@article{
 title = {Using a virtual reality interview simulator to explore factors influencing people’s behavior},
 type = {article},
 year = {2024},
 pages = {56},
 volume = {28},
 websites = {https://link.springer.com/10.1007/s10055-023-00934-5},
 month = {3},
 day = {28},
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 abstract = {Virtual reality interview simulator (VRIS) is an effective and valid tool that uses virtual reality technology to train people’s interview skills. Typically, it offers candidates prone to being very nervous during interviews the opportunity to practice interviews in a safe and manageable virtual environment and realistic settings, providing real-time feedback from a virtual interviewer on their performance. It helps interviewees improve their skills, reduce their fears, gain confidence, and minimize the cost and time associated with traditional interview preparation. Yet, the major anxiety-inducing elements remain unknown. During an interview, the anxiety levels, overall experience, and performance of interviewees might be affected by various circumstances. By analyzing electrodermal activity and questionnaire, we investigated the influence of five variables: (I) Realism ; (II) Question type ; (III) Interviewer attitude ; (IV) Timing ; and (V) Preparation . As such, an orthogonal design $$L_8(4^1 \times 2^4)$$ L 8 ( 4 1 × 2 4 ) with eight experiments ( $$O A_8$$ O A 8 matrix) was implemented, in which 19 college students took part in the experiments. Considering the anxiety, overall experience, and performance of the interviewees, we found that Question type plays a major role; secondly, Realism , Preparation , and Interviewer attitude all have middle influence; lastly, Timing has little to no impact. Specifically, professional interview questions elicited a greater degree of anxiety than personal ones among the categories of interview questions. This work contributes to our understanding of anxiety-stimulating factors during job interviews in virtual reality and provides cues for designing future VRIS.},
 bibtype = {article},
 author = {Luo, Xinyi and Wang, Yuyang and Lee, Lik-Hang and Xing, Zihan and Jin, Shan and Dong, Boya and Hu, Yuanyi and Chen, Zeming and Yan, Jing and Hui, Pan},
 doi = {10.1007/s10055-023-00934-5},
 journal = {Virtual Reality},
 number = {1}
}

Virtual reality interview simulator (VRIS) is an effective and valid tool that uses virtual reality technology to train people’s interview skills. Typically, it offers candidates prone to being very nervous during interviews the opportunity to practice interviews in a safe and manageable virtual environment and realistic settings, providing real-time feedback from a virtual interviewer on their performance. It helps interviewees improve their skills, reduce their fears, gain confidence, and minimize the cost and time associated with traditional interview preparation. Yet, the major anxiety-inducing elements remain unknown. During an interview, the anxiety levels, overall experience, and performance of interviewees might be affected by various circumstances. By analyzing electrodermal activity and questionnaire, we investigated the influence of five variables: (I) Realism ; (II) Question type ; (III) Interviewer attitude ; (IV) Timing ; and (V) Preparation . As such, an orthogonal design $$L_8(4^1 \times 2^4)$$ L 8 ( 4 1 × 2 4 ) with eight experiments ( $$O A_8$$ O A 8 matrix) was implemented, in which 19 college students took part in the experiments. Considering the anxiety, overall experience, and performance of the interviewees, we found that Question type plays a major role; secondly, Realism , Preparation , and Interviewer attitude all have middle influence; lastly, Timing has little to no impact. Specifically, professional interview questions elicited a greater degree of anxiety than personal ones among the categories of interview questions. This work contributes to our understanding of anxiety-stimulating factors during job interviews in virtual reality and provides cues for designing future VRIS.

@inbook{
 type = {inbook},
 year = {2024},
 pages = {325-346},
 websites = {https://link.springer.com/10.1007/978-981-99-8141-0_25},
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 author = {Wang, Yuyang and Chardonnet, Jean-Rémy and Merienne, Frédéric},
 doi = {10.1007/978-981-99-8141-0_25},
 chapter = {Modeling Online Adaptive Navigation in Virtual Environments Based on PID Control}
}

@inproceedings{
 title = {Text2VRScene: Exploring the Framework of Automated Text-driven Generation System for VR Experience},
 type = {inproceedings},
 year = {2024},
 keywords = {Index Terms},
 pages = {701-711},
 websites = {https://github.com/Williamy946/Text2VRScene,https://ieeexplore.ieee.org/document/10494137/},
 month = {3},
 publisher = {IEEE},
 day = {16},
 id = {48697da0-ede0-34a2-b461-85fe47498a5f},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
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 abstract = {With the recent development of the Virtual Reality (VR) industry, the increasing number of VR users pushes the demand for the massive production of immersive and expressive VR scenes in related industries. However, creating expressive VR scenes involves the reasonable organization of various digital content to express a coherent and logical theme, which is time-consuming and labor-intensive. In recent years, Large Language Models (LLMs) such as ChatGPT 3.5 and generative models such as stable diffusion have emerged as powerful tools for comprehending natural language and generating digital contents such as text, code, images, and 3D objects. In this paper, we have explored how we can generate VR scenes from text by incorporating LLMs and various generative models into an automated system. To achieve this, we first identify the possible limitations of LLMs for an automated system and propose a systematic framework to mitigate them. Subsequently, we developed Text2VRScene, a VR scene generation system, based on our proposed framework with well-designed prompts. To validate the effectiveness of our proposed framework and the designed prompts, we carry out a series of test cases. The results show that the proposed framework contributes to improving the reliability of the system and the quality of the generated VR scenes. The results also illustrate the promising performance of the Text2VRScene in generating satisfying VR scenes with a clear theme regularized by our well-designed prompts. This paper ends with a discussion about the limitations of the current system and the potential of developing similar generation systems based on our framework.},
 bibtype = {inproceedings},
 author = {Yin, Zhizhuo and Wang, Yuyang and Papatheodorou, Theodoros and Hui, Pan},
 doi = {10.1109/VR58804.2024.00090},
 booktitle = {2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)}
}

