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

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

"I look like a gorilla, but don’t move like one!": Impact of Avatar-Locomotion Congruence in Virtual Reality

"I look like a gorilla, but don’t move like one!": Impact o...

引用

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

作者： Omar Khan 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

As virtual reality (VR) continues to expand, particularly in social VR platforms and immersive gaming, understanding the factors that shape user experience is becoming increasingly important. Avatars and locomotion methods play central roles in influencing how users identify with their virtual representations and navigate virtual spaces. However, little is known about the impact of congruence between these two factors. We conducted a user study with 30 participants, employing two avatar types (human and gorilla) and two locomotion methods (human-like arm-swing and gorilla-like arm-roll), to assess the effects of avatar-locomotion congruence. Our results indicate that congruent avatar-locomotion conditions enhance avatar identification and user experience.

关键词： Three-dimensional displays Shape Navigation Avatars Conferences User interfaces User experience Usability

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of COVID-19 Using Deep Convolutional Neural Network (CNNs) Using Chest Radiograph and CT Scan Images 1st

Automated Detection of COVID-19 Using Deep Convolutional Neu...

引用

1st International Conference on Computing and Emerging Technologies, ICCET 2023

作者： Uallah, Naeem Khan, Javed Ali Raza, Asaf Shah, Syed Yaqub Assam, Muhammad Arshad, Hasna Department of Software Engineering University of Engineering and Technology Taxila Taxila Pakistan Department of Software Engineering University of Science and Technology Bannu Bannu Pakistan Department of Computer Science HITEC University Taxila Pakistan

ISBN: (纸本)9783031776199

Many countries are severely affected by COVID-19, and massive efforts are required to mitigate the terrible impacts of the COVID-19 global epidemic. To stop COVID-19 from spreading widely and minimize COVID-19 patient treatment issues, early discovery of the virus in its early stages is essential. Conventional methods for COVID-19 detection are time-consuming, cumbersome, unreliable, and yield an incorrect diagnosis. Most deep learning (DL) methods for COVID-19 identification described in the past only support one data type (chest radiographs or CT scan images). Examining unusual patterns in various data types may yield high classification performance. For this purpose, we use two image datasets: chest radiographs and chest computer tomography (CT). This research study proposed an excellent COVID-19 detection strategy based on the Resnet-18 deep convolutional neural network (CNN) to timely and efficiently identify COVID-19 spread. Also, we used each image data type to conduct extensive Covid-19 detection experiments with the proposed DL model. We performed a trinary classification task (normal, covid-19, and pneumonia) using chest radiographs and a binary classification (COVID-19 and Normal) using CT scan images. We validated the performance of the proposed approach on two standard Kaggle datasets, i.e., the COVID-19 Radiography Database and the SARS-CoV-2 CT scan dataset. The Resnet model's detection accuracy of 99.42% using chest radiographs (CRs) and 100% using CT scans for COVID-19 detection indicates its efficacy in detecting COVID-19. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Intelligent Spatial Anomaly Activity Recognition Method Based on Ontology Matching

引用

computers, Materials and Continua 2025年第3期83卷 4447-4476页

作者： Longgang Zhao Seok-Won Lee The Knowledge-intensive Software Engineering (NiSE) Research Group Department of Artificial Intelligence Ajou University Suwon City 16499 Republic of Korea Department of Software and Computer Engineering Ajou University Suwon City 16499 Republic of Korea

This research addresses the performance challenges of ontology-based context-aware and activity recognition techniques in complex environments and abnormal activities, and proposes an optimized ontology framework to improve recognition accuracy and computational efficiency. The method in this paper adopts the event sequence segmentation technique, combines location awareness with time interval reasoning, and improves human activity recognition through ontology reasoning. Compared with the existing methods, the framework performs better when dealing with uncertain data and complex scenes, and the experimental results show that its recognition accuracy is improved by 15.6% and processing time is reduced by 22.4%. In addition, it is found that with the increase of context complexity, the traditional ontology inference model has limitations in abnormal behavior recognition, especially in the case of high data redundancy, which tends to lead to a decrease in recognition accuracy. This study effectively mitigates this problem by optimizing the ontology matching algorithm and combining parallel computing and deep learning techniques to enhance the activity recognition capability in complex environments.

