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

共 2033 条记录，以下是61-70 订阅

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Using an HCI Perspective to Encourage Young Students to Pursue computer Science and engineering Careers: the "Envisioning the Digital City" Workshop 19th

Using an HCI Perspective to Encourage Young Students to Purs...

引用

19th international-Federation-for-Information-Processing-Technical-Committee-13 (ifip TC13) international conference on human-computer interaction (INTERACT)

作者： Diaz, Paloma Onorati, Teresa Montero, Alvaro Univ Carlos III Madrid Comp Sci Dept Madrid Spain

ISBN: (纸本)9783031616877;9783031616884

In recent decades, the demand for STEM professionals has increased, and consequently, the effort of educational institutions to sponsor their STEM degrees. In the context of a university program promoting STEM careers among high-school students, we designed a workshop for middle and high-school students to show them a different perspective of computing as a pragmatic, social, and people-centered profession. We focus on teaching basic concepts of human-computer interaction (HCI) as part of a problem-solving strategy to offer creative solutions to real problems of real people. the workshop proposes a list of well-known problems in urban environments, like social integration, elderly loneliness, or recycling, and asks the students to solve them envisioning an innovative mobile app by following a design thinking approach and applying several design artifacts, like scenario boards, user personas, thematic cards, and paper-based sketches. the results show that with little or no experience in designing and programming, participants engage in fruitful brainstorming sessions, offer creative solutions, and even implement low-level prototypes.

关键词： Design thinking Design Workshop STEM computer Science & engineering

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MUNE: A Multi-Level User-News Embedding Model for Personalised News Recommendations 24

MUNE: A Multi-Level User-News Embedding Model for Personalis...

引用

8th international conference on computer Science and Artificial Intelligence, CSAI 2024

作者： Long, Haixiang Luo, Xudong School of Computer Science and Engineering Guangxi Key Lab of Multi-Source Information Mining & Security Key Lab of Education Blockchain and Intelligent Technology of Ministry of Education Guangxi Normal University Guangxi Guilin China

ISBN: (纸本)9798400718182

Personalised news recommendation systems are critical for delivering relevant content, but effectively capturing and modelling users’ diverse and evolving interests is challenging. In this paper, we introduce a Multi-level User-News Embedding (MUNE) model for personalised news recommendations. MUNE uses pre-trained BERT embeddings to generate contextual representations, enabling dynamic, multi-level interaction modelling between users and candidate news. It incorporates a Dynamic Multi-Level interaction Attention (DMIA) module for capturing complex interactions and a Dynamic Similarity Unit (DSU) for enhancing feature fusion using cosine similarity and non-linear transformations. Evaluated on large-scale datasets (MIND and EB-NeRD), MUNE significantly outperforms state-of-the-art baselines in key metrics, with ablation studies validating the importance of DMIA and DSU in improving user interest modelling and recommendation quality. MUNE’s integration of multi-level features makes it highly effective in capturing user behaviours and understanding news content. © 2024 Copyright held by the owner/author(s).

关键词： Linear transformations

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Research on A Gesture Recognition Method of Arc Curve 8

Research on A Gesture Recognition Method of Arc Curve

引用

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

作者： Xing, Yiliang Lei, Huajun Hainan College of Software Technology Software Engineering Department Hainan Province Qionghai City China

ISBN: (纸本)9798350335231

Gesture recognition is an important way of human-computer interaction, improving gesture recognition rate is of great significance for human-computer interaction applications. To solve the problems of few categories and low performance of gesture recognition in traditional methods, a new method of gesture recognition based on circular arc curve is proposed in this paper. Firstly, the hand detection arc curve based on geometric characteristics of the hand is constructed. then, key pixels intersecting with the curve are selected, clustered and are divided into different categories according to their spatial adjacency. then spatial angle of key pixels is calculated by vectorial angle method. Finally, number and angle of the categories are used as gesture features, and gesture recognition is based on decision table. Experimental results show that the method has the characteristics of high recognition rate, high performance and good robustness. © 2023 IEEE.

关键词： Gesture recognition

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Renal Irregularities Detection Using Convolutional Neural Network 8th

Renal Irregularities Detection Using Convolutional Neural Ne...

