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Development of a Portable Charger for Electric Vehicles

Development of a Portable Charger for Electric Vehicles

引用

ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Oksana Shpak Volodymyr Samotyy Ulyana Dzelendzyak Department of Computerized Automation Systems Lviv Polytechnic National University Lviv Ukraine Department of Automation and Computer Science Cracow University of Technology Cracow Poland

An additional portable charging station system for electric vehicles (EV) is proposed. The classification of electric vehicles is presented and the implementation of a portable charging station for electric cars is described. A photovoltaic system design is considered, including photovoltaic power generation module (PVPGM) and power transmission module design, system modelling and analysis, including solar radiation analysis, photovoltaic power generation analysis, and wireless power transmission analysis. The research method is presented and an innovative system is designed, which will be an additional portable charging station for an electric car. This system will use a photovoltaic power generation module for charging electric vehicles in combination with a WPT and a supercapacitor. A system consisting of two main parts is obtained: the PVPGM and the power transmission module. The developed system will be able to charge an electric car using solar energy. A mathematical model of solar cells for effective use in an innovative system is given. Relevant conclusions and results were obtained.

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An intelligent Machine Learning Approach to Detect Spam in Social Media 5

An Intelligent Machine Learning Approach to Detect Spam in S...

引用

5th international conference on data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Mohandas, R. Prasanna, D.S. John Deva Meenakshi, N. Kaviyaraj, R. Nathiya, S. Arivazhagan, N. Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Kattankulathur India Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Kattankulathur India

ISBN: (纸本)9798350389609

Machine learning based intelligent approach is applied to finding spam in YouTube videos. Spam comments are ones that are promotional or unrelated. A growing number of users have been drawn to the idea of making money by placing advertisements on popular social networking platforms over time. These remarks damage a channel's reputation. YouTube has addressed the issue with a limited set of solutions that concentrate on preventing comments from including links. Such heuristics are now futile since spammers have found ways to get around them. Despite the fact that common machine learning classification techniques have demonstrated considerable success, new methods can still increase accuracy. Therefore, this research attempt to identify such statements using machine learning techniques like Random Forest, SVM, and Naive Bayes. In order to convey a clear concept, graphs are used to illustrate data cleaning, data analysis, text preparation, and model building in this research. © 2024 ieee.

关键词： Adversarial machine learning

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Refined Node data Mining Platform in the Construction Phase of Building Installation Engineering based on BIM Technology 6

Refined Node Data Mining Platform in the Construction Phase ...

引用

6th international conference on intelligent computing and Control systems, ICICCS 2022

作者： Zhao, Jiamin Yunnan Open University Kunming650500 China

ISBN: (纸本)9781665410359

The article analyzes the installation cost management based on BIM technology, and then discusses the model construction in the installation project cost management based on BIM technology. Building installation construction is the longest time, the most complicated technology, and the most risky in the whole process management of engineering projects. At this stage, a large amount of project management information is carried. Using the concept of refined management, a BIM solution for the whole process of construction and installation engineering was proposed. Combined with the analysis of engineering examples, the construction unit should also actively apply advanced technology methods such as BIM to provide a dynamic and reliable reference basis for fine management, so as to promote the data mining of the fine management node of building installation and construction. © 2022 ieee.

关键词： data mining

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Five-layer IoT and Fog computing Framework Towards Digital Twinning of Battery Management systems for e-Transportation 4

Five-layer IoT and Fog Computing Framework Towards Digital T...

引用

4th international conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Karnehm, Dominic Samanta, Akash Neve, Antje Williamson, Sheldon University of the Bundeswehr Munich Institute of Intelligent Distributed Systems Neubiberg Germany Ontario Tech University Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350306262

It is needless to mention that the proven capability of cloud computing and digital twin-based monitoring and control systems will play a major role in the implementation of digital twin-based lithium-ion battery management systems (BMS) for e-transportation. In this context, the combination of the Internet of Things (IoT) and fog computing emerges as an enabling technology that facilitates bidirectional data communication and processing. This paper proposes a five-layer IoT framework for the implementation of cloud-based battery monitoring and BMS. Additionally, it critically analyzes the existing IoT frameworks applied to BMS and justifies the suitability of the five-layer architecture. Furthermore, the advantages of fog computing, such as low latency, fault tolerance, limitless systems, multiple applications, and shared responsibility, are discussed. The paper also explores four previously proposed computing-enabled architectures: centralized, hybrid, distributed, and hybrid-distributed computing. Moreover, the potential of utilizing hybrid computing architectures, incorporating fog computing as a supplement to cloud computing, is highlighted to address fault, privacy, or latency issues in cloud-based BMS. © 2024 ieee.