关键词： Context awareness activity recognition ontological reasoning complex context anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Critical Role of Individual Cell Temperature Monitoring in Mitigating Thermal Runaway and Reducing Accelerated Degradation in Lithium-Ion Batteries

Critical Role of Individual Cell Temperature Monitoring in M...

引用

Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Mohit Sharma Akash Samanta William Locke Sheldon Williamson Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

Thermal runaway in lithium-ion batteries (LIBs) is a critical risk, potentially leading to fires and explosions. This phenomenon can be triggered by overcharging, short-circuiting, physical damage, manufacturing defects, and overheating. Effective mitigation of thermal runaway relies on precise and close monitoring of individual cells within the battery pack, a task often complicated by the complexity and cost of implementing temperature sensors on each cell in automotive applications. This study demonstrates the importance of individual cell temperature monitoring by intentionally including an unhealthy cell (C#12) in a 14-cell LIB 21700 module equipped with an automotive-grade battery management system (BMS) from NXP®. Experimental results reveal that despite efficient BMS balancing, the weak cell exhibited a significantly higher temperature rise, with a final temperature difference of 6°C and a voltage difference of over 200 mV compared to healthy cells. These findings underscore the potential for thermal failure and runaway if individual cell temperatures are not closely monitored. Additionally, reliance on voltage-based control alone can lead to suboptimal battery pack utilization, as evidenced by a 5% capacity loss due to the weak cell. This research highlights the necessity of monitoring the temperature of each cell to prevent thermal runaway and ensure efficient battery performance.

关键词： Temperature measurement Temperature sensors Lithium-ion batteries Degradation Accuracy Automotive applications Battery management systems Voltage control Monitoring Thermal degradation

来源：评论

学校读者我要写书评

暂无评论

A Predictive Model for Early Effort Estimation of Mobile Games

A Predictive Model for Early Effort Estimation of Mobile Gam...

引用

International Conference on Advancements in Computational Sciences (ICACS)

作者： Ahrar Javed Ali Afzal Malik Department of Software Engineering National University of Computer and Emerging Sciences Lahore Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

Mobile games are a popular, cheap, and convenient source of entertainment. However, the increasing complexity of these games is making it more difficult to thoroughly plan, monitor, and control mobile game development projects. Possessing the ability to accurately estimate the development effort for these projects early in their life cycle is expected to make the jobs of their managers much easier. The objective of this study was to build a calibrated and validated early effort prediction model for mobile games developed using the Unity game engine. First, we identified factors that potentially influence development effort in these projects by conducting an industrial survey. Once these factors were identified, we gathered information about these factors and actual development effort for more than 100 real mobile games developed by different game studios. Then, we performed a simple linear regression (SLR) analysis to rank these factors with respect to their individual influence on mobile game development effort. Finally, we used the games data collected earlier to build, assess, and validate a forward step-wise multiple linear regression (FSMLR)-based model for early effort prediction of such mobile games. The MMRE value of this model is 0.136 and its PRED (25) value is $85.98 \%$. These values indicate that this model has reasonably good estimation accuracy. It can be a useful tool in the arsenal of managers interested in effectively planning their mobile game development projects early in the life cycle.

关键词： Surveys Accuracy Linear regression Estimation Entertainment industry Games Predictive models Planning Monitoring Land mobile radio

来源：评论

学校读者我要写书评

暂无评论

An Experimental Study on Dynamic Lifelong Learning with GPT for Mitigating Catastrophic Forgetting in Aspect-Based Sentiment Analysis

引用

IEEE Access 2025年 13卷 90316-90332页

作者： Huang, Huang Asemi, Adeleh Universiti Malaya Faculty of Computer Science Information Technology Department of Software Engineering Kuala Lumpur Malaysia

