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检索条件"任意字段=Proceedings - 3rd International Conference on Distributed Computing Systems."

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distributed Denial of Services (DDoS) Botnet Attack Prevention in Internet of Things (IoT) Devices Using AI

Distributed Denial of Services (DDoS) Botnet Attack Preventi...

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Smart Generation computing, Communication and Networking (SMART GENCON), international conference on

作者： Kaushiv Garg Kanwarpartap Singh Gill Rahul Chauhan Devyani Rawat Deepak Banerjee Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India

The expeditious adoption of Internet of Things (IoT) devices has facilitated the emergence of complex cybersecurity risks, notably distributed Denial of Service (DDoS) botnet assaults, which pose a substantial danger. With the exponential growth of interconnected devices inside the Internet of Things (IoT), the task of identifying malicious linkages becomes more challenging. The identification of these hazards has significant importance for intrusion detection systems.(IDS), with the use of machine learning (ML) having been a prevailing practice due to the continuous advancement of cyberattacks. In order to effectively combat such dangers, it is essential that machine learning technologies has the capability to observe a diverse range of attack patterns, hence illustrating the intricacies involved in targeting network traffic. Regrettably, a significant portion of the datasets accessible to the machine learning community lack comprehensive representation of well recognized attack patterns. This is particularly true for datasets pertaining to distributed Denial of Service (DDoS) attacks, such as ACK and PUSH-ACK floods. The objective of this project is to address the existing disparity by curating a compilation of assault approaches that are underutilized. This dataset provides IDS developers with the necessary resources to enhance their detection rates. This research work enhances the security of IoT devices against DDoS botnet assaults, hence contributing to the overall safety of the IoT ecosystem.

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distributed Network Carbon Emission Forecasting Based on Adaptive Graph Convolutional Recurrent Neural Networks

Distributed Network Carbon Emission Forecasting Based on Ada...

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Power systems.and Electrical Technology (PSET), IEEE international conference on

作者： Binxie Ren Pengfei Zhao Shi Jing Zhenyuan Zhang Ying Liu Zheng Wang School of Mechanical and Electrical Engineering the University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350353204

ISBN: (纸本)9798350353211

Achieving carbon peak and carbon neutrality is a critical goal for sustainable development worldwide. Accurate carbon emission forecasting plays an important role in carbon trading and low-carbon management in distributed systems. This paper proposes a carbon emission forecasting method based on an Adaptive Graph Convolutional Recurrent Network (AGCRN), it features two distinct modules designed for adaptive graph learning: one module adjusts node parameters adaptively, while the other module creates data-specific graphs. The node adaptive parameter learning module captures node-specific patterns in the carbon emission sequences of each power grid node, while the data-adaptive graph generation module infers the spatial correlations between the carbon emission flows of different nodes in the power grid. To evaluate the accuracy and performance of the proposed model, we compared it with two popular forecasting methods. The results demonstrate that the proposed method can achieve more accurate carbon emission predictions than other baselines.

关键词： Adaptation models Adaptive systems Correlation Accuracy Carbon dioxide Predictive models Power grids Data models Topology Forecasting

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Research and implementation of unified management method for power distribution and distributed new energy data resources 3

Research and implementation of unified management method for...

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3rd international conference on Electronics, Electrical and Information Engineering, ICEEIE 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Shen, Xiaofeng Chen, Jingde Gu, Hua State Grid Laboratory of Power cyber-Security Protection & Monitoring Technology State Grid Smart Grid Research Institute Co.LTD Jiangsu Nanjing210003 China Qingpu Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai201799 China

ISBN: (纸本)9781510671423

The physical types of equipment in the distribution network are diverse and the quantity is huge. This is because the distribution network requires a large number of various types of power supply and other auxiliary equipment such as substations to provide power supply services for electricity customers, resulting in a very rich and diverse data resources in the distribution network. Moreover, with the continuous integration of new energy sources, the distribution network has become increasingly complex, not only increasing the dimensions of operational management, but also facing huge challenges in data resource management. This paper proposes a unified management method for power distribution and new energy data resources, which manages a large number of non digital data and unstructured data such as file text in the distribution network in a unified manner, integrates heterogeneous data from different business systems. solves data quality problems caused by management, data processing and other reasons, meets the data management needs of power grid enterprises, and promotes Digital transformation of enterprises. On the basis of achieving unified management of data resources in the distribution network, the deep mechanisms between data resources are explored to reveal the operational laws and characteristics of the distribution network. At the same time, data analysis algorithms are used to mine distribution network data, design and implement distribution network business analysis functional modules, and upgrade distribution network data management from digitalization to intelligence. © 2023 SPIE.

关键词： Information management

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proceedings of the 3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

Proceedings of the 3rd International Conference on Intellige...