With the recent development of the Virtual Reality (VR) industry, the increasing number of VR users pushes the demand for the massive production of immersive and expressive VR scenes in related industries. However, creating expressive VR scenes involves the reasonable organization of various digital content to express a coherent and logical theme, which is time-consuming and labor-intensive. In recent years, Large Language Models (LLMs) such as ChatGPT 3.5 and generative models such as stable diffusion have emerged as powerful tools for comprehending natural language and generating digital contents such as text, code, images, and 3D objects. In this paper, we have explored how we can generate VR scenes from text by incorporating LLMs and various generative models into an automated system. To achieve this, we first identify the possible limitations of LLMs for an automated system and propose a systematic framework to mitigate them. Subsequently, we developed Text2VRScene, a VR scene generation system, based on our proposed framework with well-designed prompts. To validate the effectiveness of our proposed framework and the designed prompts, we carry out a series of test cases. The results show that the proposed framework contributes to improving the reliability of the system and the quality of the generated VR scenes. The results also illustrate the promising performance of the Text2VRScene in generating satisfying VR scenes with a clear theme regularized by our well-designed prompts. This paper ends with a discussion about the limitations of the current system and the potential of developing similar generation systems based on our framework.

@inproceedings{
 title = {Jump Cut Effects in Cinematic Virtual Reality: Editing with the 30-degree Rule and 180-degree Rule},
 type = {inproceedings},
 year = {2024},
 pages = {51-60},
 websites = {https://ieeexplore.ieee.org/document/10494084/},
 month = {3},
 publisher = {IEEE},
 day = {16},
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 author = {Zhang, Junjie and Lee, Lik-hang and Wang, Yuyang and Jin, Shan and Fei, Dan-Lu and Hui, Pan},
 doi = {10.1109/VR58804.2024.00029},
 booktitle = {2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)}
}

@article{
 title = {Dataset for predicting cybersickness from a virtual navigation task},
 type = {article},
 year = {2023},
 websites = {http://arxiv.org/abs/2303.13527},
 month = {2},
 day = {6},
 id = {4b260738-6e30-3ea6-afdc-4971ce6e330d},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
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 abstract = {This work presents a dataset collected to predict cybersickness in virtual reality environments. The data was collected from navigation tasks in a virtual environment designed to induce cybersickness. The dataset consists of many data points collected from diverse participants, including physiological responses (EDA and Heart Rate) and self-reported cybersickness symptoms. The paper will provide a detailed description of the dataset, including the arranged navigation task, the data collection procedures, and the data format. The dataset will serve as a valuable resource for researchers to develop and evaluate predictive models for cybersickness and will facilitate more research in cybersickness mitigation.},
 bibtype = {article},
 author = {Wang, Yuyang and Li, Ruichen and Chardonnet, Jean-Rémy and Hui, Pan}
}

This work presents a dataset collected to predict cybersickness in virtual reality environments. The data was collected from navigation tasks in a virtual environment designed to induce cybersickness. The dataset consists of many data points collected from diverse participants, including physiological responses (EDA and Heart Rate) and self-reported cybersickness symptoms. The paper will provide a detailed description of the dataset, including the arranged navigation task, the data collection procedures, and the data format. The dataset will serve as a valuable resource for researchers to develop and evaluate predictive models for cybersickness and will facilitate more research in cybersickness mitigation.