关键词： Battery management systems

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A Correlative Survey on Imbalanced Breast Cancer data Using Ensembled Oversampling Techniques and Deep Learning Algorithms 4

A Correlative Survey on Imbalanced Breast Cancer Data Using ...

引用

4th international conference on Emerging systems and intelligent computing, ESIC 2024

作者： Datta, Debaleena Singha, Pinaki Pritam Sen, Uddalok Mallick, Pradeep Kumar Techno India Saltlake Department of Cse Kolkata India University of Engineering and Management Department of Cse Kolkata India Mckv Institute of Engineering Department of Cse Kolkata India Kalinga Institute of Industrial Technology Department of Cse Bhubaneswar India

ISBN: (纸本)9798350349856

Inadequacy of labeled breast cancer data causes imbalance and inaccuracy in classifiers. Our proposed research aims for a computer assisted detection (CAD) system to detect maligned cancer cells using the Wisconsin Breast Cancer dataset through a novel ensembled approach that combines various oversampling methods with standard machine learning and deep learning classifiers. The work is three-folds: (1) Use of 6 oversampling techniques: Random oversampling, Synthetic minority oversampling technique, Borderline SMOTE, k-means SMOTE, Support vector machine SMOTE, Adaptive synthetic minority oversampling, (2) Use of 5 ML models: Logistic Regression, Decision Tree, Random Forest, Adaptive boosting, Extreme gradient boosting, and (3) Use of 3 DL models: Artificial neural network, Multilayer perceptron, Convolutional neural network (CNN). The experimental results deduce that CNN has performed better than the others when assisting the SMOTE family and achieves the maximum accuracy of 98.25%. © 2024 ieee.

关键词： Multilayer neural networks

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Construction of University data Warehouse Based on Multidimensional data computing Model

Construction of University Data Warehouse Based on Multidime...

引用

2024 international conference on Interactive intelligent systems and Techniques, IIST 2024

作者： Zhang, Jun Wang, Fenfen Hunan Railway Professional Technology College School of Artificial Intelligence Zhuzhou China Hunan Railway Professional Technology College Finance Department Zhuzhou China

ISBN: (纸本)9798350374421

To meet the needs of universities for integrating, summarizing, and analyzing all operational data generated by various business systems, it is necessary to apply data warehouse technology to complete the collection and governance of business system data, and provide standardized and effective data services for upper-level applications. Based on this, the article combines the characteristics of university business data and practical application needs, and proposes a framework design for the university data warehouse platform. In response to the changing needs of university data analysis and complex statistical characteristics, the article designs a centralized extraction, partitioned governance, and multidimensional modeling construction plan, focusing on analyzing the dimension model construction method of the subject data area, and designing a star model for teacher basic data and a snowflake model for student enrollment data. Finally, it provides a data cleaning strategy, which provides a reference for the construction of university data warehouses. © 2024 ieee.

关键词： data warehouses

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Design and Implementation of Monitoring System for New Energy data Call Based on Blockchain 23

Design and Implementation of Monitoring System for New Energ...

引用

23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in Sensor, Cloud and Big data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Liu, Ziang Huang, Yuanyuan Zhou, Qiang Zhang, Yingli Zhou, Xiaokang Zhou, Rui School of Information Science and Engineering Lanzhou University Lanzhou China State Grid Gansu Electric Power Research Institute Lanzhou China Shiga University Faculty of Data Science Hikone Japan Riken Center for Advanced Intelligence Project Tokyo Japan

ISBN: (纸本)9781665494571

With the energy revolution starting the third transformation to new energy, new energy has become essential for human energy. In order to better organize and utilize new energy, more and more research is committed to predicting the power generation capacity of new energy through the power generation data collected by intelligent systems to make better use of new energy. However, with the increase of new energy digital platforms and supporting infrastructure improvement, the distribution and management of relevant data also begin to face significant challenges. New energy data faces a substantial potential threat in distributing and using data to various digital platforms. Based on this, this paper designs and implements a new energy data call monitoring system based on blockchain to ensure the security of new energy data by tracking data operation information. © 2021 ieee.

