517 research outputs found

    Real and Virtual Nucleon Compton Scattering in the Perturbative Limit

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    We present the results of calculations analyzing nucleon Compton scattering to lowest order using perturbative QCD (pQCD) methods. Two scenarios are considered: (1) the incoming photon is real; and (2) the incoming photon is virtual. The case of a real photon has been previously analyzed at least 5 times using pQCD, but no two results are in agreement. Here it is shown that our result agrees with that of Brooks and Dixon published in 2000. The case of a virtual photon has been previously analyzed only once using pQCD. However, doubt has been cast on the validity of that result. The results presented here for virtual photon are believed to be more reliable. Some consideration is given of how to compare these results with experiment. Following the lead of Brooks and Dixon, for the proton, this involves normalizing the cross section using the Dirac proton form factor, which we also calculate. Finally, there is a comparison of our results with recent experiments.Comment: 36 pages, 11 figure

    A microfluidic 2×2 optical switch

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    A 2×2 microfluidic-based optical switch is proposed and demonstrated. The switch is made of an optically clear silicon elastomer, Polydimethylsiloxane (PDMS), using soft lithography. It has insertion loss smaller than 1 dB and extinction ratio on the order of 20 dB. The device is switching between transmission (bypass) and reflection (exchange) modes within less than 20 m

    Pandemic-induced course and assessment changes for undergraduate engineering education: The Development of Graduate Attributes

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    Educators constantly need to make adjustments to their pedagogy and learning activities to reflect the fast changes in society, the economy and industry. This has been clearly demonstrated throughout the world in the response to the COVID-19 pandemic required fully remote delivery of tertiary education. The aim of this study was comparing the experiences and perceptions of tertiary students in a fully online and a blended delivery mode, particularly in response to their laboratory skills and development of graduate attributes. Pedagogical aspects were kept consistent across delivery modes to minimise the differences in learning activities across cohorts. A comparison was made between the 2020 fully online cohort and the 2021 blended delivery cohort. The students were asked about their perceptions of how well they thought the course developed their graduate attributes; how authentic they thought the course was; and how easy the content was to navigate and understand. A mixed methods approach was used, where both quantitative and qualitative data was gathered. The blended delivery mode students appeared to benefit from having a specific reflective task, which allowed them to see their learning in a broader context. The paper discusses the blending and online learning from the students’ perspectives of developing graduate attributes and experiential learning. Specifically, where hands on skills are required, students need further guidance in “learning how to learn” or metacognition. A key challenge for future blended learning is getting the balance right between achieving efficiency in online learning and lack of social and dynamic interactions aspect of the online community

    Displaying Properties of PDFs

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    PDFVis is a computer program that assists in visualization of uncertainty as represented by a probability density function (PDF) located at each grid cell in a spatial domain. The functions that PDFV performs are listed

    Does an assessment rubric provide a better learning experience for undergraduates in developing transferable skills?

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    There is ongoing interest in developing rigorous and accurate assessment methods in higher education, particularly in the use of assessment rubrics and in providing more useful feedback to students rather than a simple grade. However, there has been little used of reliable assessment rubrics that provide feedback to individual students on their teamwork participation and skills, and which assist academic staff in assessing teamwork among students. This paper reports on the second phase of a study that aimed to evaluate a rubric to assess skills and processes in teamwork, and whether a rubric facilitated a better learning experience than a simple marking scheme. The second phase focused on the implementation of a revised assessment rubric designed to assist students and staff in understanding what was expected in the assessment process, and in particular the creation of efficient tools and metrics to measure both teamwork and individual performance during collaborative team design projects. Findings from two surveys of students provided the dataset for this second phase of the study. The findings demonstrate that assessment rubrics provide an important adjunct in improving students’ teamwork performance and their understanding of their learning activities. This study will also contribute to ongoing discussions on higher education assessment methods

    Self-adaptive parameter and strategy based particle swarm optimization for large-scale feature selection problems with multiple classifiers

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    This work was partially supported by the National Natural Science Foundation of China (61403206, 61876089,61876185), the Natural Science Foundation of Jiangsu Province (BK20141005), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (14KJB520025), the Engineering Research Center of Digital Forensics, Ministry of Education, and the Priority Academic Program Development of Jiangsu Higher Education Institutions.Peer reviewedPostprin

    Folgers: The New Era of Coffee

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    The primary purpose of this paper is to discuss the repositioning of the Folgers brand through a new and improved Brand Pyramid and two strategic recommendations. In order to come to these conclusions, the group utilized secondary research to gain a background on the coffee industry as a whole, the acquisition of the Folgers brand by Smucker’s, the competition relative to Folgers in the coffee market, a social media analysis focusing on the competitors, and finally research regarding the Millennial generation. The conclusions from this secondary research led to the methodology used in order to come up with the new pyramid and recommendations. This methodology included two surveys, the first being sent out to friends and relatives through the use of social media, and the second which utilized the tool Survey Monkey Audience, which was sent to a paid panel of 18-34 year-old coffee drinkers. A stipend of $500 was utilized by the group in order to use the survey resources and to provide monetary rewards to participants in said surveys

    PartDiff: Image Super-resolution with Partial Diffusion Models

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    Denoising diffusion probabilistic models (DDPMs) have achieved impressive performance on various image generation tasks, including image super-resolution. By learning to reverse the process of gradually diffusing the data distribution into Gaussian noise, DDPMs generate new data by iteratively denoising from random noise. Despite their impressive performance, diffusion-based generative models suffer from high computational costs due to the large number of denoising steps.In this paper, we first observed that the intermediate latent states gradually converge and become indistinguishable when diffusing a pair of low- and high-resolution images. This observation inspired us to propose the Partial Diffusion Model (PartDiff), which diffuses the image to an intermediate latent state instead of pure random noise, where the intermediate latent state is approximated by the latent of diffusing the low-resolution image. During generation, Partial Diffusion Models start denoising from the intermediate distribution and perform only a part of the denoising steps. Additionally, to mitigate the error caused by the approximation, we introduce "latent alignment", which aligns the latent between low- and high-resolution images during training. Experiments on both magnetic resonance imaging (MRI) and natural images show that, compared to plain diffusion-based super-resolution methods, Partial Diffusion Models significantly reduce the number of denoising steps without sacrificing the quality of generation
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