引用

8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Daniel, Rosy Salomi Victoria Rajesh, Ashwin Roberts Saravanan, Gokul Ganeshkumar, Gowtham Kasinathan, Arulan Sabari Department of Computer Science and Engineering Chennai Institute of Technology Kundrathur Chennai600069 India Department of Computer Science and Engineering St. Joseph’s College of Engineering OMR Chennai600119 India

ISBN: (纸本)9783031736162

Renal irregularities are serious medicinal condition that is becoming more common and killing more people each year. In its early stages, renal irregularities are curable, but it can progress irreversibly and result in renal failure. Cyst development, kidney tumours, and stone are the three predominant kidney irregularities that impair renal function among numerous diseases. the prompt detection and treatment of renal disease is a major challenge to the medical community. If renal problems like stones, cysts and tumours are not detected at an early stage, renal failure may ensue. computer-assisted diagnostics is necessary to complement medical assessments made by clinicians and specialists as renal disease is more spread, there are less clinicians accessible, assessment and monitoring rates are rising, especially in developing nations. though they still don’t perform well, artificial intelligence methods like machine and deep learning have been utilized in literature to identify illness. this study uses CNN model for renal disease categorization and prognosis that is based on deep learning. For exploration, we use a benchmark CT kidney dataset from Computed Tomography. CNN first preprocesses the data before extracting the features from the pictures. the suggested method successfully classifies renal illness, with a notable accuracy of 99.3%, 99.5% precision, 95.3% recall, and 9.88% F1-score. © ifip international Federation for Information Processing 2025.

关键词： Convolutional neural networks

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Design of An Adjustable Monitor Arm via Collaborative Robot 8

Design of An Adjustable Monitor Arm via Collaborative Robot

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Wang, Weijun Sun, Wei Liu, Yunfei Liu, Shujian Li, Wenjie Liu, Jian Robotics Engineering Center The 21ST Research Institute of China Electronic Technology Group Corporation Shanghai200233 China Beijing Microelectronics Technology Institute BeijingBJ 100076 China Beijing Institute of Radio Measurement BJ 1000854 China

ISBN: (纸本)9798350300178

With the development of monitor technology, more and more monitor terminals can be controlled by touch. With the continuous development of man-machine interaction, the traditional fixed monitor cannot meet the changing requirements. A collaborative robot is a robotic arm that can interact with people in real time. It is widely used in human-machine interaction scenarios. this paper studies an adjustable monitor arm via collaborative robot (AMACR). On the one hand, this arm needs to have a strong overall capacity to support the weight of the monitor. On the other hand, this arm needs to have compact structure and good human-computer interaction ability. Firstly, a new type of monitor arm is proposed. Secondly, simulations of this robot are performed. Finally, discussion on the prototype is presented. © 2023 IEEE.

关键词： human computer interaction

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Precision Exercise Monitoring through Advanced Body Language Detection Using computer Vision 8th

Precision Exercise Monitoring Through Advanced Body Language...

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8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Balaji, V.S. Sangeetha, K. Ganapathy, P. S. Anirudh Banu, M. Shafiya Kumar, S. Dinesh Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9783031736162

the paper aims to assist individuals in performing physical exercises with precision and safety. this model delivers real-time feedback on an individual’s workout style by utilising powerful computer vision and machine learning technology. It uses deep learning models for position estimation to recognise and track essential body features while exercising. It classifies workouts and their phases, such as "down" and "up," based on a continual monitoring of the user’s body position. Advanced computer vision algorithms are used to analyse video frames from the camera feed in order to extract critical data about the user’s form. It can recognise and classify certain workouts such as the deadlift, squat, and push-up by continually monitoring the user’s body position. the system provides useful information such as the current stage of the exercise, the number of repetitions, and the chance of correct performance. the model can recognize and detect the exercises performed by the person and it also iterates the number of times the exercises are done and it also detects the position of the body of the person. Healthcare professionals who want to promote safe and successful exercise regimens. © ifip international Federation for Information Processing 2025.

关键词： Deep learning

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Research on high precision real-time digital twin model 8

Research on high precision real-time digital twin model

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

作者： Tao, Zhangzhi Li, Yulou Cccc Second Harbor Engineering CO. Ltd NO.5 Branch Hubei Wuhan China

ISBN: (纸本)9798331506230

With the development of digital twin technology, high-precision digital twin technology is becoming increasingly urgent in production practice. this article proposes a high-precision digital twin model construction method for electromechanical actuators based on practical production needs. Firstly, a twin mechanism model was constructed from the aspects of geometry, physics, behavior, and rules. the time-varying transfer function of the electromechanical actuator was established, and the parameters were identified and updated through particle swarm optimization to achieve digital mapping. Secondly, a twin data model was constructed, taking historical data of relevant features as input, and a BP neural network-based input voltage prediction model was constructed. Finally, the accuracy and feasibility of the twin mechanism model were verified through simulation, and the introduced digital twin technology provides a new method for real-time interaction and adjustment between the theoretical model of electromechanical actuators and actual data. © 2024 IEEE.

