PUG : A Symbolic Verifier of GPU Programs

posterPUG is a automated verifier for GPU programs written in C/CUDA. PUG verifies GPU kernels for Data Races, Barrier mismatches, Totally wrong results, and Weak memory model related bugs. SMT-based correctness checking methods for these error are often more scalable, general and modular

Emotional tech

The Emotional Tech project applies emotional design as a research approach for investigating how people feel about state of the art and new emerging mobility technologies. How technology influences people at an emotional level and what factors can be improved in the design process has received little research attention and been rarely implemented in urban mobility. We explored the interactions and experiences of people and vehicles from the perspective of 'emotion as affective artefacts' which tackles 'emotion' as a conduit to help with problem-solving, decision-making and sense-making. The study focuses on subtle details of people's emotional transitions during, before and after journeys, and during long term use of mobility services. We created vehicle concepts to explore what innovation opportunities could be applied to bring cutting edge technologies into real world use

Attitudes & Behaviors Surrounding Active Commuting in Chittenden County, VT

Climate Change, Active Commuting, and Health • Climate change contributes to 7 million deaths/year globally • Negative health outcomes from increased carbon emissions include heat-related illness, mental health issues, and respiratory and allergic disease • Active commuting reduces carbon emissions, promotes physical activity, and reduces chronic diseases such as hypertension, diabetes, and obesity Active Commuting in Chittenden County • Only 8.5% of Vermonters commute actively • Burlington has been intensely promoting active commuting through developments in infrastructure and safety • Most Burlington residents still commute by car Project Goal • Compare how active commuters and non-active commuters in Chittenden County differ on attitudes and beliefs on health, vehicle emissions, economics, convenience, and safety. • Advise VTCHA on possible targets for the promotion of active commuting.https://scholarworks.uvm.edu/comphp_gallery/1281/thumbnail.jp

On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data

With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. We show that the random forest (RF) classifier is superior to other machine-learned methods in terms of accuracy, speed, and relative immunity to features with no useful class information; the RF classifier can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which further reduces the catastrophic error rate to 7.8%. Excluding low-amplitude sources, our overall error rate improves to 14%, with a catastrophic error rate of 3.5%.Comment: 23 pages, 9 figure

Promoting students’ interest through culturally sensitive curricula in higher education

Previous studies have emphasized culturally sensitive curricula in the context of enhancing minoritized students’ education. We examined the relationship between second-year higher education students’ perceptions of the cultural sensitivity of their curriculum and both majoritized and minoritized students’ interest in their course. A total of 286 (228 F) students rated the cultural sensitivity of their curriculum on six scales using a revised version of the Culturally Sensitive Curricula Scales (CSCS-R), the perceived quality of their relationships with teachers, and their interest. The CSCS-R widened the construct with two new scales and showed better reliability. Ethnic minority students (n = 99) perceived their curriculum as less culturally sensitive than White students (n = 182), corroborating previous findings. Black students perceived their curriculum as less culturally sensitive than Asian students. There were no significant differences between ethnic minority and White students on interest or perceived quality of relationships with teachers. Five dimensions of cultural sensitivity (Diversity Represented, Positive Depictions, Challenge Power, Inclusive Classroom Interactions, Culturally Sensitive Assessments) and perceived quality of relationships with teachers predicted interest. Ethnicity did not. Ensuring curricula and assessments represent diversity positively, challenge power and are inclusive may support students’ interest while reflecting an increasingly diverse society