@inproceedings{
 title = {ARCam: A User-Defined Camera for AR Photographic Art Creation},
 type = {inproceedings},
 year = {2023},
 pages = {999-1000},
 websites = {https://ieeexplore.ieee.org/document/10108810/},
 month = {3},
 publisher = {IEEE},
 id = {2d35d885-509b-3265-9595-5e1b682d4df8},
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 bibtype = {inproceedings},
 author = {Luo, Xinyi and Zhu, Zihao and Wang, Yuyang and Hui, Pan},
 doi = {10.1109/VRW58643.2023.00342},
 booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@inproceedings{
 title = {An immersive simulator for improving chemistry learning efficiency},
 type = {inproceedings},
 year = {2023},
 pages = {841-842},
 websites = {https://ieeexplore.ieee.org/document/10108889/},
 month = {3},
 publisher = {IEEE},
 id = {b4a20964-b3e8-36bc-ae6c-2cd8f167ba94},
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 author = {Shan, Jin and Wang, Yuyang and Lee, Lik-Hang and Wang, Xian and Chen, Zeming and Dong, Boya and Luo, Xinyi and Hui, Pan},
 doi = {10.1109/VRW58643.2023.00263},
 booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@inproceedings{
 title = {Development and penta-metric evaluation of a virtual interview simulator},
 type = {inproceedings},
 year = {2023},
 pages = {917-918},
 websites = {https://ieeexplore.ieee.org/document/10108628/},
 month = {3},
 publisher = {IEEE},
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 bibtype = {inproceedings},
 author = {Luo, Xinyi and Wang, Yuyang and Lee, Lik-Hang and Xing, Zihan and Jin, Shan and Dong, Boya and Hu, Yuanyi and Chen, Zeming and Yan, Jing and Hui, Pan},
 doi = {10.1109/VRW58643.2023.00301},
 booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@inproceedings{
 title = {VR/AR/MR in the Electricity Industry: Concepts, Techniques, and Applications},
 type = {inproceedings},
 year = {2023},
 pages = {82-88},
 websites = {https://ieeexplore.ieee.org/document/10108819/},
 month = {3},
 publisher = {IEEE},
 id = {0d7dec2b-26a3-3674-b9ec-cf87284da056},
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 authored = {true},
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 bibtype = {inproceedings},
 author = {Xiao, Jiakai and Qian, Yang and Du, Wei and Wang, Yuyang and Jiang, Yuanchun and Liu, Yezheng},
 doi = {10.1109/VRW58643.2023.00022},
 booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@inproceedings{
 title = {IEEE VR 2023 Workshop: Datasets for developing intelligent XR applications (DATA4XR)},
 type = {inproceedings},
 year = {2023},
 pages = {67-68},
 websites = {https://ieeexplore.ieee.org/document/10108730/},
 month = {3},
 publisher = {IEEE},
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 author = {Wang, Yuyang and Chardonnet, Jean-Rémy and Lee, Lik-Hang and Hui, Pan},
 doi = {10.1109/VRW58643.2023.00019},
 booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@article{
 title = {Efficient Task Offloading Algorithm for Digital Twin in Edge/Cloud Computing Environment},
 type = {article},
 year = {2023},
 websites = {http://arxiv.org/abs/2307.05888},
 month = {7},
 day = {11},
 id = {cbccb76f-5301-35e2-8700-3468e74c3821},
 created = {2023-08-10T12:19:58.134Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
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 abstract = {In the era of Internet of Things (IoT), Digital Twin (DT) is envisioned to empower various areas as a bridge between physical objects and the digital world. Through virtualization and simulation techniques, multiple functions can be achieved by leveraging computing resources. In this process, Mobile Cloud Computing (MCC) and Mobile Edge Computing (MEC) have become two of the key factors to achieve real-time feedback. However, current works only considered edge servers or cloud servers in the DT system models. Besides, The models ignore the DT with not only one data resource. In this paper, we propose a new DT system model considering a heterogeneous MEC/MCC environment. Each DT in the model is maintained in one of the servers via multiple data collection devices. The offloading decision-making problem is also considered and a new offloading scheme is proposed based on Distributed Deep Learning (DDL). Simulation results demonstrate that our proposed algorithm can effectively and efficiently decrease the system's average latency and energy consumption. Significant improvement is achieved compared with the baselines under the dynamic environment of DTs.},
 bibtype = {article},
 author = {Zhang, Ziru and Zhang, Xuling and Zhu, Guangzhi and Wang, Yuyang and Hui, Pan}
}

In the era of Internet of Things (IoT), Digital Twin (DT) is envisioned to empower various areas as a bridge between physical objects and the digital world. Through virtualization and simulation techniques, multiple functions can be achieved by leveraging computing resources. In this process, Mobile Cloud Computing (MCC) and Mobile Edge Computing (MEC) have become two of the key factors to achieve real-time feedback. However, current works only considered edge servers or cloud servers in the DT system models. Besides, The models ignore the DT with not only one data resource. In this paper, we propose a new DT system model considering a heterogeneous MEC/MCC environment. Each DT in the model is maintained in one of the servers via multiple data collection devices. The offloading decision-making problem is also considered and a new offloading scheme is proposed based on Distributed Deep Learning (DDL). Simulation results demonstrate that our proposed algorithm can effectively and efficiently decrease the system's average latency and energy consumption. Significant improvement is achieved compared with the baselines under the dynamic environment of DTs.

@inproceedings{
 title = {VR PreM+: An Immersive Pre-learning Branching Visualization System for Museum Tours},
 type = {inproceedings},
 year = {2023},
 pages = {374-385},
 websites = {https://dl.acm.org/doi/10.1145/3629606.3629643},
 month = {11},
 publisher = {ACM},
 day = {13},
 city = {New York, NY, USA},
 id = {fca92808-2073-3d2d-baac-61de1182f6e0},
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 bibtype = {inproceedings},
 author = {Gao, Ze and Li, Xiang and Liu, Changkun and Wang, Xian and Wang, Anqi and Yang, Liang and Wang, Yuyang and Hui, Pan and Braud, Tristan},
 doi = {10.1145/3629606.3629643},
 booktitle = {Proceedings of the Eleventh International Symposium of Chinese CHI}
}

