检索结果-内蒙古大学图书馆

2025 CHI Conference on Human Factors in computing Systems, CHI EA 2025

作者： Ahmed, Nimra People and Computing Lab. University of Zürich Zürich Switzerland

ISBN: (纸本)9798400713958

This research explores how interactive technologies can raise awareness, support self-help, and create safe spaces for women affected by forced marriages. Despite legal protections, FMs persist globally, including in Switzerland, where patriarchal family structures contrast with egalitarian societal norms. The study is structured into three stages: (1) supporting awareness and realization of abuse, (2) assisting in help-seeking through self-help and enhanced communication with support organizations, and (3) facilitating life repair to ensure safety and independence post-FM. Collaborating with the Swiss Competence Center against Forced Marriages, this research uses participatory, feminist, and trauma-informed approaches. The expected outcomes include tailored technological solutions for the unique challenges of FMs, offering insights into designing for complex social, cultural, and familial dynamics. This doctoral research aims to contribute to HCI by demonstrating how technology can empower individuals in patriarchal contexts within Western societies. © 2025 Copyright held by the owner/author(s).

关键词： Domestic Abuse Forced Marriage Intimate Partner Violence Martial Captivity Women’s Safety

来源：评论

学校读者我要写书评

暂无评论

Adaptive energy-preserving algorithms for guiding center system

引用

Plasma Science and Technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

来源：评论

学校读者我要写书评

暂无评论

Towards More Accessible Scientific PDFs for people with Visual Impairments: Step-by-Step PDF Remediation to Improve Tag Accuracy 25

Towards More Accessible Scientific PDFs for People with Visu...

引用

2025 CHI Conference on Human Factors in computing Systems, CHI 2025

作者： Schmitt-Koopmann, Felix Maximilian Huang, Elaine May Hutter, Hans-Peter Darvishy, Alireza People and Computing Lab University of Zurich Zurich Switzerland Institute of Computer Science Zurich University of Applied Sciences Winterthur Switzerland

ISBN: (纸本)9798400713941

PDF inaccessibility is an ongoing challenge that hinders individuals with visual impairments from reading and navigating PDFs using screen readers. This paper presents a step-by-step process for both novice and experienced users to create accessible PDF documents, including an approach for creating alternative text for mathematical formulas without expert knowledge. In a study involving nineteen participants, we evaluated our prototype PAVE 2.0 by comparing it against Adobe Acrobat Pro, the existing standard for remediating PDFs. Our study shows that experienced users improved their tagging scores from 42.0% to 80.1%, and novice users from 39.2% to 75.2% with PAVE 2.0. Overall, fifteen participants stated that they would prefer to use PAVE 2.0 in the future, and all participants would recommend it for novice users. Our work demonstrates PAVE 2.0's potential for increasing PDF accessibility for people with visual impairments and highlights remaining challenges. © 2025 Copyright held by the owner/author(s).

关键词： Accessibility AI PDF PDF/UA Screen Readers Tagged PDF User Study

来源：评论

学校读者我要写书评

暂无评论

Charting the Design Space for Platform Cooperatives

Charting the Design Space for Platform Cooperatives

引用

2025 CHI Conference on Human Factors in computing Systems, CHI EA 2025

作者： Beloturkina, Ksenia Fedosov, Anton Huang, Elaine M. People and Computing Lab. University of Zurich Zurich Switzerland Institute for Interactive Technologies University of Applied Sciences and Arts Northwestern Switzerland Windisch Switzerland

ISBN: (纸本)9798400713958

Platform cooperatives have recently emerged as an alternative to traditional capitalistic platform models. They aim to create economic value for their members and contribute to the social sustainability of the (local) communities, and, consequently, have been regarded as a more beneficial form of the sharing economy. Our research explores the characteristics related to fairness and equity in platform cooperatives as an initial step. Guided by prior work, we identified nine key fairness criteria and analyzed 30 platform cooperatives, mapping their characteristics into a taxonomy. We subsequently interviewed 17 members of three platform cooperatives to reflect on these fairness categories within their platforms. Our findings highlight the importance of equity, trust, and a sense of community for platform cooperative members to ensure fairness. Ultimately, we draw a set of design recommendations for each taxonomy criterion, offering practical guidance for platform owners and user experience designers to bolster fairness within platform co-ops. © 2025 Copyright held by the owner/author(s).

