CeRC Story-Game Engine: An open source technology to power story based investigation games

Playing computer games is widely popular among children and teenagers as an entertainment activity; however computer games can also be easily transformed into tools for education. City University London’s City eHealth Research Centre (CeRC) - has developed such educational computer games to improve young people’s understanding of the importance of hand and respiratory hygiene and responsible antibiotic use; and to teach school syllabus concepts such as microbes, the spread and prevention of infection, antibiotic use and antibiotic resistance. We have developed a game platform as an open-source framework to promote game development for education and entertainment. The platform enables the efficient development of new games with new learning objectives along with the ability to support translation into any language. For example, the current CeRC games have been translated into 11 European languages (English, BelgianFrench, Flemish, Czech, Danish, French, Greek, Italian, Polish, Portuguese, and Spanish). The existing CeRC games are targeted towards school children; however, we investigate the usability of utilizing such games for adult education as well as examining the effectiveness of these games to convey messages to particular academic, industrial (or otherwise) communities

Desenvolvimento e capacitaçao para novos colaboradores no SICOOB Vale Sul

Orientador: Prof. Me. Weber Henrique RadaelArtigo apresentado como trabalho de conclusão de curso Artigo (especialização) - Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Curso de Especialização MBA em Banking para Cooperativas de CréditoInclui referênciasResumo: Todo o treinamento realizado é sempre de grande valia para a carreia profissional do colaborador, a partir deste, consegue um melhor desempenho profissional como também pessoal, proporcionando melhores resultados. Com este objetivo, propomos um novo modelo de capacitação de colaboradores ingressantes na Cooperativa de Crédito Sicoob Vale Sul, com fácil implementação e com um custo operacional baixo, podendo ter resultados excelentes para os novos colaboradores desempenhar suas funções com maestria na agenci

Evaluation of Popularity of Multi-lingual Educational Web Games – Do All Children Speak English?

Playing computer games is widely popular among children and teenagers as an entertainment activity; however, computer games can also be easily transformed into tools for education. City University London’s City eHealth Research Centre (CeRC) has developed such educational web games as a part of a European Project, e-Bug (www.e-bug.eu) to improve pupils understanding of the importance of hand and respiratory hygiene and responsible antibiotic use. This paper studies the usage of the Games between January 2009 and March 2010, specifically for 10 European Union countries. The Games were first provided in English-only and it was found that over half of the users were from non-UK countries. Once the Games were translated into multiple European languages, it was found that users preferred to play the Games in their native tongue. Thus, English was not a hindrance to Game playing/access; however, the option of using another language was always taken once provided. Users found the website through search engines and direct links from schools and other websites, and over 60,000 visitors played the Games at least once. The quantitative data used to investigate our research questions stemmed from the Games website server logs

Understanding the relevance of in-mouth food processing. A review of in vitro techniques

[EN] Oral processing of food is the first step in the eating process. Although the food undergoes a number of changes during mastication that influence the subsequent steps, this stage has very often been neglected in studies of digestion, bioavailability, flavor release, satiety potential, glycemic index determination, etc. The present review draws on different sources such as nutrition, medicine, phoniatry and dentistry to explain some in vitro oral processing methods and techniques that could be transferred to food technology studies to mimic in vivo comminution, insalivation, and bolus formation, describing, as a necessary reference, the respective in vivo physiological processes they attempt to imitate. Developing a deeper understanding of all the aspects of in-mouth process will help food technologists to give this crucial step the necessary attention its due importance and to consider better ways to incorporate it into their studies.The authors wish to acknowledge the financial support of the Spanish Government (project AGL2012-36753-C02) and gratefully acknowledge the financial support of EU FEDER funds. Mary Georgina Hardinge assisted with the translation and corrected the English text.Morell Esteve, P.; Hernando Hernando, MI.; Fiszman, SM. (2014). Understanding the relevance of in-mouth food processing. A review of in vitro techniques. Trends in Food Science and Technology. 35(1):18-31. https://doi.org/10.1016/j.tifs.2013.10.005S183135

Investigation of breathing-disordered sleep quantification using the oxygen saturation signal

