检索结果-内蒙古大学图书馆

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sarpal, Sumeet Singh Kumar, V. Mathan Pimplapure, Vivek Patil, Shrinivas Marathe, Vijay Henrietta, H. Mary Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Dr. Ambedkar Institute of Management Studies And Research Department of Management Nagpur India School of Mangement - Pg Karnataka Bangalore India Prince Shri Vishwakarma Institute of Technology Department of Electrical Pune India Saveetha Engineering College Department of Mathematics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350370249

With the enhancement of Big Data and Smart Cities, Cloud Computing has emerged as an advanced technology. Innovative city operations require real-time processing of vast volumes of data from various sources like sensors, IOT devices, or social media so that it can be analyzed and acted on in real-time with better automation for its infrastructure against different parameters. This article examines the potential of cloud computing to enable real-time big data analytics for smart cities and infrastructure automation. The cloud allows for real-time big data analytics, collecting input from disparate sources across a business ecosystem and analyzing it immediately for actionable insights. The need for large amounts of data combined with the nature of many Iota devices necessitates processing and storage at scale, a task uniquely suited to cloud computing due to its ability to provide scalability, flexibility, and lower cost essential qualities in building intelligent cities or automated infrastructure. Cloud computing offers a space for shared data and collaborative analysis, allowing the city government to open up its vast browser-based datasets so that other agencies (both within government and outside it), researchers, and even citizens can access this information, in turn driving innovation or assisting with strategic planning. Moreover, the evolution not just in cloud-based machine learning and artificial intelligence algorithms but also device-side AI/ML allows for predictive analytics, which can be helpful to preemptively discern potential failures to prevent them pro-actively, thus augmenting city operations efficacy as well as resource utilization besides operational efficiency of infrastructural management. Cloud computing is integral for real-time and big data analytics and innovates cities, organizations, and infrastructure. © 2024 IEEE.

关键词： Automation Infrastructure Intelligent Organizations Parameters

来源：评论

学校读者我要写书评

暂无评论

Improving Energy Efficiency using Colliding Bodies Optimization based Routing Protocol for Wireless Sensor Networks 2

Improving Energy Efficiency using Colliding Bodies Optimizat...

引用

2nd International Conference on Electronics and Renewable Systems, ICEARS 2023

作者： Prabakaran, P. Shalini, R. Hariharan, N. Marieswari, S. Kumar, Kallakunta Ravi Apoorva, Maturi Gayatri Lakshmi Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Department of Computer Applications Chennai India Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Department of Bca and It Chennai India R.M.K. College of Engineering and Technology Science and Humanities - Eee Thiruvallur601206 India P. S. R. Engineering College Biomedical Engineering India Koneru Lakshmaiah Education Foundation Department of Ece Vaddeswaram India Amrita School of Engineering Ece Department India

ISBN: (纸本)9798350346640

Wireless sensor network (WSN) contains millions of small, low-power gadgets with a lack of resources are memory and battery power. Such gadgets were deployed in a dispersed manner and were often utilized to monitor and sense applications. Owing to constraints and limited resources of WSNs, routing can be a great difficulty. Routing in WSN was the process of choosing the optimal path for data to travel from a source node to a destination node. The goal of routing in WSN offer dependable and effective transmission while minimizing network overhead and energy consumption. This study designs an Energy Efficient Colliding Bodies Optimization based Routing Protocol (EECBO-RP) for WSN. The end goal of the EECBO-RP algorithm lies in the optimal election of routes to a destination. For achieving reasonable results for the minimization of energy exploitation, the EECBO-RP system derives the fitness function using the following variables: residual energy, distance to BS, and node degree. The EECBO-RP technique chooses the relay nodes so that a way that the overall efficiency of the WSN gets maximized. The simulation values of the EECBO-RP system are tested under several dimensions and the outcomes pointed out the betterment of the EECBO-RP technique. © 2023 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Spatial Feature Topology-Based Heterogeneous Knowledge Transfer Framework for Long-Term Fingerprint Positioning

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Si, Haonan Guo, Xiansheng Boateng, Gordon Owusu Yang, Yin Ansari, Nirwan University of Electronic Science and Technology of China Department of Electronic Engineering Chengdu611731 China New Jersey Institute of Technology Advanced Networking Lab. Department of Electrical and Computer Engineering NewarkNJ07102 United States

Transfer learning (TL) is effective for addressing distribution discrepancies in fingerprint positioning. However, existing TL frameworks cannot react well to the heterogeneous feature dimensions of fingerprints caused by the topology variations of base stations (BSs) in evolving long-term environments. To address this issue, we propose a spatial feature topology-based heterogeneous knowledge transfer framework tailored for long-term fingerprint positioning (SFTP). Firstly, we partition the heterogeneous features into common and domain-specific (including source and target-specific) features from static and dynamic environmental components perspectives, respectively. Notably, we observe that the features captured from BSs with significant spatial distances differ across all samples, while those from BSs with close spatial distances show higher similarity. Based on these observations, we approximate the cross-domain mapping for each domain-specific feature by integrating the mappings of similar common features, which are easy to achieve using deep neural networks (DNNs). Subsequently, the heterogeneous feature spaces are effectively transformed into homogeneous counterparts, and a deep adaptation network (DAN) is utilized to further predict the positions for testing samples. Hence, SFTP is capable of capturing evolutionary environmental information for long-term positioning. Finally, real-world experimental results demonstrate the superiority and robustness of the proposed framework. © 1967-2012 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

