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Evaluation of Mixed Reality Technologies in Remote Teaching 9th

Evaluation of Mixed Reality Technologies in Remote Teaching

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9th international conference on Learning and Collaboration Technologies (LCT) Held as Part of the 24th international conference on human-computer interaction (HCII)

作者： Daling, Lea M. Khoadei, Samira Kalkofen, Denis thurner, Stefan Sieger, Johannes Shepel, Taras Abdelrazeq, Anas Ebner, Markus Ebner, Martin Isenhardt, Ingrid Rhein Westfal TH Aachen Informat Management Mech Engn IMA Aachen Germany Graz Univ Technol Inst Comp Graph & Vis Graz Austria Graz Univ Technol Educ Technol Graz Austria Rhein Westfal TH Aachen Inst Mineral Resources Engn Aachen Germany Freiberg Univ Min & Technol Freiberg Germany

ISBN: (纸本)9783031056758;9783031056741

the trend towards remote teaching is steadily increasing and intensified by the current situation of the global pandemic. this is a particular challenge for subjects with a high practical relevance, such as mining engineering education, as practical experiences and on-site excursions are an integral part of the curriculum. In face-to-face teaching settings, mixed reality technologies are already considered a promising medium for the implementation of e.g., virtual field trips. Based on this, the current study addresses the question to what extent the integration of mixed reality technologies is suitable for remote teaching and which strengths and challenges are perceived by students and teachers. For this purpose, two 60min remote lectures in the field of mining engineering were conducted, in which the use of mixed reality was tested on the basis of shared 360 degrees experiences and 3D models and evaluated by students and teachers. Results reveal that the use of mixed reality in remote teaching was perceived as useful, enabled a realistic experience and improved students' understanding of presented theory compared to traditional teaching methods. In this paper, we discuss possible potentials and risks of using mixed reality in remote teaching and derive directions for further research.

关键词： Remote teaching Mixed reality Virtual excursions Mining engineering Education

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Research on Effective Teaching Based on the BOPPPS Model Under the Background of engineering Education Professional Certification 8th

Research on Effective Teaching Based on the BOPPPS Model Und...

引用

8th international conference on Pioneering computer Scientists, Engineers and Educators (ICPCSEE)

作者： Yin, Fang Li, Chengyan Sun, Dongpu Zhou, Libo Harbin Univ Sci & Technol Sch Comp Sci & Technol Harbin 150080 Peoples R China

ISBN: (纸本)9789811952098;9789811952081

According to the general requirement of the engineering education professional certification and aiming at the problem of how to develop undergraduates with the ability to solve complex engineering problems by teaching research and curriculum construction, a new effective teaching model is built by analyzing the relationship between BOPPPS and effective teaching. Our contributions are as follows: we combine professional training objectives with curriculum characteristics, focus on the importance of participating in the main position of students in learning, and emphasize that students' participatory interaction and feedback and diversified assessment methods for evaluation are adopted to focus on the development and improvement of the comprehensive quality of students and classroom teaching quality and teaching effect to ensure the effectiveness of teaching. the practice in the Oracle database course proves that the teaching mode proposed in this paper can effectively improve the teaching effect, and it plays a positive role in strengthening students' practical abilities to solve practical engineering problems.

关键词： engineering education professional certification BOPPPS model Effective teaching Diversified assessment

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Multi dimensional intelligent interaction method for distribution network fault information based on similarity clustering and regularization

Multi dimensional intelligent interaction method for distrib...

引用

2024 8th international conference on Electrical, Mechanical and computer engineering (ICEMCE)

作者： Yan Xu Bin Zhao Jiabao Liu Junhao Lin Shu Zhu State Grid Shanghai Shibei Electric Power Supply Company Shanghai China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

In order to ensure the stable operation of the power grid, a multi-dimensional intelligent interaction method for distribution network fault information based on similarity clustering and regularization is proposed. Use reachability matrix to analyze the connectivity status of the network in depth. By regularizing certain parameters or variables during the constraint clustering process, thereby improving the accuracy and stability of the clustering results. Combined with the set distribution network fault information exchange system, the accurate positioning of the distribution network fault section is achieved by calculating the current of the distribution network fault line, and the multi-dimensional intelligent exchange of distribution network fault information is completed. the experimental results show that the information similarity clustering effect of the proposed method is close to 1, and the localization accuracy remains above $\mathbf{9 8 \%}$ when facing different distribution network faults. the proposed method can effectively reflect the fault information of the distribution network and ensure the effective operation of the distribution network.

关键词： Location awareness Accuracy Clustering algorithms Distribution networks Power system stability Fault location Stability analysis Power grids Information exchange

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Speech Emotion Recognition by using Philips Fingerprint and Spectral Entropy 22

Speech Emotion Recognition by using Philips Fingerprint and ...

