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检索条件"机构=Dept. of Computer and Electrical Engineering and Computer Science"

共 55359 条记录，以下是301-310 订阅

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Impacts of Earthing Variations on Overvoltage in Meshed Multi-terminal DC Grid 50

Impacts of Earthing Variations on Overvoltage in Meshed Mult...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Bader, Amir Ar-Rahman Ukil, Abhisek Dept. of Engineering Science The University of Auckland Auckland New Zealand Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (纸本)9781665464543

This paper investigates the impact of different earthing methods on overvoltage within modular multilevel Voltage Source Converter (MMC VSC) based Direct Current (DC) transmission and distribution grids, particularly in meshed multi-terminal (MTDC) configurations. A bipolar MTDC grid is modelled and simulated in PSCAD/EMTDC to investigate the influence of earthing on midpoint overvoltages. The transient response of the grid under DC fault scenarios is analysed through various case-studies, including solid earthing placement, variations in earthing impedance, and the application of surge arresters. The findings show the critical role of earthing in mitigating overvoltage, with low-resistive earthing options proving to be the most effective trade-off. © 2024 IEEE.

关键词： bipolar dedicated metallic return earthing meshed MTDC overvoltage

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Using the Wavelet Packet Transform to Evaluate Parameters of Harmonics Clustered in Quadruples Using Linear Systems

Using the Wavelet Packet Transform to Evaluate Parameters of...

引用

2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Nicolae, Ileana-Diana Nicolae, Petre - Marian Nicolae, Marian-Ştefan University of Craiova Dept. of Computer Science and It Craiova Romania University of Craiova Dept. of Electrical Engineering Energetic and Aeronautics Craiova Romania

ISBN: (纸本)9798350360394

The paper presents an original technique used to evaluate the parameters of quadruples of harmonics clustered in an almost exclusive manner to quadruples of nodes from the bottom level of a Wavelet Packet Tree. The harmonic signal (RHS) generated by harmonics from a quadruple can be deduced with approximation from the analyzed signal by using original computational techniques. Linear systems were conceived based on the harmonics superposition and randomly chosen components of RHC (the approximated version of RHS). Their solving yields sets of possible solutions, that are afterward refined to exclude values with non-zero imaginary parts or deviant values. Averages over refined values are used. The indetermination relative to phase-shifts is solved considering the criterion of "best approximation"of RHC by the signal obtained through the superposition of the computed clustered harmonics. The harmonics from the studied quadruples are: (11, 13, 19, 21), (23,25,39,41) and (27,29,35,37). This paper provides the complementary technique for the odd harmonic identification within the range 3...41 (the odd harmonics not belonging to quadruples are coupled in pairs and were approached in a previous publication). © 2024 IEEE.

关键词： Wavelet analysis

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A Multistage Cascaded Neural Network Model to Identify the Severity of Epileptic Attack

A Multistage Cascaded Neural Network Model to Identify the S...

引用

2024 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2024

作者： Simon, Martha Thampi, Lidiya Lilly Dept. of Computer Science College of Engineering Trivandrum India Indian Institute of Information Technology Kottayam Dept. of Computer Science Kottayam India

ISBN: (纸本)9798350376135

Epilepsy is a neurological disorder characterized by recurrent seizures, impacting the quality of life for millions of individuals worldwide. Timely and accurate detection of epileptic seizures is crucial for proper diagnosis and effective treatment. Electroencephalogram (EEG) signals provide vital information about brain activity and serve as a valuable tool for epilepsy detection. The methodology opted for this study was an enhanced multilayer feed forward neural network for automatic detection of epilepsy from EEG signals and hence predicting the severity. The authors build a multistage cascaded neural network model for achieving the same. Initially a Simple Artificial Neural Network (SimpleANN) is designed to classify EEG segments into seizure, healthy and interictal. Later a Multilayer Feed Forward Neural Network (MFFNN) is employed for detecting the severity of epileptic patients and hence can be classified into primary and secondary stages. The experimental results showed that the proposed SimpleANN classifier had provided noticeable results, and outperforms all tested classifiers. The study involves the collection of EEG data from a diverse group of patients, including those with epilepsy and healthy individuals. This automated epilepsy identifying system passes through different stages including decomposition, feature extraction for achieving a better performance model. The proposed system was tested and compared with SVM, KNN, MLP and Decision Tree under different measurement metrics. ANN has managed to give an accuracy of 80 - 90% which is significantly higher as compared to other machine learning models. The proposed work can automatically learn complex patterns from EEG data provides an advantage in identifying subtle seizure related features that may not be evident through manual analysis. Furthermore, the model offers real-time capabilities, making it suitable for continuous monitoring of patients at risk of seizures. © 2024 IEEE.

