检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Sit, Moumita Ling, Jarren Jiang, Chulin Zhang, Zhongyi Khalfallah, Moussa Ioos, Fanny Grossmann, Erwan Dhakal, Hom Nath Research Group School of Mechanical and Design Engineering University of Portsmouth PortsmouthPO1 3DJ United Kingdom Kairos 1 rue des senneurs ZI du Moros Concarneau29900 France Teesside University School of Computing Engineering and Digital Technologies Tees Valley MiddlesbroughTS1 3BX United Kingdom

The aim of the present study is to investigate the influence of accelerated weathering conditions (temperature and humidity) on the mechanical and physical properties of the flax fibre reinforced poly lactic acid (PLA) biocomposites. Two different types of biocomposites namely New Non-woven (NNW) and Conventional Non-woven (CNW) were developed for this study. After 500 hours of exposure to humid environment with 95% relative humidity at 30 and 60°C temperatures, the mechanical (tensile and flexural) and physical (surface roughness and hardness) behaviours were evaluated and compared with that of the dry specimens. Tensile and flexural properties were found to decrease significantly upon 500 hours of exposure to accelerated weathering. The tensile strength of the biocomposite specimens exposed to 30°C temperature and 95% RH demonstrated noteworthy improvement. Scanning electron microscopy (SEM) and X-ray micro CT images of fractured surfaces showed delamination, plasticisation of matrix and fibre debonding due to exposure to various environmental conditions. © 2022, The Authors. All rights reserved.

关键词： Flax

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Ask Me or Tell Me? Enhancing the Effectiveness of Crowdsourced design Feedback 21

Ask Me or Tell Me? Enhancing the Effectiveness of Crowdsourc...

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Proceedings of the 2021 CHI Conference on Human Factors in computing Systems

作者： Fritz Lekschas Spyridon Ampanavos Pao Siangliulue Hanspeter Pfister Krzysztof Z. Gajos School of Engineering Harvard University United States Graduate School of Design Harvard University United States B12 United States Visual Computing Group Harvard University United States School of Engineering and Applied Sciences Harvard University United States

ISBN: (纸本)9781450380966

Crowdsourced design feedback systems are emerging resources for getting large amounts of feedback in a short period of time. Traditionally, the feedback comes in the form of a declarative statement, which often contains positive or negative sentiment. Prior research has shown that overly negative or positive sentiment can strongly influence the perceived usefulness and acceptance of feedback and, subsequently, lead to ineffective design revisions. To enhance the effectiveness of crowdsourced design feedback, we investigate a new approach for mitigating the effects of negative or positive feedback by combining open-ended and thought-provoking questions with declarative feedback statements. We conducted two user studies to assess the effects of question-based feedback on the sentiment and quality of design revisions in the context of graphic design. We found that crowdsourced question-based feedback contains more neutral sentiment than statement-based feedback. Moreover, we provide evidence that presenting feedback as questions followed by statements leads to better design revisions than question- or statement-based feedback alone.

关键词： questioning crowdsourced design feedback sentiment feedback framing

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Attention-Guided Second-Order Pooling Convolutional Networks

Attention-Guided Second-Order Pooling Convolutional Networks

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shannan Chen Qiule Sun Cunhua Li Jianxin Zhang Qiang Zhang Key Lab of Advanced Design and Intelligent Computing Dalian University China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology China School of Computer Engineering Jiangsu Ocean University China School of Computer Science and Engineering Dalian Minzu University China

Recently, channel attention-guided convolutional networks (ConvNets) have shown great advance on visual recognition tasks. However, they mainly exploit coarse first-order statistics to characterize holistic image and rarely focus on long-range feature dependencies, which limits the representation power in a certain. To handle above limitations, this paper proposes a novel attention-guided second-order pooling convolutional network (ASP-Net). ASP-Net introduces bilinear pooling that captures pairwise feature interactions to model second-order statistics. Meanwhile, it explicitly collects long-range dependencies via non-local operations, thus providing a global view in lower layers. Then, the second-order statistics and non-local context features are fused to obtain the enhanced representation for predicting channel-wise attention map and scaling convolution features. Experiment results on three commonly used datasets illuminate that ASP-Net outperforms its counterparts and achieves competitive performance.

