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2023 ASEE Annual Conference and Exposition - The Harbor of Engineering: Education for 130 Years, ASEE 2023

作者： Jaber, Alaa Lechasseur, Kimberly Mottakin, Khairul Song, Zheng Computer and Information Science Department University of Michigan Dearborn United States Center for Project-based Learning Worcester Polytechnic Institute United States

In this work-in-progress paper, we report our experience of applying project-based learning (PjBL) in a web technology course, with a focus on how different feedback tactics affect students' learning outcomes. Giving high-quality feedback can have an immediate impact on students' learning progress. Although process-level feedback is considered more effective than task-level feedback in traditional pedagogies, it is still unclear whether this conclusion can be exacerbated or mitigated when applied to PjBL, as PjBL emphasizes students' ownership and authenticity. We divided students into two groups and applied different feedback strategies. We report findings and insights to help instructors develop feedback policies and practices that are effective and likely to benefit students. Our results suggest that giving low-level feedback still improves students' learning outcomes in the context of PjBL, especially for technical tasks. © American Society for Engineering Education, 2023.

关键词： Students

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project-based APPROACH FOR ELECTRICAL ENGINEERING EDUCATION AT ETH ZURICH 52

PROJECT-BASED APPROACH FOR ELECTRICAL ENGINEERING EDUCATION ...

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52nd Annual Conference of the European Society for Engineering: Educating Responsible Engineers, SEFI 2024

作者： Magno, Michele Abou-Khalil, Victoria Schurgers, Curt Center for Project-Based Learning Department of Information Technology and Electrical Engineering ETH Zürich Zürich Switzerland Lausanne Switzerland Electrical and Computer Engineering Department UC San Diego CA United States

ISBN: (纸本)9782873520274

This practice paper introduces the project-based approach of the Center for project-based learning within the Department of Information Technology and Electrical Engineering of ETH Zürich. This center's approach to education is built around a three-stage education model that includes projects early on in the students' educational journeys, gradually increasing their complexity in alignment with their growing level of experience. This approach ensures students develop both technical expertise and essential professional skills necessary for their engineering careers, scaffolding course work, small scale group projects and interdisciplinary flagship projects. The center is further enhanced by an evidence-based approach to continued improvement, using regular surveys, reflective journals, and research findings to refine course design and supervision. Students have reported high satisfaction levels with the courses, expressing that the projects aided their understanding of future aspirations and helped develop crucial soft skills, notably in collaboration, communication, and presentation. projects focus on real-world applicability, ensuring students are well-prepared to tackle real-world challenges, with many focusing on contemporary problems in areas such as sustainability. © 2024 SEFI 2024 - 52nd Annual Conference of the European Society for Engineering, Proceedings: Educating Responsible Engineers. All rights reserved.

关键词： Students

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Removing Scattered Light in Biomedical Images via an Unsupervised Deep Neural Network

Removing Scattered Light in Biomedical Images via an Unsuper...

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2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Gong, Yuanhao Xu, Meng Li, Yawei Magno, Michele Shenzhen University Faculty of Electronics and Information Engineering China Queen Mary University of London School of Computer Science United Kingdom Eth Zurich Computer Vision Lab Switzerland Eth Zurich Center for Project-based Learning Switzerland

ISBN: (纸本)9798350383386

Scattered light is unavoidable during biomedical imaging, leading to downgraded images. Removing such scattered light, however, is challenging, because the imaging objects are complex and the light path is complicated. In this paper, we propose to use deep learning methods to computationally remove such scattered light. Inspired by the dehazing methods for natural images, we first developed a novel mathematical model for biomedical images. Then, we developed a deep neural network method to solve this model. Our network simultaneously estimates the clear image and the scattered light. Several experiments are conducted to confirm the network's effectiveness and efficiency. © 2023 IEEE.

