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Collaborative City Digital Twin for the COVID-19 Pandemic:A Federated Learning Solution

Tsinghua science and Technology 2021年第5期26卷 759-771页

作者： Junjie Pang Yan Huang Zhenzhen Xie Jianbo Li Zhipeng Cai the College of Computer Science and Technology Qingdao UniversityQingdao 266000China the Business School Qingdao UniversityQingdao 266000China the College of Computing and Software Engineering Kennesaw State UniversityAtlantaGA 30060USA the College of Computer Science and Technology Jilin UniversityChangchun 130012China the Department of Computer Science Georgia State UniversityAtlantaGA 30303USA

The novel coronavirus,COVID-19,has caused a crisis that affects all segments of the *** the knowledge and understanding of COVID-19 evolve,an appropriate response plan for this pandemic is considered one of the most effective methods for controlling the spread of the *** studies indicate that a city Digital Twin(DT)is beneficial for tackling this health crisis,because it can construct a virtual replica to simulate factors,such as climate conditions,response policies,and people's trajectories,to help plan efficient and inclusive ***,a city DTsystem relies on long-term and high-quality data collection to make appropriate decisions,limiting its advantages when facing urgent crises,such as the COVID-19 *** Learning(FL),in which all clients can learn a shared model while retaining all training data locally,emerges as a promising solution for accumulating the insights from multiple data sources ***,the enhanced privacy protection settings removing the privacy barriers lie in this *** this work,we propose a framework that fused city DT with FL to achieve a novel collaborative paradigm that allows multiple city DTs to share the local strategy and status *** particular,an FL central server manages the local updates of multiple collaborators(city DTs),providing a global model that is trained in multiple iterations at different city DT systems until the model gains the correlations between various response plans and infection *** approach means a collaborative city DT paradigm fused with FL techniques can obtain knowledge and patterns from multiple DTs and eventually establish a"global view"of city crisis ***,it also helps improve each city's DT by consolidating other DT's data without violating privacy *** this paper,we use the COVID-19 pandemic as the use case of the proposed *** experimental results on a real dataset with various response plans val

关键词： COVID-19 Digital Twin(DT) Federated Learning(FL) deep learning

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State-of-the-Art Approach: Boosting IoT Sensor Network Security with Visual Secret Sharing

State-of-the-Art Approach: Boosting IoT Sensor Network Secur...

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Smart World Congress (SWC), IEEE

作者： Sijjad Ali Jia Wang Victor Chung Ming Leung Uzair Aslam Bhatti Mughair Aslam Bhatti College of Computer Science and Software Engineering Shenzhen University Guangdong China School of Information and Communication Engineering Hainan University China

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

This research paper is based on the issue of protecting the sensor networks in the era of IoT because the data is very sensitive and huge, and is collected in resource-constrained environments. We put forward a new approach to the enhancement of the security of IoT sensor networks by applying VSS on visual data. Our approach is based on the implementation of the VSS approach which implies that no single node will contain full information about the visual input which will be divided among the nodes. Furthermore, this approach also increases the security of the data, and at the same time is appropriate for the IoT environments since it does not require a large amount of computational power and network bandwidth. In addition, we explain how this method can be used, discuss its features, and based on the data from the experiments, prove the effectiveness of the suggested approach. The results of the research show that data security and the ability to counteract attacks can be resist if VSS is used in systems of IoT sensor networks.

关键词： Visualization Resists Bandwidth Network security Boosting Internet of Things Cryptography

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Visualizing Student Attention in Smart Classrooms: A Preliminary Study 15

Visualizing Student Attention in Smart Classrooms: A Prelimi...

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15th International Conference on Innovations in Information Technology, IIT 2023

作者： Parambil, Medha Mohan Ambali Alhammadi, Amna Mohammed Abdulla Alnajjar, Fady Trabelsi, Zouheir Ali, Luqman Swavaf, Muhammed United Arab Emirate University Department of Information Systems and Security College of IT Al Ain United Arab Emirates United Arab Emirate University Department of Computer Science and Software Engineering College of IT Al Ain United Arab Emirates

ISBN: (纸本)9798350382396

In recent years, there has been a swift progression in employing novel methods in classrooms to enhance students' academic achievements, especially in line with the growing digitization of education. Such methods often encompass systems like facial recognition to monitor various aspects of students, including attendance, emotional states, and attention. These tools are capable of evaluating students' presence and engagement in class, offering quantifiable metrics regarding their concentration and emotions. However, a prominent challenge has been the translation of this data into an accessible form that enables educators to assess and enhance their teaching techniques swiftly. Our suggested solution tackles this issue by offering a real-Time visual depiction of students' classroom status through different visualization techniques. These visual aids allow teachers to promptly recognize trends in student focus, thus aiding in the strategic alteration of teaching styles. Furthermore, these visual representations can be tailored to display various metrics and applied to tasks beyond monitoring attention, like overseeing attendance or assessing student progress. By integrating these advanced visualizations into the educational process, both teaching efficacy and the learning experience for students and teachers alike can be substantially elevated. © 2023 IEEE.

