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Network Performance Analysis of Smart Grid Communications Over LTE cat-M 14

Network Performance Analysis of Smart Grid Communications Ov...

引用

14th IEEE international conference on Communications, control, and computing Technologies for Smart Grids, SmartGridComm 2023

作者： Dash, Biswajit Kumar Shah, Sureel Malandra, Filippo State University of New York at Buffalo Department of Electrical Engineering NY United States University of California Department of Electrical and Computer Engineering San DiegoCA United States

ISBN: (纸本)9781665455541

Smart grid applications heavily rely on communication infrastructures that offer flexibility, scalability, and cost-effectiveness to enable bi-directional information exchange across geographically distributed grid elements. Wireless cellular networks, such as LTE cat-M, provide extensive coverage at a reduced cost, both in terms of installation and power consumption. This paper presents a multi-node testbed to assess the suitability of LTE cat-M technology for a variety of smart grid applications, with distributed nodes collecting and transmitting data at a variable rate, from 0.25 to 100 frames per second (fps). Based on field experiments, an extensive performance analysis is presented with Key Performance Indicators (KPIs), such as delay, jitter, and frame loss. The impact of the number of smart grid nodes and propagation quality are also considered in the analysis. Finally, a calibration method to optimize the packet transmission time is presented with a 33.91% delay reduction under different conditions. © 2023 IEEE.

关键词： Network performance

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Base-backstepping Continuous Time-varying Feedback control of automatic Magazine with Modelling Uncertainty

Base-backstepping Continuous Time-varying Feedback Control o...

引用

2022 international Symposium on Advanced Launch Technologies, ISALT 2022

作者： Lin, Y.B. Hou, B.L. School of Mechanical Engineering Nanjing University of Science and Technology Nanjing210094 China

This paper proposes a continuous time-varying feedback control based on back-stepping for automatic magazine system, in which the control gains depend on the Lyapunov function to ensure the robustness against modelling uncertainty. The Lyapunov function, which is implicit, is differentiable functions of system error variables. Integrated with backstepping control, the performance of the automation magazine system is greatly improved, while retaining the advantage of only needing to ensure the bounds of disturbances. Lyapunov analysis shows tracking errors of the system are asymptotically stable. In addition, this proposed controller is continuous and has the characteristics of simplicity and practicality, which are beneficial to practical applications. Finally, Numerical simulations are provided to verify the high performance of the controller by comparing the simulation experimental results in automation magazine system. © Published under licence by IOP Publishing Ltd.

关键词： Lyapunov functions

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Cloud Cost Prediction with LSTM on Parametric Data 16th

Cloud Cost Prediction with LSTM on Parametric Data

引用

16th international conference on Genetic and Evolutionary computing, ICGEC 2024

作者： San, Khin Pyae Phyo Thein, Nwe Nwe Myint Data Distribution Management Lab University of Information Technology Parami Road Hlaing Campus Yangon Myanmar Faculty of Computer Science Data Distribution Management Lab University of Information Technology Parami Road Hlaing Campus Yangon Myanmar

ISBN: (纸本)9789819615308

In the distributed computing paradigm, cloud computing provides a wide range of software, platforms and computing infrastructure. It has ability sharable elastic resource pools in dynamic. In this way, cloud computing offers many benefits. It reduces the cost of deployment in applications. It makes easy to increase the capacity of local infrastructures. And it can reduce power consumption by sharing resources. There are challenges over the benefits. The virtual instances needed to be shared equally distributed across different availability zones per demand. That can be categorized into operational and business challenges. In this paper, we implement the cloud prediction system using historical billing data and study the measurement of the model accuracy using Mean Absolute Error and Root Mean Squared Error. The trained model evaluates by the predicted and targeted value graph in this study. By leveraging historical financial data, this method aims to aid organizations in better foreseeing and managing AWS expenditures, leading to improved cost control and financial planning for cloud infrastructure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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Soft computing Tools for Multiobjective Optimization of Offshore Crude Oil and Gas Separation Plant for the Best Operational Condition 18

Soft Computing Tools for Multiobjective Optimization of Offs...

