Profiling the educational value of computer games

There are currently a number of suggestions for educators to include computer games in formal teaching and learning contexts. Educational value is based on claims that games promote the development of complex learning. Very little research, however, has explored what features should be present in a computer game to make it valuable or conducive to learning. We present a list of required features for an educational game to be of value, informed by two studies, which integrated theories of Learning Environments and Learning Styles. A user survey showed that some requirements were typical of games in a particular genre, while other features were present across all genres. The paper concludes with a proposed framework of games and features within and across genres to assist in the design and selection of games for a given educational scenari

Kinematic modelling of a 3-axis NC machine tool in linear and circular interpolation

Machining time is a major performance criterion when it comes to high-speed machining. CAM software can help in estimating that time for a given strategy. But in practice, CAM-programmed feed rates are rarely achieved, especially where complex surface finishing is concerned. This means that machining time forecasts are often more than one step removed from reality. The reason behind this is that CAM routines do not take either the dynamic performances of the machines or their specific machining tolerances into account. The present article seeks to improve simulation of high-speed NC machine dynamic behaviour and machining time prediction, offering two models. The first contributes through enhanced simulation of three-axis paths in linear and circular interpolation, taking high-speed machine accelerations and jerks into account. The second model allows transition passages between blocks to be integrated in the simulation by adding in a polynomial transition path that caters for the true machining environment tolerances. Models are based on respect for path monitoring. Experimental validation shows the contribution of polynomial modelling of the transition passage due to the absence of a leap in acceleration. Simulation error on the machining time prediction remains below 1%

The abnormal electrical and optical properties in Na and Ni codoped BiFeO3 nanoparticles

published_or_final_versio

Dramatic escalation in metabolic syndrome and cardiovascular risk in a Chinese population experiencing rapid economic development

Background Metabolic syndrome (MetSyn) increases the incidence of cardiovascular disease. Information on changes in prevalence of MetSyn in developing countries is limited. This study aims to compare MetSyn prevalence and its associated vascular risk over the period between 2002 and 2010 in a population which has had the world’s fastest economic development over the past three decades. Methods Two health surveys were conducted by using the multistage cluster random sampling method in a Chinese population of 85 million in southern China. The participants received a full medical check-up, including measurement of blood pressure (BP), obesity indices, fasting lipids and glucose levels. Data describing socio-economic status and lifestyle factors were also collected through interview. Metabolic syndrome was defined in accordance with the International Diabetes Federation criteria. Results A total of 3,561 participants from Survey 2010 were included in the data analysis. Women had a significantly higher prevalence of MetSyn than men. Comparison between the two surveys shows that age-standardized prevalence of MetSyn increased fourfold (from 5.4% in 2002 to 21.3% in 2010) in those ≧ 20 years. Among the MetSyn components, prevalence of hyperglycaemia has increased most (from 9.1% to 53.1%). The age-standardized prevalence of central obesity, hypertension, hypertriglyceridaemia and low HDL-cholesterol increased from 13.5% to 25.4%, from 23.6% to 40.8%, from 12.1% to 17.4% and from 32.1% to 71.1%, respectively. Differences between rural and urban residents in the prevalence in MetSyn and its components narrowed in 2010. Conclusions Cardiovascular risk escalated dramatically in this population between 2002 and 2010. The escalation may relate to the rapid economic development, which led to accelerating changes in nutrition, lifestyle, and socio-economic status. Our findings suggest that health transition in rapidly developing second- and third-world countries may be much faster than what has been observed in Western countries.published_or_final_versio

Disentangling human error from the ground truth in segmentation of medical images

Recent years have seen increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depends on the quality of labels. This problem is particularly pertinent in the medical image domain, where both the annotation cost and inter-observer variability are high. In a typical label acquisition process, different human experts provide their estimates of the "true'' segmentation labels under the influence of their own biases and competence levels. Treating these noisy labels blindly as the ground truth limits the performance that automatic segmentation algorithms can achieve. In this work, we present a method for jointly learning, from purely noisy observations alone, the reliability of individual annotators and the true segmentation label distributions, using two coupled CNNs. The separation of the two is achieved by encouraging the estimated annotators to be maximally unreliable while achieving high fidelity with the noisy training data. We first define a toy segmentation dataset based on MNIST and study the properties of the proposed algorithm. We then demonstrate the utility of the method on three public medical imaging segmentation datasets with simulated (when necessary) and real diverse annotations: 1) MSLSC (multiple-sclerosis lesions); 2) BraTS (brain tumours); 3) LIDC-IDRI (lung abnormalities). In all cases, our method outperforms competing methods and relevant baselines particularly in cases where the number of annotations is small and the amount of disagreement is large. The experiments also show strong ability to capture the complex spatial characteristics of annotators' mistakes. Our code is available at \url{https://github.com/moucheng2017/LearnNoisyLabelsMedicalImages}

