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Fast Contingency Filtering Using Machine Learning for Power System Planning 11

Fast Contingency Filtering Using Machine Learning for Power ...

引用

11th ieee international conference on Smart energy grid engineering, SeGe 2023

作者： Alvarez, David L. Nour, Georges Abdul Gaha, Mohamed Cote, Alain Université du Québec À Trois-Rivières Department of Industrial Engineering Trois-Rivières Canada Data Science and High Performance Computing Varennes Canada Asset Sustainability Varennes Canada

ISBN: (纸本)9798350340716

Modern power systems assess reliability N -k and k = 2, 3, 4,⋖ criteria to guarantee the secure, sustainable and optimal operation of power networks. However, performing these studies with traditional methods is computation-intensive and time-prohibitive for the long-term planning of large networks. In this paper, we present a Machine Learning (ML) model for rapid contingency filtering in order to evaluate problematic N - k contingency scenarios. Our proposed model is trained with data sets stochastically created and labeled with AC load flows considering load forecasting. Their inputs are the time and N - quad k status of network equipment. The performance of the proposed ML model was evaluated on the ieee 39-Bus System for a planning period of 10yr with a time resolution of 1h. The performance obtained was an accuracy greater than 95% with a time acceleration of approx. 2500x. This result makes the proposed model suitable for supporting decision making during the planning of power systems. © 2023 ieee.

关键词： Machine learning

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Visual simulation of bone cement blending and dynamic flow

Visual simulation of bone cement blending and dynamic flow

引用

2024 ieee international conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Shen, Long Zhang, Yalan Frey, Steffen Telea, Alex Kosinka, Jiri Wang, Xiaokun Ban, Xiaojuan University of Science and Technology Beijing School of Intelligence Science and Technology Beijing China University of Groningen Bernoulli Institute Groningen Netherlands Utrecht University Department of Information and Computing Sciences Utrecht Netherlands University of Science and Technology Beijing Beijing Key Laboratory of Knowledge Engineeringfor Materials Science Beijing China

ISBN: (纸本)9798350386226

Bone cement filling is an important method for preventing osteoporosis and treating fractures. In bone cement filling surgery, the preparation and dosage of the cement usually depend on specific product manuals and the doctor's experience. If bone cement is not used properly, it may cause additional damage. For teaching and auxiliary medical purposes, for example, assisting doctors to observe the possible flow of bone cement, this paper proposes a multiphase non-Newtonian fluid simulation method to simulate and visualize the flow behavior during the wet sand phase of bone cement blending and polymerization. Our method enables showing intuitively the application process of bone cement under different scene settings to obtain dynamic bone cement effects with high stability and performance. Compared with other methods, our method can simulate highly viscous mixed fluids efficiently and robustly, which supports our method's usage in the aforementioned training and experimentation scenarios. © 2024 ieee.

关键词： Non Newtonian flow

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Prediction of Cloud API Performance Using Uncertainty-Based Fusion of Predictive and Analytical Modeling 25

Prediction of Cloud API Performance Using Uncertainty-Based ...

引用

25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data science and Systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Hewavitharana, Jayani Jihan, Nadheesh Jayasinghe, Malith Gunawardana, Kasun Fernando, Duneesha University of Colombo School of Computing Colombo Sri Lanka Ltd. Colombo Sri Lanka

ISBN: (纸本)9798350330014

Performance prediction for cloud applications is important due to multiple reasons, including ensuring service level agreements, cost optimization, and resource provisioning. However, accurately predicting performance is challenging on account of different characteristics of performance data, such as noise, which can occur due to errors in measurements or specific behaviors of cloud applications, and imbalanced data (i.e., regions of missing data), which can occur due to various access patterns of users. existing prediction methods using analytical, machine learning, as well as hybrid approaches assume uniformly distributed performance data, and these methods have high uncertainty and low accuracy when interpolating and generalizing into areas that do not contain reference data. In this paper, we introduce two novel approaches, Uncertainty-based Sub-modeling, and Uncertainty-based Iterative Sampling, as methods of combining analytical and machine learning approaches based on the uncertainty of predictions (i.e., predictive uncertainty). We focus on improving the predictions in under-represented regions by utilizing the analytical model based on an inference threshold as well as by incorporating data generated using analytical models for machine learning model training. Our approaches outperform their baseline models in 8 and 12 out of 15 cases with respect to RMSe and MAe respectively. Further analysis reveals that our approaches excel in addressing imbalanced data scenarios within performance modeling, outperforming previously proposed machine learning and hybrid models. © 2023 ieee.

关键词： Analytical models

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Development of a Seven-Level Inverter with Minimized Switch Count for grid-Integrated Solar PV Applications 6

Development of a Seven-Level Inverter with Minimized Switch ...