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3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

ISBN: (纸本)9780738111834

The proceedings contain 263 papers. The topics discussed include: towards development of a virtual reality game for children with autism spectrum disorder;automated classification of glaucoma using DWT and hog features with extreme learning machine;intrusion detection systems.for distributed environment;secured college bus management system using IoT for Covid-19 pandemic situation;a study of landslide susceptibility mapping using machine learning approach;impact of machine learning in natural language processing: a review;maximum geographical coverage deployment of ambulances using genetic algorithm;sentiment analysis using deep learning;and remote controlled painter combined window washer using quadopter.

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Improved Privacy Conservation Applicability for the Disturbed Data in Multi Partitioned Data Collection Environment 3

Improved Privacy Conservation Applicability for the Disturbe...

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3rd international conference on Communication, computing and Industry 4.0, C2I4 2022

作者： Prakash, V.S. Chitra, K. Britto Jacob, S. Yuvaraj, S. Shiva Kumar, B.N. Kristu Jayanti College Department of Computer Science Bangalore Karnataka India CMR Institute of Technology Department of EEE Bengaluru Karnataka India Kristu Jayanti College Department of Mathematics Bangalore Karnataka India Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9781665474979

The perturbation technique was widely considered for the protection of the privacy for different datasets in data mining. Multi-partitioned datasets generally consist of together horizontal and vertical data Collection, that are a existing demand in the data mining environment of e- Pay and e-Commerce. In the phase of perturbation, arbitrary disturbance from a known scattering is processed as data susceptible to privacy, prior to the information miner being thrown. Consequently, the data-miner reconstitutes estimates for the specific distribution of data from the disrupted data and exercises the restored delivery of data mining principles. According to the count of noise, information loss versus privacy protection in perturbation-based techniques is a constant transaction. The problem is to what degree of privacy are consumers able to cooperate? This is a choice which is shifting from person to person. The first work is to define the technique of data perturbation with validation and authentication in order to determine a trade-off between data protection and the usability of the data. Diverse people may have different secrecy strategies, focused on customs and cultures. Inappropriately, the earlier privacy-included perturbation that preserves data mining procedures does not allow entities to choose their preferred levels of privacy. It is a negative thing, because privacy is a preference for individuals. Researchers in this study suggest an independently adaptable perturbation model that allows persons to select their own degree of confidentiality. The success of the proposed model lies in Enhancing the Privacy Conservation Applicability for Disturbed Data in Multi-partitioned datasets (PADDM), as validated by numerous studies performed on both unreal and real-world data Collection. Focused on the experimental evaluation, researchers are proposing a simple, useful and resourceful method for building data mining representations from disturbed facts and enhancing the

关键词： Data Collection distributed Data Privacy Privacy Conservation

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3rd international conference on Intelligent computing and Optimization, ICO 2020

3rd International Conference on Intelligent Computing and Op...

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3rd international conference on Intelligent computing and Optimization, ICO 2020

ISBN: (纸本)9783030681531

The proceedings contain 113 papers. The special focus in this conference is on Intelligent computing and Optimization. The topics include: Intellectualized Control System of Technological Processes of an Experimental Biogas Plant with Improved System for Preliminary Preparation of Initial Waste;way for Intensifying the Process of Anaerobic Bioconversion by Preliminary Hydrolysis and Increasing Solid Retention Time;evaluation of Technical Damage Caused by Failures of Electric Motors;development of a Prototype Dry Heat Sterilizer for Pharmaceuticals Industry;optimization of Parameters of Pre-sowing Seed Treatment in Magnetic Field;development of a Fast Response Combustion Performance Monitoring, Prediction, and Optimization Tool for Power Plants;Industry 4.0 Approaches for Supply Chains Facing COVID-19: A Brief Literature Review;ontological Aspects of Developing Robust Control systems.for Technological Objects;a New Initial Basis for Solving the Blending Problem Without Using Artificial Variables;review of the Information that is Previously Needed to Include Traceability in a Global Supply Chain;modeling of the Thermal State of systems.of Solar-Thermal Regeneration of Adsorbents;online Technology: Effective Contributor to Academic Writing;a Secured Electronic Voting System Using Blockchain;preconditions for Optimizing Primary Milk Processing;optimization of Compost Production Technology;economic Aspects and Factors of Solar Energy Development in Ukraine;a Method for Ensuring Technical Feasibility of distributed Balancing in Power systems. Considering Peer-to-Peer Balancing Energy Trade;the Results of a Compromise Solution, Which Were Obtained on the Basis of the Method of Uncertain Lagrange Multipliers to Determine the Influence of Design Factors of the Elastic-Damping Mechanism in the Tractor Transmission.

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Energy Management Strategy in the Synthesis of an Algorithm for Multi-step Conveyor Belt Speed Control 3rd

Energy Management Strategy in the Synthesis of an Algorithm ...