Understanding vehicular routing behavior with location-based service data

This is the final published version, also available from Springer Nature via the DOI in this record.Properly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records (CDRs), which offer resolutions triangulated from antennas, are route choices, travel modes detection and close encounters. Nowadays, there is not a standard and large scale data set collected over long periods that allows us to characterize these. In this work we thoroughly examine the use of data from smartphone applications, also referred to as location-based services (LBS) data, to extract and understand the vehicular route choice behavior. Taking the Dallas-Fort Worth metroplex as an example, we first extract the vehicular trips with simple rules and reconstruct the origin-destination matrix by coupling the extracted vehicular trips of the active LBS users and the United States census data. We then present a method to derive the commonly used routes by individuals from the LBS traces with varying sample rate intervals. We further inspect the relation between the number of routes and the trip characteristics, including the departure time, trip length and travel time. Specifically, we consider the travel time index and buffer index for the LBS users taking different number of routes. Empirical results demonstrate that during the peak hours, travelers tend to reduce the impact of traffic congestion by taking alternative routes. Overall, the proposed data analysis framework is cost-effective to treat sparse data generated from the use of smartphones to inform routing behavior. The potential in practice is to inform demand management strategies, by targeting individual users while generating large scale estimates of congestion mitigation.MIT Energy InitiativeBerkeley Deep Drive consortiu

Initial validation of Chinese Pain Assessment in Advanced Dementia Scale (C-PAINAD)

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Molecular mediators of the association between child obesity and mental health

Biological mechanisms underlying the association between obesity and depression remain unclear. We investigated the role of metabolites and DNA methylation as mediators of the relationship between childhood obesity and subsequent poor mental health in the English Avon Longitudinal Study of Parents and Children. Obesity was defined according to United Kingdom Growth charts at age 7 years and mental health through the Short Mood and Feelings Questionnaire (SMFQ) completed at age 11 years. Metabolites and DNA methylation were measured by nuclear magnetic resonance spectroscopy and Illumina array in blood at the age of 7 years. The associations between obesity and SMFQ score, as continuous count data or using cut-offs to define depressive symptoms (SMFQ >7) or depression (SMFQ >11), were tested using adjusted Poisson and logistic regression. Candidate metabolite mediators were identified through metabolome-wide association scans for obesity and SMFQ score, correcting for false-discovery rate. Candidate DNA methylation mediators were identified through testing the association of putative BMI-associated CpG sites with SMFQ scores, correcting for look-up false-discovery rate. Mediation by candidate molecular markers was tested. Two-sample Mendelian randomization (MR) analyses were additionally applied to test causal associations of metabolites with depression in independent adult samples. 4,018 and 768 children were included for metabolomics and epigenetics analyses, respectively. Obesity at 7 years was associated with a 14% increase in SMFQ score (95% CI: 1.04, 1.25) and greater odds of depression (OR: 1.46 (95% CI: 0.78, 2.38) at 11 years. Natural indirect effects (mediating pathways) between obesity and depression for tyrosine, leucine and conjugated linoleic acid were 1.06 (95% CI: 1.00, 1.13, proportion mediated (PM): 15%), 1.04 (95% CI: 0.99, 1.10, PM: 9.6%) and 1.06 (95% CI: 1.00, 1.12, PM: 13.9%) respectively. In MR analysis, one unit increase in tyrosine was associated with 0.13 higher log odds of depression (p = 0.1). Methylation at cg17128312, located in the FBXW9 gene, had a natural indirect effect of 1.05 (95% CI: 1.01,1.13, PM: 27%) as a mediator of obesity and SMFQ score. Potential biologically plausible mechanisms involving these identified molecular features include neurotransmitter regulation, inflammation, and gut microbiome modulation. These results require replication in further observational and mechanistic studies