检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Xu, Minrui Ng, Wei Chong Lim, Wei Yang Bryan Kang, Jiawen Xiong, Zehui Niyato, Dusit Yang, Qiang Shen, Xuemin Sherman Miao, Chunyan The School of Computer Science and Engineering Nanyang Technological University Singapore Alibaba Group Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Webank China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Dubbed "the successor to the mobile Internet", the concept of the Metaverse has grown in popularity. While there exist lite versions of the Metaverse today, they are still far from realizing the full vision of an immersive, embodied, and interoperable Metaverse. Without addressing the issues of implementation from the communication and networking, as well as computation perspectives, the Metaverse is difficult to succeed the Internet, especially in terms of its accessibility to billions of users today. In this survey, we focus on the edge-enabled Metaverse to realize its ultimate vision. We first provide readers with a succinct tutorial of the Metaverse, an introduction to the architecture, as well as current developments. To enable ubiquitous, seamless, and embodied access to the Metaverse, we discuss the communication and networking challenges and survey cutting-edge solutions and concepts that leverage next-generation communication systems for users to immerse as and interact with embodied avatars in the Metaverse. Moreover, given the high computation costs required, e.g., to render 3D virtual worlds and run data-hungry artificial intelligence-driven avatars, we discuss the computation challenges and cloud-edge-end computation framework-driven solutions to realize the Metaverse on resource-constrained edge devices. Next, we explore how blockchain technologies can aid in the interoperable development of the Metaverse, not just in terms of empowering the economic circulation of virtual user-generated content but also to manage physical edge resources in a decentralized, transparent, and immutable manner. Finally, we discuss the future research directions towards realizing the true vision of the edge-enabled Metaverse. © 2022, CC BY.

关键词： Blockchain

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Semantic Communications for Future Internet: Fundamentals, applications, and Challenges

arXiv

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arXiv 2022年

作者： Yang, Wanting Du, Hongyang Liew, Zi Qin Lim, Wei Yang Bryan Xiong, Zehui Niyato, Dusit Chi, Xuefen Shen, Xuemin Sherman Miao, Chunyan The Department of Communications Engineering Jilin University Changchun130012 China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore The School of Computer Science and Engineering The Energy Research Institute Ntu Interdisciplinary Nanyang Technological University Singapore Singapore Alibaba Group The Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Singapore School of Computer Science and Engineering Ntu Singapore Singapore The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada The School of Computer Science and Engineering Nanyang Technological University Singapore Singapore The Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Singapore The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University Singapore Singapore

With the increasing demand for intelligent services, the sixth-generation (6G) wireless networks will shift from a traditional architecture that focuses solely on a high transmission rate to a new architecture that is based on the intelligent connection of everything. Semantic communication (SemCom), a revolutionary architecture that integrates user as well as application requirements and the meaning of information into data processing and transmission, is predicted to become a new core paradigm in 6G. While SemCom is expected to progress beyond the classical Shannon paradigm, several obstacles need to be overcome on the way to a SemCom-enabled smart wireless Internet. In this paper, we first highlight the motivations and compelling reasons of SemCom in 6G. Then, we provide an overview of SemCom-related theory development. After that, we introduce three types of SemCom, i.e., semantic-oriented communication, goal-oriented communication, and semantic-aware communication. Following that, we organize the design of the communication system into three dimensions, i.e., semantic information (SI) extraction, SI transmission, and SI metrics. For each dimension, we review existing techniques and discuss their benefits and limitation, as well as the remaining challenges. Then, we introduce the potential applications of SemCom in 6G and portray the vision of future SemCom-empowered network architecture. Finally, we outline future research opportunities. In a nutshell, this paper provides a holistic review of the fundamentals of SemCom, its applications in 6G networks, and the existing challenges and open issues with insights for further in-depth investigations. Copyright © 2022, The Authors. All rights reserved.