关键词： Mapping

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human-Centered Software engineering: Rethinking the Interplay of human-computer interaction and Software engineering in the Age of Digital Transformation 19th

Human-Centered Software Engineering: Rethinking the Interpla...

引用

19th international-Federation-for-Information-Processing-Technical-Committee-13 (ifip TC13) international conference on human-computer interaction (INTERACT)

作者： Ardito, Carmelo Bernhaupt, Regina Sauer, Stefan LUM Giuseppe Degennaro Univ Casamassima BA Italy Eindhoven Univ Technol Eindhoven Netherlands Paderborn Univ Paderborn Germany

ISBN: (纸本)9783031422928;9783031422935

Digital transformation is a fundamental change process for improving organizations, industries or society and redefining key values for its stakeholders. Digital transformation represents the transition process that has to be dealt with to innovate organizational processes, to improve their interaction with customers and to offer innovative services that are based on the intensive use of digital technologies. Digital transformation affects the life of end users who can access services in completely new ways, made possible by innovative technologies. Digital transformation is therefore a process of organizational, economic, social and creative change enabled by the adoption and development of digital technologies. human-Centered Software engineering (HCSE) as a research domain is thus more relevant than when it comes to the sole introduction of novel technologies in a socio-technical system. the interplay between human-computer interaction and software engineering needs to be rethought for a rapid response to the evolution of technologies, while also considering aspects such as greater agility in service development, sustainability, ethical considerations, cybersecurity, user mindset and awareness, to name a few. Beyond the traditional themes of ifipWG13.2 workshops, this edition promotes sharing of knowledge and experiences that address how to deal with the challenges of the digital transformation and its influence on human-centered socio-technical system design and development practices.

关键词： digital transformation sustainability agile development low-code development digital twin ethical considerations cybersecurity

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Revelatory Insights into Parkinson’s: Hand Gestures Deciphering with Mobilenet SSD 8th

Revelatory Insights into Parkinson’s: Hand Gestures Deciphe...

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8th ifip TC 12 international conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Balaji, V.S. Sangeetha, K. Anand, V. Aatrey Velayutharaj, J. Abishek Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9783031736162

Hand gestures have evolved into a natural and intuitive means of engaging with technology. Parkinson’s disease is a neurological ailment that worsens with time. Sophisticated deep learning-based system for the precise identification of Parkinson’s Disorder is developed through the interpretation and analysing of hand gestures exhibited by affected individuals. Relevant features are extracted from the images, employing computer vision techniques, enabling the analysis of hand movements. A deep learning model is trained to recognize distinctive motor symptoms associated with the disorder. Object detection algorithms are employed to pinpoint specific deviations in finger and hand positions, thereby quantifying tremors, bradykinesia, and other relevant motor symptoms. the approach lies in the utilisation of a dataset comprising 40 images for each Parkinson’s hand gesture, enabling robust model training. the Mobilenet SSD algorithm for object detection to find the specific deviations in finger and hand positions. the model exhibits a high level of accuracy in distinguishing between individuals with the possibility of Parkinson’s disorder and those without, based on the subtle motor symptoms exhibited in their hand gestures. © ifip international Federation for Information Processing 2025.

关键词： Object detection

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Intelligent Document interaction with Advanced Vector Embeddings and FAISS-CPU Indexing 8

Intelligent Document Interaction with Advanced Vector Embedd...

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8th international conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Sriman, B. Annie Silviya, S.H. Mouleesh, Y. Vinod, S. Nishanthini, S. Nikitha, Polimera Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Computer Science and Engineering Chennai India Rajalakshmi Institute of Technology Computer Science and Engineering Chennai India Rajalakshmi Institute of Technology Computer and Communication Engineering Chennai India Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Computer Science and Engineering Chennai India

ISBN: (纸本)9798350367904

Our research project aims to introduce an artificial intelligence (AI) conversational model that can be used to efficiently communicate with multiple PDF documents. Our solution uses natural language processing algorithms to enable users to have lively conversations with PDFs that have been uploaded. We have built a comprehensive platform that can interpret user queries and provide pertinent responses based on the content of uploaded documents by integrating Python with Streamlit for interface development, FAISSCPU for storage and similarity search, PyPDF2 for text extraction, ChromaDB, Langchain, and Google Gemini Generative AI for enhanced functionality. Our goals include developing a UI that is easy to use, processing documents correctly, and having strong conversational capabilities. © 2024 IEEE.

关键词： Conversational Model Google Gemini Generative AI Natural Language Processing

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