检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Wu, Hongjia Zeng, Hui Xiong, Zehui Kang, Jiawen Cai, Zhiping Chan, Tse-Tin Niyato, Dusit Han, Zhu Department of Mathematics and Information Technology The Education University of Hong Kong Hong Kong The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Automation Guangdong University of Technology China College of Computer National University of Defense Technology China College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

Updates of extensive Internet of Things (IoT) data are critical to the immersion of vehicular metaverse services. However, providing high-quality and sustainable data in unstable and resource-constrained vehicular networks remains a significant challenge. To address this problem, we put forth a novel immersion-aware model trading framework that incentivizes metaverse users (MUs) to contribute learning models trained by their latest local data for augmented reality (AR) services in the vehicular metaverse, while preserving their privacy through federated learning. To comprehensively evaluate the contribution of locally trained learning models provided by MUs to AR services, we design a new immersion metric that captures service immersion by considering the freshness and accuracy of learning models, as well as the amount and potential value of raw data used for training. We model the trading interactions between metaverse service providers (MSPs) and MUs as an equilibrium problem with equilibrium constraints (EPEC) to analyze and balance their costs and gains. Moreover, considering dynamic network conditions and privacy concerns, we formulate the reward decisions of MSPs as a multi-agent Markov decision process. Then, a fully distributed dynamic reward method based on deep reinforcement learning is presented, which operates without any private information about MUs and other MSPs. Experimental results demonstrate that the proposed framework can effectively provide higher-value models for object detection and classification in AR services on real AR-related vehicle datasets compared to benchmark schemes. Copyright © 2024, The Authors. All rights reserved.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Justifying the prediction of major soil nutrients levels (N, P, and K) in cabbage cultivation

引用

MethodsX 2024年 12卷 102793页

作者： Abekoon, Thilina Sajindra, Hirushan Buthpitiya, B.L.S.K. Rathnayake, Namal Meddage, D.P.P. Rathnayake, Upaka Water Resources Management and Soft Computing Research Laboratory Athurugiriya Millennium City 10150 Sri Lanka Department of Chemistry Faculty of Science University of Kelaniya 11600 Sri Lanka Graduate School of Engineering The University of Tokyo Tokyo 113-8654 Japan School of Engineering and Information Technology University of New South Wales Northcott Drive Canberra 2612 ACT Australia Department of Civil Engineering and Construction Faculty of Engineering and Design Atlantic Technological University Sligo F91 YW50 Ireland

In a recent paper by Sajindra et al. [1], the soil nutrient levels, specifically nitrogen, phosphorus, and potassium, in organic cabbage cultivation were predicted using a deep learning model. This model was designed with a total of four hidden layers, excluding the input and output layers, with each hidden layer meticulously crafted to contain ten nodes. The selection of the tangent sigmoid transfer function as the optimal activation function for the dataset was based on considerations such as the coefficient of correlation, mean squared error, and the accuracy of the predicted results. Throughout this study, the objective is to justify the tangent sigmoid transfer function and provide mathematical justification for the obtained results. • This paper presents the comprehensive methodology for the development of deep neural network for predict the soil nutrient levels. • Tangent Sigmoid transfer function usage is justified in predictions. • Methodology can be adapted to any similar real-world scenarios. © 2024 The Author(s)

关键词： Cabbage cultivation Deep neural network Soil nutrient levels TanSig function

来源：评论

学校读者我要写书评

暂无评论

DSD-MatchingNet:Deformable sparse-to-dense feature matching for learning accurate correspondences

引用

Virtual Reality & Intelligent Hardware 2022年第5期4卷 432-443页

作者： Yicheng ZHAO Han ZHANG Ping LU Ping LI Enhua WU Bin SHENG Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China ZTE Corporation Shenzhen 518057China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518057China Department of Computing The Hong Kong Polytechnic UniversityHong Kong 999077China School of Design The Hong Kong Polytechnic UniversityHong Kong 999077China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Faculty of Science and Technology University of MacaoMacao 999078China