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18th international conference on electrical engineering, computing science and automatic control (CCE)

作者： Mendoza, Jose H. Tariq, Rasikh Santis Espinosa, Luis F. Anguebes, Francisco Bassam, A. Univ Autonoma Carmen Fac Engn 56 4 Esq Ave Concordia Ciudad del Carmen 24180 Campeche Mexico Univ Autonoma Yucatan Fac Ingn Av Ind Contaminantes Anillo Perifer Norte Merida Yucatan Mexico

ISBN: (纸本)9781665400299

The selection of operating conditions in the oil and gas separation plants is obtained through data monitoring or through the experience of the operating personnel which can bring operational difficulties leading to inefficiencies and capital loss. The modern techniques of soft computing including artificial intelligence and genetic algorithm-based optimization can add value to this operation. In this work, five key controllable design variables of an oil and gas separation plant are optimized considering two performance indicators (oil flow productivity and gas compression power). The physical model of the plant is simulated using ASPEN HYSYS, and a digital twin model is generated using an artificial neural network. It is followed by a multiobjective optimization using non-dominating sorting genetic algorithm II to obtain the Pareto front. The results have indicated that operational optimization can enhance oil production by up to similar to 6.2% and decrease the compression work by similar to 3.2%. It is concluded that the proposed operation of the plant is energy-efficient and can increase productivity.

关键词： simulation oil and gas separation optimization data science soft computing artificial neural network

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An Intensive Technical Analysis of Home Automation using IOT with Node MCU 3

An Intensive Technical Analysis of Home Automation using IOT...

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3rd international conference on Advance computing and Innovative Technologies in engineering, ICACITE 2023

作者： Singh, Aman Kumar Chaudhary, Aditya Verma, Abhishek Alwan, Adil Abbas Allwi Ftaiet, Adnan Mohammed, Aymen Galgotia College of Engineering and Technology India National University of Science and Technology Collage of Engineering Dhi Qar Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad Iraq

ISBN: (纸本)9798350399264

Home automation has become an ever-increasing number of well-known lately. It targets assisting individuals with dealing with home appliances openly and constructing an autonomous climate in the home. The Internet of Things (IoT) with remote control is an innovation that computerized basic home administrations and choices overall over the Web utilizing PCs or cell phones. Associating home apparatus electrical gadgets with the web or distributed storage can bring about home automation. The Internet of Things (IoT) is an augmentation of the webserver to give correspondence, association, and inter' networking between different gadgets or physical objects also known as "Things''. Node-MCU is the most important component of this system and it can proceed as a miniature web server it goes probably as a mark of cooperation for the extensive variety of hardware modules. To control lights, fans, and other home machines which are associated with the handoff framework, the framework offers exchanging functionalities. This task expects to carry out a voice control home computerization framework utilizing a framework that is executed utilizing common domestic devices. © 2023 IEEE.

关键词： Internet of things

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Using Augmented Reality to enhance the experience of IoT-based Home Automation Systems

Using Augmented Reality to enhance the experience of IoT-bas...

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2023 IEEE international conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Kaur, Deepti Prit Sharma, Manmohan Sharma, Preeti Malik, Garvit Mehakdeep Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of computer Science and Engineering Manipal University Jaipur Jaipur India

ISBN: (纸本)9798350305708

Internet of Things (IoT) is an integral part of home automation, where physical devices are interconnected such that, they enable communication amongst electronics, sensors, software, and network. The data collection and analysis in IoT, and unified framework in cloud computing strives to improve living standards and productive outcomes by interacting with smart devices. In various fields such as education, control, and entertainment, Augmented Reality (AR) technology attempts to improve user experiences through improved interactions within the available settings. This paper presents an IoT based Home Automation System, which uses Augmented Reality as an additional technology to enable utilization of real time visualization and interaction for better experience. The application is beneficial for children, elderly and differently abled persons as it would aid them with control of electrical appliances just by scan through a device camera, connected to internet. From a safety perspective also, it offers electrical isolation. © 2023 IEEE.

关键词： Augmented Reality Home Automation IoT

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Classification of Sleep Stages Using Single-Channel ECG Signals: A Comparative Analysis of Machine Learning and Deep Learning Methods 14

Classification of Sleep Stages Using Single-Channel ECG Sign...

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14th IEEE international conference on Signal Processing, Communications and computing, ICSPCC 2024

作者： Ullah, Ahmad Khan, Muhammad Salman College of Engineering Qatar University Department of Computer Science and Engineering Doha Qatar College of Engineering Qatar University Department of Electrical Engineering Doha Qatar

