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检索条件"任意字段=9th International Conference on Computer Aided Design and Computer Graphics"

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Collaborative design and Creation of Digital Sculpture Based on Augmented Reality Technology 24

Collaborative Design and Creation of Digital Sculpture Based...

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9th international conference on Cyber Security and Information Engineering, ICCSIE 2024

作者： Zheng, Yanmin Sculpture Department School of Fine Arts Minjiang University China

ISBN: (纸本)9798400718137

Traditional digital sculpture research is limited to computer-generated 3D models, which restricts creative freedom and collaboration. In this paper, AR (Augmented Reality) technology is used to improve the creation of digital sculpture, improve the cooperation efficiency of artists and designers, and expand the creation possibility. First of all, ARCore technology can be integrated into the user interface of Unity3D engine design platform to realize digital sculpture display in virtual environment. Secondly, through real-time data synchronization and communication, multiple users can collaborate in the same virtual environment. Finally, the productivity of the creators on the platform can be measured. the evaluation results showed that the creation time of digital sculpture based on AR technology was reduced by about 63.3% compared with traditional methods, and the average quality assessment of 287 professional judges for eight different digital sculpture works was 8.75. the results show that the AR technology adopted in this paper can effectively expand the field of digital engraving creation and provide artists with more creative freedom and collaboration opportunities. © 2024 Copyright held by the owner/author(s).

关键词： Virtual environments

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Learning with Pedagogical Agent: Effects of Transfer of Information Function 9th

Learning with Pedagogical Agent: Effects of Transfer of Info...

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9th international conference on Human Aspects of IT for the Aged Population, ITAP 2023, held as part of the 25th international conference on Human-computer Interaction, HCII 2023

作者： Xu, Linran Li, Xingmiao Tang, Naimi Wang, Hefeng Liao, Manqiu Liu, Na School of Digital Media and Design Arts Beijing University of Posts and Telecommunications Beijing China International School Beijing University of Posts and Telecommunications Beijing China School of Economics and Management Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9783031348655

In order to investigate the effect of the transfer of information function of instructional agents on learning and whether different combinations of pedagogical agents’ functions are more conducive to learning than single-function agents, we designed a one-factor within-subject design experiment to explore the effect of pedagogical agent functions (motivational, information transfer, and combined functions) on learners’ learning outcomes and subjective perceptions (social presence perception, role perception, and self-efficacy). Obtained data were analyzed by repeated measures ANOVA. Results confirmed that the presence of pedagogical agents with particular functions significantly improved the learning outcomes and self-efficacy. And the transfer of information function of pedagogical agents is more conducive to learning than motivation function. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Functions of Agent Learning Outcomes Pedagogical Agent Social Agency theory

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Transfer Learning Enabled CAD System for Monkey Pox Classification 9

Transfer Learning Enabled CAD System for Monkey Pox Classifi...

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9th IEEE international conference on Internet of things - Systems, Management and Security (IOTSMS)

作者： AlZu'bi, Shadi AbuShanab, Samai AlMi'ani, Muder M. Mughaid, Ala Al Zaytoonah Univ Jordan Fac Sci & Informat Technol Amman Jordan Gulf Univ Sci & Technol Dept Management Informat Syst Kuwait Kuwait Hashemite Univ Fac Prince Al Hussien Bin Abdullah IT POB 330127 Zarqa Jordan

ISBN: (纸本)9798350320459

Skin disease diagnosis using modern artificial intelligence (AI) approaches proved impressive results in classifying diseases compared to dermatologists. Employing AI techniques in computer- aided diagnosis systems will helps in self-identification using intelligent nodes in healthcare facilities. Convolutional Neural Networks (CNN) have been employed by many previous researchers for skin lesion classification. In this work, the use of several Transfer Learning will be introduced for classifying monkey pox from other skin diseases. Even though deep learning (DL) and Transfer Learning (TL) have advantages over a dermatologist, they also have significant weaknesses, such as the potential to incorrectly identify photos in some cases. the achieved results conclude the best environment and techniques for diagnosing monkey pox from other skin diseases. Accuracy, loss, precision, recall, and F1 score will be used to assess the suggested system's performance. Using TL in Keras and computer vision models, the system successfully diagnoses 3 distinct types of skin illnesses with an accuracy rate of 99.3 %. the best model was InceptionResNetV2 with exponents with epoch 50 and Adam optimizer.