关键词： Network architecture

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Semantic communication meets edge intelligence

arXiv

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arXiv 2022年

作者： Yang, Wanting Liew, Zi Qin Lim, Wei Yang Bryan Xiong, Zehui Niyato, Dusit Chi, Xuefen Cao, Xianbin Letaief, Khaled B. Department of Communications Engineering Jilin University Changchun130012 China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore Alibaba Group Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Singapore School of Computer Science and Engineering NTU Singapore Singapore School of Electronic and Information Engineering Beihang University Beijing China Hong Kong Hong Kong

The development of emerging applications, such as autonomous transportation systems, are expected to result in an explosive growth in mobile data traffic. As the available spectrum resource becomes more and more scarce, there is a growing need for a paradigm shift from Shannon's Classical Information Theory (CIT) to semantic communication (SemCom). Specifically, the former adopts a "transmit-before-understanding" approach while the latter leverages artificial intelligence (AI) techniques to "understand-before-transmit", thereby alleviating bandwidth pressure by reducing the amount of data to be exchanged without negating the semantic effectiveness of the transmitted symbols. However, the semantic extraction (SE) procedure incurs costly computation and storage overheads. In this article, we introduce an edge-driven training, maintenance, and execution of SE. We further investigate how edge intelligence can be enhanced with SemCom through improving the generalization capabilities of intelligent agents at lower computation overheads and reducing the communication overhead of information exchange. Finally, we present a case study involving semantic-aware resource optimization for the wireless powered Internet of Things (IoT). Copyright © 2022, The Authors. All rights reserved.

关键词： Resource allocation

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Movement Detection Controller for Customized Smart Automation

Movement Detection Controller for Customized Smart Automatio...

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Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Kushagra Kulshreshtha Sandeep Bisht Jejji Singh Arora Muntather Almusawi Urinbaev Sharofiddin Vinay Kandpal Institute of Business Management GLA University Mathura India School of Management Graphic Era Hill University Uttarakhand India Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges Jhanjeri Mohali Punjab India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University Tashkent Uzbekistan Western Caspian University Scientific Researcher Baku Azerbaijan Department of Management Studies Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

Intelligent settings, including smart houses, are becoming easier to create because to recent advancements in internet of things and declining sensor costs. Smart homes have the potential to enhance people's lives, freedom, and health by offering home support services, particularly for older people and people in need of care. Smart houses need to be able to comprehend its residents' everyday activities in order to provide these features. The ability to recognize human movement in intelligent dwellings is becoming more advanced every day. But fresh issues crop up every day. This article describes the latest algorithms, achievements, problems, and taxonomies in the field of identifying human activities in smart homes using environmental sensors. Furthermore, since activity recognition in automated homes is an emerging topic, we identify not only unique problems but also important missed contributions. It also provides guidance, research opportunities, and solutions to advance the development of this field.

关键词： Taxonomy Layout Smart homes Hardware Energy efficiency Telecommunication computing Internet of Things Human activity recognition Reliability Population density

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Model Checking Quantum Continuous-Time Markov Chains 32

Model Checking Quantum Continuous-Time Markov Chains

引用

32nd International Conference on Concurrency Theory, CONCUR 2021

作者： Xu, Ming Mei, Jingyi Guan, Ji Yu, Nengkun MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Lab of Trustworthy Computing East China Normal University Shanghai China Shanghai Key Lab of Trustworthy Computing East China Normal University Shanghai China State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney Australia

ISBN: (纸本)9783959772037

Verifying quantum systems has attracted a lot of interests in the last decades. In this paper, we initialise the model checking of quantum continuous-time Markov chain (QCTMC). As a real-time system, we specify the temporal properties on QCTMC by signal temporal logic (STL). To effectively check the atomic propositions in STL, we develop a state-of-the-art real root isolation algorithm under Schanuel's conjecture;further, we check the general STL formula by interval operations with a bottom-up fashion, whose query complexity turns out to be linear in the size of the input formula by calling the real root isolation algorithm. A running example of an open quantum walk is provided to demonstrate our method. © Ming Xu, Jingyi Mei, Ji Guan, and Nengkun Yu;.