Driverless futures: Design for acceptance and adoption in urban environments

The driverless or autonomous car offers a range of challenges and opportunities – technical, economic and social – to the UK and the world. Harrow led the academic research for GATEway, an £8M Innovate UK project led for industry by the Transport Research Laboratory in which the RCA was the principal university. It created a world-leading test-bed for driverless cars that enabled automotive and software industries, local authorities, planners, insurers, Government ministers, policy makers and others to evaluate new vehicles and new technologies applied to existing vehicles, and to understand the human behaviours and attitudes emerging around these new forms of transport. The work is crucial to the future of mobility and to future cities, the connected digital economy, and future manufacturing. Harrow focused on design research, comprising stakeholder engagement, codesign with user groups, scenario building, studies of users through observation and interview, attitude discovery through traditional and digital means, and dissemination through multiple media. A key motivation was to use autonomous vehicles for social benefit especially for groups ill-served by current transport. The research led to new knowledge about vehicles, systems and behaviours, much of which was distilled into the RCA GATEway report. Additional dissemination included: peer-reviewed journal article in Municipal Engineer (2018); paper at 6th International Conference for Universal Design, Nagoya, Japan (2016); feature in exhibition and book NEW OLD: Designing for Our Future Selves, Design Museum, London (2017); book chapter for Institute of Civil Engineering Publishing (in press); keynote for Seoul Smart Mobility (29 September 2016) as a central part of Seoul Design Week

QUOTIENT: Two-Party Secure Neural Network Training and Prediction

Recently, there has been a wealth of effort devoted to the design of secure protocols for machine learning tasks. Much of this is aimed at enabling secure prediction from highly-accurate Deep Neural Networks (DNNs). However, as DNNs are trained on data, a key question is how such models can be also trained securely. The few prior works on secure DNN training have focused either on designing custom protocols for existing training algorithms, or on developing tailored training algorithms and then applying generic secure protocols. In this work, we investigate the advantages of designing training algorithms alongside a novel secure protocol, incorporating optimizations on both fronts. We present QUOTIENT, a new method for discretized training of DNNs, along with a customized secure two-party protocol for it. QUOTIENT incorporates key components of state-of-the-art DNN training such as layer normalization and adaptive gradient methods, and improves upon the state-of-the-art in DNN training in two-party computation. Compared to prior work, we obtain an improvement of 50X in WAN time and 6% in absolute accuracy

Examination of the neural basis of psychotic-like experiences in adolescence during processing of emotional faces

Contemporary theories propose that dysregulation of emotional perception is involved in the aetiology of psychosis. 298 healthy adolescents were assessed at age 14- and 19-years using fMRI while performing a facial emotion task. Psychotic-like experiences (PLEs) were assessed with the CAPE-42 questionnaire at age 19. The high PLEs group at age 19 years exhibited an enhanced response in right insular cortex and decreased response in right prefrontal, right parahippocampal and left striatal regions; also, a gradient of decreasing response to emotional faces with age, from 14 to 19 years, in the right parahippocampal region and left insular cortical area. The right insula demonstrated an increasing response to emotional faces with increasing age in the low PLEs group, and a decreasing response over time in the high PLEs group. The change in parahippocampal/amygdala and insula responses during the perception of emotional faces in adolescents with high PLEs between the ages of 14 and 19 suggests a potential ‘aberrant’ neurodevelopmental trajectory for critical limbic areas. Our findings emphasize the role of the frontal and limbic areas in the aetiology of psychotic symptoms, in subjects without the illness phenotype and the confounds introduced by antipsychotic medication

Promoting students’ interest through culturally sensitive curricula in higher education

Previous studies have emphasized culturally sensitive curricula in the context of enhancing minoritized students’ education. We examined the relationship between second-year higher education students’ perceptions of the cultural sensitivity of their curriculum and both majoritized and minoritized students’ interest in their course. A total of 286 (228 F) students rated the cultural sensitivity of their curriculum on six scales using a revised version of the Culturally Sensitive Curricula Scales (CSCS-R), the perceived quality of their relationships with teachers, and their interest. The CSCS-R widened the construct with two new scales and showed better reliability. Ethnic minority students (n = 99) perceived their curriculum as less culturally sensitive than White students (n = 182), corroborating previous findings. Black students perceived their curriculum as less culturally sensitive than Asian students. There were no significant differences between ethnic minority and White students on interest or perceived quality of relationships with teachers. Five dimensions of cultural sensitivity (Diversity Represented, Positive Depictions, Challenge Power, Inclusive Classroom Interactions, Culturally Sensitive Assessments) and perceived quality of relationships with teachers predicted interest. Ethnicity did not. Ensuring curricula and assessments represent diversity positively, challenge power and are inclusive may support students’ interest while reflecting an increasingly diverse society