引用

8th international conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Cao, Xuan Jia, Maoshen Li, Lu Pai, Tun-Wen Faculty of Information Technology Beijing University of Technology Beijing China Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9781450396110

Speech Emotion Recognition (SER) has become an indispensable part of human-computer interaction. In order to obtain a higher recognition rate, in this paper, a joint feature based on Philips fingerprint and spectral entropy is used, and it is combined with some underlying features to perform speech emotion recognition on the four emotions of angry, neutral, happy, and sad. Firstly, the Mel Frequency Cepstral Coefficients (MFCC), Linear Prediction Coefficient (LPC), logarithmic amplitude-frequency characteristics, Philips fingerprints and spectral entropy are extracted for speech dataset. Secondly, Principal Component Analysis (PCA) is used to reduce the dimension of the extracted feature. thirdly, SVM is used to train and classify the features after dimension reduction. the experimental results show that by comparing the recognition results with other feature combinations, the method proposed in this paper has good recognition results. © 2022 ACM.

关键词： Principal component analysis

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Interpretable SincNet-Based Spatiotemporal Neural Network for Seizure Prediction 46

Interpretable SincNet-Based Spatiotemporal Neural Network fo...

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46th Annual international conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Shan, Baolian Yu, Haiqing Jiang, Hanzhe Huang, Yongzhi Xu, Minpeng Ming, Dong Tianjin University Academy of Medical Engineering and Translational Medicine Tianjin300072 China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin300392 China

ISBN: (纸本)9798350371499

Spatiotemporal convolutional neural networks (CNNs) have emerged as potent tools for seizure prediction (SP) using electroencephalogram (EEG) signals, probing spatiotemporal biomarkers in epileptic brains. Nevertheless, it poses significant challenges for clinical practice due to the poor interpretability of learned features and the numerous trainable parameters in existing CNNs. To improve the interpretability and performance, this study proposed an interpretable SincNet-based architecture for spatiotemporal CNNs, encompassing EEGNet-8,2, ShallowConvNet, DeepConvNet, and EEGWaveNet, enabling direct visualization of the bandpass temporal filter range using a sinc-convolution layer. Furthermore, we also constructed a visualization analysis method to demonstrate the crucial spatiotemporal features learned by the proposed optimal CNN. Results on the CHB-MIT dataset revealed that both ShallowConvNet and EEGWaveNet had significantly improved performance with more lightweight parameters. Notably, the architecture enabled ShallowConvNet to achieve an average accuracy of 87.2%, sensitivity of 88.3%, weighted F1-score of 87.1%, and AUC of 92.7% for 21 epilepsy patients. Besides, the visualization outcomes underscored the ability of the optimal model to extract statistically significant spatiospectral energy differences within high-frequency EEG bands for SP classification tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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Dual-View Spatio-Temporal Interactive Network for Video human Action Recognition 17th

Dual-View Spatio-Temporal Interactive Network for Video Huma...

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17th international conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Wu, Hanbo Ma, Xin School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9789819607761

Capturing discriminative spatiotemporal feature information is crucial for enhancing the performance of video action recognition. Currently, most methods generally embed spatiotemporal feature modeling modules into the backbone network to achieve human action recognition under a single view. However, action video has a 3D structure, and multi-view information helps to acquire more comprehensive body-related clues to improve the robustness and accuracy of action recognition. Depth data is insensitive to lighting and color changes, particularly in providing reliable 3D geometric information of human actions. In this paper, we focus on the task of depth video-based action recognition and propose a Dual-view Spatio-Temporal Interactive Network (DSTIN), which enhances action recognition performance by effectively integrating spatiotemporal interactive features from front and side views. Specifically, the core of the DSTIN is the Dual-view Spatio-Temporal Interactive Module (DSTIM), which operates on convolutional feature maps from two views. It first exchanges spatiotemporal information along the channel dimension to achieve inter-view channel feature interaction, and then applies temporal shift along the time dimension within each view to model motion information. the proposed DSTIM can be flexibly embedded into any 2D deep network architectures to enhance their ability. We choose 2D Resnet50 as the backbone to generate DSTIN, which takes depth dynamic image sequences from two different views as the input and achieves an end-to-end action recognition training framework through inter-view spatiotemporal information interaction and fusion. Extensive experiments on two large-scale RGBD datasets demonstrate that the proposed method significantly improves the performance of video human action recognition. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Spatio-temporal data

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Effects of 15-Day -6° Head-Down Bed Rest and HD-tDCS on Cognitive Functions 46

Effects of 15-Day -6° Head-Down Bed Rest and HD-tDCS on Cog...

