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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Li, Pingping Yu, Leilei Song, Linqi Hou, Hanxu Dongguan University of Technology School of Computer Science & Technology Dongguan China University of Electronic Science & Technology of China Shenzhen Institute for Advanced Study China City University of Hong Kong Department of Computer Science Hong Kong Dongguan University of Technology School of Electrical Engineering & Intelligentization Dongguan China

ISBN: (纸本)9798350324662

Finding all roots of polynomials over finite fields is a crucial problem in algebraic coding techniques, such as decoding BCH codes and Reed-Solomon codes. The current commonly used methods are Chien search or fast Fourier transform (FFT), which evaluates all elements in a finite field and results in field multiplications whose number increases linearly with the field size. In this paper, we propose a new approach that enables the multiplicative complexity to grow sub-linearly with the field size. To our knowledge, this is the currently lowest multiplicative complexity for this problem. Additionally, the proposed approach maintains the additive complexity similar to that of FFT-based method. © 2023 IEEE.

关键词： error-correction codes error-locator polynomial fast Fourier transforms (FFT) Polynomial evaluation

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Soft,full Wheatstone bridge 3D pressure sensors for cardiovascular monitoring

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npj Flexible Electronics 2024年第1期8卷 910-917页

作者： Yoonseok Park Haiwen Luan Kyeongha Kwon Ted S.Chung Seyong Oh Jae-Young Yoo Gooyoon Chung Junha Kim Suhyeon Kim Sung Soo Kwak Junhwan Choi Hoang-Phuong Phan Seonggwang Yoo Hyoyoung Jeong Jaeho Shin Sang Min Won Hong-Joon Yoon Yei Hwan Jung John A.Rogers Department of Advanced Materials Engineering for Information and Electronics Integrated Education Institute for Frontier Science&Technology(BK21 Four)Kyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea Department of Mechanical and Aerospace Engineering University of California San DiegoLa JollaCA 92093USA School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Department of Mechanical Engineering Columbia UniversityNew YorkNYUSA Division of Electrical Engineering Hanyang University ERICAAnsan 15588Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Biomedical Research Division Korea Institute of Science and TechnologySeoul 02792Republic of Korea Department of Chemical Engineering Dankook UniversityYonginGyeonggi-do 16890Republic of Korea School of Mechanical and Manufacturing Engineering Tyree Institute of Health EngineeringUniversity of New South WalesSydneyNSW 2052Australia Querrey Simpson Institute for Bioelectronics Northwestern University EvanstonEvanstonIL 60208USA Department of Electrical and Computer Engineering University of California DavisDavisCA 95616USA Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-do 16419Republic of Korea Department of Electronic Engineering Gachon UniversitySeongnamsiGyeonggi-do 13120Republic of Korea Department of Electronic Engineering Hanyang UniversitySeoulRepublic of Korea Department of Materials Science and Engineering Biomedical EngineeringNeurological SurgeryChemistryMechanical EngineeringElectrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical SchoolCenter for Bio-Integrated ElectronicsNorthwestern University EvanstonEvanstonIL 60208USA

Variations in parameters associated with the ambient environment can introduce noise in soft,body-worn *** example,many piezoresistive pressure sensors exhibit a high degree of sensitivity to fluctuations in temperature,thereby requiring active compensation *** research presented here addresses this challenge with a multilayered 3D microsystem design that integrates four piezoresistive sensors in a full-Wheatstone bridge *** optimized layout of the sensors relative to the neutral mechanical plane leads to both an insensitivity to temperature and an increased sensitivity to pressure,relative to previously reported devices that rely on similar operating *** this 3D pressure sensor into a soft,flexible electronics platform yields a system capable of real-time,wireless measurements from the surface of the *** above the radial and carotid arteries yields high-quality waveforms associated with pulsatile blood flow,with quantitative correlations to blood *** results establish the materials and engineering aspects of a technology with broad potential in remote health monitoring.