关键词： Deep neural networks

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CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking

CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Nicolas Baumann Michael Baumgartner Edoardo Ghignone Jonas Kühne Tobias Fischer Yung-Hsu Yang Marc Pollefeys Michele Magno Center for Project-Based Learning D-ITET ETH Zurich Computer Vision and Geometry Group D-INFK ETH Zurich

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

To enable self-driving vehicles accurate detection and tracking of surrounding objects is essential. While Light Detection and Ranging (LiDAR) sensors have set the benchmark for high-performance systems, the appeal of camera-only solutions lies in their cost-effectiveness. Notably, despite the prevalent use of Radio Detection and Ranging (RADAR) sensors in automotive systems, their potential in 3D detection and tracking has been largely disregarded due to data sparsity and measurement noise. As a recent development, the combination of RADARs and cameras is emerging as a promising solution. This paper presents Camera-RADAR 3D Detection and Tracking (CR3DT), a camera-RADAR fusion model for 3D object detection, and Multi-Object Tracking (MOT). Building upon the foundations of the State-of-the-Art (SotA) camera-only BEVDet architecture, CR3DT demonstrates substantial improvements in both detection and tracking capabilities, by incorporating the spatial and velocity information of the RADAR sensor. Experimental results demonstrate an absolute improvement in detection performance of 5.3% in mean Average Precision (mAP) and a 14.9% increase in Average Multi-Object Tracking Accuracy (AMOTA) on the nuScenes dataset when leveraging both modalities. CR3DT bridges the gap between high-performance and cost-effective perception systems in autonomous driving, by capitalizing on the ubiquitous presence of RADAR in automotive applications. The code is available at: https://***/ETH-PBL/CR3DT.

关键词： Solid modeling Meteorological radar Three-dimensional displays Accuracy Radar detection Radar Object detection Radar tracking Sensor systems Sensors

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CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking

arXiv

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arXiv 2024年

作者： Baumann, Nicolas Baumgartner, Michael Ghignone, Edoardo Kühne, Jonas Fischer, Tobias Yang, Yung-Hsu Pollefeys, Marc Magno, Michele The Center for Project-Based Learning D-ITET ETH Zurich Switzerland The Computer Vision and Geometry Group D-INFK ETH Zurich Switzerland

关键词： Radar measurement

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Removing Scattered Light in Biomedical Images via an Unsupervised Deep Neural Network

Removing Scattered Light in Biomedical Images via an Unsuper...

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Data Science and Engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Yuanhao Gong Meng Xu Yawei Li Michele Magno Faculty of Electronics and Information Engineering Shenzhen University China School of Computer Science Queen Mary University of London U.K. Computer Vision Lab ETH Zurich Switzerland Center for Project-based Learning ETH Zurich Switzerland

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LocalViT: Analyzing Locality in Vision Transformers

LocalViT: Analyzing Locality in Vision Transformers

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yawei Li Kai Zhang Jiezhang Cao Radu Timofte Michele Magno Luca Benini Luc Van Goo Computer Vision Lab D-ITET ETH Zurich Switzerland Center for Artificial Intelligence and Data Science (CAIDAS) University of Wurzburg Germany Center for Project-Based Learning D-ITET ETH Zurich Switzerland Integrated Systems Laboratory D-ITET ETH Zurich Switzerland Department of Electrical Electronic and Information Engineering University of Bologna Italy Processing Speech and Images (PSI) KU Leuven Belgium

The aim of this paper is to study the influence of locality mechanisms in vision transformers. Transformers originated from machine translation and are particularly good at modelling long-range dependencies within a long sequence. Although the global interaction between the token embeddings could be well modelled by the self-attention mechanism of transformers, what is lacking is a locality mechanism for infor-mation exchange within a local region. In this paper, locality mechanism is systematically investigated by carefully designed controlled experiments. We add locality to vision transformers into the feed-forward network. This seemingly simple solution is inspired by the comparison between feed-forward networks and inverted residual blocks. The importance of locality mechanisms is validated in two ways: 1) A wide range of design choices (activation function, layer placement, expansion ratio) are available for incorporating locality mechanisms and proper choices can lead to a performance gain over the baseline, and 2) The same locality mechanism is successfully applied to vision transformers with different architecture designs, which shows the generalization of the locality concept. For ImageNet2012 classification, the locality-enhanced transformers outperform the baselines Swin-T [1], DeiT-T [2] and PVT-T [3] by 1.0%, 2.6 % and 3.1 % with a negligible increase in the number of parameters and computational effort. Code is available at https://***/ofsoundof/LocalViT.

