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A Survey of Classification and Detection of Fake and Real News using Machine Learning algorithms and Techniques 14

A Survey of Classification and Detection of Fake and Real Ne...

引用

14th international conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Rangdale, Sonali Mali, Nilesh Rathod, Sunil Department of Information Technology Rajarshi Shahu College of Engineering Tathawade SPPU Maharashtra Pune411033 India Department of Information Technology International Institute of Information Technology Hinjewadi SPPU Maharashtra Pune411057 India Department of Computer Engineering Indira College of Engineering and Management SPPU Maharashtra Pune410506 India

False news for various commercial and political goals has been appearing in enormous numbers and spreading across the internet in recent years. It is a result of the tremendous growth in online contents published on different social networking sites like Facebook and Instagram. Users of online social networks can become infected by these online trends by using false language. Fake news dissemination has been a serious concern for social media in recent years, causing problems for ordinary people by diverting their attention. Fake news leads readers to believe misleading information spread on the internet. Identifying fake news in real time is an essential goal in improving the credibility of information in online social networks. The survey took into account research papers published between 2018 and 2022 from a variety of standard databases. The study begins by discussing various algorithms for detecting bogus news. The goal of this survey is to look into different techniques, algorithms and methods used for detecting false news. The unknown properties of fake news, as well as the numerous linkages among news stories, creators, and subjects, provide issues in this work. The goal of the study is to develop a system that consumers may use to find and filter out the fake websites data that contain inaccurate or misleading information. © Grenze Scientific Society, 2023.

关键词： Social networking (online)

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Heuristic Elastic Scaling for Kubernetes Heterogeneous Microservices 21

Heuristic Elastic Scaling for Kubernetes Heterogeneous Micro...

引用

21st international conference on networking, Sensing and Control, ICNSC 2024

作者： Wang, Song He, Sheng Ning, Yishuang Gao, Xiang Ding, Zhijun The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China The Department of Computer Science and Technology Tongji University Shanghai201804 China Kingdee Research Kingdee International Software Group Co. Ltd Shenzhen518057 China Intelligent Computing Facility Innovation Center ZhejiangLab Hangzhou30012 China

ISBN: (纸本)9798350365221

Kubernetes has become the basic platform for building cloud native applications. However, existing horizontal scaling methods based on Kubernetes have problems with resource redundancy. Furthermore, the combined horizontal and vertical scaling based on Kubernetes takes a long time. Regarding the issue above, first, we describe the execution processes of three scaling techniques and compare them in different dimensions;second, we construct a formal elastic scaling model for expansion scenarios, with the goal of minimizing the total cost;and third, we introduce a heuristic expansion algorithm after balancing resource redundancy and execution time as the heuristic information. The experiment results show that the elastic scaling algorithm proposed in this paper achieves better performance than other algorithms. © 2024 IEEE.

关键词： Cloud platforms

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Adaptive Adjustment of Factor's Weight for a Multi-Sensor SLAM 2

Adaptive Adjustment of Factor's Weight for a Multi-Sensor SL...

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2022 2nd international conference on computer, Internet of Things and Control Engineering, CITCE 2022

作者： Zhu, Zihan Zhang, Yi Wang, Weijun Feng, Wei Luo, Haowen Zhang, Yaojie Shenzhen Institute of Advanced Technology Chinese Academy of Sciences 518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Lab of Construction Robotics and Intelligent Manufacturing Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial International Joint Research Center for Robotics and Intelligent Construction Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

A multi-sensor fusion simultaneous localization and mapping(SLAM) method based on factor graph optimization that can adaptively modify the weight of the graph factor is proposed in this study, to enhance the localization and mapping capability of autonomous robots in tough situations. Firstly, the algorithm fuses multi-lines lidar, monocular camera, and inertial measurement unit(IMU) in the odometry. Second, the factor graph is constructed using lidar and visual odometry as the unary edge and binary edge constraints, respectively, with the motion determined by IMU odometry serving as the primary odometry in the system. Finally, different increments of IMU odometry, lidar odometry and visual odometry are computed as favor factors to realize the adaptive adjustment of the factor's weight. The suggested method has greater location accuracy and a better mapping effect in complex situations when compared to previous algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Optical radar

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An Online Learning and Co-construction Platform for Fragmented Knowledge Based on computer technology

An Online Learning and Co-construction Platform for Fragment...