DCSK-based Waveform Design for Self-sustainable RIS-aided Noncoherent SWIPT

arXiv

引用

arXiv 2024年

作者： Mukherjee, Priyadarshi Psomas, Constantinos Krikidis, Ioannis The Advanced Computing & Microelectronics Unit Indian Statistical Institute Kolkata India The Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus

This paper investigates the problem of transmit waveform design in the context of a chaotic signal-based self-sustainable reconfigurable intelligent surface (RIS)-aided system for simultaneous wireless information and power transfer (SWIPT). Specifically, we propose a differential chaos shift keying (DCSK)-based RIS-aided point-to-point set-up, where the RIS is partitioned into two non-overlapping surfaces. The elements of the first sub-surface perform energy harvesting (EH), which in turn, provide the required power to the other sub-surface operating in the information transfer (IT) mode. In this framework, by considering a generalized frequency-selective Nakagami-m fading scenario as well as the nonlinearities of the EH process, we derive closed-form analytical expressions for both the bit error rate (BER) at the receiver and the harvested power at the RIS. Our analysis demonstrates, that both these performance metrics depend on the parameters of the wireless channel, the transmit waveform design, and the number of reflecting elements at the RIS, which switch between the IT and EH modes, depending on the application requirements. Moreover, we show that, having more reflecting elements in the IT mode is not always beneficial and also, for a given acceptable BER, we derive a lower bound on the number of RIS elements that need to be operated in the EH mode. Furthermore, for a fixed RIS configuration, we investigate a trade-off between the achievable BER and the harvested power at the RIS and accordingly, we propose appropriate transmit waveform designs. Finally, our numerical results illustrate the importance of our intelligent DCSK-based waveform design on the considered framework. © 2024, CC BY-NC-ND.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

Cloud-Based Intelligent Patient Triage Systems with SVM Classifiers for Emergency departments 1

Cloud-Based Intelligent Patient Triage Systems with SVM Clas...

引用

1st International Conference on Innovations in Communications, electrical and computer engineering, ICICEC 2024

作者： Shibu, N.V. Sujatha, M. Suresh, M. Xavier Sindhuja, K. Raj, T. Saju Srinivasan, C. SRM Institute of Science and Technology Department of Computing Technologies School of Computing Kattankulathur Tamil Nadu Chennai India Easwari Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Vit Bhopal University Department of Physics School of Advanced Sciences and Languages Madhya Pradesh Bhopal India J.J College of Engineering and Technology Department of Information Technology Tamil Nadu Tiruchirappalli India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376517

Efficient patient triage in emergency departments is crucial for the timely and successful allocation of resources and treatment in the constantly changing healthcare environment. To improve patient triage systems, this research suggests a new strategy that makes use of cloud computing and support vector machine (SVM) classifiers. The proposed solution endeavors to enhance patient outcomes in emergency departments by optimizing resource allocation via the use of cloud infrastructure's scalability and accessibility in conjunction with SVM algorithms' strong classification capabilities. Quickly classifying patients according to severity, the system integrates and analyzes data in real-time, allowing healthcare providers to prioritize high-risk situations and distribute resources appropriately. Healthcare practitioners can work together more efficiently and share patient data with cloud-based architecture, which promotes a more comprehensive approach to treatment. Results from the experiments prove that the system works as advertised and can be easily scaled up, highlighting its revolutionary potential to change the way emergency healthcare facilities handle patient triage. The growing body of evidence demonstrates the value of intelligent systems for healthcare delivery optimization and emergency patient care improvement via the use of technology. © 2024 IEEE.

关键词： Data-driven triage Emergency medicine Healthcare efficiency Healthcare optimization Real-time decision support Resource management

来源：评论

学校读者我要写书评

暂无评论

Multi-Stage Model Predictive Control with Enhanced Discrete-Time Models for Multilevel Inverters

Multi-Stage Model Predictive Control with Enhanced Discrete-...

