1,720,983 research outputs found

    Internet of Things for Earthquake Early Warning Systems: A Performance Comparison Between Communication Protocols

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    Earthquake Early Warning Systems (EEWSs) characterize seismic events in real time and estimate the expected ground motion amplitude in specific areas to send alerts before the destructive waves arrive. Together with the reliability of the results, the rapidity with which an EEWS can detect an earthquake becomes a focal point for developing efficient seismic node networks. Internet of Things (IoT) architectures can be used in EEWSs to expand a seismic network and acquire data even from low-cost seismic nodes. However, the latency and the total alert time introduced by the adopted communication protocols should be carefully evaluated. This study proposes an IoT solution based on the message queue-telemetry transport protocol for the waveform transmission acquired by seismic nodes and presents a performance comparison between it and the most widely used standard in current EEWSs. The comparison was performed in evaluation tests where different seismic networks were simulated using a dataset of real earthquakes. This study analyzes the phases preceding the earthquake detection, showing how the proposed solution detects the same events of traditional EEWSs with a total alert time of approximately 1.6 seconds lower

    Earthquake Early Warning Services Based on Very Low-Cost Internet of Things Devices

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    The performance of an Earthquake Early Warning system is often tied to the density of its stations. The use of Internet of Things and Cloud technologies could further enhance the capabilities of these systems, providing tools to analyze, store and process data, and also to efficiently monitor devices. Moreover, the technological developments in Micro-electromechanical systems have allowed the creation of low-cost and small size seismic monitoring devices that can be used to create denser seismic networks. In this work we propose and evaluate the performance of an IoT-based Early Warning device based on MEMS technology. The results of the performance evaluation show that the device is able to detect events of magnitude greater than 4.1 and located less than 30km away. Furthermore, the integration of the device into a Cloud IoT Architecture gives the proposed solution event detection, device monitoring and alarm dissemination capabilities

    Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison

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    Internet of Things (IoT) aims to connect the real world made up of devices, sensors and actuators to the virtual world of Internet in order to interconnect devices with each other generating information from the gathered data. Devices, in general, have limited computational power and limited storage capacity. Cloud Computing (CC) has virtually unlimited capacity in terms of storage and computing power, and is based on sharing resources. Therefore, the integration between IoT and CC seems to be one of the most promising solutions. In fact, many of the biggest companies that offer Cloud Services are focusing on the IoT world to offer services also in this direction to their users. In this paper we compare the three main Cloud Platforms (Amazon Web Services, Google Cloud Platform and Microsoft Azure) regarding to the services made available for the IoT. After describing the typical architecture of an IoT application, we map the Cloud-IoT Platforms services with this architecture analyzing the key points for each platform. At the same time, in order to conduct a comparative analysis of performance, we focus on a service made available by all platforms (MQTT middleware) building the reference scenarios and the metrics to be taken into account. Finally, we provide an overview of platform costs based on different loads. The aim is not to declare a winner, but to provide a useful tool to developers to make an informed choice of a platform depending on the use case

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Databases Performance Evaluation for IoT Systems: The Scrovegni Chapel Use Case

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    Internet of things devices are used to collect data from the physical world, and to present the results in a way well usable to the end user. Therefore, an accurate choice of the most appropriate technology for storing data collected from the network is relevant. In this paper we focus the attention on the selection of the best database management system for cultural heritage applications, in particular referring to the use case of light monitoring at the Scrovegni Chapel (Padua, Italy), to emphasize the Giotto's frescoes. For doing so, SQL and NoSQL solutions are compared, and the obtained results are used to find the best solution for this application. Moreover these results can be used as a practical reference for the more appropriate selection of the right database for real use cases

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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