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关键词： Graphics processing units   Memory management   Data transfer   Parallel processing   Lead   Computer science   Sparse matrices   Data reuse   GPU memory oversubscription   graph computing   partition-based method   zero-copy  

摘要： Graph analytics are widely used including recommender systems, scientific computing, and data mining. Meanwhile, GPU has become the major accelerator for such applications. However, the graph size increases rapidly and often exceeds the GPU memory, incurring severe performance degradation due to frequent data transfers between the main memory and GPUs. To relieve this problem, we focus on the utilization of data in GPUs by taking advantage of the data reuse across iterations. In our studies, we deeply analyze the memory access patterns of graph applications at different granularities. We have found that the memory footprint is accessed with a roughly sequential scan without a hotspot, which infers an extremely long reuse distance. Based on our observation, we propose a novel framework, called Liberator, to exploit the data reuse within GPU memory. In Liberator, GPU memory is reserved for the data potentially accessed across iterations to avoid excessive data transfer between the main memory and GPUs. For the data not existing in GPU memory, a Merged and Aligned memory access manner is employed to improve the transmission efficiency. We also further optimize the framework by parallel processing of data in GPU memory and data in the main memory. We have implemented a prototype of the Liberator framework and conducted a series of experiments on performance evaluation. The experimental results show that Liberator can significantly reduce the data transfer overhead, which achieves an average of 2.7x speedup over a state-of-the-art approach.

关键词： Continuing professional development   CPD   teacher professional development   computer science   computing education  

摘要： As technology and curricula continue to evolve and develop, the prevalence and effectiveness of continuing professional development (CPD) opportunities for computer science teachers is becoming increasingly more important. However, key questions remain about what the characteristics are for effective CPD in this context. Through the presentation of existing literature and the qualitative analysis of interviews with 32 employees from 13 English colleges (n = 14 computer science lecturers, 10 course leaders, and 8 members of senior leadership), this article answers the following question: What are the characteristics of effective continuing professional development for computer science teachers in the 16-18 sector? Existing literature indicates how CPD benefits from (1) knowledge development and application to classroom teaching;(2) self-efficacy development and measurement;(3) observation, feedback, and reflection;(4) collaboration and communities of practice;(5) sufficient time;and (6) institution support. Meanwhile, the thematic analysis of interview data led to the creation of five overarching themes: (1) computer science CPD should address various knowledge domains, (2) CPD requires institutional support, (3) CPD should be engaging, (4) computer science CPD should involve a combination of activities, and (5) CPD should be measurable. This qualitative article also presents interview excerpts and contributes to computing education research and practice by presenting a set of 30 guidelines that outlines the characteristics of effective CPD in the context of computer science teachers in the 16-18 sector. These guidelines could be beneficial for both CPD providers and educators in ensuring CPD opportunities are designed more effectively and with an understanding of both parties' needs.

关键词： Black engineering students   STEM   Transfer student adjustment  

摘要： Black engineering transfer students face unique challenges while navigating the transfer process from a community college to a 4-year institution. The purpose of this paper is to better understand the experiences of these students and the ways in which they adjust to the 4-year school. We identify specific challenges noted by Black engineering transfer students in their experiences related to: (1) heuristics of teaching and learning that they had to adapt to in order to successfully navigate new campus environments;(2) information gaps that students encountered in what faculty seemed to expect them to already know;and (3) problems in having to adjust to the differences in the academic demands of the 4-year engineering program. In addition to unpacking our findings along these specific domains, we attend to the potential impact of having these challenges in a large, urban, metropolitan area. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.

关键词： Handwriting recognition   Features extraction   Transfer-learning   CNN   Concatenation technique  

摘要： Handwriting recognition is a multi-step process that includes data collection, preprocessing, feature extraction, and classification in order to create a final prediction. This process becomes more and more delicate when dealing with the scriptures of college or secondary school learners. The primary purpose of this research is to offer an improved model for classifying images of computer science words vocabulary written by learners. Indeed, the aim is to develop a reliable handwriting recognition system for the benefit of the educational field. The proposed recognition model based on the combination of four pre-trained CNNs models, namely ResNet50 V2, MobileNet V2, ResNet101 V2, and Xception. Our earlier established Computer Science Vocabulary Dataset (CSVD) is used to build and validate the proposed concatenated model. Then, we have applied preprocessing operations to reduce irregularities, like fuzzy letters and distorted undefined symbols. The proposed CNN model is trained on the concatenated features generated by the four pre-trained CNNs using a parallel deep feature extraction approach. To evaluate the performance of our recognition system, we have used different common evaluation measures. The average accuracy of the proposed system for handwritten words vocabulary is 99.97%, and the overall loss rate is 3.56%. In addition, these performances have been compared with alternative state-of-the-art models and better performance has been observed.

