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23rd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024

作者： Guo, Zixuan Xu, Wenge Wang, Hongyu Wan, Tingjie Baghaei, Nilufar Lo, Cheng-Hung Liang, Hai-Ning Xi'an Jiaotong-Liverpool University School of Advanced Technology Suzhou China The University of Liverpool Department of Computer Science Liverpool United Kingdom Birmingham City University College of Computing Birmingham United Kingdom The University of Queensland School of Electrical Engineering and Computer Science Brisbane Australia Xi'an Jiaotong-Liverpool University Department of Industrial Design Suzhou China Computational Media and Arts Thrust Guangzhou China

ISBN: (纸本)9798331516475

Virtual reality (VR) not only allows head-mounted display (HMD) users to immerse themselves in virtual worlds but also to share them with others. When designed correctly, this shared experience can be enjoyable. However, in typical scenarios, HMD users are isolated by their devices, and non-HMD observers lack connection with the virtual world. To address this, our research investigates visually representing observers on both HMD and 2D screens to enhance shared experiences. The study, including five representation conditions, reveals that incorporating observer representation positively impacts both HMD users and observers. For how to design and represent them, our work shows that HMD users prefer methods displaying real-world visuals, while observers exhibit diverse preferences regarding being represented with real or virtual images. We provide design guidelines tailored to both displays, offering valuable insights to enhance co-located shared VR experiences for HMD users and non-HMD observers. © 2024 IEEE.

关键词： Virtual environments

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A Survey Analysis on Decentralized Land Registry System Using Blockchain and Smart Contracts

A Survey Analysis on Decentralized Land Registry System Usin...

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computer Science and Emerging Technologies (CSET), International Conference on

作者： K. Narayanaprakash P. D. Sheba Kezia Malarchelvi Ranjithkumar S Sridevi. R P. Anitha N.Suresh Kumar Department of Computer Science and Engineering Alliance University Anekal Bengaluru Department of Computer Science and Engineering Saranathan College of Engineering Tiruchirappalli India School of Computer Science and Engineering Vellore Institute of Technology Vellore Department of Computer Science and Engineering K.Ramakrishnan College of Engineering(A Utonomous) Trichy India Department of Computer Science and Engineering OASYS institute of technology Pulivalam Trichy School of of Computer Science and Engineering Jain (Deemed-to-be- University) Bangalore India

This study investigates the potential use of blockchain technology and smart contracts to construct a decentralised land registry system. It looks at the problems with traditional land registry systems and provides a technical breakdown of how to create a blockchain-based land registry system. The research also evaluates the countries that have already adopted such systems and discusses the possible adoption of a blockchain-based land register system in India. The implementation of a blockchain-based land registration system, per the research, can increase the security and efficacy of land transactions, reduce fraud and mistakes, and promote economic growth.

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Area and Energy Efficient Method Using AI for Noise Cancellation in Ear Phones

Area and Energy Efficient Method Using AI for Noise Cancella...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), International Conference on

作者： R. Manikandan S. Ramkumar M. Prabhakaran Department of Lean Operations and Systems School of Business and Management Christ (Deemed to be University) Bengaluru Karnataka India Department of Computer Science School of Sciences Christ (Deemed to be University) Bengaluru Karnataka India Department of computer science and engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India

Adaptive filters are suitable for most of the Digital Signal Processing (DSP) applications such as channel equalization, noise cancellation, echo cancellation, channel estimation and system identification. Nowadays due to the advancement in semiconductor technology, the need for Active Noise Cancellation (ANC) headphones in compact devices is increased. The major idea behind this proposed work is to design an area and energy efficient novel adaptive filter suitable for in-ear headphones by combining Normalized Least Mean Square (NLMS) and Block LMS (BLMS). The proposed filter is designed and simulated using Xilinx ISE 13.2. The simulation results shows that the proposed design mitigates the unwanted noises in various frequency bands.

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Netflix Recommendation System by Genre Categories Using Machine Learning 3

Netflix Recommendation System by Genre Categories Using Mach...

