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Development of a LabVIeW-Based Data Acquisition and Monitoring System for Demand Response Laboratory 4

Development of a LabVIEW-Based Data Acquisition and Monitori...

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4th international conference on Smart grid Metrology, SMAGRIMeT 2023

作者： Culjak, Marija Havelka, Juraj Pandzic, Hrvoje University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia KONČAR-Electrical Engineering Institute Ltd. Zagreb Croatia

ISBN: (纸本)9798350323597

Active involvement of residential consumers in smart home initiatives is a key for realization of the smart grid. In this framework, the active customers are subject to demand response programs used to efficiently reduce the amount and timing of electricity consumption. The main requirements for residential demand response programs are acquiring real-Time electricity consumption data and load profiles of residential appliances. Development of communication technologies and smart load monitoring applications has simplified the access to this information. This paper investigates and describes the design of a developed data acquisition and monitoring system for demand response implementation in the residential sector. Our smart monitoring system integrates a number of residential electric appliances to study their daily energy consumption profiles and, in the future, forecasts their potential demand response capacity. We describe the design of a LabView application for acquiring, logging, processing and visualizing data derived from the Demand Response Laboratory (DR Lab) at the University of Zagreb Faculty of electrical engineering and computing (UNIZG-FeR). The monitoring system is implemented in a way that enables an-cillary service provisioning and participation in demand response programs. © 2023 ieee.

关键词： electric power utilization

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Intelligent Monitoring Algorithm for Transmission Lines Based on Lightning Fusion Technology 3

Intelligent Monitoring Algorithm for Transmission Lines Base...

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3rd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Liu, Weigang Liu, Xinmin Chen, Dazhi Lv, Fubin Zhou, Hongze Liu, Yan State Grid Xinjiang Electric Power Co. Ltd. Changji Power Supply Company Changji Xinjiang831100 China

ISBN: (纸本)9798331519032

The traditional safety detection method for transmission lines heavily relies on manual inspection, which is not only inefficient but also limited by personnel experience, environmental factors, and inspection cycles. It is difficult to achieve real-time and accurate identification and warning of transmission line anomalies, and has significant limitations and safety hazards. In recent years, lightning fusion technology has emerged as an innovative solution that cleverly combines the high-precision ranging and speed measurement capabilities of advanced radar detection technology with the intuitive image recognition advantages of video surveillance technology. Through complex data processing algorithms, it achieves deep fusion and intelligent analysis of the two data. This article explores an intelligent monitoring algorithm for transmission lines based on lightning vision fusion technology, and proposes a monitoring system that combines deep learning (DL) algorithms to automatically capture and analyze environmental changes around transmission lines, significantly improving the timeliness and accuracy of transmission line monitoring. The experimental results show that this system not only significantly reduces manual intervention and operation costs, but also effectively avoids missed and false alarms, providing a more solid technical guarantee for the safe and stable operation of the power system (ePS). © 2024 ieee.

关键词： Alarm systems

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computing for Mobile Ad Hoc Network in IoT Fuelled Smart environments: Computer Integration in Smart environment 2

Computing for Mobile Ad Hoc Network in IoT Fuelled Smart Env...

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2nd ieee international conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Taneja, Dev Gupta, Pooja Taneja, Kavita Manipal University Jaipur Department of Computer and Communication Engineering India Panjab University Chandigarh Department of Computer Science and Applications India

ISBN: (纸本)9798350369960

Present Information Technology scenario is engulfed with exponential rise in mobile computing devices mostly embedded in diverse equipments of our daily life. This has led to evolutionary demand of new solutions to mobile computing for smart environments equipped with Internet of Things (IoT). A plethora of challenges are emerging to ensure effective internet connectivity for such mobile devices. These devices are mostly equipped with sensors and demand continuous computing and data transfers. The globe is evolving to humancentred society, i.e., Society 5.0 loaded with innovations of Big Data, IoT, Artificial Intelligence and much more to make social life comfortable and sustainable. Hence, this trend is the need of the hour but has brought a range of new challenges to MANeTs for mobile computing in smart environments. This paper explores the MANeT-IoT computing trends and provides a detailed analysis of the challenges for computing in the smart environment having MANeT-IoT as backbone for mobile communications. © 2023 ieee.

关键词： Internet of Things (IoT) Mobile Ad Hoc Network (MANeT) Mobile computing Society 5.0

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A Deep Unsupervised Representation Learning Architecture using Coefficient of Variation in Hidden Layers 9

A Deep Unsupervised Representation Learning Architecture usi...