关键词： Fairness Platform cooperatives User Experience

来源：评论

学校读者我要写书评

暂无评论

All Muscle Activity Test and Evaluation (AMATE): An analytical tool to assess lower limb muscle activation for stroke patients 46

All Muscle Activity Test and Evaluation (AMATE): An analytic...

引用

46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Xiong, Xiyan Gao, Nan Zhang, Qing Ma, Xiao Smirnov, Pavel Zeng, Duchun Xue, Junxiao Yang, Chun Lin, Feng Research Center for Frontier Fundamental Studies Zhejiang Lab Zhejiang Hangzhou China School of Aerospace Engineering Tsinghua University Beijing China Research Center for Astronomical Computing Zhejiang Lab Zhejiang Hangzhou China Zhejiang Provincial People's Hospital Department of Physical Medicine and Rehabilitation Hangzhou China Research Center for Space Computing System Zhejiang Lab Zhejiang Hangzhou China

ISBN: (纸本)9798350371499

Assessing muscle activation and monitoring stroke recovery progress are vital aspects of evaluating motor impairment. Surface electromyography, a common tool for measuring muscle activity, has practical limitations for clinical implementation and fails to capture deep muscle activities, leading to challenges in accurately identifying muscle activation patterns in stroke patients. To address these limitations, we introduce an All Muscle Activity Test and Evaluation (AMATE) system, combining wearable sensor technology with a musculoskeletal model. AMATE computes activation levels of all lower limb muscles during various activities without requiring surface electrodes. It also generates an Activation Dissimilarity Index (ADI) to illustrate muscle activation patterns among individuals. We evaluated AMATE's effectiveness through a pilot study involving 22 walking trials with healthy subjects and stroke patients. The results highlight AMATE's capability in aiding clinicians to analyze and understand diverse lower limb muscle activation patterns in stroke patients, particularly identifying muscles with abnormal activation for targeted rehabilitative training. © 2024 IEEE.

关键词： Electromyography

来源：评论

学校读者我要写书评

暂无评论

What Matters in Graph Class Incremental Learning? An Information Preservation Perspective 38

What Matters in Graph Class Incremental Learning? An Informa...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Li, Jialu Wang, Yu Zhu, Pengfei Lin, Wanyu Hu, Qinghua College of Intelligence and Computing Tianjin University Tianjin China Engineering Research Center of City Intelligence and Digital Governance Ministry of Education of the People's Republic of China Tianjin China Haihe Lab of ITAI Tianjin China Department of Computing The Hong Kong Polytechnic University Hong Kong

Graph class incremental learning (GCIL) requires the model to classify emerging nodes of new classes while remembering old classes. Existing methods are designed to preserve effective information of old models or graph data to alleviate forgetting, but there is no clear theoretical understanding of what matters in information preservation. In this paper, we consider that present practice suffers from high semantic and structural shifts assessed by two devised shift metrics. We provide insights into information preservation in GCIL and find that maintaining graph information can preserve information of old models in theory to calibrate node semantic and graph structure shifts. We correspond graph information into low-frequency local-global information and high-frequency information in spatial domain. Based on the analysis, we propose a framework, Graph Spatial Information Preservation (GSIP). Specifically, for low-frequency information preservation, the old node representations obtained by inputting replayed nodes into the old model are aligned with the outputs of the node and its neighbors in the new model, and then old and new outputs are globally matched after pooling. For high-frequency information preservation, the new node representations are encouraged to imitate the near-neighbor pair similarity of old node representations. GSIP achieves a 10% increase in terms of the forgetting metric compared to prior methods on large-scale datasets. Our framework can also seamlessly integrate existing replay designs. The code is available through https://***/Jillian555/GSIP. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards More Accessible Scientific PDFs for people with Visual Impairments: Step-by-Step PDF Remediation to Improve Tag Accuracy

arXiv

引用

arXiv 2025年

作者： Schmitt-Koopmann, Felix M. Huang, Elaine M. Hutter, Hans-Peter Darvishy, Alireza Institute of Computer Science ZHAW Winterthur8401 Switzerland People and Computing Lab University of Zurich Zurich8050 Switzerland

PDF inaccessibility is an ongoing challenge that hinders individuals with visual impairments from reading and navigating PDFs using screen readers. This paper presents a step-by-step process for both novice and experienced users to create accessible PDF documents, including an approach for creating alternative text for mathematical formulas without expert knowledge. In a study involving nineteen participants, we evaluated our prototype PAVE 2.0 by comparing it against Adobe Acrobat Pro, the existing standard for remediating PDFs. Our study shows that experienced users improved their tagging scores from 42.0% to 80.1%, and novice users from 39.2% to 75.2% with PAVE 2.0. Overall, fifteen participants stated that they would prefer to use PAVE 2.0 in the future, and all participants would recommend it for novice users. Our work demonstrates PAVE 2.0’s potential for increasing PDF accessibility for people with visual impairments and highlights remaining challenges. © 2025, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration 41

