1,720,987 research outputs found
Advanced Ceramics for Sustainable Energy Conversion Processes: from High Functionality Chemical Tailoring to Nanoscale Designed Materials
Full text linkThe last decades have been characterized by a constant increase in the need of energy coupled with an increase in the greenhouse gases emissions, since a large amount of the energy is provided by combustion plants burning fossil fuels. The level of CO2 has reached a negative record and this tendency has to be reversed in favor of a more environmentally sustainable approach. In this scenario different solutions for energy conversion and storage need to be found: the use of fossil fuels has to be reduced and replace with other and more sustainable forms of energy conversion. At the same time the change has to be guided by an improvement in the current technology for energy conversion to facilitate the transition process. For this purpose, the traditional combustion process can be improved using oxy-fuel conditions, where a stream of pure O2 provided by an oxygen transport membrane is used instead of air and the resulting high concentrated CO2 flue gas is easier to capture. A cleaner form of energy can be obtained using Solid Oxide Reversible Cells (SORCs), highly efficient electrochemical devices able convert chemicals directly into electrical current without production of pollutants. When operated in electrolysis mode, SORCs allow to store electrical energy in the form of fuels, obtained from CO2 reduction.
Despite being extremely appealing, both these possibilities are not integrated in large scale energy plants yet, due mainly to their cost and long-term stability issues. These aspects can be improved with materials having a better performance and this can be achieved by an appropriate tailoring of their properties.
This thesis presents the attempt to address these issues by developing novel advanced ceramic materials with high performances in order to fulfill a lower temperature application. In particular, this has been pursued aiming at improving the ionic conductivity of the materials. A GDC/YSZ nanocomposite has been prepared by inkjet printing and characterized as electrolyte, with attention to the interaction between the two phases. Complex perovskites have been designed and optimized to stabilize a high oxygen defective crystal phase displaying mixed ionic and electronic conductivity. These materials have been characterized in their structure, oxygen mobility and conductivity, before being tested as oxygen transport membranes and cathodes for solid oxide fuel cells
Optimizing edge computing resources towards greener networks and services
Full text linkThe world is at the dawn of a new era, characterized by a large number of connected devices and a resulting massive availability of networked data. In this scenario, multi-access edge computing (MEC) is the candidate reference paradigm to provide mobile users with low latency processing and storage services. In contrast with mobile cloud computing (MCC), MEC entails the deployment of computing facilities closer to the end devices, thus becoming a key enabler for applications such as augmented reality, tactile Internet, smart home, healthcare monitoring, connected cars, online gaming, etc. However, the problem of the energy efficiency of the decentralized MEC infrastructure arises. In this doctoral thesis, the management of the MEC platform is optimized to reduce the global carbon footprint of the network, i.e., to maximize the use of renewable energy resources (RERs) for the initial placement and the subsequent execution and offloading of jobs. The main body of the thesis is organized into three chapters: the first one tackles the green energy management of edge servers equipped with a battery in a hierarchical MEC network and the electricity trade with the power grid; the second chapter considers a vehicular scenario where vehicles' trajectories are proactively tracked when migrating the users' computing tasks towards increasing the energetic efficiency of this process; the third chapter presents a comparison of the two decentralized optimization approaches designed, based on message passing. The results show that the proposed optimization frameworks, based on model predictive control (MPC), can significantly reduce the carbon footprint of the edge network when compared to simple heuristics and other approaches in the scientific literature. The designed algorithms can reach almost complete carbon neutrality in a vast range of network conditions.The world is at the dawn of a new era, characterized by a large number of connected devices and a resulting massive availability of networked data. In this scenario, multi-access edge computing (MEC) is the candidate reference paradigm to provide mobile users with low latency processing and storage services. In contrast with mobile cloud computing (MCC), MEC entails the deployment of computing facilities closer to the end devices, thus becoming a key enabler for applications such as augmented reality, tactile Internet, smart home, healthcare monitoring, connected cars, online gaming, etc. However, the problem of the energy efficiency of the decentralized MEC infrastructure arises. In this doctoral thesis, the management of the MEC platform is optimized to reduce the global carbon footprint of the network, i.e., to maximize the use of renewable energy resources (RERs) for the initial placement and the subsequent execution and offloading of jobs. The main body of the thesis is organized into three chapters: the first one tackles the green energy management of edge servers equipped with a battery in a hierarchical MEC network and the electricity trade with the power grid; the second chapter considers a vehicular scenario where vehicles' trajectories are proactively tracked when migrating the users' computing tasks towards increasing the energetic efficiency of this process; the third chapter presents a comparison of the two decentralized optimization approaches designed, based on message passing. The results show that the proposed optimization frameworks, based on model predictive control (MPC), can significantly reduce the carbon footprint of the edge network when compared to simple heuristics and other approaches in the scientific literature. The designed algorithms can reach almost complete carbon neutrality in a vast range of network conditions
Divide and Save: Splitting Workload Among Containers in an Edge Device to Save Energy and Time
Full text linkThe increasing demand for edge computing is leading to a rise in energy consumption from edge devices, which can have significant environmental and financial implications. To address this, in this paper we present a novel method to enhance the energy efficiency while speeding up computations by distributing the workload among multiple containers in an edge device. Experiments are conducted on two Nvidia Jetson edge boards, the TX2 and the AGX Orin, exploring how using a different number of containers can affect the energy consumption and the computational time for an inference task. To demonstrate the effectiveness of our splitting approach, a video object detection task is conducted using an embedded version of the state-of-the-art YOLO algorithm, quantifying the energy and the time savings achieved compared to doing the computations on a single container. The proposed method can help mitigate the environmental and economic consequences of high energy consumption in edge computing, by providing a more sustainable approach to managing the workload of edge devices
Decentralized LLM Inference over Edge Networks with Energy Harvesting
Full text linkLarge language models have significantly transformed multiple fields with their exceptional performance in natural language tasks, but their deployment in resource-constrained environments like edge networks presents an ongoing challenge. Decentralized techniques for inference have emerged, distributing the model blocks among multiple devices to improve flexibility and cost effectiveness. However, energy limitations remain a significant concern for edge devices. We propose a sustainable model for collaborative inference on interconnected, battery-powered edge devices with energy harvesting. A semi-Markov model is developed to describe the states of the devices, considering processing parameters and average green energy arrivals. This informs the design of scheduling algorithms that aim to minimize device downtimes and maximize network throughput. Through empirical evaluations and simulated runs, we validate the effectiveness of our approach, paving the way for energy-efficient decentralized inference over edge networks
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
- …