This thesis investigates the feasibility of using the non-invasive biomedical signal of oxygen saturation, or SpO2 , to diagnose a sleep disorder known as Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAHS). Epidemiologically, OSAHS is the most common condition investigated by sleep clinics. In a patient suspected of having the disorder, the upper airway is obstructed during sleep and a cessation in respiration results. An apnoea is defined as a temporary cessation of breathing. Similarly, a hypopnoea is defined as any reduction in breathing (i.e., less severe than an apnoea). The work has three main objectives; the first being to establish automated evaluation procedures for methods of quantifying apnoeic activity from the SpO2 signal, the second being to accurately identify apnoeic and normal activity on a minute-by-minute basis, the third being to create a Respiratory Disturbance Index (RDI) based on the analysis which is comparable to the gold-standard Apnoea Hypopnoea Index (AHI) derived by experts. The detection of apnoeic activity is determined using three separate analyses: time domain, frequency domain, and autoregressive modelling with an incorporated amplitude criterion. A training dataset is utilised for algorithm development, and an independent dataset is employed for testing . All three methods result in comparable overall classification accuracies of: 81.2% (time domain), 82.1% (frequency domain), and 80.0% (autoregressive modelling with amplitude). In addition, particular attention is given to the resultant sensitivity, specificity, and accuracy values partitioned according to patient category; i.e., patients with OSAHS may be divided into normal, mild, moderate and severe. Lastly, a simple RDI is computed based on the automated analyses; i.e., the number of apnoeic segments detected divided by the total number of segments used. A comparison between computed RDI and AHI values for the test database show correlation values above 0.8. In conclusion, this thesis shows that through the automated analysis of the SpO2 signal, OSAHS severity in patients suspected of having the disorder can be quantified. The AR-modelling with an incorporated amplitude criterion, in particular, shows the most promise for further work in this area.</p

Investigation of breathing-disordered sleep quantification using the oxygen saturation signal

This thesis investigates the feasibility of using the non-invasive biomedical signal of oxygen saturation, or SpO2 , to diagnose a sleep disorder known as Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAHS). Epidemiologically, OSAHS is the most common condition investigated by sleep clinics. In a patient suspected of having the disorder, the upper airway is obstructed during sleep and a cessation in respiration results. An apnoea is defined as a temporary cessation of breathing. Similarly, a hypopnoea is defined as any reduction in breathing (i.e., less severe than an apnoea). The work has three main objectives; the first being to establish automated evaluation procedures for methods of quantifying apnoeic activity from the SpO2 signal, the second being to accurately identify apnoeic and normal activity on a minute-by-minute basis, the third being to create a Respiratory Disturbance Index (RDI) based on the analysis which is comparable to the gold-standard Apnoea Hypopnoea Index (AHI) derived by experts. The detection of apnoeic activity is determined using three separate analyses: time domain, frequency domain, and autoregressive modelling with an incorporated amplitude criterion. A training dataset is utilised for algorithm development, and an independent dataset is employed for testing . All three methods result in comparable overall classification accuracies of: 81.2% (time domain), 82.1% (frequency domain), and 80.0% (autoregressive modelling with amplitude). In addition, particular attention is given to the resultant sensitivity, specificity, and accuracy values partitioned according to patient category; i.e., patients with OSAHS may be divided into normal, mild, moderate and severe. Lastly, a simple RDI is computed based on the automated analyses; i.e., the number of apnoeic segments detected divided by the total number of segments used. A comparison between computed RDI and AHI values for the test database show correlation values above 0.8. In conclusion, this thesis shows that through the automated analysis of the SpO2 signal, OSAHS severity in patients suspected of having the disorder can be quantified. The AR-modelling with an incorporated amplitude criterion, in particular, shows the most promise for further work in this area.</p

Investigation of breathing-disordered sleep quantification using the oxygen saturation signal

This thesis investigates the feasibility of using the non-invasive biomedical signal of oxygen saturation, or SpO2 , to diagnose a sleep disorder known as Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAHS). Epidemiologically, OSAHS is the most common condition investigated by sleep clinics. In a patient suspected of having the disorder, the upper airway is obstructed during sleep and a cessation in respiration results. An apnoea is defined as a temporary cessation of breathing. Similarly, a hypopnoea is defined as any reduction in breathing (i.e., less severe than an apnoea). The work has three main objectives; the first being to establish automated evaluation procedures for methods of quantifying apnoeic activity from the SpO2 signal, the second being to accurately identify apnoeic and normal activity on a minute-by-minute basis, the third being to create a Respiratory Disturbance Index (RDI) based on the analysis which is comparable to the gold-standard Apnoea Hypopnoea Index (AHI) derived by experts. The detection of apnoeic activity is determined using three separate analyses: time domain, frequency domain, and autoregressive modelling with an incorporated amplitude criterion. A training dataset is utilised for algorithm development, and an independent dataset is employed for testing . All three methods result in comparable overall classification accuracies of: 81.2% (time domain), 82.1% (frequency domain), and 80.0% (autoregressive modelling with amplitude). In addition, particular attention is given to the resultant sensitivity, specificity, and accuracy values partitioned according to patient category; i.e., patients with OSAHS may be divided into normal, mild, moderate and severe. Lastly, a simple RDI is computed based on the automated analyses; i.e., the number of apnoeic segments detected divided by the total number of segments used. A comparison between computed RDI and AHI values for the test database show correlation values above 0.8. In conclusion, this thesis shows that through the automated analysis of the SpO2 signal, OSAHS severity in patients suspected of having the disorder can be quantified. The AR-modelling with an incorporated amplitude criterion, in particular, shows the most promise for further work in this area