Background Exploring correspondences across multiview images is the basis of various computer vision ***,most existing methods have limited accuracy under challenging *** To learn more robust and accurate correspondences,we propose DSD-MatchingNet for local feature matching in this ***,we develop a deformable feature extraction module to obtain multilevel feature maps,which harvest contextual information from dynamic receptive *** dynamic receptive fields provided by the deformable convolution network ensure that our method obtains dense and robust ***,we utilize sparse-to-dense matching with symmetry of correspondence to implement accurate pixel-level matching,which enables our method to produce more accurate *** Experiments show that our proposed DSD-MatchingNet achieves a better performance on the image matching benchmark,as well as on the visual localization ***,our method achieved 91.3%mean matching accuracy on the HPatches dataset and 99.3%visual localization recalls on the Aachen Day-Night dataset.

关键词： Image matching Deformable convolution network Sparse-to-dense matching

来源：评论

学校读者我要写书评

暂无评论

Revisiting the onsets and frames model with additive attention

arXiv

引用

arXiv 2021年

作者： Cheuk, Kin Wai Luo, Yin-Jyun Benetos, Emmanouil Herremans, Dorien Information Systems Technology and Design Singapore University of Technology and Design Institute of High Performance Computing A*STAR School of Electronic Engineering and Computer Science Queen Mary University of London

Recent advances in automatic music transcription (AMT) have achieved highly accurate polyphonic piano transcription results by incorporating onset and offset detection. The existing literature, however, focuses mainly on the leverage of deep and complex models to achieve state-of-the-art (SOTA) accuracy, without understanding model behaviour. In this paper, we conduct a comprehensive examination of the Onsets-and-Frames AMT model, and pinpoint the essential components contributing to a strong AMT performance. This is achieved through exploitation of a modified additive attention mechanism. The experimental results suggest that the attention mechanism beyond a moderate temporal context does not benefit the model, and that rule-based post-processing is largely responsible for the SOTA performance. We also demonstrate that the onsets are the most significant attentive feature regardless of model complexity. The findings encourage AMT research to weigh more on both a robust onset detector and an effective post-processor. © 2021, CC BY.

关键词： Additives

来源：评论

学校读者我要写书评

暂无评论

REVISITING THE PREDICTABILITY OF DYNAMICAL SYSTEMS: A NEW LOCAL DATA-DRIVEN APPROACH

arXiv

引用

arXiv 2024年

作者： Dong, Chenyu Faranda, Davide Gualandi, Adriano Lucarini, Valerio Mengaldo, Gianmarco College of Design and Engineering National University of Singapore Singapore LSCE Université Paris-Saclay France London Mathematical Laboratory United Kingdom IPSL École Normale Supérieure France Department of Earth Sciences University of Cambridge Istituto Nazionale di Geofisica e Vulcanologia United Kingdom School of Computing and Mathematical Sciences University of Leicester United Kingdom

Nonlinear dynamical systems are ubiquitous in nature and they are hard to forecast. Not only they may be sensitive to small perturbations in their initial conditions, but they are often composed of processes acting at multiple scales. Classical approaches based on the Lyapunov spectrum rely on the knowledge of the dynamic forward operator, or of a data-derived approximation of it. This operator is typically unknown, or the data are too noisy to derive a faithful representation. Here, we propose a new data-driven approach to analyze the local predictability of dynamical systems. This method, based on the concept of recurrence, is closely linked to the well-established framework of local dynamical indices. Applied to both idealized systems and real-world datasets, this new index shows results consistent with existing knowledge, proving its effectiveness in estimating local predictability. Additionally, we discuss its relationship with local dynamical indices, illustrating how it complements the previous framework as a more direct measure of predictability. Furthermore, we explore its reflection of the scale-dependent nature of predictability, its extension that includes a weighting strategy, and its real-time application. We believe these aspects collectively demonstrate its potential as a powerful diagnostic tool for complex systems. © 2024, CC BY.

关键词： Nonlinear dynamical systems

来源：评论

学校读者我要写书评

暂无评论

design automation for mass customisation via additive manufacture: A case study on continuous positive airway pressure mask

Design automation for mass customisation via additive manufa...