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3rd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2025

作者： Thete, Sharda Sumedh Jare, Ramdas Popat Jungare, Minal Bhagat, Gauri Durgule, Sonal Borate, Vishal International Institute of Information Technology Department of Information Technology Pune India Pimpri Chinchwad College of Engineering Ravet Pune India Indira College of Engineering and Management Department of Computer Engineering Pune India Mit Art Design & Technology University Loni Pune India Dit Department of Aids Pimpri Pune India Dr. D. Y. Patil College of Engineering and Innovation Department of Computer Engineering Varale Talegaon Pune India

ISBN: (纸本)9798331543358

The ascent of web-based features, customized content suggestion is one of the basic elements improving client commitment and maintenance. This paper presents a thorough investigation of the Netflix proposal framework, which puts together its forecasts with respect to AI and cooperative separating from conduct information about the watchers' inclinations. It consolidates the two methods into a half breed way to deal with make customized proposals. It further sharpened the framework utilizing the technique of Singular Value Decomposition with upgraded exactness for proposals pertinent to the watcher. This is acknowledged by dynamism by which it is feasible to learn through the models that the watchers' preferences change over the long haul by include designing and procedures in light of profound learning. Consequently, there is arrangement with genuine watcher inclinations at the more exact level. This exploration shows and portrays how these procedures efficiently pursue further developing watcher fulfillment, and consequently fundamentally contribute towards the upper hand of an organization like Netflix, inside the exceptionally cutthroat streaming business sector. The review gives prime thoughts and rules to advance into future headway in regards to the proposal framework in streaming stages. © 2025 IEEE.

关键词： engineering education

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Optimal AoI-based Block Propagation and Incentive Mechanism for Blockchain Networks in Web 3.0

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IEEE Transactions on Cognitive Communications and Networking 2024年

作者： Wen, Jinbo Kang, Jiawen Xiong, Zehui Du, Hongyang Yang, Zhaohui Niyato, Dusit Shen, Meng Jiao, Yutao Zhang, Yang Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology China Guangdong University of Technology School of Automation China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore Hong Kong University Department of Electrical and Electronic Engineering Hong Kong Zhejiang University College of Information Science and Electronic Engineering China Nanyang Technological University College of Computing and Data Science Singapore Beijing Institute of Technology School of Cyberspace Science and Technology China Army Engineering University of PLA College of Communications Engineering China

Web 3.0 is regarded as a revolutionary paradigm that enables users to securely manage data without a centralized authority. Blockchains, which enable data to be managed in a decentralized and transparent manner, are key technologies for achieving Web 3.0 goals. However, blockchain-based Web 3.0 is still in its infancy, such as ensuring block freshness and optimizing block propagation to improve blockchain performance. In this paper, we develop a freshness-aware block propagation optimization framework for Web 3.0. We first propose a novel metric called Age of Block Information (AoBI) based on the concept of age of information to quantify block freshness. AoBI measures the time elapsed from the freshest transaction generation to the completion of block consensus. To make block propagation optimization tractable, we classify miners into five different states and propose a block propagation model for public blockchains inspired by epidemic models. Moreover, considering that the miners are bounded rational, we propose an incentive mechanism based on the evolutionary game for block propagation to improve block propagation efficiency. Numerical results demonstrate that compared with other block propagation mechanisms in public blockchains, the proposed scheme has a higher block forwarding probability, which improves block propagation efficiency and decreases the minimum value of average AoBI. © 2015 IEEE.

关键词： age of information block propagation evolutionary game Web 3.0 wireless networks

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Generative AI for Secure and Privacy-Preserving Mobile Crowdsensing

arXiv

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arXiv 2024年

作者： Yang, Yaoqi Zhang, Bangning Guo, Daoxing Du, Hongyang Xiong, Zehui Niyato, Dusit Han, Zhu College of Communications Engineering Army Engineering University of PLA Nanjing210000 China School of Computer Science and Engineering NTU Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

