检索结果-内蒙古大学图书馆

Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： Asma Anjum Dattathreya Salman Arafath Mohammed Dhaval Rabadiya K. B. Venkata Brahma Rao Ramya Maranan Department of Computer Science and Engineering HKBK College of Engineering Bengaluru Karnataka Department of Electronics and Communication Engineering Alva’s Institute of Engineering and Technology Moodbidri Karnataka Department of Electrical Engineering Computer Engineering Section College of Engineering King Khalid University Abha Asir Region Saudi Arabia Faculty of Management Studies Parul University Dist. Vadodara Gujarat Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

The fundamental requirement for WSNs made up of power-efficient and inexpensive sensor nodes depends on short-distance multi-hop communication. The potential of WSNs expands through new digital electronics and wireless communications technology despite the ongoing critical challenge related to energy efficiency. The main energy issues in WSNs stem from the excessively high control signal overhead between base stations and sensor nodes together with packet losses that require retransmissions to reduce energy efficiency. The proposed routing technique solves energy inefficiencies by employing RBDN-HMOA as an energy-efficient routing method. The proposed approach lowers system power consumption through its algorithm which picks distance and energy residual-based optimum forwarding nodes and adapts sampling rates automatically. The algorithm adopts Human Memory Optimization Algorithm (HMOA) to optimize network parameters. Research data shows that experimental results demonstrate both power efficiency and enhanced data transfer rate. The network demonstrates scalability because both throughputs reach 1100 kbps and energy usage reduces to 0.08 J when using 10 nodes. The RBDN-HMOA creates a practical method which extends network duration in practical deployments by diminishing WSN energy utilization without compromising data integrity.

关键词： Wireless sensor networks Energy consumption Fluctuations Heuristic algorithms Throughput Routing Energy efficiency Real-time systems Delays Optimization

来源：评论

学校读者我要写书评

暂无评论

A Review of Non-fungible Tokens Applications in the Real-world and Metaverse 9th

A Review of Non-fungible Tokens Applications in the Real-wor...

引用

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Far, Saeed Banaeian Bamakan, Seyed Mojtaba Hosseini Qu, Qiang Jiang, Qingshan Department of Electrical and Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Management Sciences Yazd University Yazd89195-741 Iran Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

The growth of the popularization of blockchain technology has caused new concepts to emerge. Non-Fungible Token (NFT) is one of these concepts introduced based on blockchain technology in 2017. As newly-emerged concepts, NFTs have rapidly become a popular technology in industry and academic research. NFTs currently have various applications in the industry, which are reviewed in the present study. They have also attracted a broad spectrum of research. Metaverse is another exciting blockchain-based technology that enables people to connect with digital avatars in a virtual universe. The importance of this study is to identify new applications of NFTs in the Metaverse making NFTs more applicable. Assisting with identity management and ownership right of digital assets are examples of NFT applications in the Metaverse that are explained in this study in detail. Ultimately, this study presents some future directions of NFT applications in industry and academic research. © 2022 The Authors. Published by Elsevier B.V.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Timing Controller for a Superconductor Microwave Switch using Adiabatic Quantum Flux Parametron Circuits

引用

IEEJ Transactions on Fundamentals and Materials 2022年第5期142卷 197-201页

作者： Shen, Hongxiang Takeuchi, Naoki Yamanashi, Yuki Yoshikawa, Nobuyuki Department of Electrical and Computer Engineering Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan 1-1-1 Umezono Tsukuba305-8568 Japan The Institute of Advanced Sciences Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan

We are developing a microwave pulse generator, whose pulse width and amplitude can be arbitrarily controlled, to manipulate superconducting quantum computing systems. The proposed microwave pulse generator is made using superconducting circuits. It can be placed at a 4.2 K or lower temperature stages to control a large-scale quantum computing system effectively. One of the key components of the microwave pulse generator is the timing controller, which generates trigger pulses for the microwave switch to start and stop the microwave irradiation. The target frequency of the microwave is 5 GHz, and the timing controller has to generate trigger pulses with a time resolution of several nanoseconds. We designed a 4-bit timing controller using an adiabatic quantum flux parametron (AQFP) circuit, which is extremely energy-efficient superconducting logic. The designed timing controller derives two trigger pulses, start and stop, to the microwave switch at the timing designated by digital data. We implemented the AQFP timing controller using the AIST HSTP process and demonstrated its operation at 1 GHz. Its power dissipation was estimated as about 1.25×10-9 W at 1 GHz. © 2022 The institute of electrical Engineers of Japan.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Renewable Energy Applications Based Bi-Directional Buck-Boost Converter

Design and Implementation of Renewable Energy Applications B...

引用

Innovative Practices in Technology and Management (ICIPTM), International Conference on

作者： K. Venkata Ramana S. Arulkumar Asmita Marathe Kedir Beshir V Jaiganesh K. Tamilselvi M. Sudhakar Department of Computer Scinece And Engineering VNR Vignana Jyothi Institute of Engineering & Technology Hyderabad India Department of Electrical And Computer Engineering Wachemo University Centre For Energy Studies Department of Technology Savitribai Phule Pune University Pune India Department of Electrical And Computer Engineering Wachemo University Ethiopia Department of Mechanical Engineering Bharath Institute of Higher Education and Research Chennai Tamil Nadu India Department of Computer science and Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Mechanical Engineering Sri Sai Ram Engineering College Chennai India

Our main focus was on creating a Two directional power converter for a standalone photo-voltaic energy-generating technology as well as technology energy control when a lead-acid energy storage device is used to control the energy supply. We utilized a light bulb as the load to evaluate the effectiveness of the directional power converter developed as part of our project as well as the functionality of energy control technologies. The suggested technology was composed of an energy control technology, a lead-acid battery, a bulb, a two-directional buck-boost converter, an utmost power point tracking controller, and these components. An energy control technique was developed to grow the rate at which the Photo-voltaic power producing technology consumed energy. The circuits are intended to charge the battery between upper and lower voltage limits, as well as to continuously check the battery's state of charge and add or release current as necessary. The bidirectional buck-boost converter's ability to function as a charge controller on its own, along with the use of particular BUCK and BOOST converter properties to optimize the home application, is the primary distinction between the method used in the proposed technology and other techniques used in the past. The battery is charged and discharged using a bidirectional dc-dc converter. Measurement data are employed to support the viability of a photovoltaic air conditioning technology.

关键词： Lead acid batteries Photovoltaic systems Air conditioning Renewable energy sources Switches DC-DC power converters Bidirectional control

来源：评论

学校读者我要写书评

暂无评论

Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models

arXiv

引用

arXiv 2024年

作者： Pazos, Camila Aeron, Shuchin Beauchemin, Pierre-Hugues Croft, Vincent Huan, Zhengyan Klassen, Martin Wongjirad, Taritree Department of Physics and Astronomy Tufts University MedfordMA United States Department of Electrical and Computer Engineering Tufts University MedfordMA United States Leiden Institute for Advanced Computer Science LIACS Leiden University Netherlands The NSF AI Institute for Artificial Intelligence and Fundamental Interactions United States

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy. © 2024, CC BY.

关键词： High energy physics

来源：评论

学校读者我要写书评

暂无评论

Deep learning frequent pattern mining on static semi structured data streams for improving fast speed and complex data streams 7

Deep learning frequent pattern mining on static semi structu...

引用

7th International Conference on Optimization and Applications, ICOA 2021

作者： Suseendran, G. Balaganesh, D. Akila, D. Pal, Souvik Technology Advanced Studies Vels Institute of Science Department of Information Technology Chennai India Lincoln University College Faculty of Computer Science and Multimedia Malaysia Global Institute of Management and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9781665441032

This paper illustrated deep learning Semi-structured Tree Miner for Data Stream's algorithm focused on frequent pattern mining used in data streams on semi-structured data. In the target time, the algorithm obtains a frequent pattern. The Semistructured Tree Miner for Data Streams algorithm can handle sliding windows use the Time attenuation model to minimise historical data on the mining process relative to traditional algorithms, following the concept of inclusion and exclusion conservation at the same time and full real-time mining operations. And it is effective. © 2021 IEEE.