@inproceedings{
 title = {A Deep Cybersickness Predictor through Kinematic Data with Encoded Physiological Representation},
 type = {inproceedings},
 year = {2023},
 keywords = {Cybersickness Prediction,Deep Neural Classifiers,Kinematic data,Physiological Representation,VR},
 pages = {1132-1141},
 websites = {https://ieeexplore.ieee.org/document/10316407/},
 month = {10},
 publisher = {IEEE},
 day = {16},
 id = {9a3113ac-8f48-34e9-beac-68808b90539c},
 created = {2024-03-05T07:53:31.355Z},
 file_attached = {true},
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 last_modified = {2024-03-05T07:53:35.628Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Users would experience individually different sickness symptoms during or after navigating through an immersive virtual environment, generally known as cybersickness. Previous studies have predicted the severity of cybersickness based on physiological and/or kinematic data. However, compared with kinematic data, physiological data rely heavily on biosensors during the collection, which is inconvenient and limited to a few affordable VR devices. In this work, we proposed a deep neural network to predict cybersickness through kinematic data. We introduced the encoded physiological representation to characterize the individual susceptibility; therefore, the predictor could predict cybersickness only based on a user's kinematic data without counting on biosensors. Fifty-three participants were recruited to attend the user study to collect multimodal data, including kinematic data (navigation speed, head tracking), physiological signals (e.g., electrodermal activity, heart rate), and Simulator Sickness Questionnaire (SSQ). The predictor achieved an accuracy of 97.8% for cybersickness prediction by involving the pre-computed physiological representation to characterize individual differences, providing much convenience for the current cybersickness measurement.},
 bibtype = {inproceedings},
 author = {Li, Ruichen and Wang, Yuyang and Yin, Handi and Chardonnet, Jean-Rémy and Hui, Pan},
 doi = {10.1109/ISMAR59233.2023.00130},
 booktitle = {2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}
}

Users would experience individually different sickness symptoms during or after navigating through an immersive virtual environment, generally known as cybersickness. Previous studies have predicted the severity of cybersickness based on physiological and/or kinematic data. However, compared with kinematic data, physiological data rely heavily on biosensors during the collection, which is inconvenient and limited to a few affordable VR devices. In this work, we proposed a deep neural network to predict cybersickness through kinematic data. We introduced the encoded physiological representation to characterize the individual susceptibility; therefore, the predictor could predict cybersickness only based on a user's kinematic data without counting on biosensors. Fifty-three participants were recruited to attend the user study to collect multimodal data, including kinematic data (navigation speed, head tracking), physiological signals (e.g., electrodermal activity, heart rate), and Simulator Sickness Questionnaire (SSQ). The predictor achieved an accuracy of 97.8% for cybersickness prediction by involving the pre-computed physiological representation to characterize individual differences, providing much convenience for the current cybersickness measurement.

@inproceedings{
 title = {Re-shaping Post-COVID-19 Teaching and Learning: A Blueprint of Virtual-Physical Blended Classrooms in the Metaverse Era},
 type = {inproceedings},
 year = {2022},
 pages = {241-247},
 websites = {http://arxiv.org/abs/2203.09228,https://ieeexplore.ieee.org/document/9951355/},
 month = {7},
 publisher = {IEEE},
 day = {17},
 id = {419c6903-244f-3cb2-ac74-ec43f747e988},
 created = {2022-03-19T11:01:03.156Z},
 file_attached = {true},
 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2023-01-13T06:12:06.889Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {During the COVID-19 pandemic, most countries have experienced some form of remote education through video conferencing software platforms. However, these software platforms fail to reduce immersion and replicate the classroom experience. The currently emerging Metaverse addresses many of such limitations by offering blended physical-digital environments. This paper aims to assess how the Metaverse can support and improve e-learning. We first survey the latest applications of blended environments in education and highlight the primary challenges and opportunities. Accordingly, we derive our proposal for a virtual-physical blended classroom configuration that brings students and teachers into a shared educational Metaverse. We focus on the system architecture of the Metaverse classroom to achieve real-time synchronization of a large number of participants and activities across physical (mixed reality classrooms) and virtual (remote VR platform) learning spaces. Our proposal attempts to transform the traditional physical classroom into virtual-physical cyberspace as a new social network of learners and educators connected at an unprecedented scale.},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Lee, Lik-Hang and Braud, Tristan and Hui, Pan},
 doi = {10.1109/ICDCSW56584.2022.00053},
 booktitle = {2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)}
}

During the COVID-19 pandemic, most countries have experienced some form of remote education through video conferencing software platforms. However, these software platforms fail to reduce immersion and replicate the classroom experience. The currently emerging Metaverse addresses many of such limitations by offering blended physical-digital environments. This paper aims to assess how the Metaverse can support and improve e-learning. We first survey the latest applications of blended environments in education and highlight the primary challenges and opportunities. Accordingly, we derive our proposal for a virtual-physical blended classroom configuration that brings students and teachers into a shared educational Metaverse. We focus on the system architecture of the Metaverse classroom to achieve real-time synchronization of a large number of participants and activities across physical (mixed reality classrooms) and virtual (remote VR platform) learning spaces. Our proposal attempts to transform the traditional physical classroom into virtual-physical cyberspace as a new social network of learners and educators connected at an unprecedented scale.