关键词： Monkey Pox computer Added Diagnosis Health Intelligence Smart Health Skin Disease Classification Transfer Learning

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Cutting-Edge Travel Planner: Intelligent Route Recommendation System using Enhanced Learning Scheme with AI Principles 9

Cutting-Edge Travel Planner: Intelligent Route Recommendatio...

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9th international conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Gladiss Merlin, N.R. Anandakumar, D. Devilavanya, S. Kumari, P.K. Sheela Shantha Jayakumar, T. R.M.K Engineering College Department of Ai&ds Chennai Kavarapettai India Nandha Engineering College Department of Ece Erode India Dr. Mahalingam College of Engineering And Technology Department of Computer Science And Engineering Pollachi India VeltechHightech Dr Rangarajan Dr Sakunthala Engineering College Department of Cse Chennai Avadi India Kcg College of Technology Department of Mechatronics Engineering Chennai India

ISBN: (纸本)9798350365092

A route planner is crucial as it optimizes travel efficiency, minimizes time and fuel consumption, and enhances overall navigation convenience and safety. this paper presents the design and implementation of CollabRouteNet, an intelligent route recommendation system that leverages collaborative filtering and reinforcement learning principles. the proposed model aims to provide personalized and contextually relevant route recommendations tailored to individual user preferences and dynamic environmental conditions. Collaborative filtering techniques are employed to analyze user interactions and discern patterns within historical route data. this involves constructing a user-item matrix and applying matrix factorization to learn latent representations for users and routes. In parallel, reinforcement learning is utilized to optimize route recommendations in real-time by defining the problem as a Markov Decision Process (MDP) and training an agent to learn an optimal route selection policy. the model balances exploration and exploitation to adaptively recommend routes that optimize user satisfaction and navigation efficiency. Implemented in PyCharm, the CollabRouteNet model demonstrates promising results in providing accurate and responsive route recommendations. through its integrated approach, CollabRouteNet offers a promising solution for enhancing navigation experiences in diverse urban and rural settings. © 2024 IEEE.

关键词： Reinforcement learning

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9th EAI international conference on IoT as a Service, IoTaaS 2023

9th EAI International Conference on IoT as a Service, IoTaaS...

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9th EAI international conference on IoT as a Service, IoTaaS 2023

ISBN: (纸本)9783031705069

the proceedings contain 33 papers. the special focus in this conference is on IoT as a Service. the topics include: Highway Obstacle Recognition Based on Improved YOLOv7 and Defogging Algorithm;cloud Gaming Resource Management Platform Based on Edge Intelligence;hardware-Efficient Polar Decoder for 5G Internet of things Communication;design and Optimization of a Solar-Powered IRS and Relay Assisted MEC System;highway Image Enhancement Method Based on Jade;method and Practice of Borehole Group Detection in Borehole Drilling Based on Six-Axis Sensing;Deep Reinforcement Learning-Based Channel and Power Allocation in Multibeam LEO Satellite Systems;CSI-Based Signal Reconstruction for WiFi Localization;an Indoor Navigation Algorithm Using Multi-dimensional Euclidean Distance and the Adaptive Particle Filter;Research on the PID Controllers Algorithm of the Quad Rotor;Based on the Nonlinear State Equations of 6-DOF Robot with Application to Autonomous Flight;a Study on Collaborative Lane Change Decision Making of Multi-automated Vehicles Based on Deep Graph Reinforcement Learning;a Short Term Traffic Prediction Model Based on Deep Capture of Temporal Periodic Drift;multi-agent Reinforcement Learning for Cooperative On-Ramp Merging of Connected Automated Vehicles;SVM Multi-class Classification Method for Device Identification Using Eye Diagram Parameters;users Collaborative Computing for Hierarchical Federated Learning Based on Incentive Mechanism;spatio-Temporal Traffic Prediction of Wireless Communication Network Based on Multi-source Data;flying Ad-Hoc Network Routing Protocol Based on Backward Algorithm;A Novel HPSO-IGWO Algorithm for Rapidly Searching Optimal Fire Rescue Paths Based on IoT Architecture;A Hybrid WOA-MTCNN Algorithm for Accurate Face Detection Based on IoT Architecture.

