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检索条件"任意字段=8th IFIP International Conference on Engineering for Human-Computer Interaction"

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Creating a Post-sedentary Work Context for Software engineering 18th

Creating a Post-sedentary Work Context for Software Engineer...

引用

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

作者： Hedlund, Martin Bogdan, Cristian Meixner, Gerrit KTH Royal Inst Technol Stockholm Sweden Heilbronn Univ UniTyLab Heilbronn Germany

ISBN: (纸本)9783030983888;9783030983871

Software engineers are sedentary and need technological help for a more healthy life. Current software engineering tasks are mostly confined to the standard sedentary desktop user interface. We believe that software engineering should be restructured so that it offers a non-sedentary alternative. In this paper, we describe a new research approach, called Post-sedentary Software engineering. Our ambition with this approach is to provide an alternative, healthier work context without decreasing productivity. We take a spatial approach to post-sedentary tool design, starting from the assumption an interactive 3D environment with appropriate metaphors is necessary for full body movement. We discuss available technologies for achieving this goal and outline four studies that incorporate the software engineering phases of code comprehension, code creation and debugging in a non-sedentary context.

关键词： Sedentary Post-sedentary Spatial Metaphor Software engineering

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Revisiting Constraints for Monocular Visual Quadric SLAM

Revisiting Constraints for Monocular Visual Quadric SLAM

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

作者： Xiaolong Yu Junqiao Zhao The School of Computer Science and Technology Tongji University Shanghai China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

In recent years, numerous objectoriented SLAM systems have been proposed to enhance scene understanding and human-computer interaction by reconstructing semantic objects. Although significant progress has been made in semantic object reconstruction, these methods have not led to effective improvements in localization accuracy. In this paper, we systematically review the existing constraints used in visual quadric-based SLAM, revealing their limitations-particularly in handling mismatches between complex object contours and dual quadrics. To quantitatively evaluate the performance of these constraints, we conduct experiments on public datasets, which demonstrate the impact of different constraints on dual quadric SLAM methods and validate our analysis.

关键词： Location awareness human computer interaction Visualization Simultaneous localization and mapping Control engineering Accuracy Reviews Semantics Robustness

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Gamification through the Lens of Safety engineering 25th

Gamification Through the Lens of Safety Engineering

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25th international conference on human-computer interaction (HCI international)

作者： Bowles, Bryce Duffy, Vincent G. Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9783031480492;9783031480508

the purpose of this study was to examine the applications of gamification and game-based learning in the field of safety engineering. this systematic literature reviewused an extensive set of databases and data analysis tools to defend the rising importance of gamification in safety engineering. Databases such as Scopus, Web of Science, and Google Scholar using Harzing's Publish or Perish were used to analyze existing works, and their metadata was extracted and imported into data analysis tools such as VOSviwer, Citespace, BibExcel, and MAXQDA. Results show that gamification has been used in safety training for industrial jobs to promote learning in the workplace and reduce the risk of accidents. A variety of studies also focus on improving road safety when driving by keeping the driver engaged, reducing boredom, improving hazard recognition, and providing driving recommendations to discourage risky driving habits. Mendeley software was used to generate a bibliography out of all references. this paper utilizes several bibliometric analysis methods for a systematic literature review and explains the potential that gamification has for the future of safety engineering.

关键词： Gamification Safety Training Serious Games Road Safety

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Comparative Analysis of Machine-Learning Techniques for Insult Detection in Social Commentary 8

Comparative Analysis of Machine-Learning Techniques for Insu...

引用

8th international conference on Communication and Electronics Systems, ICCES 2023

作者： Aakash, K.G. Juliet, Sujitha Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350396638

Social media users' immediate and long-term well-being is seriously threatened by cyberbullying. With an eye towards creating early warning systems for the anticipation of harmful comments vulnerable to attacks, we investigate the detection of cyberbullying in social networks. Online harassment disturbs by cyberbullying has grave repercussions. the ability to automatically detect cyberbullying and recognize the roles that individuals assume in social interaction is required to address this issue in online contexts. the use of technology as a bullying tool is known as cyberbullying. Cyberbullying is a problem that has arisen along with technology development and poses a risk to adolescents' psychological welfare. A framework is suggested to provide two distinct descriptions of cyberbullying. Cyberbullying is a significant issue on the internet that affects both adults and teenagers. Mistakes like despair and suicide have resulted from it. there is an increasing demand for content on social media platforms to be regulated. the following study builds a model based on the identification of cyberbullying in text data using a Naive Bayes classifier, utilizing data from Twitter and comments based on personal assaults from Wikipedia forums. the model offers accuracy levels above 90% for data from Tweets and accuracy levels above 80% for data from Wikipedia. © 2023 IEEE.