关键词： Active learning   computer science engineering (CSE)   higher education   model of empathy   perspective taking (PT)   professional skills   transversal competence  

摘要： Contribution: This article proposes and applies a new systemic 3-D model and a methodology for empathy awareness and development, integrating different partial approaches found in the literature for developing empathy as a transversal ***: Empathy is a competence linked to collaboration and teamwork. Perspective taking (PT) is an important component of empathy and it is key for professionals today. Even though empathy is valued in computer science engineering (CSE) courses, it is not yet fully addressed as an integral part of the training *** Outcomes: Both the model and the methodology are put into practice with a group of first-year CSE students, highlighting the possibilities of the proposal for this course of studies. The experience presented here is an example of a classroom activity in which awareness and PT are addressed, as key components, in relation to the collaborative work toward achieving *** Design: The methodological proposal is applied to guide educators' decisions so that they can work on empathy in the classroom. Responses to several standardized and ad-hoc questionnaires by students from two universities are ***: The results revealed low to medium empathy levels in participating students, but a higher perception of their own empathic ability. The proposed methodology allows students to become aware of and develop some initial changes in relation to empathy, particularly in its PT component, through classroom work.

关键词： Imaging and sensing   Imaging techniques   Computer science   Optical sensors  

摘要： Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras. The sparse, noisy, and distorted raw photon data captured by single-photon cameras make it difficult to estimate scene properties under challenging illumination conditions. Here, the authors present Collaborative photon processing for Active Single-Photon Imaging (CASPI), a technology-agnostic, application-agnostic, and training-free photon processing pipeline for high-resolution single-photon cameras.

关键词： Batteries   Computer science   Electrical and electronic engineering   Solar cells   Energy grids and networks  

摘要： Photovoltaics supply a growing share of power to the electric grid worldwide. To mitigate resource intermittency issues, these systems are increasingly being paired with electrochemical energy storage devices, e.g., Li-ion batteries, for which ensuring long and safe operation is critical. However, in this operation framework, secondary Li-ion batteries undergo sporadic usage, which prevents the application of standard diagnostic methods. Here, we propose a diagnostic methodology that uses machine learning algorithms trained directly on data obtained from photovoltaic charging of Li-ion batteries. The training is carried out on synthetic voltage data at various degradation conditions calculated from clear sky model irradiance data. The method is validated using synthetic voltage responses calculated from plane of array irradiance observations for a photovoltaic system located in Maui, HI, USA. We report an average root mean square error of 2.75% obtained for more than 10,000 different degradation paths with 25% or less degradation on the Li-ion cells. Li-ion batteries are used to store energy harvested from photovoltaics. However, battery use is sporadic and standard diagnostic methods cannot be applied. Here, the authors propose a methodology for diagnosing photovoltaics-connected Li-ion batteries that use trained machine learning algorithms.

关键词： Computer science   Diseases   Health services   Public health  

摘要： In this work, we aim to accurately predict the number of hospitalizations during the COVID-19 pandemic by developing a spatiotemporal prediction model. We propose HOIST, an Ising dynamics-based deep learning model for spatiotemporal COVID-19 hospitalization prediction. By drawing the analogy between locations and lattice sites in statistical mechanics, we use the Ising dynamics to guide the model to extract and utilize spatial relationships across locations and model the complex influence of granular information from real-world clinical evidence. By leveraging rich linked databases, including insurance claims, census information, and hospital resource usage data across the U.S., we evaluate the HOIST model on the large-scale spatiotemporal COVID-19 hospitalization prediction task for 2299 counties in the U.S. In the 4-week hospitalization prediction task, HOIST achieves 368.7 mean absolute error, 0.6 R-2 and 0.89 concordance correlation coefficient score on average. Our detailed number needed to treat (NNT) and cost analysis suggest that future COVID-19 vaccination efforts may be most impactful in rural areas. This model may serve as a resource for future county and state-level vaccination efforts. Amid the COVID-19 pandemic, accurate hospitalization predictions are vital. Here, the authors show that a deep learning model based on statistical mechanics is able to forecast hospitalizations, supporting targeted vaccination efforts.

关键词： Autism spectrum disorder   adults   psychiatry   comorbidity   neurodevelopmental disorders  

摘要： BackgroundPatients with 'underlying' autism spectrum disorder (ASD) constitute a significant minority in adult out-patient psychiatry. Diagnoses of previously unrecognised ASD are increasing in adults. Characteristics of patients with autism within adult out-patient psychiatry have not been sufficiently explored, and there have not been any systematic comparisons of characteristics between patients with and those without autism within adult out-patient psychiatric populations. AimsTo examine psychiatrically relevant characteristics in autistic adult psychiatric out-patients, and to compare the characteristics with non-autistic adult psychiatric out-patients. MethodWe assessed 90 patients who were referred to a Swedish psychiatric out-patient clinic and screened for ASD during 2019-2020. Sixty-three patients met the DSM-5 criteria for ASD or 'subthreshold' ASD. The 27 who did not meet the criteria for ASD were used as a comparison group. Assessments were made with structured and well-validated instruments, including parent ratings of developmental history. ResultsNo differences were found between the groups regarding self-reported sociodemographic variables. The ASD group showed a higher number of co-occurring psychiatric disorders than the non-ASD group (t((88)) = 5.17, 95% CI 1.29-2.91, d = 1.19). Functional level was lower in the ASD group (t((88)) = -2.66, 95% CI -9.46 to -1.27, d = -0.73), and was predicted by the number of co-occurring psychiatric disorders. ConclusionsThe results underscore the need for thorough assessment of psychiatric disorders in autistic patients in adult psychiatric services. ASD should be considered as a possible 'underlying' condition in adult psychiatry, and there is no easy way of ruling out ASD in this population.

关键词： Computer science   Machine learning   Mathematics and computing   Quantum information  

摘要： Jungsang Kim discusses his interest in the pioneering technology.