检索结果-内蒙古大学图书馆

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Omar Khan Zaid Ahmed Hyeongil Nam Kangsoo Kim Department of Computer Science University of Calgary Department of Electrical and Software Engineering University of Calgary

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

The increasing prevalence of Extended Reality (XR) and head-mounted displays (HMDs), alongside rapid advancements in 3D reality capture technology, unlocks a new paradigm for capturing and reliving past memories/experiences through XR. Current methods for accessing and interacting with these "XR Memories" still lack the ability to fully leverage the range of capabilities afforded by XR and HMDs. We introduce TangibleMoments, a novel framework that enables users to embed XR memories onto physical objects, transforming those objects into "Moments"—tangible user interfaces for accessing and interacting with XR memories. We describe and illustrate five interaction methods as part of this framework: Creating Moments, Recalling Moments, Sharing Moments, Copying Moments, and Clearing Moments. We showcase an initial prototype and discuss possible extensions.

关键词： Three-dimensional displays Head-mounted displays Extended reality Conferences Prototypes Mixed reality User interfaces Cultural differences Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Capturing Temporal Components for Time Series Classification 27th

Capturing Temporal Components for Time Series Classificatio...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Vavilthota, Venkata Ragavendra Ramanathan, Ranjith Aakur, Sathyanarayanan N. Department of Computer Science Oklahoma State University StillwaterOK74078 United States Department of Animal and Food Sciences Oklahoma State University StillwaterOK74078 United States Department of Computer Science and Software Engineering Auburn University Auburn36849 United States

ISBN: (纸本)9783031781063

Analyzing sequential data is crucial in many domains, particularly due to the abundance of data collected from the Internet of Things paradigm. Time series classification, the task of categorizing sequential data, has gained prominence, with machine learning approaches demonstrating remarkable performance on public benchmark datasets. However, progress has primarily been in designing architectures for learning representations from raw data at fixed (or ideal) time scales, which can fail to generalize to longer sequences. This work introduces a compositional representation learning approach trained on statistically coherent components extracted from sequential data. Based on a multi-scale change space, an unsupervised approach is proposed to segment the sequential data into chunks with similar statistical properties. A sequence-based encoder model is trained in a multi-task setting to learn compositional representations from these temporal components for time series classification. We demonstrate its effectiveness through extensive experiments on publicly available time series classification benchmarks. Evaluating the coherence of segmented components shows its competitive performance on the unsupervised segmentation task. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Collaborative Filtering-Based Recommender System for Ethiopian Tourism Sites 11th

Collaborative Filtering-Based Recommender System for Ethiopi...

引用

11th EAI International Conference on Advancement of Science and Technology, ICAST 2023

作者： Assefa, Yibeltal Meshesha, Million Nibret, Shegaw Gedif, Birku Software Engineering Wollo University Kombolcha Ethiopia Computer Science Addis Ababa University Addis Ababa Ethiopia Information Science NGO Bahir Dar Ethiopia Information Science University of Gondar Gondar Ethiopia

ISBN: (纸本)9783031641503

Tourism is a significant source of income for countries and regions, and with the advancement of technology, everything is now interconnected, generating massive amounts of data. Recommender systems are one way to utilize this generated big data. However, currently, Ethiopian Tourism Institutions do not have a system to manage tourist sites, analyze customer preferences and behavior, or filter based on their interests. Therefore, the purpose of this research is to develop a collaborative-based recommender system for Ethiopian tourism sites. This study applies both user-based collaborative filtering using a cosine similarity algorithm and model-based collaborative filtering using singular value decomposition (SVD), nonnegative matrix factorization(NMF), and K-nearest neighbors (KNNBasic) to analyze the data collected from the Amhara tourism office, which describes the Ethiopian tourism site. After the analysis, the results show that cosine similarity has the lowest root mean square error (RMSE) score. The methodology followed in this research is the design science approach, and the artifact recommender system is developed using the flask framework. After demonstrating the recommender system, domain experts evaluate it, achieving a promising result of 84.2%. The scarcity of data is a significant challenge, and thus, limited attributes for clustering are selected. Using more attributes to make the similarity of tourists will improve the development of the tourist site recommender system, which is left for future researchers to consider. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Two dimensional DOA estimation of coherent signals based on covariance matrix element transformation 24

Two dimensional DOA estimation of coherent signals based on ...