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9th ieee international conference on Cloud computing and Intelligence Systems, CCIS 2023

作者： Ding, Xuemei Chu, Jielei Hu, Jiangtao Yu, Hua Li, Tianrui Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu611756 China Chengdu Customs District Technological Center Chengdu China China E-port Data Center Chengdu Branch Chengdu China

ISBN: (纸本)9798350304428

The aim of this paper is to present a novel cov-RBM model on the basis of Restricted Boltzmann Machine (RBM) and the coefficient of variation (CoV), where the learning process is instructed by the CoV eigenvalues with respect to the hidden layer. Further, a deep unsupervised representation learning architecture (DURLA) is proposed to explore the capacity for representation learning with continuous excitation of CoV eigenvalues. We subject the proposed DURLA to extensive experimentation on nine real-valued datasets. The final experimental results show that our methods have a better effect than traditional and state-of-The-Art ways. © 2023 ieee.

关键词： eigenvalues and eigenfunctions

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Direct power control of a brushless doubly-fed induction generator under an unbalanced power grid 2

Direct power control of a brushless doubly-fed induction gen...

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2nd Asia conference on electrical, Power and Computer engineering, ePCe 2023

作者： Yang, Xiaoliang Bai, Jiajun Qin, Yixuan Zhao, Jiane Zhengzhou University of Light Industry School of Electrical and Information Engineering Zhengzhou China Zhengzhou University of Science and Technology School of Electrical and Electronic Engineering Zhengzhou China

ISBN: (纸本)9798350310818

The output power of the brushless doubly-fed generator (BDFIG) in unbalanced power system contains the second-harmonic fluctuation and the stator current is distorted. To reduce the influnce of unbalanced power grid on BDFIG, the composition of instantaneous active and reactive power of BDFIG stator output under unbalanced power grid is deduced and analyzed, and a new approaching rate integral sliding mode variable structure with PI controller is proposed. The integral sliding mode variable structure is used to control the DC component of the output power of BDFIG under the unbalanced power grid. The double frequency fluctuation of power and the distortion of stator current are suppressed by PI control of stator current instruction. Finally, the influence of unbalanced power grid on BDFIG is reduced. In this article, the calculation principle of voltage positive and negative sequence decomposition for unbalanced power grid voltage is studied, and a fast positive and negative sequence decomposition method is designed to improve the delay problem of T/4 delay separation method, the BDFIG direct power control capability under unbalanced grid voltage is improved effectively. Finally, Matlab/Simulink simulation results demonstrate the effectiveness of the control strategy. © 2023 ieee.

关键词： MATLAB

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Stability Impact of Frequency Measurement Accuracy on Decoupling Control of GCI under Weak grids

Stability Impact of Frequency Measurement Accuracy on Decoup...

引用

ieee international Instrumentation and Measurement Technology conference (I2MTC) - Rising Above Covid-19

作者： Lin, Xianfu Zhu, Liang Huang, Chang Wen, He Hunan Univ Coll Elect & Informat Engn Changsha Peoples R China State Grid Jiangxi Elect Power Co Power Supply Serv Ctr Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781665453837

Due to the inherited coupling between d channel and q channel, the decoupling control is often introduced into the control of three phase grid-connected inverter (GCI) in dq-frame. Therein, the system's fundamental frequency needs to be adopted in the decoupling control. The published literature often uses the nominal frequency.1 or the estimated *** via a Phase-Locked Loop (PLL). However, it has not yet been revealed what is different between employing.1 *** for the decoupling control. In this article, a detailed discussion of the decoupling control with the two frequencies, i. e.,.1 ***, is provided. Initially, the small-signal impedance models of GCI considering the decoupling control with.1 *** are proposed. Afterward, the comparisons of the system's stability and decoupling precision with these two frequencies are given. The results demonstrate that 1) Frequency measurement accuracy has little impact on the system. 2) The control precision is approximately equal in the quasi-steady-state using the two decoupling frequencies even in the scenarios of frequency deviation (+/- 2Hz). 3) The system will be unstable *** is utilized, and then a lower PLL bandwidth should be adopted. Lastly, the theoretical analysis is verified by simulation results.

关键词： PLL GCI Frequency Measurement

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Dual-Scale Cellular Traffic Prediction Based on FastDTW for Graph Neural Network 16

Dual-Scale Cellular Traffic Prediction Based on FastDTW for ...

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16th international conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Jia, Junrong Zhang, Haixia Zhou, Xiaotian School of Control Science and Engineering Shandong University Jinan250061 China Shandong University Shandong Key Laboratory of Intelligent Communication and Sensing-Computing Integration Jinan250061 China

ISBN: (纸本)9798350390643

Cellular traffic prediction is crucial to the network efficiency as it provides prior knowledge to guide the wireless resource allocation. The artificial intelligence (AI) based traffic prediction can provide better prediction performance and has drawn increasing interests. Nevertheless, most existing works utilized euclidean structure data, which can provide traffic prediction to only certain grid area rather than specific spot, such as each base station (BS). To give more precise BS level prediction, in this work we propose a dual-scale spatiotemporal prediction framework based on fast dynamic time warping (FastDTW) algorithm. The proposed framework can capture both the overall neighborhood relationship of historical traffic and the local neighborhood relationship graph to improve the prediction accuracy. More importantly, due to the utilization of FastDTW, it solves the disadvantage of the high complexity of the dynamic time warping (DTW) algorithm and completes the prediction at the BS level more efficiently. Simulation results confirms the generality and performance of the proposed method, which outperforms the benchmark algorithms. © 2024 ieee.