关键词： Social networking (online)

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Object Detection for Functional Assessment Applications 1

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24th international conference on engineering Applications of Neural Networks (EANN)

作者： Melino-Carrero, Alessandro Nieva Suarez, Alvaro Losada-Gutierrez, Cristina Marron-Romera, Marta Guardiola Luna, Irene Baeza-Mas, Javier Univ Alcala Dept Elect Edificio PolitecnCtra Madrid Barcelona KM 33600 Alcala De Henares 28805 Spain

ISBN: (数字)9783031342042

ISBN: (纸本)9783031342035;9783031342042

this paper presents a proposal for object detection as a first stage for the analysis of human-Object interaction (HOI) in the context of automated functional assessment. the proposed system is based in a two-step strategy, thus, in the first stage there are detected the people in the scene, as well as large objects (table, chairs, etc.) using a pre-trained YOLOv8. then, there is defined a ROI around each person that is processed using a custom YOLO to detect small elements (forks, plates, spoons, etc.). Since there are no large image datasets that include all the objects of interest, there has also been compiled a new dataset including images from different sets, and improving the available labels. the proposal has been evaluated in the novel dataset, and in different images acquired in the area in which the functional assessment is performed, obtaining promising results.

关键词： Image processing Object detection Occupational therapy Functional assessment human-Object interaction

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Simulation Operation System of Civil Aviation Professional Electromechanical Equipment Based on human-computer interaction 8th

Simulation Operation System of Civil Aviation Professional E...

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8th EAI international conference on e-Learning, e-Education, and Online Training, eLEOT 2022

作者： Zhao, Dan Zhang, Xin College of Aeronautical Engineering Beijing Polytechnic Beijing100176 China

ISBN: (纸本)9783031211607

Traditional equipment simulation operating system adopts the principle of combining real object with simulation, which has the problems of poor feedback accuracy and slow operation feedback speed. In view of the above problems, this research designs a civil aviation professional electromechanical equipment simulation and operation system based on human-computer interaction. Taking FPGA and arm as the core, the hardware part of the system is designed by connecting Kinect sensor. After the electromechanical equipment simulation model is established by using 3D Max software, the key frames in the actual operation interactive action video are extracted by using k-means clustering algorithm, and then the simulation operation gestures are recognized by combining with the expert judgment module, so as to realize the electromechanical equipment simulation operation training under human-computer interaction. Experimental results show that the feedback accuracy of the system is higher than 95%, and the feedback is sensitive, interactive and the simulation scene is clearer. © 2022, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Feedback

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Facial Expression Recognition Based on An Improved Data Augmentation Method and A Multichannel Convolutional Neural Network Model 8

Facial Expression Recognition Based on An Improved Data Augm...

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8th international conference on Image, Vision and Computing, ICIVC 2023

作者： Wang, Xiuling Lu, Xiao Wang, Yingying Wang, Haixia Zhang, Zhiguo College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China College of Energy Storage Technology Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9798350335231

With the development of artificial intelligence and human-computer interaction, the recognition and analysis of facial expressions have recently received increasing attention. Considering the excellence of the convolutional neural network (CNN) model in the field of image recognition, this paper applies the CNN model to recognize facial expressions. the deep neural network is inseparable from large-scale data. In the real world, it is expensive to obtain large scale data sets with labels. A reliable method of expanding the number and diversity of the samples must be found. the generative adversarial networks (GAN) model can generate more images and solve the imbalance of data volume. However, the experiments indicated that the image sharpness generated by the traditional GAN model was insufficient. the model was challenging to train stably and prone to over-fitting or under-fitting. Given these situations, this paper optimized the structure of the GAN model by combining the advantages of the DCGAN and StarGAN models, and improved the training strategy. Moreover, a new multichannel CNN model is proposed and applied in this paper to obtain more comprehensive facial expression features. the experimental results reveal that the proposed method significantly improves the performance of the evaluated baseline facial expression recognition methods. © 2023 IEEE.

关键词： Neural network models

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An Investigation Method Incorporates with Contextual Information and Transformer Residual BiLSTM to Improve the Accuracy of Detecting Sensitive Content in Various Contexts 8

An Investigation Method Incorporates with Contextual Informa...