ISBN: (纸本)9798350366556

In this paper, we provide an extensive evaluation of machine learning (ML) and deep learning (DL) methods for automatic sleep stage classification using a single-channel electrocardiogram (ECG) signal. To explore ML methods, we extracted 21 heart rate variability (HRV) features using the R-peak detection. These features were used to train and compare the performance of various models such as support vector machine (SVM), decision tree (DT), random forest (RF), k-nearest neighbor (K-NN), and Naïve Bayes (NB). Furthermore, we analyzed the DL methods to overcome the manual feature extraction. This method involved feeding raw time-series ECG signal to a 1-dimensional convolutional neural network (CNN) and short-time Fourier transform (STFT) based spectrogram to a 2D CNN. The overall evaluation was performed using 15-subject data each from two publicly available datasets. To process the data for analysis, resampling, bandpass filtering, baseline correction, 30-second interval extraction from whole-night ECG recordings, and z-score normalization techniques were applied. We conducted experiments on one dataset and then replicated the experiments on the other dataset to assess the robustness and generalizability of the methods. Through a comparative analysis, the spectrogram-based 2D CNN emerged as the effective method with the highest test accuracy and k-score of 87.65% and 0.82 respectively. This study contributes to ECG-based sleep classification research, highlighting the effectiveness of deep learning for effective classification. © 2024 IEEE.

关键词： Convolutional neural networks

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Securing Medical Data Records using Blockchain in a Cloud computing Environment 3

Securing Medical Data Records using Blockchain in a Cloud Co...

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3rd international conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Hebballi, Anandarshan K Bharath, J. Agarwal, Akansha Challa, Manoj CMR Institute of Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665494007

In the current age of Information technology and Smart systems, where data is the new oil, it has become highly crucial to effectively store and share any sort of digital data. In recent years the high volumes of Medical Health Data have been under the data breaches by the third parties in the current centralized storage systems, raising concerns for patient data privacy and also the inconvenience for patients to access their own Health records. Blockchain technology with the integration of cloud storage for medical records provides enhanced security of data over the network through the immutable nature of blocks in blockchain and an effective decentralized storage system can be achieved by cloud computing. The model discussed in this paper gives the architecture and implementation of Medical Health Records systems secured through Blockchain and cloud technologies with various tools used. The working prototype which has been implemented is discussed with the demonstration of accessing and sharing of medical data by the patients with the doctors and insurance agencies. The proposed system meets the requirements of patient data privacy by giving greater control of medical data to patients. © 2023 IEEE.

关键词： Blockchain

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Photon Coincidence Simulation Through a Random Splitting of Virtual Photon Timestamps 3

Photon Coincidence Simulation Through a Random Splitting of ...

引用

3rd IEEE international Maghreb Meeting of the conference on sciences and Techniques of automatic control and Computer engineering, MI-STA 2023

作者： Ehtaiba, Jamal M. Higher Institute of Science and Technology Dept. of Electrical Engineering Misurata Libya

ISBN: (纸本)9798350319897

The single-photon nature and the purity of emitted photons from a light source can be quantified using the second-order correlation function, g(2)(τ). Here, we present simulation results that show how the photon coincidence time window, a characteristic of the utilized photodetection system, affects g(2)(0) for dummy photon timestamps digitally generated at constant emission rates. We use a two-channel virtual interferometer with a beam splitter controlled by a uniform random number selection. We find that g(2)(0) remarkably and quickly squeezes towards the maximum value of a chaotic light photon correlation as the coincidence time window widens. In contrast, tuning the coincidence time window close to the emitter emission decay time yields a coincidence probability of slightly less than one, an antibunching property of light. These simulation findings can participate in improving measurements of quantum light emitters' coherence functions and revealing the degree of their photon emission purity. © 2023 IEEE.

关键词： Photons

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Dynamic Obstacle Avoidance Method for Road Vehicles Via Improved Artificial Potential Field 7

Dynamic Obstacle Avoidance Method for Road Vehicles Via Impr...

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7th CAA international conference on Vehicular control and Intelligence, CVCI 2023

作者： Xu, Mingyang Xu, Chen Qi, Gengxin Yue, Ming Zhao, Xudong School of Automotive Engineering Dalian University of Technology Dalian China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350340488

In order to solve the safety problems caused by the vehicles collision on the highway, an automatic controller is proposed based on the artificial potential field (APF) method and the model predictive control (MPC) theory to keep the automatic driving vehicles collision-free. Firstly, in the path planning, the road potential field is constructed to satisfy the constraints of vehicle safe driving based on the driving characteristics of vehicles and road boundary conditions. Secondly, according to the shape of the obstacle vehicle in the study, the obstacle vehicle potential field is established. Finally, in order to ensure that the vehicle can drive along the planned path in a stable and safe manner, this paper combines the MPC and vehicle dynamics to design the path tracking module. Then the designed automatic controller is verified on the Carsim-Simulink joint simulation platform based on the obstacle vehicle uniform speed and acceleration test scenarios. The results show that the automatic controller enables road vehicles to safely avoid dynamic obstacle vehicles by updating design parameters in real time to adapt to the changing environment while satisfying environmental constraints and vehicle stability. © 2023 IEEE.

关键词： artificial potential field model predictive control obstacle vehicles path planning

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