Harmonic analysis of EMUs in railway systems

Author name used in this publication: Edward W. C. LoVersion of RecordPublishe

Intelligent integration of BIPV and load management systems for modern buildings

This paper outlines the basics of load management, and highlights the possibility of maximising the contribution from the Building Integrated Photovoltaic (BIPV) power generation. It will also explain the underlying principles of a dynamic modelling approach and its application in supporting the anticipatory control strategy for load shifting. For many types of building applications, the load profiles are well matched with the BIPV generation profiles such that the BIPV power source is already acting as the peak clipping device. The application of Building Management Systems (BMS) in load shifting should consider the supply from BIPV system. Secondly, due to the thermal mass of the building, there exists time delay in the response of the power requirement of the HVAC system in the building from the solar radiation data. The BIPV system, on the contrary, is responding almost instantaneously to the solar irradiance. A dynamic BIPV model could be applied in aiding the prediction of the load profile. This paper will outline these aspects of the BIPV system as a demonstration of its application in BMS.postprintThe 8th Annual Power Symposium, Hong Kong, 19 June 2009

Integration of BIPV systems and load management

This paper outlines the basics of load management, and highlights the possibility of maximising the contribution from the Building Integrated Photovoltaic (BIPV) power generation. It will also explain the underlying principles of a dynamic modelling approach and its application in supporting the anticipatory control strategy for load shifting. For many types of building applications, the load profiles are well matched with the BIPV generation profiles such that the BIPV power source is already acting as the peak clipping device. The application of Building Management Systems (BMS) in load shifting should consider the supply from BIPV system. Secondly, due to the thermal mass of the building, there exists time delay in the response of the power requirement of the HVAC system in the building from the solar radiation data. The BIPV system, on the contrary, is responding almost instantaneously to the solar irradiance. A dynamic BIPV model could be applied in aiding the prediction of the load profile. This paper will outline these aspects of the dynamic model developed as a demonstration of its application.postprintThe International Conference on Electrical Engineering 2009

Clinical predictors of fetal and maternal outcome in Chinese patients with systemic lupus erythematosus

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Cervical dysplasia in patients with systemic lupus erythematosus

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Designing theoretically-informed implementation interventions

Clinical and health services research is continually producing new findings that may contribute to effective and efficient patient care. However, the transfer of research findings into practice is unpredictable and can be a slow and haphazard process. Ideally, the choice of implementation strategies would be based upon evidence from randomised controlled trials or systematic reviews of a given implementation strategy. Unfortunately, reviews of implementation strategies consistently report effectiveness some, but not all of the time; possible causes of this variation are seldom reported or measured by the investigators in the original studies. Thus, any attempts to extrapolate from study settings to the real world are hampered by a lack of understanding of the effects of key elements of individuals, interventions, and the settings in which they were trialled. The explicit use of theory offers a way of addressing these issues and has a number of advantages, such as providing: a generalisable framework within which to represent the dimensions that implementation studies address, a process by which to inform the development and delivery of interventions, a guide when evaluating, and a way to allow for an exploration of potential causal mechanisms. However, the use of theory in designing implementation interventions is methodologically challenging for a number of reasons, including choosing between theories and faithfully translating theoretical constructs into interventions. The explicit use of theory offers potential advantages in terms of facilitating a better understanding of the generalisability and replicability of implementation interventions. However, this is a relatively unexplored methodological area

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

Location of chlorogenic acid biosynthesis pathway and polyphenol oxidase genes in a new interspecific anchored linkage map of eggplant

© Gramazio et al.; licensee BioMed Central. 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

Data-Driven Understanding of Smart Service Systems Through Text Mining

Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define ???smart service system??? based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems