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4th IEEE World engineering Education Conference, EDUNINE 2020

作者： Rojas, Julio Ernesto Quispe Tuesta, Julio Enrique Quispe Universidad Nacional Pedro Ruiz Gallo Computing and Electronics Departament Lambayeque Peru Universidad Nacional Tecnologica de Lima sur Systems Engineering Program Lima Peru

ISBN: (纸本)9781728166384

The development of competencies in the professional training of an engineer includes: knowledge, skills and attitudes. For the development of skills, laboratory practices with physical equipment, virtual systems and remote systems are alternatives;the practices in the place of work performance through technical visits or pre-professional practices in the factories and maintenance workshops. Dual learning includes the participation of students in theoretical sessions in the center of studies and practical sessions of the installation and maintenance of machines and equipment in factories and workshops. The semidual learning proposal considers 50% of the practical sessions in the laboratories of the study center and 50% in the facilities of the industrial company. The experience of the application in the course of electrical machines is reported, where the application of the Semi-dual learning method in five academic semesters was planned, from 2019 - 1 to 2021 - 1, to date it was applied in the semester 2019 1, with satisfactory results. © 2020 IEEE.

关键词： Professional aspects

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Quantum Contextuality Requires Counterfactual Gain

arXiv

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arXiv 2025年

作者： Sagawa, Yuki Hance, Jonte R. Hofmann, Holger F. Ono, Takafumi Program in Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Kagawa Takamatsu761-0396 Japan School of Computing Newcastle University 1 Science Square Newcastle upon TyneNE4 5TG United Kingdom Quantum Engineering Technology Laboratories Department of Electrical and Electronic Engineering University of Bristol Woodland Road BristolBS8 1US United Kingdom Department of Quantum Matter Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama 1-3-1 Higashi Hiroshima739-8530 Japan

Quantum contextuality, where measurement outcomes depend on the measurement context, implies a failure of classical realism in quantum systems. As recently shown, the transition between measurement contexts can be mapped onto the path that a quantum particle takes through an interferometer. Here, we investigate the relation between contextuality and the counterfactual gain observed in the output ports of such an interferometer when one of the paths is blocked. It is shown that experimental evidence of contextuality can only be obtained when counterfactual gain is observed for a specific combination of blocked path and output port. Using a silicon photonic integrated circuit, we experimentally observe the counterfactual gain for a selection of input states and evaluate the associated evidence for contextuality. The results confirm that contextuality can only be observed in the presence of counterfactual gain. Copyright © 2025, The Authors. All rights reserved.

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GraCo: Granularity-Controllable Interactive Segmentation

GraCo: Granularity-Controllable Interactive Segmentation

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yian Zhao Kehan Li Zesen Cheng Pengchong Qiao Xiawu Zheng Rongrong Ji Chang Liu Li Yuan Jie Chen School of Electronic and Computer Engineering Peking University Shenzhen China AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China Peng Cheng Laboratory Shenzhen China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity out-put and multi-granularity output. The latter aims to allevi-ate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing ad-ditional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of avail-able datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control out-put granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically gen-erate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at ob-ject and part levels demonstrate that our GraCo has signifi-cant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo.

关键词： Image segmentation Adaptation models Annotations Interactive systems Pipelines Semantics Redundancy

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Hardware Architecture for the Regular Interpolation Filter of the AV1 Video Coding Standard

Hardware Architecture for the Regular Interpolation Filter o...

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European Signal Processing Conference (EUSIPCO)

作者： Daiane Freitas Rafael da Silva Ícaro Siqueira Cláudio M. Diniz Ricardo A. L. Reis Mateus Grellert Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil Graduate Program on Microelectronics Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Embedded Computing Lab Federal University of Santa Catarina (UFSC) Florianopólis Brazil

ISBN: (数字)9789082797053

ISBN: (纸本)9781728150017

This work proposes a hardware architecture for fractional-pixel interpolation filter defined in the royalty-free AV1 video coding standard. Analysis conducted in this work shows that the AV1 Regular family of filters has the highest usage especially when considering high resolution videos. The proposed architecture implements the 15 interpolation filters of the AV1 Regular family and is capable to interpolate videos of up to 8K video resolution at 120 fps. The proposed architecture achieves the highest throughput compared to related works.

关键词： Video coding Interpolation Computer architecture Parallel processing Filtering algorithms Hardware Standards

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Clarifying Assumptions about Artificial Intelligence before Revolutionising Patent Law

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GRUR International 2022年第4期71卷 295-321页

作者： Kim, Daria Alber, Maximilian Kwok, Man Wai Mitrovic, Jelena Ramirez-Atencia, Cristian Perez, Jesus Alberto Rodriguez Zille, Heiner Max Planck Institute for Innovation and Competition Munich Germany Charite Institute of Pathology Berlin Germany Chinese University of Hong Kong Department of Physics (Formerly) Hong Kong BMBF Program for Women in AI Faculty of Computer Science and Mathematics Chair of Data Science University of Passau Germany Department of Computer Systems Universidad Politecnica de Madrid Spain School of Computing Science College of Science and Engineering University of Glasgow United Kingdom Faculty of Computer Science Otto von Guericke University Magdeburg Germany

This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of 'artificial ingenuity'. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technical problems than where 'intelligent' systems autonomously yield inventions. A detailed technical perspective is presented for each assumption, followed by a discussion of pertinent uncertainties for patent law. Overall, it is argued that implications of machine learning for the patent system in its core tenets appear far less revolutionary than is often posited. © 2022 Published by OUP and CH Beck on behalf of GRUR e.V.

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Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

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Journal of Cerebral Blood Flow and Metabolism 2024年第9期44卷 1480-1514页

作者： Kostoglou, Kyriaki Bello-Robles, Felipe Brassard, Patrice Chacon, Max Claassen, Jurgen AHR Czosnyka, Marek Elting, Jan-Willem Hu, Kun Labrecque, Lawrence Liu, Jia Marmarelis, Vasilis Z Payne, Stephen J Shin, Dae Cheol Simpson, David Smirl, Jonathan Panerai, Ronney B Mitsis, Georgios D Department of Electrical and Computer Engineering McGill University Montreal QC Canada Institute of Neural Engineering Graz University of Technology Graz Austria Departamento de Ingeniería Informática Universidad de Santiago de Chile Santiago Chile Department of Kinesiology Faculty of Medicine Université Laval QC Canada Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec Quebec QC Canada Department of Geriatrics Radboud University Medical Center Research Institute for Medical Innovation and Donders Institute Nijmegen Netherlands Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM) Department of Cardiovascular Sciences University of Leicester Leicester United Kingdom Department of Clinical Neurosciences Neurosurgery Department University of Cambridge Cambridge United Kingdom Department of Neurology and Clinical Neurophysiology University Medical Center Groningen Groningen Netherlands Medical Biodynamics Program Division of Sleep and Circadian Disorders Brigham and Women's Hospital Harvard Medical School Boston MA United States Division of Sleep Medicine Harvard Medical School Boston MA United States Laboratory for Engineering and Scientific Computing Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department Biomedical Engineering Viterbi School of Engineering University of Southern California Los Angeles CA United States Institute of Applied Mechanics National Taiwan University Taipei Taiwan Institute of Sound and Vibration Research University of Southampton Southampton United Kingdom Cerebrovascular Concussion Laboratory Faculty of Kinesiology University of Calgary Calgary AB Canada Sport Injury Prevention Research Centre Faculty of Kinesiology University of Calgary Calgary AB Canada Hotchkiss Brain Institute University of Calgary Calgary AB Canada NIHR Leicester Biomedical Research Centre Bri

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA. © The Author(s) 2024.

关键词： CARNet cerebral autoregulation cerebral blood flow time-domain methods white paper

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Reflections About Conducting Qualitative Research During Pandemic Times as Part of an Extension Project in the Rural Community of San Ramón de La Virgen de Sarapiquí, Costa Rica 1

引用

5th World Conference on Qualitative Research, WCQR 2021

作者： López-Estrada, Patricia Fernández-Mora, Lady Pérez-Hidalgo, Estefanía School of Languages and Social Sciences Instituto Tecnológico de Costa Rica San Carlos Campus San Carlos Costa Rica Rural Tourism Management Academic Program Instituto Tecnológico de Costa Rica San Carlos Campus San Carlos Costa Rica Computing Engineering Program Instituto Tecnológico de Costa Rica San Carlos Campus San Carlos Costa Rica

ISBN: (数字)9783030701871

ISBN: (纸本)9783030701864

Conducting qualitative research has drastically changed during this pandemic. Not only have conceptualizing and designing become challenging practices, but also dealing with the processes of data collection and analysis have presented challenges. The extension project titled "Diagnosis of the linguistic needs of San Ramón de La Virgen de Sarapiquí," aimed at collecting qualitative data during 2020 to determine the linguistic needs of the community. The main goal was to contribute to the design of an exclusive English program to empower community members to better deal with their entrepreneurial projects based on rural tourism. The data of this exploratory study were collected and triangulated through a focus group interview, an online survey, and document gathering, and used thematic analysis to organize the linguistic needs. WebQDA was used to conduct digital semantic coding for the data collected during the focus interview. As the study took place amid the pandemic, some methodological adaptations took place to carry out data collection under the "new normality." The extension group reflected and designed specific protocols for the community members to engage them in technology use and present the results as comprehensive descriptions of the linguistic needs of the rural community. Nowadays, qualitative research should become a more reflective practice, and the participants—as well as their contexts—must be considered, as this pandemic is changing the way qualitative research is perceived and conducted. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data acquisition

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Effect of Periodic Poling on Self-phase Modulation in Thin-film Lithium Niobate Waveguides

Effect of Periodic Poling on Self-phase Modulation in Thin-f...

引用

Frontiers in Optics, FiO 2022

作者： Gül, Gamze Abdelsalam, Kamal Fathpour, Sasan Lee, Kim F. Kanter, Gregory S. Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States CREOL The College of Optics and Photonics University of Central Florida OrlandoFL32816 United States Department of Electrical and Computer Engineering University of Central Florida OrlandoFL32816 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We study self-phase modulation of sub-picosecond telecom wavelength pulses in partially periodically poled thin-film lithium niobate waveguides. We experimentally and computationally investigate the effect of phase mi... 详细信息

ISBN: (纸本)9781557528209

关键词： Thin films

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Generalizing Reduction-Based Algebraic Multigrid

arXiv

引用

arXiv 2022年

作者： Zaman, Tareq Nytko, Nicolas Taghibakhshi, Ali MacLachlan, Scott Olson, Luke West, Matthew Interdisciplinary Program in Scientific Computing Memorial University of Newfoundland NL Canada Department of Computer Science University of Illinois at Urbana-Champaign IL United States Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign IL United States

Algebraic Multigrid (AMG) methods are often robust and effective solvers for solving the large and sparse linear systems that arise from discretized PDEs and other problems, relying on heuristic graph algorithms to achieve their performance. Reduction-based AMG (AMGr) algorithms attempt to formalize these heuristics by providing two-level convergence bounds that depend concretely on properties of the partitioning of the given matrix into its fine- and coarse-grid degrees of freedom. MacLachlan and Saad (SISC 2007) proved that the AMGr method yields provably robust two-level convergence for symmetric and positive-definite matrices that are diagonally dominant, with a convergence factor bounded as a function of a coarsening parameter. However, when applying AMGr algorithms to matrices that are not diagonally dominant, not only do the convergence factor bounds not hold, but measured performance is notably degraded. Here, we present modifications to the classical AMGr algorithm that improve its performance on matrices that are not diagonally dominant, making use of strength of connection, sparse approximate inverse (SPAI) techniques, and interpolation truncation and rescaling, to improve robustness while maintaining control of the algorithmic costs. We present numerical results demonstrating the robustness of this approach for both classical isotropic diffusion problems and for non-diagonally dominant systems coming from anisotropic diffusion. Copyright © 2022, The Authors. All rights reserved.

关键词： Matrix algebra

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Boosting the Efficiency of the Harmonics Elimination VLSI Architecture by Arithmetic Approximations

Boosting the Efficiency of the Harmonics Elimination VLSI Ar...

引用

IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Patricia da Costa Pedro T. L. Pereira Guilherme Paim Eduardo da Costa Sergio Bampi Graduate Program in Microelectronics (PGMICRO) - Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Graduate Program in Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

Approximate computing emerged as a key alternative for trading off accuracy against energy efficiency and area reduction. Error-tolerant applications, such as multimedia processing, machine learning, and signal processing, can process the information with lower-than-standard accuracy at the circuit level while still fulfilling a good and acceptable service quality at the application level. Adaptive filtering-based systems have been demonstrating high resiliency against hardware errors due to their intrinsic self-healing characteristic. This paper investigates the design space exploration of arithmetic approximations in a Very Large-Scale Integration (VLSI) harmonic elimination (HE) hardware architecture based on Least Mean Square (LMS) adaptive filters. We evaluate the Pareto front of the area- and power versus quality curves by relaxing the arithmetic precision and by adopting both approximate multipliers (AxMs) in combination with approximate adders (AxAs). This paper explores the benefits and impacts of the Dynamic Range Unbiased (DRUM), Rounding-based Approximate (RoBA), and Leading one Bit-based Approximate (LoBA) multipliers in the power dissipation, circuit area, and quality of the VLSI HE architectures. Our results highlight the LoBA 0 as the most efficient AxM applied in the HE architecture. We combine the LoBA 0 with Copy and LOA AxAs with variations in the approximation level (L). Notably, LoBA 0 and LOA with $L=6$ resulted in savings of 43.7% in circuit area and 45.2% in power dissipation, compared to the exact HE, which uses multiplier and adder automatically selected by the logic synthesis tool. Finally, we demonstrate that the best hardware architecture found in our investigation successfully eliminates the contaminating spurious noise (i.e., 60 Hz and its harmonics) from the signal.

关键词： Power quality Computer architecture Very large scale integration Harmonic analysis Boosting Hardware Power dissipation

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