Recently, generative AI has attracted much attention from both academic and industrial fields, which has shown its potential, especially in the data generation and synthesis aspects. Simultaneously, secure and privacy-preserving mobile crowdsensing (SPPMCS) has been widely applied in data collection/ acquirement due to an advantage on low deployment cost, flexible implementation, and high adaptability. Since generative AI can generate new synthetic data to replace the original data to be analyzed and processed, it can lower data attacks and privacy leakage risks for the original data. Therefore, integrating generative AI into SPPMCS is feasible and significant. Moreover, this paper investigates an integration of generative AI in SPPMCS, where we present potential research focuses, solutions, and case studies. Specifically, we firstly review the preliminaries for generative AI and SPPMCS, where their integration potential is presented. Then, we discuss research issues and solutions for generative AI-enabled SPPMCS, including security defense of malicious data injection, illegal authorization, malicious spectrum manipulation at the physical layer, and privacy protection on sensing data content, sensing terminals' identification and location. Next, we propose a framework for sensing data content protection with generative AI, and simulations results have clearly demonstrated the effectiveness of the proposed framework. Finally, we present major research directions for generative AI-enabled SPPMCS. © 2024, CC BY.

关键词： Privacy-preserving techniques

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Cloud Computing’s Effect on Video Games Streaming

Cloud Computing’s Effect on Video Games Streaming

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： A. Komathi J. Lenin S. Asha A. Suresh M. Suguna C. Srinivasan Department of Computer Science Nadar Saraswathi College of Arts and Science College Theni Tamilnadu India Department of ComputerScience and Engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India Department of Information Technology S.A. Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Siddharth Institute of Engineering & Technology Puttur Andhra Pradesh India Department of Computer Science Vinayaka Mission’s Kirupananda Variyar Arts and Science College Vinayaka Mission’s Research Foundation (DU) Salem Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

The disruptive power of cloud computing is altering the gaming industry. Real-time gaming is now feasible because to advancements in streaming algorithms, further blurring the lines between the digital and physical worlds. Understanding the potential of Cloud computing to change the gaming industry is the emphasis which investigates the complicated relationship between numerous technologies. By using cutting-edge streaming protocols and techniques like Adaptive Bitrate Streaming (ABS), buffering, caching, and compression, users may have uninterrupted, high-quality gaming experiences. The study’s findings herald a new era of interactive entertainment and shed light on the transformative possibilities of these technologies. Asynchronous Bit-Rate (ABR) encoding, buffering, caching algorithms, video compression standards, and streaming protocols are just few of the numerous digital components that work together to provide uninterrupted data transmission. The rapid progress of ABR algorithms has made it possible to dynamically alter video quality to maximize the user experience across a broad variety of network scenarios. Buffering and caching algorithms play crucial roles by proactively managing data flow and storage to avoid disruptions in the streaming experience.

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Revolutionizing Healthcare With Cloud Computing: The Impact of Clinical Decision Support Algorithm

Revolutionizing Healthcare With Cloud Computing: The Impact ...

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Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), International Conference on

作者： J. Lenin A. Komathi Hima Vijayan Anantha Raman Rathinam A. Kasthuri C. Srinivasan Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India Department of Computer Science Nadar Saraswathi College of Arts and Science College Theni Tamilnadu India Department of Information Technology S.A. Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering KL University Vijayawada Andhra Pradesh India Department of Computer Science and Engineering Vinayaka Mission's Kirupananda Variyar Engineering College Vinayaka Mission's Research Foundation (DU) Salem Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

The integration of cutting-edge technology, such as cloud computing and Clinical Decision Support (CDS) algorithms, is radically altering the healthcare system. This research digs into how Inference Engines, Bayesian Networks, Machine Learning Algorithms, and Natural Language Processing (NLP) have all played critical roles in reshaping the healthcare industry. Medical professionals may more efficiently use CDS algorithms thanks to cloud-based technologies that streamline data storage, sharing, and processing. Decision-making is aided by Inference Engines because they provide organized insights based on preset criteria. This is where Bayesian Networks come in, with their ability to represent complicated, probabilistic interactions among variables for exact diagnoses and risk assessment. Machine learning algorithms improve predictive analysis by identifying trends in large datasets, paving the way for more individualized approaches to medical care. Chatbots and sentiment analysis are only two examples of how NLP is transforming the doctor-patient relationship by teaching computers to understand human language. Those in the medical field may greatly increase their diagnostic precision, treatment efficiency, and patient outcomes by adopting these innovations.