引用

2022 international conference on Education, network and Information technology, ICENIT 2022

作者： Zhao, Bairu School of Literature and Education Shaanxi Institute of International Trade and Commerce Shaanxi Province Xi'an712046 China

ISBN: (纸本)9781665463072

With the development of computer and artificial intelligence technology, the application of online learning has more conditions, and has the advantages of convenient resource information and real-time communication. Fragmented learning makes learning time more controllable and flexible, and has become a new learning method respected by young people. The purpose of this paper is to design a fragmented knowledge online learning co-construction platform based on cognitive impairment, and propose a fragmented learning product design strategy to improve the fragmented learning experience. Use a central mental model design approach. In order to clarify the behavioral path and mental model of users' fragmented learning and avoid the design scheme that may interfere with the user's initial experience evaluation, the fragmented learning experience evaluation index is used to score the usability of typical competing products before the experiment starts. The results show that the overall satisfaction score of competing products is 3.65, the overall satisfaction score of receiving goods is 4.23, and the scores of other indicators are higher than those of competing products. The online learning platform designed in this paper can effectively help learning efficiency. © 2022 IEEE.

关键词： Product design

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Interpretability Study of Pretrained Models via Transfer Learning on ImageNet for Lung Cancer Prediction 5

Interpretability Study of Pretrained Models via Transfer Lea...

引用

5th international conference on computer Information Science and Application technology, CISAT 2022

作者： Lin, Zhe Department of Computer Science and Technology Beijing Normal University Hong Kong Baptist University United International College Guangdong Zhuhai519087 China

ISBN: (纸本)9781510660076

Transfer learning is an effective strategy to obtain models for lung cancer analysis due to the limited number of labeled datasets. But few studies have made an interpretable explanation that why networks pretrained on ImageNet without medical images can be transferred to identify lung nodule images. In this paper, three convolutional neural networks with different depths, VGG16, MobileNet, and ResNet50, are selected for experiments to compare the performance and training difficulty between models with and without transfer learning, and to study the impact of transfer learning on networks of different depths. All the models are retrained on the same set of lung CT images with the same parameters, with and without the initial weights pretrained on the ImageNet dataset. The weights of the pretrained model are frozen, and pooling layers and classification output layers are created and concatenated to get the models required for experiments. The experimental results indicate that the initial network weights and feature extraction capabilities derived from ImageNet are applicable after being transferred to the lung nodule image set, making retraining easier and significantly improving prediction performance. In addition, transfer learning has a better effect on models with deeper networks, which contributes to alleviating model overfitting and poor generalization. © 2022 SPIE.

关键词： Convolutional neural networks

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Brain Stroke Prediction Using ANN

Brain Stroke Prediction Using ANN

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2022 international conference on Cyber Resilience, ICCR 2022

作者： Issa, Ghassan F. Shaalan, Khaled Shaalan, Yara Saeed, Hafiza Afia Fatima, Noor Rehman, Abd Ur Skyline University College University City Sharjah School of Information Technology Sharjah1797 United Arab Emirates The British University in Dubai Faculty of Engineering and It United Arab Emirates Misr University for Science and Technology Egypt Agriculture University Department of Computer Science Faisalabad Pakistan Fatima Memorial Hospital College of Medicine and Dentistry Lahore Lahore54000 Pakistan Riphah International University Riphah School of Computing Lahore Pakistan

ISBN: (纸本)9781665461221

Brain stroke is an intense health condition that happens when a blood clot restricts the normal flow of blood and different nutrients withinside the brain. It can cause neurologic damage, headaches and often death if not cured at a certain stage. According to the WHO, brain stroke has turned out to be the maximum rising disorder that is inflicting death because of late prognosis in both adults and elder one's. Like a 'coronary heart attack' it damages or paralyzes the brain. There have been numerous predictions about cerebrovascular, however this disorder is the one that receives less consideration. Some foremost elements that contribute to the hazard of stroke are age, gender, race, and genetic history of the patient. Artificial intelligence based cognitive modeling simulates properties of biological neural networks. Artificial Neural network offers the basis for the effectiveness of the studies. Different machine learning algorithms offer a sturdy base to discover the accuracy of the disorder. This study implements this model for higher instruction to combat pandemics in future. © 2022 IEEE.

关键词： Blood

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The grab tracking method for 3D reconstruction of a waste pool 3

The grab tracking method for 3D reconstruction of a waste po...