关键词： Miners

来源：评论

学校读者我要写书评

暂无评论

Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems

Joint Knowledge Distillation and Local Differential Privacy ...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Gad Gad Zubair Md Fadlullah Mostafa M. Fouda Mohamed I. Ibrahem Nidal Nasser Department of Computer Science Western University London ON Canada Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA School of Computer and Cyber Sciences Augusta University Augusta GA USA Department of Electrical Engineering Faculty of Engineering at Shoubra Benha University Cairo Egypt College of Engineering Alfaisal University Saudi Arabia

Federated Learning (FL) has emerged as a powerful approach to facilitate the construction of centralized models without compromising the data privacy of multiple participants. However, conventional FL methodologies do not address system heterogeneity where each participant needs to independently design its own model, a prevalent requirement in Internet of Things (IoT) applications due to the heterogeneous nature of tasks and data. Knowledge Distillation-based FL algorithms tackle this limitation by exchanging soft labels instead of model weights, thus giving each client the ability to independently design its local model architecture. While FL is inherently private, studies have indicated that exploiting gradients for a few iterations can reveal sensitive training data. To protect against privacy attacks, FL algorithms employ Differential Privacy (DP) to guarantee privacy protection, which can be applied using Local Differential Privacy (LDP). In this paper, we elaborate on preserving clients' training data privacy in KD (Knowledge Distillation)-based FL using DP, providing both privacy and flexibility. We provide theoretical analysis to extend the privacy guarantee to exchanged updates. Experimental analysis is performed utilizing Human Activity Recognition (HAR) datasets with different modalities. The results obtained demonstrate the capacity of KD-based FL to maintain a robust utility-privacy balance. Furthermore, for the same DP protection level, the utility of models trained on images was severely reduced across all FL algorithms. This suggests that the modality and complexity of a dataset are important factors for shaping the utility-privacy tradeoff of DP.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SEM image denoising with unsupervised machine learning for better defect inspection and metrology 35

SEM image denoising with unsupervised machine learning for b...

引用

Metrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV 2021

作者： Dey, Bappaditya Halder, Sandip Khalil, Kasem Lorusso, Gian Severi, Joren Leray, Philippe Bayoumi, Magdy A. Imec Kapeldreef 75 Leuven3001 Belgium The Center for Advanced Computer Studies University of Louisiana at Lafayette Louisiana United States Department of Electrical and Computer Engineering University of Louisiana at Lafayette Louisiana United States

ISBN: (纸本)9781510640559

CD-SEM images inherently contain a significant level of noise. This is because a limited number of frames are used for averaging, which is critical to ensure throughput and minimize resist shrinkage. This noise level of SEM images may lead to false defect detections and erroneous metrology. Therefore, reducing noise in SEM images is of utmost importance. Both conventional noise filtering techniques and recent most discriminative deep-learning based denoising algorithms are restricted with certain limitations. The first enables the risk of loss of information content and the later mostly requires clean ground-truth or synthetic images to train with. In this paper, we have proposed an U-Net architecture based unsupervised machine learning approach for denoising CD-SEM images without the requirement of any such ground-truth or synthetic images in true sense. Also, we have analysed and validated our result using MetroLER, v2.2.5.0. library. We have compared the power spectral density (PSD) of both the original noisy and denoised images. The high frequency component related to noise is clearly affected, as expected, while the low frequency component, related to the actual morphology of the feature, is unaltered. This indicate that the information content of the denoised images was not degraded by the proposed denoising approach in comparison to other existing approaches. © 2021 SPIE.