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8th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Karne, Niharika Ramagundam, Chandra Shekar Patnala, Ranga Rao Ramagundam, Shashishekhar Tadiboina, Sai Nitisha C&rs Platform services Dt Amtrak United States University of South Alabama Department of Electrical Engineering Electrical engineering United States Cloud Platform Services PhiladelphiaPA United States Neuberger Berman United States Software Development & Engineering Content Discovery & Ai Comcast United States Troy University Montgomery Campus AL United States Department of Computer Science United States Geico - Chevy Chase Department of Information Technology Chevy ChaseMD20815 United States

ISBN: (纸本)9798350376425

In the modern era, the internet is an emerging technology with a rapidly growing user. Sensitive content uploaders consider this platform as a way to transmit disturbing visual content, such as animated cartoon videos to circulate unsuitable content among youngsters. Previous researches show that the interaction of online sensitive information has substantial offline effects on historically impoverished communities. As a result, it is strongly recommended that social media platforms have an automatic real-time sensitive content filtering method for detecting contextual information. In this proposed model, a novel deep-learning framework is developed for detecting sensitive content from contextual information. For this, the suggested architecture performs under three stages (i) text collection, (ii) preprocessing, and (iii) detection. Initially, the required texts from the contextual information are gathered from the standard available data resource. the collected text is subjected to text preprocessing, where the text is cleaned and prepared for further analysis. Finally, in the detection phase, the developed Transformer Residual Bidirectional Long Short-Term Memory (TR-BiLSTM) is employed to learn the effective representation from the preprocessed text and perform the sensitive content detection. Furthermore, performance comparisons are carried out between the proposed frameworks with other standard approaches. the developed architecture achieved better results in detecting the sensitive content from the text. © 2024 IEEE.

关键词： Pre-processing Techniques Sensitive Content Detection Social Media Platforms Transformer Residual Bidirectional Long Short-Term Memory

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Enhancing Steady-State Visual Evoked Potential Brain-computer Interface Performance with Pyramid Squeeze Attention a Deep Learning Approach 6

Enhancing Steady-State Visual Evoked Potential Brain-Compute...

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6th international conference on Electronic engineering and Informatics, EEI 2024

作者： Liu, Junjie Xie, Jun Zhang, Huanqing Yang, Hanlin Wang, Hu Hu, Bo School of Mechanical Engineering Xinjiang University Urumqi China China School of Mechanical Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9798350353594

In the field of human-computer interaction, rapid advancements in brain-computer interface (BCI) technology are catalyzing a new era of barrier-free communication. Particularly, Steady-state visual evoked potential (SSVEP) has become a focal point in non-invasive electroencephalogram (EEG) research due to their reliable response under visual stimuli. However, existing SSVEP signal processing techniques often struggle with signal instability, environmental noise, and fluctuations in physiological and psychological states of users, significantly hindering accurate information extraction and application. interactions among channels in multi-channel EEG analysis are crucial for the extraction and recognition of signal features;yet, traditional methods often fail in adequately handling these complex interactions and do not effectively utilize multi-scale information, leading to a loss of critical feature information and diminished recognition performance. Addressing these limitations in capturing subtle and crucial time-varying features, which are essential for distinguishing various SSVEP tasks, this study introduces a novel deep learning framework-EEGNetPSA. Experimental results on a publicly available dataset of 12 targets demonstrated that EEGN etPSAs-2 and EEGNetPSA2-8 achieved recognition accuracies of 95.30% and 92.88% respectively within I-second time window, significantly surpassing the basic models EEGNets-2 at 86.980/0 and EEGNeh-s at 84.34%. these findings highlight the substantial potential of combining deep learning with multi-scale attention mechanisms. © 2024 IEEE.

关键词： Electroencephalography

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Speech Based computer Control Using CMU Sphinx 8

Speech Based Computer Control Using CMU Sphinx

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8th international conference on Smart Structures and Systems, ICSSS 2022

作者： Nagappan, G. Rohini, N. Saveetha Engineering College India

ISBN: (纸本)9781665497619

Windows Operating System users often face difficulties while operating the computer from a distance where wireless signals start to fall apart. Handling such situations are easier when speech based systems are introduced. Our proposed system solves this problem by recognizing keywords through the microphone and executing appropriate tasks for different applications the user uses. the application replicates keyboard data packets and sending different ones to the keyboard driver based on the input keyword. these Data Packets would help control third party application functions such as Tab Switching and Search input in Browsers, Window shuffle while Multitasking, Navigation, Selection and Search functions in Explorers, Slideshow control for Presentations and Playback controls for Media players, etc. this system could help users to avoid the keyboard interaction in presentation displays and navigations. © 2022 IEEE.

关键词： Wireless communication Navigation Operating systems Keyboards Speech recognition Switches Multitasking

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