关键词： Convolutional codes Visualization Convolution Conferences Network architecture Acoustics Task analysis

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When Quantum Information Technologies Meet Blockchain in Web 3.0

arXiv

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arXiv 2022年

作者： Xu, Minrui Ren, Xiaoxu Niyato, Dusit Kang, Jiawen Qiu, Chao Xiong, Zehui Wang, Xiaofei Leung, Victor C.M. School of Computer Science and Engineering Nanyang Technological University Singapore College of Intelligence and Computing Tianjin University Tianjin300072 China Shenzhen518000 China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing-force networking, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with the advantages of quantum computing and communication. Therefore, in this paper, we introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. First, we present the framework of quantum blockchain-driven Web 3.0 with future-proof security during the transmission of data and transaction information. Next, we discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0. Finally, we describe a use case for quantum non-fungible tokens (NFTs) and propose a quantum deep learning-based optimal auction for NFT trading to maximize the achievable revenue for sufficient liquidity in Web 3.0. In this way, the proposed framework can achieve proven security and sustainability for the next-generation decentralized digital society. © 2022, CC BY.

关键词： Blockchain

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ForestVO: Enhancing Visual Odometry in Forest Environments through ForestGlue

arXiv

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arXiv 2025年

作者： Pritchard, Thomas Ijaz, Saifullah Clark, Ronald Kocer, Basaran Bahadir Computing Department Imperial College London United Kingdom Department of Computer Science University of Oxford United Kingdom School of Civil Aerospace and Design Engineering University of Bristol United Kingdom

Recent advancements in visual odometry systems have improved autonomous navigation, yet challenges persist in complex environments like forests, where dense foliage, variable lighting, and repetitive textures compromise the accuracy of feature correspondences. To address these challenges, we introduce ForestGlue. ForestGlue enhances the SuperPoint feature detector through four configurations – grayscale, RGB, RGB-D, and stereo-vision inputs – optimised for various sensing modalities. For feature matching, we employ LightGlue or SuperGlue, both of which have been retrained using synthetic forest data. ForestGlue achieves comparable pose estimation accuracy to baseline LightGlue and SuperGlue models, yet require only 512 keypoints, just 25% of the 2048 keypoints used by baseline models, to achieve an LO-RANSAC AUC score of 0.745 at a 10° threshold. With a 1/4 of the keypoints required, ForestGlue has the potential to reduce computational overhead whilst being effective in dynamic forest environments, making it a promising candidate for real-time deployment on resource-constrained platforms such as drones or mobile robotic platforms. By combining ForestGlue with a novel transformer based pose estimation model, we propose ForestVO, which estimates relative camera poses using the 2D pixel coordinates of matched features between frames. On challenging TartanAir forest sequences, ForestVO achieves an average relative pose error (RPE) of 1.09 m and kitti_score of 2.33%, outperforming direct-based methods such as DSO in dynamic scenes by 40%, while maintaining competitive performance with TartanVO despite being a significantly lighter model trained on only 10% of the dataset. This work establishes an end-to-end deep learning pipeline tailored for visual odometry in forested environments, leveraging forest-specific training data to optimise feature correspondence and pose estimation for improved accuracy and robustness in autonomous navigation systems. Copyright © 2025, The A

关键词： Stereo vision

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Situating Network Infrastructure with People, Practices, and Beyond: A Community Building Workshop 25

Situating Network Infrastructure with People, Practices, and...