关键词： Electroencephalography

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IoT-based Automatic Pan Evaporimeter Monitoring and Irrigation Control System for Crops 8

IoT-based Automatic Pan Evaporimeter Monitoring and Irrigati...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Kabir, Md Shahriar Niloy, Khalid Mahmud Hossen, Md Imon Afrose, Sumaiya Mofazzol, Md. Ismail Hossain American International University-Bangladesh Dept. of Electrical & Electronics Engineering Dhaka Bangladesh Uttara University Dept. of Computer Science Engineering Dhaka Bangladesh

ISBN: (纸本)9798350376425

This research study intends to automate the manual pan evaporimeter system and scheduling irrigation by considering soil water content and crop evapotranspiration. Automating the pan evaporimeter means performing tasks without human intervention, such as measuring the daily water evaporation amount, calculating and storing data, and refilling the pan with water. A waterproof ultrasonic sensor was used to measure the water evaporation amount. The ultrasonic sensor was installed on an innovatively designed structure facing the pan's water surface. The sensor measured the distance between the water surface and the sensor. The surface level decreased as the water evaporated over time, which caused an increment in the distance between the ultrasonic and water surfaces. By this, the sensor calculated the daily evaporation amount. The pan needed to be refilled when all water evaporated;a submersible pump was used to refill the pan automatically. A relay switch controlled the pump, and a microcontroller turned on the switch based on sensor value. The entire setup was IoT-enabled to monitor and control the system remotely on a mobile device. The entire system was backed up by solar energy to run on clean energy. A solenoid valve was used to control the flow of irrigation water. Pan evaporation estimated the amount of water that could be lost owing to evaporation and transpiration. Soil moisture sensors provided a direct measurement of the amount of water present in the soil. The two combined generated a dynamic and responsive irrigation plan that maximized water use and promoted the healthy development of crops. That approach was used. The ultrasonic sensor accurately measured water evaporation, but the installation process was complex. So, a need arises to develop a simple system or scale-type sensors to overcome the complexity. © 2024 IEEE.

关键词： Solenoid valves

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UAV-Enabled Covert Cross-Technology Communication in Heterogeneous IoT Networks 100

UAV-Enabled Covert Cross-Technology Communication in Heterog...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Xia, Xiaohao Esmat, Haitham H. Lorenzo, Beatriz Goeckel, Dennis University of Massachusetts Amherst Dept. Electrical and Computer Engineering United States

ISBN: (纸本)9798331517786

Heterogeneous Internet of Things (IoT) networks enabled by Unmanned Aerial Vehicles (UAVs) operate in various protocols and spectrum bands (e.g., WiFi, LoRa, Zigbee) to collect and offload data generated from heterogeneous sensors. However, achieving timely and secure communications is challenging due to uncertain data generation, mobility, and location of wardens. This paper presents a collaborative framework that exploits cross-technology communications to achieve covertness constraints. The aim is to minimize the age of covert information (AoCI) and energy consumption by jointly optimizing data scheduling, power allocation, and offloading decisions by collaborating with UAVs. A multi-agent actor-critic algorithm that incorporates federated learning and attention mechanisms (cluster-MAAC-attention) is presented to solve the previous problem. Our simulation results show that our algorithm reduces the worst AoCI by 4 times, and reduces the penalty by 20 times compared to existing schemes. © 2024 IEEE.

关键词： Zigbee

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Transformer-Based Embeddings for Greek Language Categorization 24

Transformer-Based Embeddings for Greek Language Categorizati...

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24th IEEE/ACIS International Conference on computer and Information science, ICIS 2024

作者： Liapis, Charalampos M. Kyritsis, Konstantinos Perikos, Isidoros Paraskevas, Michael University of Patras Computer Technology Institute & Press 'Diophantus' Mathematics Dept. Patras26504 Greece University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350376647

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for accurate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior performance of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear advantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems. © 2024 IEEE.