关键词： Power spectral density

来源：评论

学校读者我要写书评

暂无评论

Do We Run Large-scale Multi-Robot Systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling

Do We Run Large-scale Multi-Robot Systems on the Edge? More ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Jonas Kuckling Robin Luckey Viktor Avrutin Andrew Vardy Andreagiovanni Reina Heiko Hamann Department of Computer and Information Science University of Konstanz Konstanz Germany Centre for the Advanced Study of Collective Behaviour University of Konstanz Germany Institute of Computer Engineering University of Lübeck Lübeck Germany Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Department of Computer Science and the Department of Electrical and Computer Engineering Memorial University of Newfoundland St. John’s Canada IRIDIA Université Libre de Bruxelles Brussels Belgium

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing behavior, a strict decentralized approach, and limiting the robot-robot communication. Despite applying such strategies, any multi-robot system breaks above a certain critical system size (i.e., number of robots) as too many robots share a resource (e.g., space, communication channel). We provide additional evidence based on simulations, that at these critical system sizes, the system performance separates into two phases: nearly optimal and minimal performance. We speculate that in real-world applications that are configured for optimal system size, the supposedly high-performing system may actually live on borrowed time as it is on a transient to breakdown. We provide two modeling options (based on queueing theory and a population model) that may help to support this reasoning.

关键词： Limiting System performance Space communications Scalability Sociology Swarm robotics Mobile robots

来源：评论

学校读者我要写书评

暂无评论

DeltaKWS: A 65nm 36nJ/Decision Bio-Inspired Temporal-Sparsity-Aware Digital Keyword Spotting IC With 0.6V Near-Threshold SRAM

IEEE Transactions on Circuits and Systems for Artificial Int...

引用

IEEE Transactions on Circuits and Systems for Artificial Intelligence 2024年第1期2卷 79-87页

作者： Qinyu Chen Kwantae Kim Chang Gao Sheng Zhou Taekwang Jang Tobi Delbruck Shih-Chii Liu Institute of Neuroinformatics University of Zürich and ETH Zürich Zurich Switzerland Leiden Institute of Advanced Computer Science (LIACS) Leiden University Leiden The Netherlands Department of Information Technology and Electrical Engineering (D-ITET) ETH Zürich Zurich Switzerland Department of Electronics and Nanoengineering School of Electrical Engineering Aalto University Espoo Finland Delft University of Technology Delft The Netherlands

This paper introduces DeltaKWS, which is to the best of our knowledge, the first $\Delta$ RNN-enabled, fine-grained, temporal sparsity-aware Keyword Spotting (KWS) integrated circuit (IC) designed for voice-controlled devices. The 65 nm prototype chip features a number of techniques to enhance performance, area, and power efficiencies, specifically: 1) a bio-inspired delta-gated recurrent neural network ( $\Delta$ RNN) classifier leveraging temporal similarities between neighboring feature vectors extracted from input frames and network hidden states, eliminating unnecessary operations and memory accesses; 2) an infinite impulse response (IIR) bandpass filter (BPF)-based feature extractor (FEx) that leverages mixed-precision quantization, low-cost computing structure and channel selection; 3) a 24 kB 0.6 V near- $V_{\text{TH}}$ weight static random-access memory (SRAM) that achieves 6.6 $\boldsymbol{\times}$ lower read power than the foundry-provided SRAM. From chip measurement results, we show that the DeltaKWS achieves an 11/12-class Google Speech Command Dataset (GSCD) accuracy of 90.5%/89.5% respectively and energy consumption of 36 nJ/decision in 65 nm CMOS process. At 87% temporal sparsity, computing latency and energy/inference are reduced by 2.4 $\boldsymbol{\times}$ /3.4 $\boldsymbol{\times}$ , respectively. The IIR BPF-based FEx, $\Delta$ RNN accelerator, and 24 kB near- $V_{\text{TH}}$ SRAM blocks occupy 0.084 mm 2 , 0.319 mm 2 , and 0.381 mm 2 respectively (0.78 mm 2 in total).

关键词： Random access memory Recurrent neural networks Accuracy Neurons Feature extraction Band-pass filters Clocks Integrated circuit modeling IIR filters computer architecture

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：