关键词： Students

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BPREC: A Bayesian Personalized Recommendation Based on User Preferences for Mining

BPREC: A Bayesian Personalized Recommendation Based on User ...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Laixiang Qiu Jianping Feng Wang Zhou College of Computer Science Chongqing College of Mobile Communication Chongqing China Mechanical and Electrica engineering college Hainan Vocational University of Science and Technology Hainan China School of Computer and Software Engineering Xihua University Chengdu China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Faced with overwhelming product information, users often struggle to make choices, impacting their shopping experience and time. To address this, recommendation systems provide precise suggestions that streamline decision-making. The BPRec model, based on user preferences, enhances recommendation relevance and quality. Experiments on realworld datasets show that BPRec significantly improves recommendation effectiveness, thus enhancing the shopping experience.

关键词： Computational modeling Decision making Information processing Media Bayes methods Recommender systems

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Recent trends in crowd management using deep learning techniques: a systematic literature review

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Journal of Umm Al-Qura University for engineering and Architecture 2024年第4期15卷 355-383页

作者： Alasmari, Aisha M. Farooqi, Norah S. Alotaibi, Youseef A. Department of Computer Science and Artificial Intelligence College of Computing Umm Al-Qura University Makkah 21955 Saudi Arabia College of Computing Umm Al-Qura University Makkah 21955 Saudi Arabia Dar Al-Hekma University Jeddah Saudi Arabia Department of Software Engineering College of Computing Umm Al-Qura University Makkah 21955 Saudi Arabia

Crowd management has become an integral part of urban planning in abnormality in the crowd and predict its future issues. Big data in social media is a rich source for researchers in crowd data analysis. In this systematic literature review (SLR), modern societies. It can organize the flow of the crowd, perform counting, recognize the related works are analyzed, which includes crowd management from both global and local sides (Hajj events—Saudi Arabia) based on deep learning (DL) methods. This survey concerns crowd management research published from 2010 to 2023. It has specified 45 primary studies that accomplish the objectives of the research questions (RQs), namely, investigation of the taxonomies, approaches, and comprehensive studies of crowd management both globally and locally and focusing on the most commonly used techniques of DL. We found both supervised and unsupervised DL techniques have achieved high accuracy, with different strengths and weaknesses for each approach. A lot of these studies discuss aspects of scene analysis of crowds, that are captured by installed cameras in the place. However, there is a dilemma regarding exploiting data provided on social media to use in the crowd analysis domain. Which we believe that the analysis of big data may raise crowd management to the upper level of enhancement. To this end, motivated by the findings of this SLR. The primary purpose of this review is strived to illustrate obstacles and dilemmas in crowd analysis fields to provide a road map for future researchers. Furthermore, it aims to find research gaps existing to focus on it in the future studies. The results indicate that the lack of Hajj research, especially in sentiment analysis and the study of the pilgrims' behavior. © The Author(s) 2024.

关键词： Crowd analysis Crowd behaviors analysis Crowed management Hajj Social media

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Speed Control of DC Motor based on H∞ Mixed-sensitivity Algorithm 3

Speed Control of DC Motor based on H∞ Mixed-sensitivity Alg...

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3rd International Conference on Electrical engineering and Mechatronics Technology, ICEEMT 2023

作者： Lu, Zhen-Wei Wang, Xin-Zui Cao, Fu-Cheng Yang, Yan-Li Jihua Medical Institute Jihua Laboratory Foshan528251 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Chinese Academy of Sciences Suzhou Institute of Biomedical Engineering and Technology Suzhou215163 China

ISBN: (纸本)9798350303698

In order to restrain the uncertainty of system parameters and the influence of external disturbances on the speed of DC motor, this paper adopts the H+ mixed-sensitivity algorithm to design a speed controller based on the model of the controlled motor. First, the Pseudo Random Binary Sequence (PRBS) is input to the motor and the corresponding speed output sequence is measured. The Least Squares Method (LSM) is used to conduct system identification;Then, design a weighting function based on the established system performance indicators, and use MATLAB to synthesize the H+ controller;Finally, this article adopts the direct form conversion method to implement the controller, and successfully controls the speed of the DC motor through the STM32F407ZGT6 microcontroller. The experimental results show that this algorithm can achieve good speed tracking performance and anti-disturbances ability for DC motors. © 2023 IEEE.

关键词： DC motors

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Influence of Key Nodes in Industrial Control Malicious Code Modeling 3

Influence of Key Nodes in Industrial Control Malicious Code ...