@article{
 title = {Identification of Key Features for VR Applications with VREVIEW : A Topic Model Approach},
 type = {article},
 year = {2022},
 keywords = {feature identification,hci,human computer,human-centered computing,index terms,interaction,interaction paradigms,topic model,user reviews,virtual reality,vr game},
 pages = {183-188},
 id = {3d05bf80-4715-3886-a601-d422cd068ecb},
 created = {2022-03-26T02:28:18.100Z},
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 authored = {true},
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 bibtype = {article},
 author = {Qian, Yang and Xiong, Yingqiu and Wang, Yuyang and Jiang, Yuanchun and Liu, Yezheng and Chai, Yidong},
 doi = {10.1109/VRW55335.2022.00046},
 journal = {2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)}
}

@article{
 title = {Identity, Crimes, and Law Enforcement in the Metaverse},
 type = {article},
 year = {2022},
 websites = {http://arxiv.org/abs/2210.06134},
 month = {10},
 day = {12},
 id = {530f9525-f526-367d-be21-3dd6136b877a},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {With the boom in metaverse-related projects in major areas of the public's life, the safety of users becomes a pressing concern. We believe that an international legal framework should be established to promote collaboration among nations, facilitate crime investigation, and support democratic governance. In this paper, we discuss the legal concerns of identity, crimes that could occur based on incidents in existing virtual worlds, and challenges to unified law enforcement in the metaverse.},
 bibtype = {article},
 author = {Qin, Hua Xuan and Wang, Yuyang and Hui, Pan}
}

With the boom in metaverse-related projects in major areas of the public's life, the safety of users becomes a pressing concern. We believe that an international legal framework should be established to promote collaboration among nations, facilitate crime investigation, and support democratic governance. In this paper, we discuss the legal concerns of identity, crimes that could occur based on incidents in existing virtual worlds, and challenges to unified law enforcement in the metaverse.

@article{
 title = {Prediction of cybersickness in virtual environments using topological data analysis and machine learning},
 type = {article},
 year = {2022},
 keywords = {TDA,cybersickness,machine learing,navigation,persistent homology,virtual reality},
 volume = {3},
 websites = {https://www.frontiersin.org/articles/10.3389/frvir.2022.973236/full},
 month = {10},
 publisher = {Frontiers Media S.A.},
 day = {11},
 id = {ef30314b-debc-3b65-889e-a4e7ef56eafb},
 created = {2022-10-30T13:28:40.268Z},
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 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2023-03-31T03:10:27.253Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Hadadi2022},
 private_publication = {false},
 abstract = {Recent significant progress in Virtual Reality (VR) applications and environments raised several challenges. They proved to have side effects on specific users, thus reducing the usability of the VR technology in some critical domains, such as flight and car simulators. One of the common side effects is cybersickness. Some significant commonly reported symptoms are nausea, oculomotor discomfort, and disorientation. To mitigate these symptoms and consequently improve the usability of VR systems, it is necessary to predict the incidence of cybersickness. This paper proposes a machine learning approach to VR’s cybersickness prediction based on physiological and subjective data. We investigated combinations of topological data analysis with a range of classifier algorithms and assessed classification performance. The highest performance of Topological Data Analysis (TDA) based methods was achieved in combination with SVMs with Gaussian RBF kernel, indicating that Gaussian RBF kernels provide embeddings of physiological time series data into spaces that are rich enough to capture the essential geometric features of this type of data. Comparing several combinations with feature descriptors for physiological time series, the performance of the TDA + SVM combination is in the top group, statistically being on par or outperforming more complex and less interpretable methods. Our results show that heart rate does not seem to correlate with cybersickness.},
 bibtype = {article},
 author = {Hadadi, Azadeh and Guillet, Christophe and Chardonnet, Jean-Rémy and Langovoy, Mikhail and Wang, Yuyang and Ovtcharova, Jivka},
 doi = {10.3389/frvir.2022.973236},
 journal = {Frontiers in Virtual Reality}
}

Recent significant progress in Virtual Reality (VR) applications and environments raised several challenges. They proved to have side effects on specific users, thus reducing the usability of the VR technology in some critical domains, such as flight and car simulators. One of the common side effects is cybersickness. Some significant commonly reported symptoms are nausea, oculomotor discomfort, and disorientation. To mitigate these symptoms and consequently improve the usability of VR systems, it is necessary to predict the incidence of cybersickness. This paper proposes a machine learning approach to VR’s cybersickness prediction based on physiological and subjective data. We investigated combinations of topological data analysis with a range of classifier algorithms and assessed classification performance. The highest performance of Topological Data Analysis (TDA) based methods was achieved in combination with SVMs with Gaussian RBF kernel, indicating that Gaussian RBF kernels provide embeddings of physiological time series data into spaces that are rich enough to capture the essential geometric features of this type of data. Comparing several combinations with feature descriptors for physiological time series, the performance of the TDA + SVM combination is in the top group, statistically being on par or outperforming more complex and less interpretable methods. Our results show that heart rate does not seem to correlate with cybersickness.