Socialized Learning: Making Each Other Better Through Multi-...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Yao, Xinjie Wang, Yu Zhu, Pengfei Lin, Wanyu Li, Jialu Li, Weihao Hu, Qinghua College of Intelligence and Computing Tianjin University Tianjin China Engineering Research Center of City Intelligence and Digital Governance Ministry of Education of the People's Republic of China Tianjin China Haihe Lab of ITAI Tianjin China Department of Computing The Hong Kong Polytechnic University Hong Kong Department of Computer Science Boston University Boston United States

Learning new knowledge frequently occurs in our dynamically changing world, e.g., humans culturally evolve by continuously acquiring new abilities to sustain their survival, leveraging collective intelligence rather than a large number of individual attempts. The effective learning paradigm during cultural evolution is termed socialized learning (SL). Consequently, a straightforward question arises: Can multi-agent systems acquire more new abilities like humans? In contrast to most existing methods that address continual learning and multi-agent collaboration, our emphasis lies in a more challenging problem: We prioritize the knowledge in the original expert classes, and as we adeptly learn new ones, the accuracy in the original expert classes stays superior among all in a directional manner. Inspired by population genetics and cognitive science, leading to unique and complete development, we propose Multi-Agent Socialized Collaboration (MASC), which achieves SL through interactions among multiple agents. Specifically, we introduce collective collaboration and reciprocal altruism modules, organizing collaborative behaviors, promoting information sharing, and facilitating learning and knowledge interaction among individuals. We demonstrate the effectiveness of multi-agent collaboration in an extensive empirical study. Our code will be publicly available at https://***/yxjdarren/SL. Copyright 2024 by the author(s)

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Uncertainty-aware Superpoint Graph Transformer for Weakly Supervised 3D Semantic Segmentation

引用

IEEE Transactions on Fuzzy Systems 2025年第6期33卷 1899-1912页

作者： Fan, Yan Wang, Yu Zhu, Pengfei Hui, Le Xie, Jin Hu, Qinghua Tianjin University College of Intelligence and Computing Tianjin300350 China Ministry of Education of the People's Republic of China Engineering Research Center of City Intelligence and Digital Governance China Haihe Laboratory of Itai Tianjin China Northwestern Polytechnical University School of Electronics and Information Shaanxi Key Laboratory of Information Acquisition and Processing China Nanjing University of Science and Technology Pca Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

Weakly supervised 3D semantic segmentation has successfully mitigated the labor-intensive and time-consuming task of annotating 3D point clouds. However, reliably utilizing the minimal point-wise annotations for unlabeled data in complex and large-scale scenes is still challenging, such as only 20 points labeled in 2 million points. To tackle this challenge, we propose a new Uncertainty-aware Superpoint Graph Transformer (UaSGT) framework that utilizes minimal annotations for unlabeled data learning through reliable long-range supervision propagation from labeled superpoints to unlabeled superpoints. First, we propose a superpoint graph transformer to achieve long-range supervision propagation along the attention-based fuzzy subsets defined on superpoints. The attention-based fuzzy subset measures the membership of unlabeled superpoints to clusters centered on labeled superpoints. Second, we employ an uncertainty-aware membership rectification technique on the fuzzy subset to ensure reliable propagation among superpoints within the same category. This technique integrates an uncertainty prediction module to mask the influence of unreliable membership and a spatial prior refinement module to reduce uncertainty in intra-class membership degrees. Finally, experimental results on two large-scale benchmarks S3DIS and ScanNet-V2 demonstrate the superiority of our approach compared to the state-of-the-art with at least 90% annotation reduction, and our method also achieves comparable performance to fully supervised methods with less than 0.1% labeled points. Our code is available at https://***/fanyan0411/UaSGT. © 2025 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Correction to: Sugeno Integral of Set-Valued Functions with Respect to Multi-submeasures and Its Application in MADM

引用

International Journal of Fuzzy Systems 2023年第6期25卷 2514-2517页

作者： Zhang, Deli Wang, Guijun Key Lab. of Soft Computing and Appl. Changchun Normal University Changchun People’s Republic of China College of Mathematics Tianjin Normal University Tianjin People’s Republic of China

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：