关键词： Wheat bridge thereby

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Efficient factored gradient descent algorithm for quantum state tomography

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Physical Review Research 2024年第3期6卷 033034-033034页

作者： Yong Wang Lijun Liu Shuming Cheng Li Li Jie Chen College of Electronics and Information Engineering Department of Mathematics and Computer Science Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study

Reconstructing the state of quantum many-body systems is of fundamental importance in quantum information tasks, but extremely challenging due to the curse of dimensionality. In this work, we present an efficient quantum tomography protocol that combines the state-factored with eigenvalue mapping to address the rank-deficient issue and incorporates a momentum-accelerated gradient descent algorithm to speed up the optimization process. We implement extensive numerical experiments to demonstrate that our factored gradient descent algorithm efficiently mitigates the rank-deficient problem and admits orders of magnitude better tomography accuracy and faster convergence. We also find that our method can accomplish the full-state tomography of random 11-qubit mixed states within one minute.

关键词： Quantum communication, protocols & technology Quantum engineering Quantum tomography

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Error estimation of practical convolution discrete Gaussian sampling with rejection sampling

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Science China(Information Sciences) 2021年第3期64卷 229-231页

作者： Zhongxiang ZHENG Xiaoyun WANG Guangwu XU Chunhuan ZHAO Department of Computer Science and Technology Tsinghua University Institute for Advanced Study Tsinghua University Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong Universtiy Department of Electrical Engineering and Computer Science University of Wisconsin-Milwaukee

Dear editor,Discrete Gaussian sampling is a fundamental tool in lattice cryptography which has been used in digital signatures,identify-based encryption, attribute-based encryption, zeroknowledge proof, and fully homomorphic cryptosystem. As a subroutine of lattice-based scheme, a high precision sampling usually leads to a high security level and also brings large time and space complexity.

关键词： Discrete Gaussian Sampling convolution theorem lattice error estimation Gaussian measure

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nmODE-MVC: Neural Memory ODE-Based Multi-View Clustering 7

nmODE-MVC: Neural Memory ODE-Based Multi-View Clustering

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7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023

作者： Zheng, Yan Wu, Song Ren, Yazhou Pu, Xiaorong Xu, Zenglin He, Lifang Yi, Zhang University of Electronic Science And Technology of China School of Computer Science And Engineering Chengdu China University of Electronic Science And Technology of China School of Computer Science And Engineering Shenzhen Institute For Advanced Study China Harbin Institute of Technology Shenzhen School of Computer Science And Technology Shenzhen China Lehigh University Department of Computer Science And Engineering Bethlehem United States Sichuan University Intelligent Interdisciplinary Research Center College of Computer Science Chengdu China

ISBN: (纸本)9798350359145

Deep multi-view clustering (MVC) has recently gained significant interest for its capability to harness complementary information across multiple views through deep neural networks, enhancing clustering performance. However, existing deep MVC methods still have two issues: (1) They separate the feature learning objective and the clustering objective, potentially leading to suboptimal embedding features due to the neglect of the global clustering structure. (2) Most works utilize the target distribution obtained by the clustering objective to supervise feature learning. However, they simply sharpen the soft clustering distribution to obtain the target distribution, lacking the dynamics of the clustering process. To address these issues, in this paper we propose a novel end-to-end self-supervised multi-view clustering approach based on NeuralODEs, namely nmODE-MVC. Our approach operates in two stages: In the first stage, all view-embedded features are extracted, and then unified them into a global feature, facilitating global clustering assignments by exploiting multi-view data's complementarity. The second stage leverages the dynamic attributes of NeuralODEs to dynamically refine the data features and generate a target distribution that actively drives the clustering decisions. We formulate these learning processes as a unified optimization problem, facilitating iterative training and refinement. The effectiveness of nmODE-MVC is validated through extensive experiments on multiple real-world multi-view datasets. © 2023 IEEE.