@inproceedings{
 title = {Helpfulness Prediction for VR Application Reviews: Exploring Topic Signals for Causal Inference},
 type = {inproceedings},
 year = {2022},
 keywords = {-hci design,and evaluation methods-user studies,cation,causal inference,hci,human computer interaction,human-centered computing-,index terms,review helpfulness,topic model,two-stage,vr appli-},
 pages = {17-21},
 websites = {https://ieeexplore.ieee.org/document/9974169/},
 month = {10},
 publisher = {IEEE},
 id = {3d719b5f-fdb6-33d3-98a8-bcf3c0bc1b4a},
 created = {2022-10-31T13:35:05.641Z},
 file_attached = {true},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Zhang, Meng and Qian, Yang and Jiang, Yuanchun and Wang, Yuyang and Liu, Yezheng},
 doi = {10.1109/ISMAR-Adjunct57072.2022.00014},
 booktitle = {2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}
}

@inproceedings{
 title = {Explore and Interpret the Correlations Among VR Applications},
 type = {inproceedings},
 year = {2022},
 pages = {22-26},
 websites = {https://ieeexplore.ieee.org/document/9974282/},
 month = {10},
 publisher = {IEEE},
 id = {c777ffee-857f-33f3-b214-93e6688bc6d2},
 created = {2023-08-10T12:19:58.364Z},
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 authored = {true},
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 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Qian, Yang and Xu, Huahua and Wang, Yuyang and Liu, Yezheng and Jiang, Yuanchun},
 doi = {10.1109/ISMAR-Adjunct57072.2022.00015},
 booktitle = {2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}
}

@article{
 title = {Enhanced cognitive workload evaluation in 3D immersive environments with TOPSIS model},
 type = {article},
 year = {2021},
 pages = {102572},
 volume = {147},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S1071581920301749},
 month = {3},
 id = {c4ef61a5-a364-3378-a05c-d9b73d21c683},
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 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2021},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Yuyang and Chardonnet, Jean-Rémy and Merienne, Frédéric},
 doi = {10.1016/j.ijhcs.2020.102572},
 journal = {International Journal of Human-Computer Studies}
}

@article{
 title = {Development of a speed protector to optimize user experience in 3D virtual environments},
 type = {article},
 year = {2021},
 pages = {102578},
 volume = {147},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S1071581920301804},
 month = {3},
 id = {a61bb4bf-2440-3a5f-b81c-886a64874cf8},
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 citation_key = {Wang2021},
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 bibtype = {article},
 author = {Wang, Yuyang and Chardonnet, Jean-Rémy and Merienne, Frédéric},
 doi = {10.1016/j.ijhcs.2020.102578},
 journal = {International Journal of Human-Computer Studies}
}

@inproceedings{
 title = {Using Fuzzy Logic to Involve Individual Differences for Predicting Cybersickness during VR Navigation},
 type = {inproceedings},
 year = {2021},
 pages = {373-381},
 websites = {https://ieeexplore.ieee.org/document/9417785/},
 month = {3},
 publisher = {IEEE},
 city = {Lisbon, Portugal},
 id = {a757423d-81f2-3d11-a317-a51ddf12f2e8},
 created = {2021-01-29T09:12:00.254Z},
 file_attached = {true},
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 last_modified = {2023-06-10T12:38:54.888Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2021},
 private_publication = {false},
 abstract = {There have been many studies about how individual differences can affect users' susceptibility to cybersickness in a VR application. However, the lack of strategy to integrate the influence of each factor on cybersickness makes it difficult to utilize the results of existing research. Based on the fuzzy logic theory that can represent the effect of different factors as a single value containing integrated information, we developed two approaches including the knowledge-based Mamdani-type fuzzy inference system and the data-driven Adaptive neuro-fuzzy inference system (ANFIS) to involve three individual differences (Age, Gaming experience and Ethnicity) and we correlated the corresponding outputs with the scores obtained from the simulator sickness questionnaire (SSQ) in a simple navigation scenario. The correlation coefficients obtained through a 4-fold cross validation were found statistically significant with both fuzzy logic approaches, indicating their effectiveness to influence the occurrence and the level of cybersickness. Our work provides insights to establish customized experiences for VR navigation by involving individual differences.},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Chardonnet, Jean-Remy and Merienne, Frederic and Ovtcharova, Jivka},
 doi = {10.1109/VR50410.2021.00060},
 booktitle = {2021 IEEE Virtual Reality and 3D User Interfaces (VR)}
}

There have been many studies about how individual differences can affect users' susceptibility to cybersickness in a VR application. However, the lack of strategy to integrate the influence of each factor on cybersickness makes it difficult to utilize the results of existing research. Based on the fuzzy logic theory that can represent the effect of different factors as a single value containing integrated information, we developed two approaches including the knowledge-based Mamdani-type fuzzy inference system and the data-driven Adaptive neuro-fuzzy inference system (ANFIS) to involve three individual differences (Age, Gaming experience and Ethnicity) and we correlated the corresponding outputs with the scores obtained from the simulator sickness questionnaire (SSQ) in a simple navigation scenario. The correlation coefficients obtained through a 4-fold cross validation were found statistically significant with both fuzzy logic approaches, indicating their effectiveness to influence the occurrence and the level of cybersickness. Our work provides insights to establish customized experiences for VR navigation by involving individual differences.