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3rd Grabchenko's international conference on Advanced Manufacturing Processes (InterPartner)

作者： Pihnastyi, Oleh Kozhevnikov, Georgii Glavchev, Maxim Natl Tech Univ Kharkiv Polytech Inst 2 Kyrpychova St UA-61002 Kharkiv Ukraine

ISBN: (纸本)9783030913274;9783030913267

The article discusses the synthesis of the optimal algorithm for multistep control of the conveyor belt speed based on Time-Of-Use (TOU) tariffs. The main methods of reducing energy costs for the transport conveyor are discussed. The perspectives of using the energy management strategy to reduce the cost of material transportation are analyzed. Common tariff classes are considered, which can be used for designing the conveyor belt speed control systems. The problem of optimal belt speed control is formulated. The criterion of the quality of the control process is written, the differential connections are determined, and the Hamiltonian function is constructed. An algorithm for multi-step speed control of the conveyor belt is synthesized. For the synthesis of the control algorithm, an analytical model of the conveyor with dimensionless parameters is used, which considers the transport delay. The synthesis of the speed control algorithm considers the limitations on the value of the maximum permissible specific load of the material on the belt.

关键词： Transport conveyor distributed system Transport delay TOU-tariff Uneven distribution

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An Improved Three-level DC-DC Boost Converter for Renewable energy systems.with High Gain 3

An Improved Three-level DC-DC Boost Converter for Renewable ...

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3rd IEEE international conference on Energy, Power and Environment - Towards Clean Energy Technologies (ICEPE)

作者： Raghavendran, S. Kumar, K. Sateesh Tirupathi, Abhilash. Chittibabu, B. SRM Inst Sci & Technol Dept Elect & Elect Engn Chennai Tamil Nadu India Career Launcher Edu Ltd Dep Elect Engn Surampalem India IIITDM Dep Elect Commun Engn Kancheepuram India

ISBN: (纸本)9781665425360

High gain DC-DC converters are essential candidates for integrating the low voltage photovoltaic (PV) sources to the grid-tied distributed power generation systems. In this paper, a simple non-isolated high gain three-level boost (TLB) converter is developed by the addition of two power switches and two diodes to the standard TLB converter. The voltage boosting and balancing is achieved by regulating the phase shift between the main switches. Moreover, the proposed converter achieves high gain without using the high frequency transformer, coupled inductor, and switched capacitor networks. Also, it has larger degree of freedom for duty ratio without any core saturation of the inductor. Therefore, use of the proposed converter in grid -tied distributed power generation systems.enhances the reliability and efficiency of the overall system. PSIM 9.0 simulation toolbox is used to validate the performance of the proposed high gain converter.

关键词： distributed power generation High gain DC DC converter Three-level DC -DC boost converter

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PGS-BFT: A Pipeline-Based Graph Structure Byzantine Fault Tolerance Consensus Algorithm

PGS-BFT: A Pipeline-Based Graph Structure Byzantine Fault To...

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Computer Science and Blockchain (CCSB), international conference on

作者： Jingwen Chen Yang Liu Xinlei Liu Song Peng Distributed Computing & BlockChain Lab Henan university of technology Zhengzhou China

The Byzantine fault-tolerant (BFT) consensus algorithm is widely used in blockchain systems.due to its ability to tolerate malicious nodes and ensure system consistency. However, existing consensus protocols still face significant challenges. This paper proposes a pipeline-based graph structure Byzantine Fault Tolerant (PGS-BFT) consensus algorithm. It leverages parallel pipeline execution to accelerate block generation efficiency. By synchronizing block dependencies among nodes, all validated blocks eventually form an ordered graph structure within a cycle, enabling nodes to achieve final consensus. The proposed PGS-BFT algorithm effectively improves system consensus efficiency and reduces transaction latency while ensuring Byzantine fault-tolerant security. It can be applied to existing consortium blockchain platforms.

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Effect of Environmental Temperature Rise on Optimal Places and Number of distributed Generators

Effect of Environmental Temperature Rise on Optimal Places a...

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Smart Technologies for Power, Energy and Control (STPEC), IEEE international conference on

作者： Meisam Mahdavi Augustine Awaafo Francisco Jurado Pasala Gopi Department of Electrical Engineering University of Jaen Linares Spain Department of Electrical and Electronics Engineering Annamacharya Institute of Technology and Sciences Rajampet India

Optimally siting distributed generations (DGs) is regarded as one of the most effective mechanisms for loss mitigation on a distribution network. Power loss curtailment on distribution networks is a very essential in power system operation and management since it constitutes the major share of the overall power loss on power systems. Losses on power systems.lead to exorbitant network operation costs as well as the distortion of the system’s voltage profile. In traditional DG placement, the optimal locations and the number of distributed generators are optimally determined for ensuring that losses are reduced to the barest minimum in order to meet the power demand of consumers. Load variation on distribution buses leads to different resultant losses in comparison with constant loads. Nevertheless, several proposed models for DG allocation problem ignored consumers’ load variability. While the selected few that considered load variation in their proposed models neglected the impact of ambient temperature change on electrical energy usage which influence appropriate places and DG number. Accordingly, the current study evaluates environment’s temperature change impact on DG allocation solutions to access environmental temperature change importance in loss optimization via DG placement. It is observed that ambient temperature variations significantly change the appropriate places and DG sources number.

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