引用

8th International Conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Qu, Zhiyu Wu, Xu Geng, Zhenya College of Information Science and Engineering Hohai University Jiangsu Nanjing China College of Computer Science and Software Engineering Hohai University Jiangsu Nanjing China The 49th Research Institute of China Electronics Technology Group Corporation Heilongjiang Harbin China

ISBN: (纸本)9798400710094

Traditional Direction of Arrival (DOA) estimation algorithms for coherent signals in uniform circular array (UCA), such as mode space transformation, allow for the adaptation of advanced algorithms initially developed for uniform linear arrays to be applied effectively in UCA. However, after mode space transformation, the array will encounter aperture loss and will also be unable to perform two-dimensional DOA estimation effectively. In this paper, we propose a new method that that integrates covariance matrix element transformation with the Multiple Signal Classification (MUSIC) to estimate the DOA of coherent signals in various symmetric antenna arrays, including UCA. The algorithm leverages the phase difference symmetry of the antenna array to decorrelate the incoming signals, effectively restoring the full rank of the covariance matrix. Subsequently, it employs two-dimensional MUSIC for DOA estimation. Simulation results demonstrate the effectiveness of the proposed algorithm. © 2024 Copyright held by the owner/author(s).

关键词： Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

EPipe: Pipeline Inference Framework with High-quality Offline Parallelism Planning for Heterogeneous Edge Devices 24

EPipe: Pipeline Inference Framework with High-quality Offlin...

引用

43rd International Conference on computer-Aided Design, ICCAD 2024

作者： Xiong, Yi Liu, Weihong Zhang, Rui Zu, Yulong Zhu, Zongwei Zhou, Xuehai School of Computer Science and Technology University of Science and Technology of China China Suzhou Institute for Advanced Research University of Science and Technology of China China School of Software Engineering University of Science and Technology of China China

ISBN: (纸本)9798400710773

Pipeline parallelism is essential for edge computing as it effectively consolidates the limited resources of edge devices, enabling the deployment of large Deep Neural Network (DNN) models and accelerating inference processes without compromising the performance of models. Accurate computation and communication latency estimation on heterogeneous edge devices is essential for searching for a superior parallelism plan. However, existing heterogeneous pipeline inference approaches either incur substantial resource wastage during online parallelism planning, as they utilize profiling strategies that occupy physical devices;or rely on cost models with inadequate representational capabilities, leading to inaccurate predictions, thereby harming the result of pipeline planning. This paper proposes EPipe, a novel pipeline inference framework that supports high-quality offline planning in heterogeneous edge environments. EPipe integrates two core components: the Task-Device Co-analyzer (TDC) and the Multi-pipeline Parallelism Planner (MPP). TDC utilizes an undirected connected graph to depict the compatibility of DNNs across device groups and precisely estimates inference and communication latencies through fine-grained modeling. Based on TDC, MPP utilizes a dynamic programming-based genetic algorithm to explore multi-pipeline solutions, extending beyond traditional single-pipeline methods. A comprehensive experimental evaluation on an edge testbed confirms the effectiveness of EPipe, demonstrating significant speedups in inference tasks for both task streams and single tasks. © 2024 Copyright is held by the owner/author(s).

关键词： Edge detection

来源：评论

学校读者我要写书评

暂无评论

Investigating Visual Guide Cues in VR: Impacts of Virtual Humans and Symbol-Based Navigation on Real-World Performance and Experience

Investigating Visual Guide Cues in VR: Impacts of Virtual Hu...

引用

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Omar Khan Anh Nguyen Hyeongil Nam Kangsoo Kim Department of Computer Science University of Calgary Department of Electrical and Software Engineering University of Calgary

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Virtual experiences can significantly influence our perception and behavior in the real world, shaping how we interact with and navigate physical environments. In this paper, we examine the impact of learning navigation routes in an immersive virtual environment (IVE) on navigation performance and user experience in a corresponding real-world indoor setting. We developed a guide system with two distinct audiovisual representations: a human agent guide and a symbol-based guide. A preliminary user study (N = 10) was conducted to evaluate the system. While no significant differences were observed between the two guide conditions, the findings reveal valuable insights into user-perceived confidence and enjoyment during real-world navigation tasks. Contrary to our expectations, the symbol-based guide elicited slightly higher positive scores compared to the human agent guide. We discuss these findings and outline directions for future research.

关键词： Visualization Three-dimensional displays Navigation Conferences Virtual environments User interfaces User experience

来源：评论

学校读者我要写书评

暂无评论

Automatic Repeat Request Design in AoI-Aware Broadcast With Heterogeneous Direct and Relay-Assisted Users

引用

IEEE Internet of Things Journal 2025年

作者： Wang, Xueer Pan, Haoyuan Chan, Tse-Tin Li, Jianqiang Shenzhen University College of Computer Science and Software Engineering Shenzhen China The Education University of Hong Kong Department of Mathematics and Information Technology Hong Kong Shenzhen University National Engineering Laboratory for Big Data System Computing Technology The College of Computer Science and Software Engineering Shenzhen China