@inproceedings{
 title = {VR Sickness Prediction for Navigation in Immersive Virtual Environments using a Deep Long Short Term Memory Model},
 type = {inproceedings},
 year = {2019},
 pages = {1874-1881},
 websites = {https://ieeexplore.ieee.org/document/8798213/},
 month = {3},
 publisher = {IEEE},
 city = {Osaka, Japan},
 id = {76c5e311-2d47-308d-96c8-ad8daf7a2f0f},
 created = {2019-02-10T17:26:33.138Z},
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 last_modified = {2023-06-10T12:41:10.547Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2019},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Chardonnet, Jean-Remy and Merienne, Frederic},
 doi = {10.1109/VR.2019.8798213},
 booktitle = {2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)}
}

@inproceedings{
 title = {Design of a Semiautomatic Travel Technique in VR Environments},
 type = {inproceedings},
 year = {2019},
 pages = {1223-1224},
 websites = {https://ieeexplore.ieee.org/document/8798004/},
 month = {3},
 publisher = {IEEE},
 city = {Osaka, Japan},
 id = {f9515e01-fc0e-3d21-97b6-facadf9137b6},
 created = {2019-02-10T17:26:33.152Z},
 file_attached = {true},
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 last_modified = {2021-11-29T08:39:44.299Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2019},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Chardonnet, Jean-Remy and Merienne, Frederic},
 doi = {10.1109/VR.2019.8798004},
 booktitle = {2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)}
}

@article{
 title = {Knowledge-Based Open Performance Measurement System (KBO-PMS) for a Garment Product Development Process in Big Data Environment},
 type = {article},
 year = {2019},
 pages = {129910-129929},
 volume = {7},
 websites = {https://ieeexplore.ieee.org/document/8805317/},
 publisher = {IEEE},
 id = {25509913-b3f3-3b51-bf31-6130eb80f51d},
 created = {2019-11-14T08:35:28.390Z},
 file_attached = {true},
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 last_modified = {2020-11-28T18:11:48.423Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Hong, Yan and Wu, Tianyu and Zeng, Xianyi and Wang, Yuyang and Yang, Wen and Pan, Zhijuan},
 doi = {10.1109/ACCESS.2019.2936294},
 journal = {IEEE Access}
}

@article{
 title = {CBCRS: An open case-based color recommendation system},
 type = {article},
 year = {2018},
 keywords = {Case-based l,Color recommendation,Dynamical system,color recommendation},
 pages = {113-128},
 volume = {141},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S095070511730535X},
 month = {2},
 publisher = {Elsevier B.V.},
 id = {24bbcad8-ab7f-39a3-b4c1-3f7730ece8b1},
 created = {2017-11-23T10:53:13.510Z},
 file_attached = {true},
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 last_modified = {2021-09-05T16:46:07.948Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Hong2017},
 private_publication = {false},
 bibtype = {article},
 author = {Hong, Yan and Zeng, Xianyi and Wang, Yuyang and Bruniaux, Pascal and Chen, Yan},
 doi = {10.1016/j.knosys.2017.11.014},
 journal = {Knowledge-Based Systems}
}

@inproceedings{
 title = {Speed Profile Optimization for Enhanced Passenger Comfort: An Optimal Control Approach},
 type = {inproceedings},
 year = {2018},
 pages = {723-728},
 websites = {https://ieeexplore.ieee.org/document/8569420/},
 month = {11},
 publisher = {IEEE},
 city = {Maui, HI, USA},
 id = {d007560f-33c8-31c9-9892-fd071f4c1311},
 created = {2018-11-29T10:12:36.722Z},
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 last_modified = {2023-06-10T12:30:22.033Z},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2018},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Chardonnet, Jean-Remy and Merienne, Frederic},
 doi = {10.1109/ITSC.2018.8569420},
 booktitle = {2018 21st International Conference on Intelligent Transportation Systems (ITSC)}
}

@inproceedings{
 title = {A Semiautomatic Navigation Interface to Reduce Visually Induced Motion Sickness in Virtual Reality},
 type = {inproceedings},
 year = {2018},
 pages = {47-52},
 websites = {https://jrv2018.sciencesconf.org/program/details},
 city = {Evry,France},
 id = {623b8cdd-4c10-385e-8022-a618435e8337},
 created = {2018-11-29T10:12:36.723Z},
 file_attached = {true},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2018},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Chardonnet, Jean-Rémy and Merienne, Frédéric},
 booktitle = {Journées de la Réalité Virtuelle}
}

@inproceedings{
 title = {Fuzzy Analytical Hierarchy Process Methods for Evaluating the Comfort of Textiles},
 type = {inproceedings},
 year = {2015},
 pages = {502-505},
 websites = {http://ieeexplore.ieee.org/document/7263621/},
 month = {6},
 publisher = {IEEE},
 id = {b7faf14b-5b5c-36ed-8e12-997d5f708ff5},
 created = {2016-10-19T14:49:00.000Z},
 file_attached = {true},
 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2021-11-23T16:32:07.307Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2015},
 private_publication = {false},
 abstract = {Because there are many indexes when evaluating the performance of clothing fabrics, the method used widely is analytic hierarchy process (AHP). However, they often neglect the fuzziness when people give the intensity of importance on an absolute scale, selecting one index with membership of one and rejecting one index with membership of zero. In this experiment, we used the Fuzzy Analytic Hierarchy Process to express brain cognition and evaluate the synthesis performance of fabrics. Triangular Fuzzy Numbers (TFN) replaced the crisp number of pair wise comparison matrix, and then the defuzzification process was used to establish fuzzy vectors, through which the final result was obtained by applying the fuzzy relation composite theory. The results showed that the tested fabric belonged to the good degree, membership at 41.0%. The combination of AHP and fuzzy decision was an efficient way to tackle uncertain problem and design intelligent wearable devices.},
 bibtype = {inproceedings},
 author = {Yuyang, Wang and Luyan, Xu and Yan, Hong and Yuqing, Liu},
 doi = {10.1109/ICMTMA.2015.128},
 booktitle = {2015 Seventh International Conference on Measuring Technology and Mechatronics Automation}
}