引用

ASME 2020 International design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Li, Shiya Ploumpis, Stylianos Zafeiriou, Stefanos Myant, Connor Dyson School of Design Engineering Imperial College London United Kingdom Intelligent Behaviour Understanding Group Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9780791884003

Additive Manufacturing (AM) has been identified as a key enabler for Mass Customization (MC) due to its negligible tooling cost associated with producing one-off items. This is especially valuable for the medical industry where the ability to create patient-specific products can greatly improve performance and comfort. However, the use of AM so far has only been limited to previously custom-made devices due to the prohibitive design costs associated with a knowledge-intensive and highly manual design process. The research community has often overlooked this area and as yet no study has shown a completely automated process that can reduce or even eliminate this design cost for existing mass-produced ergonomic products (e.g. respirators). This study investigates the methodology of developing a completely automated design pipeline through a case study on Continuous Positive Airway Pressure (CPAP) mask. Through a parametric design approach, a fully automated pipeline was constructed based on a large-scale statistical shape model "learnt"from 9,663 high-resolution facial scans. The pipeline accepts a single "in-the-wild"facial image as the only data input and produces a CAD model of CPAP mask in under a minute. The significant reduction in design time, ease of data acquisition and the complete removal of a manual CAD modelling process can make AM more accessible for CPAP masks manufacturers. The same workflow can potentially be employed to construct automation pipelines for other types of wearables, therefore encouraging the adoption of AM for MC of a wider selection of products. Copyright © 2020 ASME.

关键词： 3D printers

来源：评论

学校读者我要写书评

暂无评论

Gemnet: Group Equivariant Mesh Convolutional Neural Network

SSRN

引用

SSRN 2022年

作者： Afzal, Muhammad Kamran Zang, Yu Zeb, Adnan Afzal, H.M. Rehan Liu, Weiquan Wang, Cheng Li, Jonathan Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University 422 Siming South Road Xiamen361005 China College of Engineering Southern University of Science and Technology Shenzhen China School of Electrical Engineering and Computing University of Newcastle CallaghanNSW2308 Australia Departments of Geography and Environmental Management and Systems Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Recent convolutional neural networks (CNNs) in geometric deep-learning for 3D meshes are inadequate in a natural generalisation of CNNs that reduces sample complexity by exploiting symmetries. We propose a novel Group Equivariant Mesh Convolutional Neural Network (GEMnet) using group convolutional layers that exploit a higher degree of weight sharing than the traditional convolution layers, enhancing the expressive ability of the network without fostering additional parameters. Implementing GEMnet layers is easy, with nominal computational overhead for discrete groups produced by translations, rotations, and reflections. Our novel approach operates directly on 3D mesh data for more discriminant feature maps, exhibiting notable improvements across prior stateof-the-art methods. Employing a variety of benchmark datasets, i.e., SHREC with Split 16 & 10 reached 99.83% & 99.33%, Cubes gained 99.17%, and ModelNet40 datasets achieved 95.50% accuracies, respectively, our method surpasses traditional methods for triangular meshes in a classification task. © 2022, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Comparing Large Language Model AI and Human-Generated Coaching Messages for Behavioral Weight Loss

引用

Journal of Technology in Behavioral Science 2025年 1-12页

作者： Huang, Zhuoran Berry, Michael P. Chwyl, Christina Hsieh, Gary Wei, Jing Forman, Evan M. Khoury College of Computer Sciences Northeastern University 440 Huntington Ave Boston 02115 MA United States VA Connecticut Healthcare System West Haven 06516 CT United States Portland Psychotherapy Clinic Research and Training Center 3700 N Williams Ave. Portland 97227 OR United States Department of Human Centered Design & Engineering University of Washington Seattle 98195 WA United States School of Computing and Information Systems The University of Melbourne Parkville 3052 VIC Australia Center for Weight Eating and Lifestyle Science Drexel University 3141 Chestnut Street Stratton Hall Philadelphia 19104 PA United States Department of Psychological and Brain Sciences Drexel University 3141 Chestnut Street Stratton Hall Philadelphia 19104 PA United States