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A Robust design of Fault Nodes Identification and Recovery Model Over Wireless Sensor Network 9

A Robust Design of Fault Nodes Identification and Recovery M...

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9th international conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Vijaya Vardan Reddy, S.P. Kishore, V. Vijaya Diwakaran, S. Sujatha, V. Jayakumar, T. R.M.K Engineering College Department of Ece Chennai Kavarapettai India Department of Ece Andhra Pradesh Kavarapettai India Kalasalingam Academy of Research And Education Department of Ece Srivilliputhur India S.A.Engineering College Department of Master of Computer Applications Chennai India Kcg College of Technology Department of Mechatronics Engineering Chennai India

ISBN: (纸本)9798350365092

From environmental monitoring to industrial automation, wireless sensor networks (WSNs) are essential in many different applications. However, the reliability and robustness of WSNs are often compromised by faults such as node failures, communication disruptions, and data packet losses. this paper presents a comprehensive approach to fault management in WSNs, encompassing fault detection, localization, and recovery strategies. In the fault detection phase, machine learning techniques, including the utilization of the MobileNet model, are employed to classify normal and faulty behavior based on sensor data. Statistical analysis methods, such as hypothesis testing, complement machine learning approaches to detect anomalies in sensor readings. A hybrid approach combining machine learning with rule-based systems enhances fault detection accuracy. Subsequently, fault localization techniques leverage network topology analysis and localization algorithms to identify the location of faulty nodes within the network. By analyzing the connectivity between nodes and potential communication paths, vulnerable areas are pinpointed, facilitating efficient fault localization efforts. In the fault recovery phase, dynamic reconfiguration algorithms dynamically adjust network routing and data aggregation strategies in response to detected faults. Redundancy mechanisms, dynamic reconfiguration, and load balancing techniques are deployed to mitigate the impact of node failures and ensure uninterrupted data flow. © 2024 IEEE.

关键词： Fault detection

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Identification of Sukun (Artocarpus altilis) and Kluwih (Artocarpus camansi) Leaves using Transfer Learning 9

Identification of Sukun (Artocarpus altilis) and Kluwih (Art...

引用

9th IEEE international conference on Computing, Engineering and design, ICCED 2023

作者： Pratondo, Agus Ismail, Nanang Sujana, Aprianti Putri Novianty, Astri Telkom University School of Applied Sciences Department of Multimedia Engineering Bandung Indonesia UIN Sunan Gunung Djati Faculty of Engineering Dept. of Electrical Engineering Bandung Indonesia Telkom University School of Electrical Engineering Department of Computer Engineering Bandung Indonesia

It9;s critical to correctly identify Sukun (Artocarpus altilis) and Kluwih (Artocarpus camansi) leaves to avoid misunderstandings about their traditional medical use and to prevent fraud in the sale of plant seedli... 详细信息

ISBN: (纸本)9798350370126

It's critical to correctly identify Sukun (Artocarpus altilis) and Kluwih (Artocarpus camansi) leaves to avoid misunderstandings about their traditional medical use and to prevent fraud in the sale of plant seedlings. this study uses the well-known deep-learning algorithms VGG16 and Inception v3 to identify Sukun and Kluwih leaves. A varied collection of leaf photos in a range of sizes was gathered and used in the experiment. the results of the experiment demonstrate how profoundly useful deep learning is at identifying leaves. A remarkable accuracy rate of 99.52 percent was demonstrated by the VGG16 and Inception v3 models. the models' dependability for practical, real-world applications is highlighted by this level of accuracy. Due to the excellent accuracy attained by both models, it can be concluded that they are suitable for practical applications such as preventing the improper use of leaves and preventing potential fraud in the trading of plant saplings. the work underlines the viability of adopting these models to address relevant societal concerns while showcasing the promise of deep learning approaches in botanical classification. © 2023 IEEE.

关键词： Learning algorithms

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Security and Privacy in Internet of things (IoT) Environments 9

Security and Privacy in Internet of Things (IoT) Environment...