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46th Annual international conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Dong, Linlin Ke, Yufeng Zhu, Xiaodong Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 China Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin 300392 China

ISBN: (纸本)9798350371499

A favorable cognitive state, efficient attention, and sharp alertness are essential for successful space missions. To explore the effects of microgravity on working memory, attention, and alertness and to find effective approaches to improve them, we recruited 17 healthy participants (control: 9, active: 8) to be involved in a 15-day -6° head-down bed rest (HDBR). A 30 min HD-tDCS was applied to the active group every other day during HDBR. We adopted three types of tasks: N-back, SCWT, and PVT to evaluate the effects, which were completed before, during, and after HDBR. the results showed that: (1) there was no significant difference in accuracy or in response time between the control and the active group. (2) the accuracy of SCWT before HDBR was significantly lower than that during and after HDBR. (3) Regardless of groups, the response time of all tasks showed a gradual decrease during HDBR. For the N-back and PVT tasks, the response time increased significantly in the control group and decreased significantly in the active group after HDBR. those demonstrated that the working memory, attention, and alertness were elevated during 15-day -6° HDBR. HD-tDCS enhanced readaptation of cognitive functions after HDBR exposure. © 2024 IEEE.

关键词： Microgravity

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the Application of Augmented Reality to Generate Realistic interaction in the Property Sector 8

The Application of Augmented Reality to Generate Realistic I...

引用

8th international conference on computer Science and Computational Intelligence, ICCSCI 2023

作者： Anderies Adidarma, Rendy Chanyassen, Maximillian Lemuel Imanuel, Alexander Chowanda, Andry Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Augmented Reality is a technology that overlays computer-generated information and images in a natural environment to enhance or augment the contextual perception of the user's environment. the utilization of AR is currently one of the most important in developing several industrial sectors, such as architecture, engineering, and construction development. Nowadays, the property sector industry has always been an issue of sale for users that do not have direct access to the property. the pandemic and the economic problem in different countries have also reduced consumer interest in purchasing houses. Due to these issues, this paper aims to provide a platform for addressing these pain areas. the software can apply Augmented Reality to real estate in real-time using a mobile device. Not only can they see the outside of the property, but they can also see the interior design, furniture design, and property mapping in 3D. Our test results show that an application is needed to provide the property sector with high demands. Over 80% of our respondents confirm that our application's presence will help ease the sales problem. Because it can save the customer time, viewing property frequency, and cost saving. these increased demands, we are developing an AR-based application for the market to use and gain more traction in the property sector. © 2023 the Authors. Published by Elsevier B.V.

关键词： 3D Model Android Augmented Reality Performance Testing Property Industry Vuforia Ground Plane

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An Agent of Massage Robot for Task Planning Based on Large Language Models

An Agent of Massage Robot for Task Planning Based on Large L...

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Advanced Algorithms and Control engineering (ICAACE), international conference on

作者： Yuxiao Miao Chun Liu School of Computer Science Hubei University of Technology Wuhan China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

Traditional robot language systems have limited task planning capabilities. With the rapid development of large language model (LLM) technology, integrating its powerful language analysis capabilities with robots has become a current research hotspot. this paper focuses on the task planning domain of massage robots, and optimizes the prompt strategy using the Chain of thought (CoT) and ReAct methods. By employing Langchain to combine LLMs with massage control, an intelligent agent for massage robots with automatic task planning and environmental interaction is designed. the optimized prompt strategy is validated on the ALFWorld platform, with a task planning success rate of 72%. In addition, the success rate of using ChatGPT-4 for massage task planning in the real world is observed to be 95%. Finally, a comparison is made between using an external LLM interface and training an LLM locally for task planning. It is found that the method of calling an external interface generally has a higher success rate than the local training method.

关键词： Training Large language models Medical treatment human-robot interaction Real-time systems Planning Intelligent agents Robots Stress Optimization

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LstSim-Extended: Towards Monitoring interaction and Beyond in Web-Based Control Room Simulations 18th

LstSim-Extended: Towards Monitoring Interaction and Beyond i...

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18th ifip TC 13 international conference on human-computer interaction (INTERACT)

作者： Poehler, Jonas Flegel, Nadine Mentler, Tilo Van Laerhoven, Kristof Univ Siegen D-57076 Siegen Germany Trier Univ Appl Sci D-54293 Trier Germany

ISBN: (纸本)9783030983888;9783030983871

Control room operators rely on a range of technologies to communicate crucial information and dependably coordinate a disparate collection of tasks and procedures. Tools that are capable to design, to implement, and to evaluate interactive systems that can assist the tasks of control room operators in these environments therefore play an important role. this paper offers a framework that facilitates the early research steps into evaluating work flows, interfaces, and wearable sensors in the context of an emergency dispatch center. It entails a primarily web-based, quick-to-deploy, and scalable method that specifically targets preliminary studies in which large-scale and situated deployments are not feasible. By using open-source and affordable wrist-worn sensors, it furthermore enables investigating any relationships between interaction design in control rooms and operators' physiological data. Our evaluation on a preliminary study with 5 participants shows that basic scenarios are able to induce differences which can be measured by reaction times in the interactions as well as in the data from the smartwatch.

关键词： Usable safety and security Control rooms Web-based simulations Interfaces and cognitive load Emergency dispatch

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