Automated coaching messages for weight control can save time and costs, but their repetitive, generic nature may limit their effectiveness compared to human coaching. Large language model (LLM) based artificial intelligence (AI) chatbots, like ChatGPT, could offer more personalized and novel messages to address repetition with their data-processing abilities. While LLM AI demonstrates promise to encourage healthier lifestyles, studies have yet to examine the feasibility and acceptability of LLM-based BWL coaching. Eighty-seven adults in a weight-loss trial (BMI ≥ 27 kg/m²) rated ten coaching messages’ helpfulness (five human-written, five ChatGPT-generated) using a 5-point Likert scale, providing additional open-ended feedback to justify their ratings. Participants also identified which messages they believed were AI-generated. The evaluation occurred in two phases: messages in Phase 1 were perceived as impersonal and negative, prompting revisions for messages in Phase 2. In Phase 1, AI-generated messages were rated less helpful than human-written ones, with 66% receiving a helpfulness rating of 3 or higher. However, in Phase 2, the AI messages matched the human-written ones regarding helpfulness, with 82% scoring three or above. Additionally, 50% were misidentified as human-written, suggesting AI’s sophistication in mimicking human-generated content. A thematic analysis of open-ended feedback revealed that participants appreciated AI’s empathy and personalized suggestions but found them more formulaic, less authentic, and too data-focused. This study reveals the preliminary feasibility and perceived helpfulness of LLM AIs, like ChatGPT, in crafting potentially effective weight control coaching messages. Our findings also underscore areas for future enhancement. © The Author(s) 2025.

关键词： Artificial intelligence ChatGPT Large language model MHealth Weight loss

来源：评论

学校读者我要写书评

暂无评论

Enhancement of Co-located Shared VR Experiences: Representing Non-HMD Observers on Both HMD and 2D Screens

Enhancement of Co-located Shared VR Experiences: Representin...

引用

International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Zixuan Guo Wenge Xu Hongyu Wang Tingjie Wan Nilufar Baghaei Cheng-Hung Lo Hai-Ning Liang School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China Department of Computer Science The University of Liverpool Liverpool UK College of Computing Birmingham City University Birmingham UK School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Department of Industrial Design Xi’an Jiaotong-Liverpool University Suzhou China Computational Media and Arts Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (数字)9798331516475

ISBN: (纸本)9798331516482

Virtual reality (VR) not only allows head-mounted display (HMD) users to immerse themselves in virtual worlds but also to share them with others. When designed correctly, this shared experience can be enjoyable. However, in typical scenarios, HMD users are isolated by their devices, and non-HMD observers lack connection with the virtual world. To address this, our research investigates visually representing observers on both HMD and 2D screens to enhance shared experiences. The study, including five representation conditions, reveals that incorporating observer representation positively impacts both HMD users and observers. For how to design and represent them, our work shows that HMD users prefer methods displaying real-world visuals, while observers exhibit diverse preferences regarding being represented with real or virtual images. We provide design guidelines tailored to both displays, offering valuable insights to enhance co-located shared VR experiences for HMD users and non-HMD observers.

关键词： Visualization Head-mounted displays design methodology Resists Interference Observers Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Reducing Driver’s Cognitive Load with the Use of Artificial Intelligence and Augmented Reality 23rd

Reducing Driver’s Cognitive Load with the Use of Artificial...

引用

23rd International Conference on Human-Computer Interaction , HCII 2021

作者： Bram-Larbi, Kweku F. Charissis, Vassilis Lagoo, Ramesh Wang, Shu Khan, Soheeb Altarteer, Samar Harrison, David K. Drikakis, Dimitris School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom Research and Development Core Lab + Ltd Glasgow United Kingdom Research and Development Volkswagen Beijing China School of Design and Architecture Dar Al-Hekma University Jeddah Saudi Arabia Defence and Security Research Institute University of Nicosia Nicosia Cyprus

ISBN: (纸本)9783030909659

Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have attempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment. © 2021, Springer Nature Switzerland AG.

关键词： Augmented reality

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：