检索结果-内蒙古大学图书馆

30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Liang, Yu Collaris, Dennis Willemsen, Martijn C. Van Wijk, Jarke J. Human-Technology Interaction Eindhoven University of Technology Eindhoven Netherlands Dept. Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands Jheronimus Academy of Data Science Den Bosch Netherlands

ISBN: (纸本)9798400713064

Research in Explainable AI (XAI) has shown that explanations can improve users' understanding of AI models, improve user performance and potentially reduce overreliance on AI predictions. However, this is mostly evaluated by static rather than dynamic measures, and the role of XAI on learning over trials is rarely studied. In this study, we use a context-free sequence prediction task, in which 458 participants predict the next symbol in a fixed sequence (with some noise) over 80 trials. We compare performance with AI and XAI advice against no AI support, and subsequently we test for learning by taking away the AI support after 40 trials (i.e., a reversal study design). Our results show that users learn faster with XAI than with AI without explanations or no AI and are better able to recover in performance from the removal of AI. However, the benefits of XAI on learning are much smaller for more difficult tasks. This work demonstrates the benefits of repeated measures user studies and multilevel modeling to better understand learning processes in XAI. It also shows the potential of AI explanations to help users to learn and poses XAI design suggestions to support learning in human-AI collaboration. © 2025 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

引用

6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

来源：评论

学校读者我要写书评

暂无评论

Beyond the User: Mapping Subject Positions for Robots in Public Spaces 25

Beyond the User: Mapping Subject Positions for Robots in Pub...

引用

ACM/IEEE International Conference on human-Robot interaction (HRI)

作者： Anna Dobrosovestnova Franziska Babel Hannah Pelikan Human-Computer Interaction group TU Wien Vienna Austria Dept. of Computer and Information Science Linköping University Linköping Sweden Dept. of Culture and Society Linköping University Linköping Sweden

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

The concept of the “user” is central to research in human- Robot interaction (HRI). Drawing on the field studies of functional service robots in public spaces, the paper contributes a conceptual framework for describing positions and roles humans can take beyond being robot users. We rely on the concept of “subject position” from human-computer interaction (HCI) to map out people beyond users into three ecologies: Service, Street Life, and Public Discourse. Through the lens of these ecologies, we highlight how people encounter the robot as (i) an actor in service provision, (ii) a (social and material) actor moving with other members of the street, and (iii) a matter of public concern. The paper contributes a vocabulary for describing the diverse roles of humans and offers methodological suggestions for more holistic research and design of HRI. Further, we outline disciplinary and ethical considerations relating to designing with ecologies in mind.

关键词： human computer interaction Vocabulary Ethics Shape Service robots human-robot interaction Ecology Stakeholders Robots Lenses

来源：评论

学校读者我要写书评

暂无评论

Beyond the User: Mapping Subject Positions for Robots in Public Spaces 20

Beyond the User: Mapping Subject Positions for Robots in Pub...

引用

20th Annual ACM/IEEE International Conference on human-Robot interaction, HRI 2025

作者： Dobrosovestnova, Anna Babel, Franziska Pelikan, Hannah Human-Computer Interaction group Tu Wien Vienna Austria Linköping University Dept. of Computer and Information Science Linköping Sweden Linköping University Dept. of Culture and Society Linköping Sweden

ISBN: (纸本)9798350378931

The concept of the 'user' is central to research in human- Robot interaction (HRI). Drawing on the field studies of functional service robots in public spaces, the paper contributes a conceptual framework for describing positions and roles humans can take beyond being robot users. We rely on the concept of 'subject position' from human-computer interaction (HCI) to map out people beyond users into three ecologies: Service, Street Life, and Public Discourse. Through the lens of these ecologies, we highlight how people encounter the robot as (i) an actor in service provision, (ii) a (social and material) actor moving with other members of the street, and (iii) a matter of public concern. The paper contributes a vocabulary for describing the diverse roles of humans and offers methodological suggestions for more holistic research and design of HRI. Further, we outline disciplinary and ethical considerations relating to designing with ecologies in mind. © 2025 IEEE.

关键词： framework public discourse service stakeholders street

来源：评论

学校读者我要写书评

暂无评论

Exploring Dependence of Subject-Specific Training Strategies for EEG Based Brain-computer Interfaces

Exploring Dependence of Subject-Specific Training Strategies...