引用

6th international Youth conference on Radio electronics, electrical and Power engineering, ReePe 2024

作者： Ali, Ahmed Ismail M. Saeed, Mahmoud S. R. Ali, Abdelfatah Shabaan, Mostafa F. Youssef, Abdel-Raheem Mohamed, essam e. M. Electrical Engineering Department South Valley University Qena83523 Egypt American University of Sharjah Electrical Engineering Department Sharjah United Arab Emirates

ISBN: (纸本)9798350382891

This paper introduces a straightforward 7-level inverter sinusoidal controlled using pulse-width modulation for solar photovoltaic (PV) applications and contemporary inverter manufacturing. The design emphasizes a minimized count of power components, achieving reduced Total Harmonic Distortion (THD) in the output voltage through the integration of compact passive elements to filter the output voltage/current waveforms. In addition, the proposed inverter mitigates the complex control strategy that simplifies the required controller specifications as illustrated in the operation principles and switching strategy. Also, comparative study is enriched to compare the proposed 7-LI with its counterpart ones based-on the required number of elements as well as the number of components for required output-voltage levels, as an effective parameter for inverter selection. The proposed inverter structure has been verified through a grid-tied solar PV system using MATLAB/Simulink for high power-quality grid-integrated PV generation systems. © 2024 ieee.

关键词： DC-DC converters

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Hybrid Algorithm for Secure Routing in MANeT Using Cryptographic Applications

Hybrid Algorithm for Secure Routing in MANET Using Cryptogra...

引用

2024 ieee international conference on electronic Systems and Intelligent computing, ICeSIC 2024

作者： Muruganandam, S. Gnanavel, S. Narayana, K.e. Jaeyalakshmi, M. Antony Kumar, K. Panimalar Engineering College Department of Computer Science and Business Systems Chennai India SRM Institute of Science and Technology Kattankulathur Campus Faculty of Engineering and Technology Department of Computing Technologies Chengalpattu India Rajalakshmi Engineering College Department of Information Technology Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331522988

In Mobile sensor Networks, each and every wireless node dynamically changes its location due to its mobility nature. The routing information is maintained by the master node to deliver a data packet from source to destination. The attackers easily hack this wireless network. The performance of the complete networks is dropped by packets transmission attacks. Attacker node drops the packet. An enhanced protection technique in response to packets transmission misbehaviour attacks is provided to increase the energy efficiency of mobile nodes. This paper proposed the Cryptographic formed Malicious Node Detection and Secure Routing framework (CMNDSR). This model incorporates three various strategies specially algorithm for control of access, to protects initial illegal node in the network. The suspected identification and prevention techniques based on hop count value. Secure routing method with a private key generated at random like one time password (OTP). The proposed methods are power efficient, by operating a minimum number of nodes in challenging environment. The misbehaviour nodes are promptly identified and isolated using this proposed approach. The Cryptographic based Secure routing algorithm is applied to provide secure transmission in wireless networking environment. The outcomes of the simulation display how effectively the recommended approach can identify malicious nodes in a MANeT. In comparison with previous methods, the energy consumption is 10% lower and the suspicious node detection rate is increased by 95%. © 2024 ieee.

关键词： encryption algorithms

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Decentralized Trust: Visual Cryptography for Transparent e-Voting Solutions

Decentralized Trust: Visual Cryptography for Transparent E-V...

引用

2024 international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSeS 2024

作者： Asmitha, M. Kavitha, C.R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543617

e-voting system is a digital mechanism that enables people to vote electronically, ensuring confidentiality, security, and transparency. Visual cryptography (VC) is a cryptographic technique where a secret image is divided into two or more shares, and only by superimposing these shares can the secret be revealed. When combined, visual cryptography offers a unique and secure way to enhance e-voting systems, providing features such as transparency, privacy, and tamper-proof mechanisms. It has an exceptional way of splitting a secret image into n pieces such that each piece reveals no information about the whole. Whenever these shares are stacked or overlaid, the original image is recreated again. This means that every share taken alone does not provide any clues to what is in the hidden content, and so it is a very good option for safeguarding shared information. In terms of electronic voting systems, visual cryptography can be used as a possible solution to addressing issues such as vote tampering, coercion and confidentiality of voters. This paper aims to enhance the security and confidentiality of electronic voting systems through the implementation of visual cryptography. A high level of security and verifiability can be realized with e-voting system through visual cryptography. © 2024 ieee.

关键词： Voting machines

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Traffic Data Scheduling of Frequent Application Sets for Task Offloading in Multi-access edge computing

Traffic Data Scheduling of Frequent Application Sets for Tas...