引用

Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Hoang Le Apparao Dekka Deepak Ronanki Abdul R. Beig Department of Electrical and Computer Engineering Lakehead University Thunder Bay Canada Department of Engineering Design Indian Institute of Technology Madras Chennai India Advanced Power and Energy Systems Electrical Engineering Department Khalifa University Abu Dhabi UAE

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

Model accuracy, computational complexity, and weighting factor dependency are three primary challenges associated with multi-stage model predictive control (MS-MPC) of multilevel inverters (MLIs). Typically, existing MS-MPC employs the forward Euler integration method to discretize continuous-time models, due to the ease of implementation in real-time controllers. This approach faces a significant deterioration in computational accuracy as sampling period increases. To address this issue, this paper proposes a new formulation of MS-MPC for MLIs. Also, an enhanced discrete-time model of MLI by using Heun’s integration method is proposed to implement the proposed MS-MPC, resulting in a more precise formulation and indirect minimization of common-mode voltage (CMV). Unlike the existing methods, the proposed method does not employ a cost function with weighting factor or offline selection of voltage vectors (VVs) to minimize the CMV. Furthermore, it does not increase computational complexity compared to the existing MS-MPCs. Simulation studies are conducted on a four-level MLI system to validate the efficacy of the proposed MS-MPC, and its performance is compared with the existing methods.

关键词： Accuracy Computational modeling Predictive models Multilevel inverters Mathematical models Vectors Real-time systems Power electronics Computational complexity Predictive control

来源：评论

学校读者我要写书评

暂无评论

Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

引用

npj Computational Materials 2023年第1期9卷 1402-1410页

作者： Ying Huang David Perlmutter Andrea Fei-Huei Su Jerome Quenum Pavel Shevchenko Dilworth Y.Parkinson Iryna V.Zenyuk Daniela Ushizima Department of Materials Science&Engineering University of California IrvineIrvineCaliforniaUSA National Fuel Cell Research Center University of California IrvineIrvineCaliforniaUSA Applied Math and Computational Research Division Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Department of Chemical&Biomolecular Engineering University of California IrvineIrvineCaliforniaUSA Department of Electrical Engineering and Computer Sciences College of EngineeringUniversity of California BerkeleyBerkeleyCaliforniaUSA Advanced Photon Source Argonne National Laboratory9700 South Cass AvenueLemontIllinoisUSA Advanced Light Source Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA Berkeley Institute for Data Science University of California BerkeleyBerkeleyCaliforniaUSA

Operando X-ray micro-computed tomography(µCT)provides an opportunity to observe the evolution of Li structures inside pouch *** is an essential step to quantitatively analyzingµCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the ***,we report a computational approach,batteryNET,to train an Iterative Residual U-Net-based network to detect Li *** resulting semantic segmentation shows singular Li-related component changes,addressing diverse morphologies in the *** addition,visualizations of the dead Li are provided,including calculations about the volume and effective thickness of electrodes,deposited Li,and redeposited *** also report discoveries about the spatial relationships between these *** approach focuses on a method for analyzing battery performance,which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.

关键词： battery lithium state

来源：评论

学校读者我要写书评

暂无评论

Robust Control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

引用

2024 China Automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

来源：评论

学校读者我要写书评

暂无评论

ANALYSIS OF SELF-SUPERVISED SPEECH MODELS ON CHILDREN’S SPEECH AND INFANT VOCALIZATIONS

arXiv

引用

arXiv 2024年

作者： Li, Jialu Hasegawa-Johnson, Mark McElwain, Nancy L. Department of Electrical and Computer Engineering University of Illinois United States Beckman Institute for Advanced Science and Technology University of Illinois United States Department of Human Development and Family Studies University of Illinois United States

To understand why self-supervised learning (SSL) models have empirically achieved strong performances on several speech-processing downstream tasks, numerous studies have focused on analyzing the encoded information of the SSL layer representations in adult speech. Limited work has investigated how pre-training and fine-tuning affect SSL models encoding children’s speech and vocalizations. In this study, we aim to bridge this gap by probing SSL models on two relevant downstream tasks: (1) phoneme recognition (PR) on the speech of adults, older children (8-10 years old), and younger children (1-4 years old), and (2) vocalization classification (VC) distinguishing cry, fuss, and babble for infants under 14 months old. For younger children’s PR, the superiority of fine-tuned SSL models is largely due to their ability to learn features that represent older children’s speech and then adapt those features to the speech of younger children. For infant VC, SSL models pre-trained on large-scale home recordings learn to leverage phonetic representations at middle layers, and thereby enhance the performance of this task. © 2024, CC BY.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Spectroscopic characterization of an on-chip squeezed quantum optical frequency comb

Spectroscopic characterization of an on-chip squeezed quantu...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Jahanbozorgi, Mandana Yang, Zijiao Parnell, Emily A. Jeong, Dongin Sun, Shuman Pfister, Olivier Lee, Hansuek Yi, Xu Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States Department of Physics University of Virginia CharlottesvilleVA22904 United States Daejeon34141 Korea Republic of Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

We experimentally characterized the spectrum of 40 quantum modes in an on-chip squeezed quantum optical frequency comb. A theoretical model is developed to explain the effect of dispersion on squeezing level and frequ... 详细信息

ISBN: (纸本)9781957171258

关键词： Natural frequencies

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：