关键词： Model checking

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A Comprehensive Survey of Few-shot Learning: Evolution, applications, Challenges, and Opportunities

arXiv

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arXiv 2022年

作者： Song, Yisheng Wang, Ting Mondal, Subrota K. Sahoo, Jyoti Prakash The Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education The Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China The Faculty of Information Technology Macau University of Science and Technology Macao China The Department of Computer Science & Information Technology Institute of Technical Education and Research Siksha 'o' Anusandhan University India

Few-shot learning (FSL) has emerged as an effective learning method and shows great potential. Despite the recent creative works in tackling FSL tasks, learning valid information rapidly from just a few or even zero samples still remains a serious challenge. In this context, we extensively investigated 200+ latest papers on FSL published in the past three years, aiming to present a timely and comprehensive overview of the most recent advances in FSL along with impartial comparisons of strengths and weaknesses of the existing works. For the sake of avoiding conceptual confusion, we first elaborate and compare a set of similar concepts including few-shot learning, transfer learning, and meta-learning. Furthermore, we propose a novel taxonomy to classify the existing work according to the level of abstraction of knowledge in accordance with the challenges of FSL. To enrich this survey, in each subsection we provide in-depth analysis and insightful discussion about recent advances on these topics. Moreover, taking computer vision as an example, we highlight the important application of FSL, covering various research hotspots. Finally, we conclude the survey with unique insights into the technology evolution trends together with potential future research opportunities in the hope of providing guidance to follow-up research. © 2022, CC BY.

关键词： Surveys

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CHECKING CONTINUOUS STOCHASTIC LOGIC AGAINST QUANTUM CONTINUOUS-TIME MARKOV CHAINS

arXiv

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arXiv 2022年

作者： Mei, Jingyi Xu, Ming Guan, Ji Deng, Yuxin Yu, Nengkun Shanghai Key Lab of Trustworthy Computing East China Normal University China Shanghai Key Lab of Trustworthy Computing & MoE Engineering Research Center of Software/Hardware Co-design Technology and Application East China Normal University China State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences China Department of Computer Science Stony Brook University United States

Verifying quantum systems has attracted a lot of interest in the last decades. In this paper, we study the quantitative model-checking of quantum continuous-time Markov chains (quantum CTMCs). The branching-time properties of quantum CTMCs are specified by continuous stochastic logic (CSL), which is famous for verifying real-time systems, including classical CTMCs. The core of checking the CSL formulas lies in tackling multiphase until formulas. We develop an algebraic method using proper projection, matrix exponentiation, and definite integration to symbolically calculate the probability measures of path formulas. Thus the decidability of CSL is established. To be efficient, numerical methods are incorporated to guarantee that the time complexity is polynomial in the encoding size of the input model and linear in the size of the input formula. A running example of Apollonian networks is further provided to demonstrate our method. © 2022, CC BY.

关键词： Stochastic systems

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Meta: Data Compression and Event Detection Grand Challenge 2024 With SPRSound Dataset

IEEE Data Descriptions

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IEEE Data Descriptions 2024年 1卷 122-130页

作者： Qing Zhang Changyan Chen Shuhua Yuan Jing Zhang Jiajun Yuan Huajie Huang Yuhang Zhang Rui Pan Xuya Jiang Jian Zhao Yongfu Li Yong Yin Liebin Zhao Guoxing Wang Yong Lian Department of Micro-Nano Electronics and MoE Key Laboratory of Artificial Intelligence Shanghai Jiao Tong University Shanghai China Shanghai Engineering Research Center of Intelligence Pediatrics Shanghai China The Pediatric AI Clinical Application and Research Center Shanghai Children’s Medical Center Shanghai Jiao Tong University School of Medicine Shanghai China Department of Respiratory Medicine Shanghai Children’s Medical Center Shanghai Jiao Tong University School of Medicine Shanghai China Child Health Advocacy Institute China Hospital Development Institute Shanghai Jiao Tong University Shanghai China School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Children’s Medical Center School of Medicine Shanghai Jiao Tong University Sanya China School of Design Jiangnan University Wuxi China