This paper investigates the design of automatic repeat request (ARQ) protocols in age of information (AoI)-aware broadcast systems with heterogeneous users, including both direct and relay-assisted users. In this setup, a direct user receives status updates directly via a single-hop link, while a relay-assisted user can receive status updates through either a direct single-hop link or a two-hop relay-assisted link. While ARQ is commonly used to ensure reliable transmission in error-prone wireless networks, previous studies suggest that ARQ does not improve the average AoI in single-hop networks. However, its impact on AoI in systems with relays, particularly those involving heterogeneous users, remains unclear. We address this gap by analyzing the average AoI under different ARQ strategies, introducing a transmission limit k ≥ 0 at the relay. Here, k = 0, k = 1, and k > 1 correspond to non-relay, non-ARQ-at-relay, and truncated-ARQ-at-relay strategies, respectively. Utilizing a unified Markov chain framework that models the transmission processes for each user type, we derive the theoretical average AoI. Our results show that the direct user benefits most from non-relay and non-ARQ strategies, similar to single-hop systems. In contrast, the relay-assisted user achieves optimal performance with truncated-ARQ-at-relay, leveraging both direct and relay-assisted links. For the overall system, applying a non-ARQ-at-relay approach strikes a balance in AoI between the direct and relay-assisted users, leading to a more stable and lower system-wide average AoI. © 2014 IEEE.

关键词： Mobile telecommunication systems

来源：评论

学校读者我要写书评

暂无评论

Exploration of software Field Engineer Training Based on AI+Capability Model 24

Exploration of Software Field Engineer Training Based on AI+...

引用

2nd International Conference on Advances in Artificial Intelligence and Applications, AAIA 2024

作者： Zhou, Junjie Wu, Qian School of Information Wuhan Software Engineering Vocational College Wuhan Open University Hubei Wuhan China School of Computer Science Wuhan University Hubei Wuhan China Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts Wuhan China

ISBN: (纸本)9798400712883

With the rapid development of artificial intelligence technology, its application in the field of education and teaching is becoming increasingly widespread, bringing revolutionary changes to traditional education models. To cultivate high-quality software vocational skills talents, a digital management platform based on AI+capability model is constructed to explore the innovative application of artificial intelligence in education and teaching, realizing intelligent auxiliary learning functions such as personalized resource recommendation, student growth monitoring, and achievement label portrait. At the same time, a series of intelligent teaching tools such as"AI+Code Generation, AI+Inspection Assistant, AI+Process Map" will be developed to explore and promote the vertical application of big models in talent cultivation. Through innovative models such as"introducing enterprises into education, cultivating students through real-life situations, AI+empowerment, teaching according to students’ aptitude, trinity, innovative training, strengthening processes, and diverse evaluations", it has been fully applied to the talent training scene of software technology field engineers, and its teaching effectiveness is significant. © 2024 Copyright held by the owner/author(s).

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

An Improved LVSL with View Consensus 25

An Improved LVSL with View Consensus

引用

Proceedings of the 2025 5th International Conference on Bioinformatics and Intelligent Computing

作者： Yuting Xu Qing Ai Bo Cui School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China

ISBN: (纸本)9798400712203

In multi-view multi-label learning (MVML), each sample can be represented by multiple view features and associated with multiple labels. Most existing MVML algorithms are based on the assumption that all views share the same label set. However, in practice, different views may contain distinct label information, that means a single view cannot fully represent all labels. Based on this issue, the LVSL algorithm effectively learns view-specific labels and obtains superior classification performance. However, LVSL still has the limitation that it fails to consider the correlations between views, leading to suboptimal learning results. In this paper, we propose an improved LVSL algorithm named LVSL_VC (LVSL with view consensus). We incorporate view consensus learning into the original LVSL framework. Firstly, we employ view weights to model view consensus, assuming that views with similar weights will yield similar prediction outputs, conversely, they will be different. Secondly, we integrate the view consensus into the LVSL framework and construct a new classification model. Finally, we utilize an alternating optimization method to solve the problem. Extensive experimental results demonstrate that the LVSL_VC outperforms other state-of-the-art MVML algorithms.

关键词： Multi-view multi-label learning

来源：评论

学校读者我要写书评

暂无评论

Functional Modelling of the Matroid and Application to the Knapsack Problem 1st

Functional Modelling of the Matroid and Application to t...

引用

1st International Symposium on software Fault Prevention, Verification, and Validation, SFPVV 2024

作者： Wan, Zikang You, Zhen Zhang, Chen Zuo, Zhengkang Wang, Changjing Hu, Qimin State International S&T Cooperation Base of Networked Supporting Software Jiangxi Normal University Nanchang330022 China Computer Information Engineering School Jiangxi Normal University Nanchang330022 China

ISBN: (纸本)9789819616206

The matroids have a wide range of applications in discrete mathematics, combinatorial mathematics, computer science and other fields. However, most of the researches about matroids focus on the mathematical level, and there is a lack of exploration on functional modelling and formal verification. In this paper, we propose a general functional modeling framework for matroids, which consists of the basic elements of matroids, the verification functions of basic properties, and the verification functions of matroids. Finally, the functional modeling framework of this paper is used to verify whether the 0-1 knapsack problem and the fractional knapsack problem conform to the matroid structure, thus exemplifying the correctness of the matroid functional modeling and the matroid verification function, and reflecting the validity and extensibility of this framework. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Combinatorial mathematics

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：