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Institution

Coventry University

EducationCoventry, United Kingdom
About: Coventry University is a education organization based out in Coventry, United Kingdom. It is known for research contribution in the topics: Population & Higher education. The organization has 4964 authors who have published 12700 publications receiving 255898 citations. The organization is also known as: Lanchester Polytechnic & Coventry Polytechnic.


Papers
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01 Jan 2009
TL;DR: This report focuses on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games and provides an overview of existing literature of relevance to the domain.
Abstract: Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented.

104 citations

Journal ArticleDOI
17 Oct 2013-PLOS ONE
TL;DR: The inhibition of mitochondrial fission protects the heart against doxorubicin-induced cardiac injury and is identified as a new therapeutic target in ameliorating dox orubic in-induced cardiotoxicity without affecting its anti-cancer properties.
Abstract: Doxorubicin is one of the most effective anti-cancer agents. However, its use is associated with adverse cardiac effects, including cardiomyopathy and progressive heart failure. Given the multiple beneficial effects of the mitochondrial division inhibitor (mdivi-1) in a variety of pathological conditions including heart failure and ischaemia and reperfusion injury, we investigated the effects of mdivi-1 on doxorubicin-induced cardiac dysfunction in naive and stressed conditions using Langendorff perfused heart models and a model of oxidative stress was used to assess the effects of drug treatments on the mitochondrial depolarisation and hypercontracture of cardiac myocytes. Western blot analysis was used to measure the levels of p-Akt and p-Erk 1/2 and flow cytometry analysis was used to measure the levels p-Drp1 and p-p53 upon drug treatment. The HL60 leukaemia cell line was used to evaluate the effects of pharmacological inhibition of mitochondrial division on the cytotoxicity of doxorubicin in a cancer cell line. Doxorubicin caused a significant impairment of cardiac function and increased the infarct size to risk ratio in both naive conditions and during ischaemia/reperfusion injury. Interestingly, co-treatment of doxorubicin with mdivi-1 attenuated these detrimental effects of doxorubicin. Doxorubicin also caused a reduction in the time taken to depolarisation and hypercontracture of cardiac myocytes, which were reversed with mdivi-1. Finally, doxorubicin caused a significant elevation in the levels of signalling proteins p-Akt, p-Erk 1/2, p-Drp1 and p-p53. Co-incubation of mdivi-1 with doxorubicin did not reduce the cytotoxicity of doxorubicin against HL-60 cells. These data suggest that the inhibition of mitochondrial fission protects the heart against doxorubicin-induced cardiac injury and identify mitochondrial fission as a new therapeutic target in ameliorating doxorubicin-induced cardiotoxicity without affecting its anti-cancer properties.

104 citations

Proceedings ArticleDOI
06 Nov 2009
TL;DR: This paper represents a first attempt at exploring a number of important concepts that the term engagement has been used to refer to, of relevance to both human-human and human-machine interaction modelling.
Abstract: Engagement is a concept of the utmost importance in human computer interaction, not only for informing the design and implementation of interfaces, but also for enabling more sophisticated interfaces capable of adapting to users. While the notion of engagement is actively being studied in a diverse set of domains, the term has been used to refer to a number of related, but different concepts. This paper represents a first attempt at exploring a number of important concepts that the term has been used to refer to, of relevance to both human-human and human-machine interaction modelling.

104 citations

Proceedings ArticleDOI
03 Apr 2017
TL;DR: In this article, the authors introduce an Arabic language dataset, which is about opinions on health services and has been collected from Twitter, and they used several Machine Learning algorithms (Naive Bayes, Support Vector Machine and Logistic Regression) alongside Deep and Convolutional Neural Networks were utilized in their experiments of sentiment analysis on their health dataset.
Abstract: The social media network phenomenon creates massive amounts of valuable data that is available online and easy to access. Many users share images, videos, comments, reviews, news and opinions on different social networks sites, with Twitter being one of the most popular ones. Data collected from Twitter is highly unstructured, and extracting useful information from tweets is a challenging task. Twitter has a huge number of Arabic users who mostly post and write their tweets using the Arabic language. While there has been a lot of research on sentiment analysis in English, the amount of researches and datasets in Arabic language is limited. This paper introduces an Arabic language dataset, which is about opinions on health services and has been collected from Twitter. The paper will first detail the process of collecting the data from Twitter and also the process of filtering, pre-processing and annotating the Arabic text in order to build a big sentiment analysis dataset in Arabic. Several Machine Learning algorithms (Naive Bayes, Support Vector Machine and Logistic Regression) alongside Deep and Convolutional Neural Networks were utilized in our experiments of sentiment analysis on our health dataset.

104 citations

Journal ArticleDOI
TL;DR: Findings highlight the diverse nature of lifestyle of youth living in different geographical areas of the world and the need for further research to explore the socio-cultural factors that impact on the prevalence of obesity and patterns of PA of youth in different populations.
Abstract: This study explores differences in weight status, obesity and patterns of physical activity (PA) in relation to gender and age of youth from two culturally, environmentally and geographically diverse countries, the United Kingdom (UK) and Saudi Arabia (SA). A total of 2,290 males and females (15–17 years) volunteered to participate in this study. Participants completed a validated self-report questionnaire that contained 47 items relating to patterns of PA, sedentary activity and eating habits. The questionnaire allows the calculation of total energy expenditure in metabolic equivalent (MET-min) values per week. Significant differences in percentage of overweight/obese and levels of PA were evident between the youth from the two countries, with males being generally more physically active than females. Additionally, there were significant associations between Body Mass Index (BMI), PA and sedentary behaviors; the youth with higher BMI reported lower levels of PA and higher amounts of sedentary time. These findings highlight the diverse nature of lifestyle of youth living in different geographical areas of the world and the need for further research to explore the socio-cultural factors that impact on the prevalence of obesity and patterns of PA of youth in different populations.

104 citations


Authors

Showing all 5097 results

NameH-indexPapersCitations
Xiang Zhang1541733117576
Zidong Wang12291450717
Stephen Joseph9548545357
Andrew Smith87102534127
John F. Allen7940123214
Craig E. Banks7756927520
Philip L. Smith7529124842
Tim H. Sparks6931519997
Nadine E. Foster6832018475
Michael G. Burton6651916736
Sarah E Lamb6539528825
Michael Gleeson6523417603
David Alexander6552016504
Timothy J. Mason6522515810
David S.G. Thomas6322814796
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202360
2022217
20211,419
20201,267
20191,097
20181,013