GPT is widely recognized as one of the most versatile and powerful large language models, excelling across diverse domains. However, its significant computational demands often render it economically unfeasible for individuals and small businesses, underscoring the need for efficient, domainspecific alternatives. In Aspect-Based Sentiment Analysis (ABSA), existing models are typically optimized for single domains, facing challenges in performing effectively across multiple domains. A key issue, known as "catastrophic forgetting," arises when models trained on one domain lose previously learned knowledge upon exposure to new domain data. This leads to two significant problems: limited cross-domain generalization and difficulty in retaining prior knowledge while learning domain-specific information. To address these challenges, we introduce the Dynamic Lifelong Learning Aspect-Based Sentiment Analysis GPT (DllaGPT), a model designed to handle multiple domains while mitigating catastrophic forgetting. Leveraging datasets from four ABSA domains—Laptops, Restaurants, Tweets, and Finance—this study fine-tunes a pretrained GPT model from HuggingFace sequentially across domains. DllaGPT employs a mechanism to retain real data from earlier domains during new domain training, effectively preserving prior knowledge. Experimental results highlight that DllaGPT achieves an average accuracy of 0.85 and a Backward Transfer (BWT) score of -0.09 across the four domains, showcasing its high accuracy and robust lifelong learning capabilities. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

PoolKANNeXt: A new pooling-based Kolmogorov Arnold convolutional neural network

引用

Alexandria engineering Journal 2025年 128卷 144-152页

作者： Fangxing Lv Qing Wei Yuwen Huang Turker Tuncer Sengul Dogan Fatih Özyurt School of Computer Heze University Heze 274015 China Department of Digital Forensics Engineering Technology Faculty Firat University Elazig Turkey Department of Software Engineering Engineering Faculty Firat University Elazig Turkey

The Kolmogorov–Arnold Network (KAN) is a new-generation neural network. It provides an alternative to multilayer perceptrons (MLPs). PoolFormer showed that pooling alone can mix features efficiently. We propose PoolKANNeXt, a CNN that merges the KAN structure with pooling-based feature mixing. This design targets high accuracy with a low number of the learnable parameters. We evaluated PoolKANNeXt on six image datasets, five biomedical and one general (CIFAR-10). The model comprises four stages. In the stem stage, a ConvNeXt-style patchify block converts each 224 × 224 × 3 image into a 56 × 56 × 96 tensor. In the main stage, average pooling first mixes local features; then two parallel 3 × 3 convolutions—one followed by GELU and the other by Swish—extract complementary representations, and a 1 × 1 convolution scales the combined output and adds it back to the input via a residual connection. In the downsampling stage, strided 3 × 3 convolutions halve spatial dimensions and double the channel count. In the output stage, global average pooling produces a feature vector that feeds into a softmax classifier. PoolKANNeXt achieved over 90 % accuracy on all datasets and reached 99.43 % on CIFAR-10, ranking among the top five models on that benchmark. PoolKANNeXt offers a lightweight yet powerful architecture. Its innovative combination of pooling and dual-activation KAN blocks yields strong performance across diverse tasks. The design is scalable and adaptable to larger or more complex datasets.

关键词： PoolKANNeXt Kolmogorov Arnold Network CNN computer Vision Image classification

来源：评论

学校读者我要写书评

暂无评论

Trauma-Informed Insights from Co-Design of Self-Disclosure Robots with Domestic Abuse Survivors 20

Trauma-Informed Insights from Co-Design of Self-Disclosure R...

引用

20th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2025

作者： Morris, Nyomi Carrine Williams, Tom Jelen, Ben Colorado School of Mines MIRRORLab GoldenCO United States Rose-Hulman Institute of Technology Department of Computer Science and Software Engineering Terre HauteIN United States

ISBN: (纸本)9798350378931

Survivors of domestic abuse face significant challenges securing recovery resources, such as housing, mental health care, and social connections. Accessing these resources requires survivors to disclose their status as survivors of domestic abuse;a process that can be traumatic and emotionally burdensome. In this work, we consider how social robots might help domestic abuse survivors to address challenges surrounding self-disclosure. To do so, we conducted a three-session co-design workshop involving 8 participants from a domestic abuse shelter. Our results provide three key contributions: (1) new insights into the benefits and barriers to self-disclosure;(2) new insights into the ways that social robots can help survivors to better achieve those benefits and overcome those barriers before, during, and after disclosure, including key design recommendations associated with each of these phases;and (3) observations into how a trauma-informed computing perspective may enable more effective design work in Human-Robot Interaction. © 2025 IEEE.

关键词： Social robots

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：