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High-accuracy ranging and localization with ultra-wideband communications for energy-constrained devices

arXiv

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arXiv 2021年

作者： Flueratoru, Laura Wehrli, Silvan Magno, Michele Lohan, Elena Simona Niculescu, Dragoş Department of Computer Science University Politehnica of Bucharest Romania Department of Electrical Engineering Tampere University Finland 3db Access AG Project-Based Learning Center ETH Zürich Switzerland

Ultra-wideband (UWB) communications have gained popularity in recent years for being able to provide distance measurements and localization with high accuracy, which can enhance the capabilities of devices in the Internet of Things (IoT). Since energy efficiency is of utmost concern in such applications, in this work we evaluate the power and energy consumption, distance measurements, and localization performance of two types of UWB physical interfaces (PHYs), which use either a low- or high-rate pulse repetition (LRP and HRP, respectively). The evaluation is done through measurements acquired in identical conditions, which is crucial in order to have a fair comparison between the devices. We performed measurements in typical line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Our results suggest that the LRP interface allows a lower power and energy consumption than the HRP one. Both types of devices achieved ranging and localization errors within the same order of magnitude and their performance depended on the type of NLOS obstruction. We propose theoretical models for the distance errors obtained with LRP devices in these situations, which can be used to simulate realistic building deployments and we illustrate such an example. This paper, therefore, provides a comprehensive overview of the energy demands, ranging characteristics, and localization performance of state-of-the-art UWB devices. © 2021, CC BY.

关键词： Energy efficiency

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LocalViT: Analyzing Locality in Vision Transformers

arXiv

引用

arXiv 2021年

作者： Li, Yawei Zhang, Kai Cao, Jiezhang Timofte, Radu Magno, Michele Benini, Luca Van Gool, Luc Computer Vision Lab D-ITET ETH Zürich Switzerland the University of Würzburg Germany Center for Project-Based Learning D-ITET ETH Zürich Switzerland Integrated Systems Laboratory D-ITET ETH Zürich Switzerland Department of Electrical Electronic and Information Engineering University of Bologna Italy KU Leuven Belgium

The aim of this paper is to study the influence of locality mechanisms in vision transformers. Transformers originated from machine translation and are particularly good at modelling long-range dependencies within a long sequence. Although the global interaction between the token embeddings could be well modelled by the self-attention mechanism of transformers, what is lacking is a locality mechanism for information exchange within a local region. In this paper, locality mechanism is systematically investigated by carefully designed controlled experiments. We add locality to vision transformers into the feed-forward network. This seemingly simple solution is inspired by the comparison between feed-forward networks and inverted residual blocks. The importance of locality mechanisms is validated in two ways: 1) A wide range of design choices (activation function, layer placement, expansion ratio) are available for incorporating locality mechanisms and proper choices can lead to a performance gain over the baseline, and 2) The same locality mechanism is successfully applied to vision transformers with different architecture designs, which shows the generalization of the locality concept. For ImageNet2012 classification, the locality-enhanced transformers outperform the baselines Swin-T [1], DeiT-T [2] and PVT-T [3] by 1.0%, 2.6% and 3.1% with a negligible increase in the number of parameters and computational effort. Code is available at https://***/ofsoundof/LocalViT. © 2021, CC BY-NC-SA.

关键词： Distribution transformers

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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017 (vol 395, pg 1779, 2020)

引用

LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

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