引用

IEEE Southeastcon

作者： T. Warren de Wit Vineetha Menon Thomas Davis Dept. of Computer Science University of Alabama Huntsville Huntsville USA Human Systems Integration Division DEVCOM Data and Analysis Center Huntsville USA

Design and deployment of brain-computer interface enabled assistive systems poses many practical questions, including the decision of whether to use a pretrained model or to customize a model to each unique end-user. In this work, we apply this question to the application domain of a passive brain- controlled drone for use in disaster relief and hostage rescue situations. A six-class intent (e.g. EEG) recognition experiment is performed with 42 subjects. This pilot study explores and evaluates the effects of subject-specific (“customized”) versus subject- independent (“uncustomized”) modeling approaches. Based on experimental validation, we present our discussions on the observed pros and cons of each training strategy. In this study, it was noted that the uncustomized training approach had the best target detection performance with a reduction in variance. Additionally, its deployment readiness attribute make it a more relevant and feasible option for our intended use case.

关键词：

来源：评论

学校读者我要写书评

暂无评论

human-centered Evaluation and Auditing of Language Models

Human-Centered Evaluation and Auditing of Language Models

引用

2025 CHI Conference on human Factors in Computing Systems, CHI EA 2025

作者： Liu, Yu Lu Deng, Wesley Hanwen Lam, Michelle S. Eslami, Motahhare Kim, Juho Liao, Q. Vera Xu, Wei Novikova, Jekaterina Xiao, Ziang Johns Hopkins University BaltimoreMD United States Human-Computer Interaction Institution Carnegie Mellon University PittsburghPA United States Dept. of Computer Science Stanford University StanfordCA United States School of Computer Science Carnegie Mellon University PittsburghPA United States School of Computing KAIST Daejeon Korea Republic of Microsoft Research MontrealQC Canada School of Interactive Computing Georgia Institute of Technology AtlantaGA United States AI Risk and Vulnerability Alliance SeattleWA United States

ISBN: (纸本)9798400713958

The recent advancements in Large Language Models (LLMs) have significantly impacted numerous, and will impact more, real-world applications. However, these models also pose significant risks to individuals and society. To mitigate these issues and guide future model development, responsible evaluation and auditing of LLMs are essential. This workshop aims to address the current "evaluation crisis" in LLM research and practice by bringing together HCI and AI researchers and practitioners to rethink LLM evaluation and auditing from a human-centered perspective. The workshop will explore topics around understanding stakeholders’ needs and goals with evaluation and auditing LLMs, establishing human-centered evaluation and auditing methods, developing tools and resources to support these methods, building community and fostering collaboration. By soliciting papers, organizing invited keynote and panel, and facilitating group discussions, this workshop aims to develop a future research agenda for addressing the challenges in LLM evaluation and auditing. Following a successful first iteration of this workshop at CHI 2024, we introduce the theme of "mind the context" for this second iteration, where participants will be encouraged to tackle the challenges and nuances of LLM evaluation and auditing in specific contexts. © 2025 Copyright held by the owner/author(s).

关键词： Audit Evaluation Generative AI Large Language Models

来源：评论

学校读者我要写书评

暂无评论

Localization of Dengue Virus Likelihood Using Image Processing Technique

Localization of Dengue Virus Likelihood Using Image Processi...

引用

Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Md. Mahbub Hosen Md. Rahatul Islam Faria Tabassum Syeda Thamina Tonni Malik Mohammad Nafiur Noor Shahid Rahman Dept. of Computer Science & Engineering Northern University of Bangladesh Dhaka Bangladesh Dept. of Human Intelligence Systems Kyushu Institute of Technology Wakamatsu Kitakyushu Japan Dept. of Computer Science & Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Human Intelligence Lab Bangladesh Advance Robotics Research Center Dhaka Bangladesh Dept. of Electrical & Electronic Engineering Canadian University of Bangladesh Dhaka Bangladesh

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes; it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Grid-Search Integrated Optimized Support Vector Machine Model for Breast Cancer Detection

Grid-Search Integrated Optimized Support Vector Machine Mode...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Ghose, Partho Sharmin, Selina Gaur, Loveleen Zhao, Zhongming Jagannath University Dept. Computer Science and Engineering Dhaka Bangladesh Amity University Amity International Business School Noida India The University of Texas Health Science Center at Houston Human Genetics Center School of Public Health HoustonTX77030 United States