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Vr-Hmt: Virtual Reality-Driven Human Motion Tracking System via Mask Rcnn for Real-Time Monitoring

Vr-Hmt: Virtual Reality-Driven Human Motion Tracking System ...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Kannan R Suguna T Sivasubramanian R Bhuvanesh A Vemulapalli Sri Lakshmi Harshitha Kulwant Singh Chellam S Ahilan Appathurai Department of Electrical and Electronics Engineering Nehru Institute of Engineering and Technology Coimbatore India Department of Information Technology Government College of Technology Coimbatore Tamil Nadu India Department of AIML Malla Reddy University Dulapally Hyderabad India Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tirunelveli India Department of BE Computer Science and Design Rmk Engineering College (An Autonomous College) Kavaraipettai Tamil Nadu India Yadavindra Department of Engineering Electronics And Communication Engineering Punjabi University Guru Kashi Campus Department of Electrical and Electronics Engineering Velammal College of Engineering and Technology Madurai Tamil Nadu India Department of Electronics and Communication Engineering PSN College of Engineering and Technology Tirunelveli Tamilnadu India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Human motion tracking (HMT) is capturing and analyzing the movement of individuals and objects, focusing on their location, speed, and acceleration. It is used in various fields including filmmaking, animation, sports analysis, robotics, and augmented reality. Unauthorized physical access to facilities presents significant challenges for organizations as it can result in theft, sabotage, and data breaches, these incidents lead to financial losses, and compromised sensitive information. To overcome these challenges, a novel virtual reality (VR) based XXX system has been proposed for tracking human motion to identify any suspicious activity within an organization. The system uses various sensors such as cameras and motion sensors to capture real-world activity in a monitored space. These sensors capture continuous video, which has been converted into frames for further processing. The bilateral filter is used as a pre-processing step to minimize sound while maintaining edges in the frames. The Mask R-CNN model is used for HMT from the frames assigns bounding boxes around each detected human and predicts segmentation masks on each detected frame. The tracking data is stored in a database server and displayed on a large screen to observe the environment. The processed data is further transferred to an application server which serves as a control unit for managing the data and coordinating with the central platform. According to the result, the proposed model attains a 98.45% accuracy rate for human motion tracking. The proposed XXX model achieves an overall accuracy of 2.18%, 8.99%, and 1.47% compared to the existing method such as DBSCAN, cluster segmentation, and k-fold cross-validation.

关键词： Solid modeling Accuracy Tracking Motion segmentation Organizations Predictive models Sensor systems Sensors Servers Monitoring

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AI Based Variable Step Size Block Least Mean Square Filter for Noise Cancellation System

AI Based Variable Step Size Block Least Mean Square Filter f...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), International Conference on

作者： R. Manikandan K. Sathesh Kumar S. Ramkumar Department of Lean Operations and Systems School of Business and Management Christ (Deemed to be University) Bengaluru Karnataka India Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India Department of Computer Science School of Sciences Christ (Deemed to be University) Bengaluru Karnataka India

Most of the Active Noise Cancellation (ANC) systems working properly in low-frequency noises only. To make it suitable for isolating high-frequency noise, it needs an additional circuit which consumes more energy. This problem is mitigated in this study by designing a Variable Step size Block Least Mean Square (VSBLMS) filter which is suitable for an effective noise cancellation system. VSBLMS filter is designed with RCA to make a design area efficient and it is designed with a novel adder to achieve high speed as well as less energy consumption. The proposed filter is designed and simulated using Xilinx ISE 13.2. The simulation results shows that the proposed VSBLMS filter design mitigates the unwanted noises in various frequency bands. The proposed VSBLMS reduces the energy consumption by 9.32%, 27.63%, 13.53%, 11.80%, 10.71 %, 13.14% and 9.26% when compared with state of the art methods.

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