引用

ieee international conference on Communications (ICC)

作者： Hu, Yifeng Qiu, Tie Chi, Jiancheng Yang, Xuan Wang, Zimu Li, Wenguang Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China State Grid Elect Commerce Co Ltd Beijing Peoples R China State Grid Ecommerce Technol Co Ltd Tianjin Peoples R China

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

Frequently task offloading in the Multi-access edge computing (MeC) system takes up a lot of network resources, which leads to serious network congestion problems. To deal with such problems, applying data pricing strategies in task offloading to schedule traffic data is perceived as a promising solution for Internet service providers (ISPs). However, the traditional application-oriented data pricing strategies do not consider user satisfaction of the task executing process, resulting in lower ISP profit. In this paper, a novel scheme named Appset Usage Patterns-Aware task offloading scheme (AUPA) is proposed to alleviate the tension between traffic data supply and user satisfaction. We mine the sequential patterns in frequent application sets to extract temporal association rules. Then these association rules are used to design a smart data pricing strategy to guide the task offloading decision. Finally, we formulate the ISP's profit maximization problem as a nonlinear programming (NLP) problem based on partial offloading, and we simulate the scheduling processuse using the Stackelberg game model. The performance of our solution is evaluated in terms of ISP's profit, consumers' surplus, capacity utilization, and traffic efficiency. The results show that our scheme significantly improves the ISP's profit by about 20% while ensuring capacity constraints compared with other baseline schemes.

关键词： task offloading multi-access edge computing data pricing sequential pattern mining

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A Research on the evaluation Technical Means and Value Identification Method of eV Load Response to Power grid Regulation Instructions 13

A Research on the Evaluation Technical Means and Value Ident...

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13th international conference on Power, energy and electrical engineering, CPeee 2023

作者： Yu, Qingguang Li, Xiaoyu Li, Yong Zhu, Rui Qing, Quan Zhou, Yuqing Lan, Qiang Zhang, Mingmei Zhan, Hang Guo, Min Sun, Yi He, Jiajun Tsinghua University Dept. of E.E Beijing China Southwest Branch of State Grid Corporation of China Chengdu China State Grid Chongqing Electric Power Company Chongqing China Tsinghua University Fundamental Industry Training Center Beijing China

ISBN: (纸本)9781665490146

This paper concentrates on new features of electric vehicle (eV) cluster in vehicle-to-grid (V2G) process. Two new variables are proposed to describe the impacts of V2G on grid considering differences between eV and generating units. Taking electricity price and battery wear cost into account, this paper presents a baseline cost of eV offering ancillary service and pricing coefficients with piecewise linearity. © 2023 ieee.

关键词： Costs

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Research on 3D Visualization of Geographic Information Data in Big Data environment

Research on 3D Visualization of Geographic Information Data ...

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2023 international conference on Applied Physics and computing, ICAPC 2023

作者： Zhang, Jiantao Lai, Weiping Huang, Yanshan Wu, Jianbin Lin, Xiaojun State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fujian Fuzhou350000 China

ISBN: (纸本)9798350359244

This paper introduces a system framework for rapid construction and rendering of 3D virtual environment using 2D GIS data. A large-scale GIS data 3D visualization system is designed and implemented. ArcSDe and SQL Server are used to store data. After extraction, processing and registration of multi-band images, the images are stored in the database in Shape form. SURF feature points were extracted and images were matched. DeM is combined with preprocessed multi-band remote sensing images. It was 3D visualized by AcrScene software. The system can well realize correlation analysis, two-dimensional and three-dimensional attribute correlation query, and big data rendering. After testing, this design has good smoothness, fast response and good picture quality. It has nice interactive features. The system can automatically load and splice terrain data. © 2023 ieee.

关键词： Big data

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Non Linear grid Based Search energy Optimization for AUV Aided Underwater Acoustic Sensor Network 10

Non Linear Grid Based Search Energy Optimization for AUV Aid...

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10th international conference on Communication and Signal Processing, ICCSP 2024

作者： Ayyadurai, M. Maniraj, S.P. Sujatha, K. Deeptha, R. Anu, D. Suresh Babu, T.N. Rajalakshmi Engineering College Department of Cse Chennai India Srm Institute of Science and Technology Department of Cse Chennai Ramapuram India Srm Institute of Science and Technology Department of It Chennai Ramapuram India Presidency College Department of Computer Applications Bangalore India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Melmaruvathur India

ISBN: (纸本)9798350353068

Recently, the significance of the Underwater Acoustic Sensor Network (UWASN) attracts the researchers due to the huge benefits of data collection obtained from the sensor nodes under the ocean. Resource exploration in underwater uses a sensor node for data sensing, collecting, processing and forwarding. These sensor nodes are energy constrained and often depleted, then becomes inactive. This occurrence may lead to network failure while computing optimal node selection, hence proposes non linear grid-Based Search energy Optimization (GBSeO) algorithm to find the optimal forwarding node with Autonomous Underwater Vehicle (AUV). The GBSeO algorithm considers the underwater Doppler effect, sedimental drift and water current based on non linear searching and thereby improves the overall efficiency of the network by optimizing the energy of sensor nodes. AUV utilizes non linear optimization to improve the path selection based on GBSeO and thereby increases the network lifetime, energy efficiency and reduces the time delay. The results show that the proposed GBSeO algorithm outperforms the traditional algorithm Clustering Algorithm Optimization (CAO). © 2024 ieee.

关键词： Autonomous underwater vehicles

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