关键词： Prediction models

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Impact of Mobile Coding Apps on Student Autonomous Learning in Tertiary education: A Case Study 6

Impact of Mobile Coding Apps on Student Autonomous Learning ...

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6th international conference on Computer science and Technologies in education, CSTe 2024

作者： Malimata, Charlyn A. Miranda, John Paul P. Mababa, Jonilo C. Canlas, Joel D. Hernandez, Hilene e. Yambao, Jaymark A. Pelayo, earl Lawrence B. National University Philippines Computing and Information Technology Department Manila Philippines Don Honorio Ventura State University Mexico Campus Mexico Philippines College of Computer Studies Angeles University Foundation Angeles Philippines College of Computing Studies Don Honorio Ventura State University Bacolor Philippines

ISBN: (纸本)9798350351804

This study looks into the impact of mobile coding apps on autonomous learning among tertiary students through a cross-sectional survey. Analyzing data from 377 students, primarily from the BS Information Technology program, the research reveals a potential gender gap in app usage and a reliance on smartphones for coding due to limited access to traditional computing devices. It highlights the widespread use of mobile coding applications, valued for their accessibility and hands-on experience, resulting in improved coding skills, critical thinking, and problem-solving abilities. While preferences leaned towards C++, a growing interest in Python was noted. These findings underscore the pivotal role of these apps in education, especially in resource-constrained environments, emphasizing the need for educational adaptation and policy changes to fully harness the transformative potential of technology in IT education, addressing disparities in access linked to income and gender while promoting autonomous learning. © 2024 ieee.

关键词： Application programs

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Half-Precision Scalar Support in Kokkos and Kokkos Kernels: An engineering Study and experience Report 18

Half-Precision Scalar Support in Kokkos and Kokkos Kernels: ...

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ieee 18th international conference on e-science (e-science)

作者： Harvey, evan Milewicz, Reed Trott, Christian Berger-Vergiat, Luc Rajamanickam, Siva Sandia Natl Labs Ctr Comp Res 1450 Innovat Pkwy SE Albuquerque NM 87123 USA

ISBN: (数字)9781665461245

ISBN: (纸本)9781665461245

To keep pace with the demand for innovation through scientific computing, modern scientific software development is increasingly reliant upon a rich and diverse ecosystem of software libraries and toolchains. Research software engineers (RSes) responsible for that infrastructure perform highly integrative work, acting as a bridge between the hardware, the needs of researchers, and the software layers situated between them;relatively little, however, has been written about the role played by RSes in that work and what support they need to thrive. To that end, we present a two-part report on the development of half-precision floating point support in the Kokkos ecosystem. Half-precision computation is a promising strategy for increasing performance in numerical computing and is particularly attractive for emerging application areas (e.g., machine learning), but developing practicable, portable, and user-friendly abstractions is a nontrivial task. In the first half of the paper, we conduct an engineering study on the technical implementation of the Kokkos half-precision scalar feature and showcase experimental results;in the second half, we offer an experience report on the challenges and lessons learned during feature development by the first author. We hope our study provides a holistic view on scientific library development and surfaces opportunities for future studies into effective strategies for RSes engaged in such work.

关键词： research software engineering scientific computing software libraries floating-point arithmetic

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Image Super-Resolution Reconstruction Based on Holistic Attention Dual Regression 2

Image Super-Resolution Reconstruction Based on Holistic Atte...

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2nd international conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Liu, JunChen You, Yuan Zhang, TianYou Li, ShiYu Shenyang Ligong University School of Information Science and Engineering Shenyang China College of Foreign Studies Liaoning University Shenyang China North Huajin Chemical Industries Group Corporation Panjin China State Grid Corporation of China Huludao China

ISBN: (纸本)9798350368888

When addressing the challenges of an excessively large solution space and the difficulties in channel attention mechanisms to restore texture details during the generation of High-Resolution (HR) images from Low-Resolution (LR) images, an image super-resolution reconstruction algorithm based on the Holistic Residual Attention Dual Network (HRADN) is proposed. The use of a Dual Regression Network (DRN) with additional mappings is employed to estimate the downsampling kernel and impose constraints on the LR images, thereby reducing the solution space of functions. The incorporation of the Layer Attention Module (LAM) and Channel-Spatial Attention Module (CSAM) explores the correlations between different modules in the network and uncovers deeper information within the training data. experimental evaluations conducted on five benchmark datasets have shown that the proposed algorithm outperforms several prevalent models in terms of Peak Signal-to-Noise Ratio (PSNR), indicating its superior performance in super-resolution reconstruction. It significantly improves the clarity of details and reconstructs sharper high-frequency textures in subjective visual effects. © 2024 ieee.

关键词： Image reconstruction

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