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25th ACM Conference on Computer-Supported Cooperative Work and Social computing, CSCW 2022

作者： Jang, Esther Han Beol Bidwell, Nicola Liu, Jen Sengers, Phoebe Bagalkot, Naveen Verdezoto, Nervo Densmore, Melissa Vigil-Hayes, Morgan Hasan, Shaddi Paul G. Allen School for Computer Science and Engineering SeattleWA United States International University of Management Windhoek Namibia Cornell University Information Science IthacaNY United States Cornell University Information Science and Science & Technology Studies IthacaNY United States Srishti Manipal Institute of Art Design and Technology Karnataka Bengaluru India Cardiff University School of Computer Science and Informatics Cardiff United Kingdom University of Cape Town Cape Town South Africa Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Virginia Tech Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9781450391900

Our world is now connected and even entangled in unprecedented ways through networked technologies. Yet pockets of unequal connectivity persist, and technical infrastructures for connectivity remain difficult to design and build even for experts. In this workshop we aim to bring together a global community of multi- and inter-disciplinary researchers and implementers working on infrastructure development and connectivity to explore the existing design challenges and opportunities for bringing technical dimensions of networked infrastructures in conversation with human-computer interaction (HCI) and the social science of infrastructure. We will share, assess and define research problems and resources for rethinking networked infrastructures from human-, community-, and society-centered perspectives, understanding them to be embedded with human values and biases. We particularly intend our collaborative work to support real-world connectivity initiatives, which have grown in critical importance over the pandemic years - especially projects in support of Global South communities. Concrete deliverables from the workshop will include: (1) an initial shared bibliography to help formalize the state of knowledge in our area, (2) an agenda of shared goals, challenges, and intentions in our field, (3) a compilation of resources to support future work, and (4) social and organizing infrastructures for continued communication and academic collaboration. © 2022 Owner/Author.

关键词： Human computer interaction

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After COVID-19: Crises, Ethics, and Socio-Technical Change

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2022年第4期3卷 248-251页

作者： Calvo, Rafael A. Deterding, Sebastian Flick, Catherine Lutge, Christoph Powell, Alison Vold, Karina V. Imperial College London Dyson School of Design Engineering LondonSW7 9EG United Kingdom De Montfort University Centre for Computing and Social Responsibility LeicesterLE1 9BH United Kingdom Institute for Ethics in Artificial Intelligence Technical University of Munich Peter Löscher Chair of Business Ethics Munich80333 Germany London School of Economics and Political Science Department of Media and Communications LondonWC2A 2AE United Kingdom Institute for the History and Philosophy of Science and Technology Schwartz Reisman Institute for Technology and Society University of Toronto TorontoONM5S 1A1 Canada

Crises like the COVID-19 pandemic accelerate social and technological changes and put new political and public demands on science, technology, and innovation systems. Their urgency clashes with the deliberate slowness of existing responsible innovation and technology ethics practices and processes, while many fast and ad-hoc changes and infrastructures brought about during a crisis become permanent fixtures. This special issue brings together work reflecting in different ways how COVID-19 as an exemplary crisis is creating new challenges for technology ethics. From epidemiological models to contact tracing, biometric recognition, and machine learning-based assisted diagnosis, the different articles show the quandaries of our increasingly datafied health systems. © 2020 IEEE.

关键词： Special issues and sections COVID-19 Ethics Pandemics Technological innovation Decision making Public healthcare Law Fake news Social networking (online) Fingerprint recognition

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Experimental Characterization and Yield Strength Model for Process-Structure-Property of Selective Laser Melted 316l

SSRN

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SSRN 2022年

作者： Chen, Yefeng Wang, Xiaowei Li, Dong Zhou, Dewen Jiang, Yong Yang, Xinyu Liu, Chenglu Leen, Sean B. Gong, Jianming School of Mechanical and Power Engineering Nanjing Tech University Nanjing211816 China Jiangsu Key Lab of Design and Manufacture of Extreme Pressure Equipment Nanjing211816 China Key Laboratory for Light-Weight Materials Nanjing Tech University Nanjing211816 China Institute of High Performance Computing A*STAR Research Entities Connexis 1 Fusionopolis Way #16-16 138632 Singapore Mechanical Engineering School of Engineering College of Science and Engineering NUI Galway Ireland

