1,721,088 research outputs found
Introduction to Digitalization and Local Energy Systems
No full textThis chapter explores the significant shift in the local energy landscape as power systems transition from traditional centralized models to modern, distributed frameworks. Historically, electricity flowed unidirectionally from large power plants to passive consumers, but today’s energy systems are increasingly dynamic and decentralized. The rise of distributed energy resources, such as solar panels, wind turbines, and energy storage, has transformed consumers into active participants, or “prosumers,” who both produce and consume energy. This transition introduces challenges, particularly in adapting existing infrastructure to handle bidirectional power flows and integrating variable renewable energy sources. Enhanced visibility and control in low-voltage distribution networks are essential to managing these complexities. The chapter also addresses the need for resilient energy systems in the face of global challenges like aging infrastructure, market volatility, and climate-related disruptions. Innovative approaches, including digitalization and decentralized energy solutions, are crucial for building resilient, equitable energy systems. The discussion includes the UK’s Future Energy Scenarios (FES) and Distribution Future Energy Scenarios (DFES), which guide planning and investment in the evolving energy landscape. Ultimately, digitalization plays a vital role in enabling real-time monitoring, predictive analytics, and the seamless integration of distributed resources, paving the way for a sustainable and reliable energy future
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
Changes in Cooling Degree Days (CDD) between the 1.5ºC and 2.0ºC global warming scenarios: Data to replicate global maps on absolute and relative changes in cooling degree days (from a 1.5ºC to a 2.0ºC global warming scenario)
No full textThese NetCDF V4 files (*.nc) contain the absolute and relative mean increase of cooling degree days (CDDs) from 1.5ºC to 2ºC global warming scenarios. Additionally, the standard deviation is provided. The data has a horizontal resolution of 0.833 longitude and 0.556 latitude over the land surface.
These annual CDDs and standard deviation globally were calculated using an ensemble of 700 simulations per climate change scenario. Cooling degree days (CDDS) were calculated for the ensemble members using the temperature threshold of 18ºC. Then, annual mean CDDs and standard deviation per coordinate across ensemble members were obtained for the 1.5ºC and 2ºC scenarios. Finally, absolute and relative differences between 1.5ºC and 2ºC were computed.
The climate data, involving 700 simulations per scenario, was generated using the HadAM4P Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Three scenarios were generated: historical (2006-16), 1.5ºC and 2ºC. The simulation outputs were mean temperatures with a 6-hour timestep and a horizontal resolution of 0.833 longitude and 0.556 latitude. Simulations took place within climateprediction.net (CPDN) climate simulation, which uses the Berkeley Open Infrastructure for Network Computing (BOINC) framework. Biases in simulated temperature were identified and corrected using a quantile mapping approach
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
Using machine learning for dynamic resource orchestration & task scheduling, in a radio access network based edge environment
Full text linkThe evolution in mobile wireless communication generations, continues to gift the world with new telecommunication capabilities towards how people live and work. For instance, the roll out of the fifth generation (5G) promises a much-enhanced cloud-native application service, through improved communication speed, higher bandwidth, improved capacity for more connected devices and many more. These exciting new 5G features have given numerous vertical and horizontal industries a reason to explore different ways of delivering value, through emerging cloud-native applications that run on access devices (i.e. the Internet of Things (IoTs) and mobile devices). These cloud-native applications such Virtual Reality, Vehicle to everything communication (V2X), artificial intelligence, video analytics and so on however have strict performance requirements for extremely low latency (10 milliseconds and below) and higher bandwidth, that 5G alone cannot deliver. Unfortunately, the traditional cloud computing and radio access network setups do not sufficiently address these key communication needs which are crucial to the performance of these cloud-native applications. There is therefore an urgency to enhance and optimize the traditional mobile telecommunication network architecture, to meet these performance needs. This thesis seeks to demonstrate how we have developed a facility called Multi-Access Edge Computing with Cloud Radio Access Networks (MECRAN) to address this issue. MECRAN is based on the edge computing paradigm and uses machine learning to optimize the round-trip delivery of data at low latency, by dynamically scheduling cloud-native applications, to run in close proximity to a mobile user, at the edge of the radio access network
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