniques that have helped me not only to perfom better in my current job as an Assistant Translator of the Inter-American BAnk (IDB), but also to use them in similar projects. The process was lenggthy and required torough research and constant communication with the author. The investigation focused on the search of terms and definitions to prepare the glossary, which was the basis to start the translation project. The translation process itself was carried out by phases, so that comments and corrections by the author could be taken into account in subsequent stages. Later, based on the glossary and the translated text, illustrations had been created in the Visio software were translated. In addition to the technical revision by the author, professor Carme Mangiron was in charge of revising the non-technical text. The result was a high-quality document that is currently used as reference and study material by the Department of Computer Science and Informatics of Costa Rica.