Heat treatment is the most common method to relieve residual stress and to adjust tensile properties in additively manufactured material. However, the well-known strengthening factors (e.g., dislocation density, cellular sub-structure, low angle grain boundaries, nano-oxide particle) in selective laser melted 316L (SLM 316L) are strongly influenced by heat-treatment temperature. In this work, horizontal and vertical oriented SLM 316L specimens are heat treated from 550 ℃ to 1150 ℃, followed by tensile tests and microstructural characterization. With increasing temperature, strength (e.g., yield strength, ultimate tensile strength) is found to decrease and elongation is found to increase. The heat treatments of 550 ℃, 650 ℃ and 750 ℃ lead to coarsening of cellular sub-structure. Furthermore, the cellular sub-structure and melt boundaries annihilate at 950 ℃. When the temperature reaches 1150 ℃, SLM 316L has finished recrystallization with volume fraction of nano-oxide particles increasing greatly. Based on microstructural characterization, the proposed model, considering strengthening mechanisms of cellular sub-structure, nano-oxide particle and grain boundaries, give satisfactory accuracy to predict yield strength for horizontal orientation. The yield strength for vertical orientation can also be predicted by this model when modified by consideration of anisotropy of columnar grains and lack-of-fusion defects. The anisotropy and lack-of-fusion lead to 5.4% reduction in yield strength for the vertical orientation. This work establishes quantitative relationships for heat treatment-microstructure-property, in which the anisotropy of tensile properties is considered. © 2022, The Authors. All rights reserved.

关键词： Yield stress

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ANN Based Sensor and Actuator Fault Detection in Nuclear Reactors 8

ANN Based Sensor and Actuator Fault Detection in Nuclear Rea...

引用

8th International Conference on Control, Mechatronics and Automation, ICCMA 2020

作者： Banerjee, Shohan Deng, Jiamei Gorse, Chris Vajpayee, Vineet Becerra, Victor Shimjith, S.R. Engineering and Computing Leeds Beckett University School of Built Environment Leeds United Kingdom University of Portsmouth School of Energy and Electronic Engineering Portsmouth United Kingdom Bhabha Atomic Research Centre and Homi Bhabha National Institute Reactor Control System Design Section Mumbai India

ISBN: (纸本)9781728192109

In the nuclear power plants (NPPs), fault detection and diagnosis (FDD) methods are very important to improve the safety and reliability of plants. Researchers have established various FDD methods such as model-based methods, data-driven methods, and signal-based methods. In practical applications, model-based methods are very difficult to achieve. Thus, various data-driven methods and signal-based methods have been applied for monitoring key subsystems in NPPs. In this paper, a brief overview of the Artificial Neural Network (ANN) based FDD method is presented. Simulated data have been generated to train the ANNs as per requirement and to compare with the plant signal during a fault. A technique has been proposed analyzing two sensors data (power sensor and coolant sensor) to determine the sensor and actuator fault in a closed-loop in presence of robust (Proportional-Integral-Derivative) PID controller. Results are produced with credible MATLAB simulation. © 2020 IEEE.

关键词： Fault detection

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Detecting Violations of Conditional Functional Dependencies in Distributed Database

Detecting Violations of Conditional Functional Dependencies ...

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Dattatray Raghunath Kale Amar Buchade Jagannath Nalavade Suhas Gajanan Sapate A. J. Umbarkar Department of Computer Science & Engg. MIT School of Computing MIT Art Design and Technology University Pune Vishwakarma Institute of Information Technology Pune Savitribai Phule Pune University Pune Department of Computer Science & Engg. SETI Panhala Dr. Babasaheb Ambedakar Technologycal University Lonere Department of Computer Science & Engg. Walchand College of Engineering Sangali

This paper develops a technique for detecting violations of conditional functional dependencies in distributed database systems. For a given database that has a set of functional dependencies as a data quality rule, we want to identify tuples in the database that violate these rules. When the provided database is a centralized database, there have been simple SQL-based techniques available for finding violations of the conditional functional dependencies for this particular database. However, it is more challenging to detect violations in distributed databases. Numerous works already published concentrate on functional dependency error estimation in centralized settings where data are kept in a single place, with the aim of reducing the time and space requirements of the estimation methods. With the design and execution of the heuristic algorithm, a remedy for breaches of conditional functional dependencies in the distributed database is suggested. Our key goal for the distributed data is to solve the shipment issue. To assess the efficacy of our plan and algorithm, a series of experiments are created and carried out.

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