引用

3rd international conference on Advanced algorithms and Signal Image Processing, AASIP 2023

作者： Ding, Xiaosong Feng, Chong Li, Liqiang Chen, Xi International Business School Beijing Foreign Studies University Beijing100089 China

ISBN: (纸本)9781510668522

With 3D reconstruction method, this paper conducts experiments based on the data of a waste incineration plant in eastern China, and analyzes and compares the visual 3D monitoring, laser sensor 3D monitoring, and grabbing bucket tracking. By comparison, the grab tracking method is very appropriate for 3D reconstruction in terms of cost, accuracy, and implementation. With the proposed method, the volume monitoring not only provides practical suggestions for the construction of the optimal waste dump volume monitoring decision-making system, but also helps waste incineration enterprises achieve the goal of ''carbon peaking and carbon neutrality''. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： computer vision

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Studies on Human Recognition Activities Based on Federated Learning

Studies on Human Recognition Activities Based on Federated L...

引用

2022 international conference on computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Xu, Shuzhen Liu, Yanhong He, Xin School of Software Henan University International Joint Laboratory of Intelligent Network Theory and Key Technology Kaifeng China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

The traditional Human activity recognition (Human Activity Recognition, HAR) failed to protect user data effectively and had low recognition accuracy in the process of training model by machine learning. Under protecting the privacy of user data, improving the accuracy of HAR recognition has become a hot spot. This paper designs the HFL framework for solving human recognition activity based on federated learning and deep learning, and proposes the P-FedAvg algorithm. The P-FedAvg algorithm solves the model bias caused by direct averaging and improves the accuracy of aggregation. Experiments show that our method improves the accuracy of HAR recognition while protecting user's privacy. © 2022 IEEE.

关键词： Deep learning

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Predictive Analysis on University Dropout Rate of Bangladesh in Covid-19

Predictive Analysis on University Dropout Rate of Bangladesh...

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2022 international conference on Innovations in Science, Engineering and technology, ICISET 2022

作者： Hossain, Mia Shamim Azad, Shams Bin Md. Hossen, Md Labib Khan, Shahidul Islam Masum, Abdul Kadar Muhammad International Islamic University Chittagong Computer Science and Engineering Chattogram4318 Bangladesh

ISBN: (纸本)9781665483971

The hard times of COVID 19 have shown mankind some harsh reality. Numerous sectors including education have been terribly victimized by the grasp of the pandemic. Schools, colleges, and universities were closed down for enumerable days and the students were detached from their studies. The dropout rate from university for the students owing to financial and circumstantial facts has been a vital concern. In our research, we conduct an effective study on the dropout rate of university students. We try to find out the inherent reasons for their dropout and try to come up with an effective solution. By an online survey, we have collected data from 422 Bangladeshi undergraduate students. After training and testing the dataset with several popular algorithms such as SVM, Logistic regression, Random Forest, Decision Tree, etc., the best methods for predicting dropout among Bangladeshi undergraduates were discovered. © 2022 IEEE.

关键词： Students

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Utilizing Hyperledger Fabric Based Private Blockchain and IPFS to Secure Educational Certificate Management

Utilizing Hyperledger Fabric Based Private Blockchain and IP...

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2022 IEEE international Women in Engineering (WIE) conference on Electrical and computer Engineering, WIECON-ECE 2022

作者： Jahid Alam, Md. Hossain, Shahrin Shekh, Amina Reno, Saha Bangladesh Army International University of Science and Technology Department of Cse Cumilla Bangladesh

ISBN: (纸本)9798350311563

In recent decades, the quantity of fake educational certificates has increased, damaging testing centers' reputations. The most common verification methods include email, phone, and proxy for background checking, which require additional costs, security, and time. As these processes are not transparent enough, it is possible to create counterfeit certificates easily. Blockchain- based solutions have basic features such as security, proof of disruption, transparency, and compliance, which give a secure network the ability to store only genuine certificates. Additionally, data history can be managed on a blockchain network in case of suspicious activity. In this project, we analyzed blockchain technology and established a blockchain-based education certification system for the issuance and certification of certificates using the hash algorithm technology for encryption and confidentiality of educational certificates to prevent disruption and copyright restrictions. The InterPlanetary File System, a peer- to-peer based decentralized storage, is used to store the soft copy of the certificates by generating a hash for each certificate. This study offers Hyperledger Fabric-based application development concepts, including the processing of assets and generating immutable transactions, to create a comprehensive private blockchain-based educational certificate management. © 2022 IEEE.

关键词： Blockchain

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