关键词： Ordinary differential equations

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Insurance Plan for Service Assurance in Cloud Computing Market with Incomplete Information

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Journal of Communications and Information Networks 2022年第1期7卷 11-22页

作者： Yanru Zhang Chunxiao Jiang Nguyen H.Tran Shengrong Bu FeiRichard Yu Zhu Han College of Computer Science and Engineering the University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study UESTCLonghuaShenzhen 518110China Tsinghua Space Center Tsinghua UniversityBeijing 10084China School of Computer Science the University of SydneySydneyNew South WalesAustralia Department of Engineering Brock UniversityONCanada School of Information Technology Depart.of Systems and Computer EngineeringCarleton UniversityOttawa K1S 5B6ONCanada Department of Electrical and Computer Engineering the University of HoustonHouston 77004TXUSA

Nowadays,cloud computing has been identified as new opportunities for migrating to the expected agility,reuse,and adaptive capabilities that can support the ever changing IT trends and ***,the rapid evolution of those technologies also comes with open issues such as security,privacy,integrity,quality of services,and their possible detrimental *** this work,the concept of insurance is introduced to compensate the cloud computing customers when encountering those failures if service providers(SPs)have insurance ***,we consider the situation when the insurer is unable to see the system failure risk levels of the SPs,which is usually seen as an incomplete information market,in contrast with the optimal situation in a complete information ***,an insurance-based cloud computing architecture is proposed to build a monetary credit system in which the cloud computing SP pays a premium for a certain coverage to the ***,problem is formulated to solve the optimal insurance plan in complete and incomplete information markets,together with detail analysis of insurance policies in both cases are ***,simulation results show the properties of the two insurance plans and parameters that affect the design of the insurance plan.

关键词： service assurance cloud computing market incomplete information game theory insurance plan

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Unsupervised Adaptive Lesion Segmentation with Similarity Based Cross Pseudo Supervision 7

Unsupervised Adaptive Lesion Segmentation with Similarity Ba...

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7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023

作者： Zhu, Yuxin Li, Shuhao Yang, Aodi Feng, Mei Pu, Xiaorong Ren, Yazhou University of Electronic Science And Technology of China School of Computer Science And Engineering China The Third People's Hospital of Sichuan Department of Medical Oncology China University of Electronic Science And Technology of China School of Computer Science And Engineering Shenzhen Institute For Advanced Study China

ISBN: (纸本)9798350359145

Notable advancement has been made in lesion segmentation based on deep learning. Nonetheless, the effectiveness of deep learning heavily relies on the availability of a substantial amount of high-quality labeled data, which is labor-intensive and expensive to require. Moreover, when applied to a different domain, deep learning-based lesion segmentation methods often experience a decline in performance due to variations in device vendors and patient populations. The unsupervised domain adaptation method is proposed to tackle the domain discrepancy problem. There are certain similarities between semi-supervised learning and unsupervised domain adaptation. From an application perspective, semi-supervised learning models can be used to solve unsupervised domain adaptation *** this end, we introduce the cross-pseudo-supervision mechanism in the semi-supervised field for unsupervised adaptive lesion segmentation. However, the method ignores the similar characteristics in medical images. To fully leverage the semantic similarity between domains, a novel similarity-based cross-pseudo-supervised lesion segmentation model is proposed. The proposed model employs a U-Net encoder, trained on source domain, to extract features from both the source and target domains. Subsequently, cosine similarity is computed based on these extracted features. The obtained similarity scores are then employed to weigh the source samples during the training process. The effectiveness of the proposed method is demonstrated through cross-domain experiments conducted on two publicly available COVID-19 lesion segmentation datasets. © 2023 IEEE.

关键词： Population statistics

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Smart and advanced electrical Skills: Identifying Current Gaps and Emerging Trends 5

Smart and Advanced Electrical Skills: Identifying Current Ga...

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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Karapidakis, Emmanuel Markaki, Marini Apostolakis, Spyridon Canizes, Bruno Androulakis, Radamanthys Castro, Fabio Hellenic Mediterranean University Electrical and Computer Engineering Department Heraklion Greece Polytechnic Institute of Porto GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal ECTE GECAD - Research Group on Research Department Rethymno Greece