关键词： Contrastive Learning

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Big Mart Sales Analysis 6

Big Mart Sales Analysis

引用

6th International Conference on Computational Intelligence and Communication Technologies, CCICT 2024

作者： Kunal Singh, Muskaan Sharma, Harshit Roy, Shweta Agarwal, Kadambri Dept. of computer science and engineering ABES engineering college Ghaziabad India

ISBN: (纸本)9798350374629

Machine learning is a powerful technology that enables computer systems to recognize patterns and make prediction and choices without performing explicit programming. The basic notion behind this technology is to create models and algorithms that can take in input information, predict an outcome using statistical computation, and adjust outputs in response to fresh information. In this research paper, we examine the Big Mart Shopping Centre scenarios in order to forecast sales of various product categories and comprehend the impact of various factors on sales of various product categories. This paper focuses on leveraging machine learning techniques to predict sales for Big Mart with the aim of optimizing inventory management and maximizing revenue. Using a variety of characteristics from a dataset that Big Mart gathered, along with the methodology used to construct a prediction model, very accurate results are produced and these findings can be utilized to make decisions aimed at increasing sales and increase operational efficiency. ©2024 IEEE.

关键词： Sales

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Synergistic Use of Offshore Wind, Wave, and Photovoltaics for Maritime Hydrogen Refueling: How the Synergy Impacts the Storage Requirements? 5

Synergistic Use of Offshore Wind, Wave, and Photovoltaics fo...

引用

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

作者： Pompodakis, Evangelos E. Karapidakis, Emmanuel Hellenic Mediterranean University Dept. of Electrical and Computer Engineering Heraklion Greece

ISBN: (纸本)9798350352863

This paper investigates the combined use of offshore wind, wave energy, and solar photovoltaics for maritime hydrogen refueling stations, with a focus on their influence on storage requirements. Eastern Crete and the Galite Islands, two Mediterranean sites with significant wind, wave, and solar energy potential, were selected as case studies for the installation of such stations. The research utilizes a Storage-to-Production Ratio (SPR) index to measure the amount of storage required to ensure a stable, uninterrupted hydrogen supply throughout the year, relative to the total annual hydrogen production. The results demonstrate that integrating either wind or wave energy with solar power significantly reduces the SPR, thanks to the weak temporal correlation between solar and the other two sources. This reduction can reach up to 20%, which, for a station providing an annual hydrogen supply of 20,000 tons, translates to a 4,000-ton reduction in storage needs. Conversely, combining wind and wave energy in the Mediterranean does not achieve a similar SPR reduction due to their strong temporal correlation. © 2024 IEEE.

关键词： Hydrogen storage

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Analyzing and Visualizing Causes of Poverty in India: A Data-Driven Approach Using HPCC Systems 8

Analyzing and Visualizing Causes of Poverty in India: A Data...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Skanda, P.R. Shobha, G. Shetty, Jyoti Rv College of Engineering Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331505462

Poverty in India is a complex issue with multiple causes. This paper mainly focuses on three of the main causes for poverty: Education, Unemployment and Consumer Price Index. This study makes use of data received from the National Informatics Center (NIC) of India to predict poverty across the various states of India. Through applying preprocessing techniques and employing the HPCC Systems Visualization bundle, the research shows that Bihar is facing a higher level of poverty, whereas Mizoram exhibits converse trend. Subsequently, the HPCC ML-Core bundle is applied to conduct linear regression analysis for predicting poverty scores. This predictive model demonstrated an accuracy of 97%. Lastly, the difference between a single-node and 8-node cluster is presented for runtime performance which clearly shows that the 8-node cluster has an advantage for similar computational tasks and thus makes it suitable. © 2024 IEEE.

关键词： Visualization

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Load Flow Analysis and Optimization for Solar PV Integration in Power Systems 21

Load Flow Analysis and Optimization for Solar PV Integration...

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21st International Learning and Technology Conference, L and T 2024

作者： Shigdar, Basmah Binsalim, Haya Almatrafi, Lina Badaam, Salma Barkat, Enfel Effat University Dept. of Electrical & Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

Saudi Arabia's Vision 2030 emphasizes renewable energy to drive sustainable development, particularly leveraging solar power due to abundant sunshine. However, integrating solar photovoltaic (PV) systems into existing grids presents multifaceted challenges. Voltage regulation, power quality issues, and reverse power flow disruption due to solar intermittency demand effective management strategies. Challenges, including voltage fluctuations, power quality issues, reverse power flow disruptions, and solutions like energy storage, advanced inverter control, demand response, and grid modernization, are explored to mitigate these challenges. A literature review and methodologies are presented, including PV generator modeling and power flow calculations. The proposed methodology is validated through case studies and a simulation based on the Institute of electrical and Electronics Engineers (IEEE) 30-Bus System, showcasing differences in voltage and angle outputs across nodes with integrated PV generators. © 2024 IEEE.

关键词： Power quality

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