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3rd International Conference on Electronic Information engineering and computer science, EIECS 2023

作者： Yang, Wei Yan, Hongwei Xu, Chao Yao, Yu Zhou, Jinlei Wang, Baile Wang, Danni Northeastem University Software College Shenyang China Northeastem University School of Computer Science and Engineering Shenyang China State Grid Liaoning Information and Communication Company Department of Cybersecurity Monitoring Shenyang China

ISBN: (纸本)9798350316674

Key nodes in complex networks play an important role in the structure of the entire network. Different nodes in the network often have different degrees, and the node with the highest degree in the network is usually called a key node. However, the heterogeneity of nodes is mostly neglected in the research of malware propagation models by scholars at home and abroad. Therefore, based on the SUIQMR model proposed in the industrial control coupling network and considering the role of key nodes in the network, an improved malware suppression strategy for key nodes in the immune network is obtained. The simulation results verify the effectiveness of the improved malware suppression strategy, showing that the immune key nodes can effectively suppress the spread of malware. © 2023 IEEE.

关键词： industrial control network key nodes Malware Propagation Model Suppression strategy

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Symmetric Graph Contrastive Learning against Noisy Views for Recommendation

arXiv

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arXiv 2024年

作者： Zhao, Chu Yang, Enneng Liang, Yuliang Zhao, Jianzhe Guo, Guibing Wang, Xingwei Software College Northeastern University Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

Graph Contrastive Learning (GCL) leverages data augmentation techniques to produce contrasting views, enhancing the accuracy of recommendation systems through learning the consistency between contrastive views. However, existing augmentation methods, such as directly perturbing interaction graph (e.g., node/edge dropout), may interfere with the original connections and generate poor contrasting views, resulting in sub-optimal performance. In this paper, we define the views that share only a small amount of information with the original graph due to poor data augmentation as noisy views (i.e., the last 20% of the views with a cosine similarity value less than 0.1 to the original view). We demonstrate through detailed experiments that noisy views will significantly degrade recommendation performance. Further, we propose a model-agnostic Symmetric Graph Contrastive Learning (SGCL) method with theoretical guarantees to address this issue. Specifically, we introduce symmetry theory into graph contrastive learning, based on which we propose a symmetric form and contrast loss resistant to noisy interference. We provide theoretical proof that our proposed SGCL method has a high tolerance to noisy views. Further demonstration is given by conducting extensive experiments on three real-world datasets. The experimental results demonstrate that our approach substantially increases recommendation accuracy, with relative improvements reaching as high as 12.25% over nine other competing models. These results highlight the efficacy of our method. The code is available at https://***/user683/SGCL. © 2024, CC BY.

关键词： Contrastive Learning

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A Nudity Detection Algorithm for Web-based Online Networking Platform 10

A Nudity Detection Algorithm for Web-based Online Networking...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Dewan, Ritu Polishetty, Rohith Jagadam, Naveen Ravulakollu, Kiran Kumar Goyal, Mayank Kumar Sharan, Bhagwati Galgotias College of Engineering and Technology Department of Computer Science and Engineering Greater Noida India Sr. Software Engineer Migo India Limited Hyderabad India Ceo N2force Technologies Inc. NapervilleIL60563 United States School of Technology Woxsen University Hyderabad India School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida India School of Engineering and Sciences Srm University Department of Computer Science and Engineering AP Amaravati India

ISBN: (纸本)9789380544472

Social media and online platforms have become an integral part of the day-to-day life of the people and the organizations, which shows a lot of diversity. Many online platforms allow users to share media extensively, like images, videos, and audio but not all the media content shared on the internet is safe for work or should be restricted from particular platforms. Images with nudity are of big concern when it comes to online media sharing and social platforms must take serious measures to restrict users to share images with nudity. The rate of growth of nudity content over the internet or social media is very high. It affects the mental and physical health of individuals. In this paper, a novel method for nudity detection in images is presented. We aim to develop a Machine Learning algorithm for nudity detection in a community networking platform and how it should be integrated with such a platform so that posted images can be thoroughly checked for nudity and if detected how it should be dealt with. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Social networking (online)

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Development of Classification Model based on Arabic Textual Analysis to Detect Fake News: Case Studies

Development of Classification Model based on Arabic Textual ...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Hanen Tarik Himdi Fatmah Yousef Assiri Computer Science and Artificial Intelligence Department College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Software Engineering Department College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

The ease of communication that has been made possible by chat messaging platforms, such as WhatsApp and Line, and their increased use and ubiquity in society, have motivated purveyors of fake news to create and present their news as legitimate. Though different organisations continued their efforts to resolve this problem, many of the developed solutions rely on verifying the associated metadata, which are not always available. Several studies have attempted to identify fake news by analysing textual content; however, there is a lack of studies on Arabic language sources. Our work filled this gap; we proposed a machine learning model that classifies Arabic fake news based on textual analysis. This paper shows the feasibility of our approach to classify Arabic text in social media applications.

关键词： Analytical models Technological innovation Freeware Social networking (online) Smart cities Machine learning Metadata

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