The development of digital stethoscopes and automatic respiratory sound algorithms is crucial for accelerating diagnosis, reducing physician workload, and lowering mortality rates from respiratory diseases. However, transmitting data from digital stethoscopes to cloud or other storage devices require substantial storage and transmission capacities, especially for wearable devices used for long-term monitoring. Besides, current automatic algorithms often predict labels for segmented sound events, lacking precision in detecting the onsets and offsets of respiratory sound events. To address these challenges, we organized a grand challenge inviting the community to develop data compression and event detection algorithms to reduce the storage and transmission burden and event segmentation workload. A new testing set was prepared to evaluate the performance of the submissions. The top teams presented their work at the 20th IEEE Biomedical Circuits and Systems Conference (BioCAS) 2024. IEEE SOCIETY/COUNCIL Circuits and Systems (CAS) Society DATA TYPE/LOCATION Sound and Text; Worldwide DATA DOI/PID 10.21227/bhw7-2044; 10.21227/nfkk-1x47

关键词： Event detection Medical diagnostic imaging Predictive models Data compression Training Stethoscope Pulmonary diseases Pediatrics Error analysis Circuits and systems

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PURSUhInT: In Search of Informative Hint Points Based on Layer Clustering for Knowledge Distillation

arXiv

引用

arXiv 2021年

作者： Keser, Reyhan Kevser Ayanzadeh, Aydin Aghdam, Omid Abdollahi Kilcioglu, Caglar Toreyin, Behcet Ugur Ure, Nazim Kemal Research Group Informatics Institute Istanbul Technical University Turkey Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States Arcelik Research and Development Turkey Artificial Intelligence and Data Science Application and Research Center Istanbul Technical University Turkey

One of the most efficient methods for model compression is hint distillation, where the student model is injected with information (hints) from several different layers of the teacher model. Although the selection of hint points can drastically alter the compression performance, conventional distillation approaches overlook this fact and use the same hint points as in the early studies. Therefore, we propose a clustering based hint selection methodology, where the layers of teacher model are clustered with respect to several metrics and the cluster centers are used as the hint points. Our method is applicable for any student network, once it is applied on a chosen teacher network. The proposed approach is validated in CIFAR-100 and ImageNet datasets, using various teacher-student pairs and numerous hint distillation methods. Our results show that hint points selected by our algorithm results in superior compression performance compared to state-of-the-art knowledge distillation algorithms on the same student models and datasets. © 2021, CC BY-NC-ND.

关键词： Distillation

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CloudBrain-NMR: An Intelligent Cloud Computing Platform for NMR Spectroscopy Processing, Reconstruction and Analysis

arXiv

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arXiv 2023年

作者： Guo, Di Li, Sijin Liu, Jun Tu, Zhangren Qiu, Tianyu Xu, Jingjing Feng, Liubin Lin, Donghai Hong, Qing Lin, Meijin Lin, Yanqin Qu, Xiaobo School of Computer and Information Engineering Fujian Engineering Research Center for Medical Data Mining and Application Xiamen University of Technology Xiamen361024 China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361005 China The Key Laboratory for Chemical Biology of Fujian Province MOE Key Laboratory of Spectrochemical Analysis & Instrumentation College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China Department of Applied Marine Physics and Engineering College of Ocean and Earth Sciences Xiamen University Xiamen361102 China The China Mobile Group Xiamen361005 China

Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful analytical tool for studying molecular structure and dynamics in chemistry and biology. However, the processing of raw data acquired from NMR spectrometers and subsequent quantitative analysis involves various specialized tools, which necessitates comprehensive knowledge in programming and NMR. Particularly, the emerging deep learning tools is hard to be widely used in NMR due to the sophisticated setup of computation. Thus, NMR processing is not an easy task for chemist and biologists. In this work, we present CloudBrain-NMR, an intelligent online cloud computing platform designed for NMR data reading, processing, reconstruction, and quantitative analysis. The platform is conveniently accessed through a web browser, eliminating the need for any program installation on the user side. CloudBrain-NMR uses parallel computing with graphics processing units and central processing units, resulting in significantly shortened computation time. Furthermore, it incorporates state-of-the-art deep learning-based algorithms offering comprehensive functionalities that allow users to complete the entire processing procedure without relying on additional software. This platform has empowered NMR applications with advanced artificial intelligence processing. CloudBrain-NMR is openly accessible for free usage at https://***/***. © 2023, CC BY.

关键词： Deep learning

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