ISBN: (纸本)9781665468190

Breast cancer is a common and highly heterogeneous cancer worldwide. Rapid detection and early diagnosis are essential in its treatment, but it is challenging due to mammogram's uncertainty. Based on machine learning, operative clinical systems can be implemented to save patients' lives. This study proposes an optimized support vector machine (SVM) model to predict breast cancer using the grid search method to find the best hyper-parameters. For validation, we offer an in-dept. experimental study and we achieve, for Benign|Malignant|Average cases, accuracy of 98.69%|99.72%|99.0%, precision of 96.0%|100.0%|98.0%, recall of 100.0%|98.0%|98.0%, and Fl-score of 98.0%|97.0%|98.0% respectively. Comparison is made between the tuned hyper-parameter and default hyper-parameter performance. SVM performance with default parameters is 96%, while the maximum accuracy is achieved by hyper-parameters tuned. An SVM model is 99%, which can be a better cancer detection system. The results show performance improves when the best hyperparameters are used for SVM training. Thus, the analysis and comparison indicate that our stated system is better than the state-of-the-art ML-based breast cancer detection system. © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Variations on a Hexagon: Iterative Design of Interactive Cyberphysical Tokens and Constraints 24

Variations on a Hexagon: Iterative Design of Interactive Cyb...

引用

18th International Conference on Tangible, Embedded, and Embodied interaction, TEI 2024

作者： Ullmer, Brygg Dai, Sida De Siqueira, Alexandre Gomes McLendon, Millon Filipiak, Breanna Shafiee, Laila Newman, Winifred Elysse Konkel, Miriam K. Tangible Visualization Group Clemson University United States Virtual Environments Research Group University of Florida United States Computer Science Division School of Computing Clemson University United States Institute for Intelligent Materials Systems and Environments Clemson University United States Dept. of Genetics and Biochemistry Center for Human Genetics Clemson University United States

ISBN: (纸本)9798400704024

We describe iterations on the design of a hexagonal token and constraint tangible and cyberphysical interface. Our system has been co-designed both for use in tangible, embedded, embodied interaction and extended reality classroom contexts, and within broader applied generalizations. We survey some of the related literature in hexagonal, rectangular, and triangular tangible interfaces. We express a design space characterizing several aspects of these prior systems;and apply these to a number of additional virtual and physical iterations. We accompany our text with 3D printable, circuit board, and virtual models for a number of these interactors, usable in both tangible and purely virtual forms, including versions engaging four different embedded computing platforms (Raspberry Pi Zero, Raspberry Pi Pico, Adafruit Circuit Playground, and Blinks). We discuss experiences from use of these in classroom settings, and steps toward broader applications. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： 3D printing

来源：评论

学校读者我要写书评

暂无评论

Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning

arXiv

引用

arXiv 2023年

作者： Lee, Daeun Son, Sejung Jeon, Hyolim Kim, Seungbae Han, Jinyoung Dept. of Applied Artificial Intelligence Sungkyunkwan University Seoul Korea Republic of Dept. of Applied Artificial Intelligence Dept. of Human-AI Interaction Sungkyunkwan University Seoul Korea Republic of Computer Science and Engineering College of Engineering University of South Florida TampaFL United States

Bipolar disorder (BD) is closely associated with an increased risk of suicide. However, while the prior work has revealed valuable insight into understanding the behavior of BD patients on social media, little attention has been paid to developing a model that can predict the future suicidality of a BD patient. Therefore, this study proposes a multi-task learning model for predicting the future suicidality of BD patients by jointly learning current symptoms. We build a novel BD dataset clinically validated by psychiatrists, including 14 years of posts on bipolar-related subreddits written by 818 BD patients, along with the annotations of future suicidality and BD symptoms. We also suggest a temporal symptom-aware attention mechanism to determine which symptoms are the most influential for predicting future suicidality over time through a sequence of BD posts. Our experiments demonstrate that the proposed model outperforms the state-of-the-art models in both BD symptom identification and future suicidality prediction tasks. In addition, the proposed temporal symptom-aware attention provides interpretable attention weights, helping clinicians to apprehend BD patients more comprehensively and to provide timely intervention by tracking mental state progression. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

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：