Because there are many indexes when evaluating the performance of clothing fabrics, the method used widely is analytic hierarchy process (AHP). However, they often neglect the fuzziness when people give the intensity of importance on an absolute scale, selecting one index with membership of one and rejecting one index with membership of zero. In this experiment, we used the Fuzzy Analytic Hierarchy Process to express brain cognition and evaluate the synthesis performance of fabrics. Triangular Fuzzy Numbers (TFN) replaced the crisp number of pair wise comparison matrix, and then the defuzzification process was used to establish fuzzy vectors, through which the final result was obtained by applying the fuzzy relation composite theory. The results showed that the tested fabric belonged to the good degree, membership at 41.0%. The combination of AHP and fuzzy decision was an efficient way to tackle uncertain problem and design intelligent wearable devices.

@inproceedings{
 title = {Characterizing the Dynamic Water Absorption and Wicking Behaviour of Sportswear by the Non-contact Near-Infrared Method},
 type = {inproceedings},
 year = {2014},
 pages = {301-307},
 city = {Singapore},
 id = {6988fbfe-ca73-3cfa-afed-500ee6e38f80},
 created = {2017-01-15T15:54:17.000Z},
 file_attached = {true},
 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2021-11-23T17:12:52.410Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2014},
 private_publication = {false},
 abstract = {The liquid diffusibility of textile fabrics is often used to assess their internal structures and porosities in relevant experiments. A new method and instrument called Fibrous Liquid Transfer System (FLTS) was devised to evaluate the liquid transfer properties of textile fabrics, and this noncontact measurement can also be used to monitor the process of liquid infiltration on fabrics dynamically. Five types of sporting textile fabrics were tested in three different directions including downward, upward as well as lateral infiltration, and the results show that their liquid transfer properties are significantly distinct from each other. This lies in the fact that different fabrics have different abilities to absorb near-infrared light after we analysed the liquid transfer properties of each specimen with the FLTS. The variant rates of liquid transfer in fabrics are due to their different liquid transfer mechanism. Gravity can also affect the liquid transfer property of fabrics and this is another factor.},
 bibtype = {inproceedings},
 author = {Wang, Yuyang and Pan, Na and Xujing, Zhang and Shouwei, Gao and Liu, Yuqing},
 doi = {10.5281/zenodo.5721229},
 booktitle = {The 1st International Conference in Sports Science and Technology}
}

The liquid diffusibility of textile fabrics is often used to assess their internal structures and porosities in relevant experiments. A new method and instrument called Fibrous Liquid Transfer System (FLTS) was devised to evaluate the liquid transfer properties of textile fabrics, and this noncontact measurement can also be used to monitor the process of liquid infiltration on fabrics dynamically. Five types of sporting textile fabrics were tested in three different directions including downward, upward as well as lateral infiltration, and the results show that their liquid transfer properties are significantly distinct from each other. This lies in the fact that different fabrics have different abilities to absorb near-infrared light after we analysed the liquid transfer properties of each specimen with the FLTS. The variant rates of liquid transfer in fabrics are due to their different liquid transfer mechanism. Gravity can also affect the liquid transfer property of fabrics and this is another factor.

@inproceedings{
 title = {Using Physiological Measures to Capture Wear Experiences after Running},
 type = {inproceedings},
 year = {2014},
 pages = {717-724},
 city = {Singapore},
 id = {5129e94f-6f4a-3d60-b591-6b91876cf751},
 created = {2017-01-15T15:59:20.000Z},
 file_attached = {true},
 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2021-11-23T17:16:48.142Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Zhang2014},
 private_publication = {false},
 abstract = {Galvanic skin response is always regarded as a direct and convenient method of recording the activities of sympathetic nerve, and we therefore researched into people's emotional reaction when the body has a contact with wool and acrylic fabrics. Our results showed that wool felt more soft and smooth than that of the acrylic fabric, and wool also performed better in the absorption of moisture. The skin resistance of wool fabric was lower than that of acrylic fabric if the respondent sat in a tranquil condition and the variation amplitude of this resistance also changed little for wool fabrics. This meant that wool may have a broader prospect for sporting garments. Sportswear can also affect people's emotion in two ways. One was that the friction between bodies and garments may have a direct effect on emotional changes. Another influence was that garments may present a balancing action if people sweated excessively or the external temperature changed.},
 bibtype = {inproceedings},
 author = {Zhang, Xujing and Wang, Yuyang and Wang, Y. and Liu, Yuqing and Zi, Y.},
 doi = {10.5281/zenodo.5721408},
 booktitle = {The 1st International Conference in Sports Science and Technology}
}

Galvanic skin response is always regarded as a direct and convenient method of recording the activities of sympathetic nerve, and we therefore researched into people's emotional reaction when the body has a contact with wool and acrylic fabrics. Our results showed that wool felt more soft and smooth than that of the acrylic fabric, and wool also performed better in the absorption of moisture. The skin resistance of wool fabric was lower than that of acrylic fabric if the respondent sat in a tranquil condition and the variation amplitude of this resistance also changed little for wool fabrics. This meant that wool may have a broader prospect for sporting garments. Sportswear can also affect people's emotion in two ways. One was that the friction between bodies and garments may have a direct effect on emotional changes. Another influence was that garments may present a balancing action if people sweated excessively or the external temperature changed.