ISBN: (纸本)9798350352863

With the rise of smart buildings, new expertise gaps and security vulnerabilities are emerging, necessitating a comprehensive understanding of their current state and proactive future planning to address these challenges. Such identification is crucial for mapping the pathway towards vocational modernization (keeping up with trends and goal alignment). To assess these gaps, this paper explores the extensive literature that draws on workshops, expert interviews, and research to identify emerging roles and training needs across seven countries: Greece, Spain, Portugal, Italy, North Macedonia, Germany, and the Netherlands. In particular, it examines the validity of its findings in critical areas such as security, privacy, and the integration of smart grids with energy markets. Additionally, the paper highlights future skills gaps emerging from advancements in IoT, automation, and renewable energy technologies. It emphasizes the growing demand for specialized electrical expertise to optimize energy production, integrate monitoring and storage systems, and manage electric vehicle charging and energy communities effectively. In conclusion, the study identifies critical gaps in expertise and training needed to keep up with the rapid evolution of smart building technologies. Emerging trends highlight the demand for interdisciplinary skills, particularly in IoT, automation, and renewable energy. As these fields advance, expertise in cybersecurity, energy management, and smart grid integration will be crucial, emphasizing the need for proactive workforce development and planning. The findings can be used to inform and direct policymakers towards the smooth reexamination of vocational training. © 2024 IEEE.

关键词： Power grids

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Harvesting Insights: Predicting Vegetable Prices with Hybrid CLA-Conv BiGRU Techniques 3

Harvesting Insights: Predicting Vegetable Prices with Hybrid...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Lal Ambashtha, Kanahaiya Praveen Kumar, Chatakunta Pandey, Vivekanand Sakthivel Padaiyatchi, S. Bharathi, A. Navaz, K. Gnsu Faculty of Information Technology Bihar Sasaram India Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad India Amity University Bihar Patna India Nehru Institute of Engineering and Technology Department of Electrical and Electronics Engineering TN Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Information Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350381931

The system delves into the important topic of agricultural market pricing, with a specific emphasis on the ever-changing realm of vegetable supply and prices. Stabilizing the supply and prices of vegetables becomes an enormous task when consider that the system are grown outdoors and that weather variables significantly impact harvests. Such unpredictability has far-reaching consequences for the country's economy, highlighting the critical need to develop efficient methods of precise forecasting. The government has made multiple attempts to stabilize vegetable prices and supplies, but these have all been unsuccessful due to the unpredictable weather patterns of late. This system uses state-of-the-art deep learning methods, notably the Hybrid CLA-Conv BiGRU model, which incorporates a novel preprocessing strategy based on the HP Filter, to conquer this obstacle. A strong prediction model for vegetable prices is constructed using the process, which includes feature extraction, scoring, and selection. © 2024 IEEE.

关键词： Vegetables

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FDD Massive MIMO: How to Optimally Combine UL Pilot and Limited DL CSI Feedback?

FDD Massive MIMO: How to Optimally Combine UL Pilot and Limi...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Kim, Jungyeon Choi, Jinseok Park, Jeonghun Alkhateeb, Ahmed Lee, Namyoon Pohang University of Science and Technology Department of Electrical Engineering Pohang Korea Republic of Korea Advanced Institute of Science and Technology School of Electrical Engineering Daejeon Korea Republic of Yonsei University School of Electrical and Electronic Engineering Seoul Korea Republic of Arizona State University School of Electrical Computer and Energy Engineering AZ United States Korea University School of Electrical Engineering Seoul Korea Republic of

ISBN: (纸本)9798350351255

In frequency-division duplexing (FDD) multipleinput multiple-output (MIMO) systems, obtaining accurate downlink channel state information (CSI) becomes challenging due to the tremendous feedback overhead that increases with the number of antennas. Using uplink pilots to estimate downlink CSI is a promising approach that can eliminate the need for CSI feedback, but its accuracy decreases significantly as the number of channel paths increases. In this paper, we propose a mean square error (MSE)-optimal downlink channel reconstruction method that jointly utilizes uplink CSI and limited downlink CSI. With the MSE-optimal estimator, we derive the MSE as a function of the number of feedback bits for channel phase quantization and show the optimal feedback bit allocation method to minimize the MSE. Harnessing robust downlink precoding, we demonstrate that the proposed downlink channel reconstruction is sufficient to achieve a sum-spectral efficiency comparable to that with perfect downlink CSI. © 2024 IEEE.

关键词： Mean square error

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