关键词： Smart cities Consensus algorithm Machine learning Blockchains Safety Recording intelligent systems

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Optimization Accuracy of Secured Cloud systems Using Deep Learning Model 4

Optimization Accuracy of Secured Cloud Systems Using Deep Le...

引用

4th international conference on intelligent Technologies, CONIT 2024

作者： Hindka, Mayank Texas A&m University-Central Texas MBA-Information Systems United States

ISBN: (纸本)9798350349900

Cloud security is vital in attracting data security and privacy customers. The online attackers disrupt the use of the on-demand services provided by the cloud service providers for their clients. It is distributed in nature for resource sharing over the Internet. Thus, security has become the main agenda for cloud computing usage by cloud customers. As a result, the financial growth of cloud-based organizations is increasing gradually. The critical situation of cloud security is identifying the types of attacks and deciding how to defend such attacks to protect the cloud data from attackers. Numerous methodologies are reviewed to determine the robust security mechanisms for cloud security to protect against DoS or DDoS attacks (by malware attacks, MITM attacks, or other medium attacks). The ML concept has incorporated algorithm conceptions like deep neural networks and quantum neural networks to enhance prediction and protection accuracy. These proposed models not only help to reduce the attack level up to 100% but also increase the trust of cloud users with financial growth to cloud service providers (CSPs). © 2024 ieee.

关键词： Cloud security

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BandX : An intelligent IoT-band for Human Activity Recognition based on TinyML 23

BandX : An Intelligent IoT-band for Human Activity Recogniti...

引用

24th international conference on Distributed computing and Networking (ICDCN)

作者： Saha, Bidyut Samanta, Riya Ghosh, Soumya K. Roy, Ram Babu Indian Inst Technol Kharagpur Kharagpur W Bengal India

ISBN: (纸本)9781450397964

Human Activity Recognition (HAR) is used in several human-centric real-world situations. In many learning-based systems, sensors capture situational data and transfer it to adjacent computing devices for processing and analysis. This concerns user data privacy and network availability, as well as increasing response latency and unnecessary power consumption. To address these, we developed a device BandX that classifies human activities from wearable sensors using an on-device deep learning inference mechanism on a microcontroller unit (MCU) based on TinyML. BandX performs with an accuracy of around 94% and reduces significant network traffic in comparison to computational offloading methods. We have also designed a framework that manages BandX sensor/inference data and provides a logical layer for user activity-level inferences. This framework includes an interactive user interface that lets people track their activity patterns and other health statistics.

关键词： TinyML On-Device Inference data acquisition Human Activity Recognition Wearable IoT

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Evolution of Consensus Algorithms in Blockchain Technology

Evolution of Consensus Algorithms in Blockchain Technology

引用

2023 international conference on intelligent systems for Communication, IoT and Security, ICISCoIS 2023

作者： Harshini Poojaa, K. Ganesh Kumar, S. School of Computing SRM Institute of Science and Technology Department of Data Science and Business Systems Chengalpattu India

ISBN: (纸本)9798350335835

Blockchain being a decentralised, distributed ledger, has attracted industries to implement the solutions on blockchain. The transactions are agreed in a deterministic manner because of the availability of consensus algorithms. The state of the machine is concluded based on the agreement generated by the consensus algorithm. The performance of the blockchain system can be increased to the order of magnitude when the right consensus is used. In this paper, the limitations and performance of various consensus algorithms have been reviewed along with the characteristics of the same. In addition to that, this paper compares the consensus algorithms based on various parameters such as speed, double-spending, 51% attack and many more. © 2023 ieee.

关键词： Blockchain

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