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9th international conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Bhoomadevi, A. Soundarraj, Prem Latha Gupta, Vishnu Kumaravel, Sathish Kumar Deivasigamani, Sudhakar Kumar, Ankit Amity Institute of Public Health & Hospital Administration Amity University Noida201303 India School of Business And Management Christ University Lavasa Maharashtra Pune412112 India Mahatma Gandhi Kashi Vidyapith Department of Commerce Varanasi India Mathematics Vel Tech Rangarajan Dr. Sagunthala R And D Institute of Science And Technology TamilNadu Chennai India Digipulse Technologies Inc 811 Church Road Suite 169 NJ08002 United States Swami Vivekanand Subharti University Department of Computer Application Faculty of Science Meerut India

ISBN: (纸本)9798350365092

Although the proliferation of IoT devices has led to unparalleled ease of use and accessibility, it has also raised serious privacy and safety issues. Using a systematic approach that incorporates security and privacy modelling, data analysis, and empirical trials, this study provides a deep dive into the topic of IoT security and privacy. Our results show how crucial it is to take precautions against 'Information Disclosure' by using strong encryption and authorization protocols. the need to protect against 'Unencrypted Data' vulnerabilities is further emphasized by vulnerability analysis. Encryption (AES-256) and other access control rules fare very well in the assessment of security systems. Furthermore, 'Homomorphic Encryption' is identified as a potential strategy to protecting user privacy while retaining data usefulness based on our review of privacy preservation strategies. A more secure and privacyaware IoT environment may be fostered thanks to the findings of this study, which have ramifications for the industry, government, consumers, and academics. Addressing the ever-evolving security and privacy issues in the IoT will need a future focus on cutting-edge security mechanisms, privacy-preserving technology, regulatory compliance, user-centric design, multidisciplinary cooperation, and threat intelligence sharing. © 2024 IEEE.

关键词： Internet of things

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Enabling Flexible Architectural design Re-representations Using a Phenotype-Based Strategy 20th

Enabling Flexible Architectural Design Re-representations Us...

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20th international conference on computer-aided Architectural design Futures, CAAD Futures 2023

作者： Ling, Ban Liang Tunçer, Bige Singapore University of Technology and Design Singapore Singapore

ISBN: (纸本)9783031371882

Architectural design is driven by qualitative variables like spatial aesthetics and geometry appreciation. At the early explorative stage, flexible re-representation of information is used to discover design solutions. However, in computational design, current data management methods are constrained by genotype and performance representations. these strategies do not enable a similar level of flexibility. As such, this paper presents a phenotype-based strategy that allows design logic to be transferred between computational design processes. Across different design spaces, similar phenotypes can be bridged based on their appearance. this will be demonstrated using room footprints and daylight distribution results which are represented using Elliptical Fourier descriptors and Gabor filters. this enables flexible re-representations as the algorithm can now appreciate geometrical properties. Examples to demonstrate design logic transfer, which are guided by the phenotype space, will be covered in two different scenarios: 1) in a search scenario—where the search direction of an unexplored design space is influenced by learnings from an explored design space, and 2) in a scenario where all design spaces are explored—the data structure and possibilities afforded to new search scenarios. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Architectural design

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Interactive design Method of Multi Person VR Distance Education for New Media Art Teaching 9th

Interactive Design Method of Multi Person VR Distance Educat...

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9th EAI international conference on e-Learning, e-Education, and Online Training, eLEOT 2023

作者： Xu, Ya Zhao, Yan Modern College of Northwest University Xi’an710130 China

ISBN: (纸本)9783031514678

In order to solve the problem of limited number of online people in the teaching of new media art majors, this research focuses on the Interaction design method of multi person VR distance education, and is committed to creating a more authentic multi person VR interactive education environment. Firstly, by improving the "dominant subject" teaching structure of new media, we aim to enhance teaching effectiveness and participation. By selecting key application technologies, determine the real-time connection status of the teaching project editor, and then define the connection conditions of the education editor for teaching new media art majors. Secondly, a multi person teaching scenario was designed, and with the help of VR remote education editor components, response objects at all levels of terminals were retrieved to construct an interactive scenario model. this design can achieve a multi person VR remote education interaction method for teaching new media art majors, providing students with a more realistic and immersive teaching experience. Finally, the effectiveness of the above method was demonstrated through experiments. the experimental results show that the application of the above methods can significantly increase the number of remote online people in the teaching task of the new media art specialty, and meet the practical application needs of creating a real multi person VR interactive education environment. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： design

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