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检索条件"任意字段=3rd International Conference on Computing and Data Science, CONF-CDS 2021"

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data Offloading in Heterogeneous Dynamic Fog computing Network: A Contextual Bandit Approach 3

Data Offloading in Heterogeneous Dynamic Fog Computing Netwo...

引用

3rd international conference on Computer Communication and the Internet, ICCCI 2021

作者： Shan, Yuchen Wang, Hui Cao, Zihao Yury, Kozyrev School of Mathematics and Computer Science Zhejiang Normal University Jinhua China

ISBN: (纸本)9781728176185

The urban environment is a particularly important application scenario for wireless sensor networks. Nevertheless, these environments are often dense and dynamic, and the sensor nodes are resource-constrained and heterogeneous. Hence, reliable data collection and scalable coordination are a challenge. In this paper, we model the data offloading problem as a bandit problem based on the context of the fog networking paradigm-an important extension of the multi-armed bandit. Through this way, we use the heterogeneity of sensor nodes as contextual information so that sensors can collaborate to offload data to the fog nodes and complete the data collection. Moreover, we have improved the algorithm for the dynamic movement characteristics of the nodes in the urban environment, so that the collaborative system has stable performance in the complex and changing urban environment. The analysis and trajectory simulations based on human movement data in urban environments demonstrate that the proposed scheme can significantly reduce the offloading delay and improve the offloading success rate. © 2021 IEEE.

关键词： Fog computing

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computing Force Network self-intelligence Based on Intent Driven and Digital Twin

Computing Force Network self-intelligence Based on Intent Dr...

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Electronic Information Engineering and Computer science (EIECS), 2021 international conference on

作者： Xiangning Li Yuqian Cai Jingyue Tian 6G Research Centre China Telecom Beijing Research Institude Beijing China

Introducing intent-driven network technology and digital twin network technology into the computing force network can solve the problem of unified management and scheduling of the computing force network and the high delay of data routing. Intent-driven network, based on technologies such as AI (artificial intelligence) and NFV (network function virtualization), can translate the service, performance and networking intents expected by users or operators into actual networking policies, so as to realize efficient and flexible reconfiguration of computing force networks. Digital twin network realizes efficient analysis, diagnosis and control of the computing force network by high-fidelity virtual real-time interaction. Combining intent-driven and digital twin, a self-intelligent optimization process of computing force network is proposed, which realizes the low delay self-organizing closed-loop control of user intent-based computing force network and the cross-domain regulation of computing force resources.

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AI-based Detection of Stress using Heart Rate data obtained from Wearable Devices 3

AI-based Detection of Stress using Heart Rate Data obtained ...

引用

3rd international conference on Evolutionary computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Mandal, Anurag Paradkar, Manasi Panindre, Prabodh Kumar, Sunil Dept. of Electr. Computer Engineering New York University Brooklyn United States Dept. of Mechanical Engineering New York University Brooklyn United States

Stress, a pervasive issue in today's world, significantly impacts mental and physical health. With approximately 20% of adults experiencing mental health disorders each year, and depression affecting over 260 million people globally, effective stress management is crucial. Chronic stress is also associated with physical ailments, including cardiovascular diseases, the leading global cause of death. In parallel, the wearable device market has witnessed substantial growth, with over 300 million units sold worldwide in 2021. These devices offer a unique opportunity to collect physiological and behavioral data, making them invaluable for stress detection and prediction. Combining artificial intelligence (AI) and wearables, this paper explores their accuracy in capturing vital data and the potential to revolutionize stress management, ultimately improving mental and physical well-being. In this paper, the ensemble-based classifier known as the Histogram-based Gradient Boosting Classifier detected stress from heart rates with an accuracy of 73%. This establishes the independent nature of Heart Rates for stress prediction, emphasizing that there is no need for sophisticated ECG and HRV readings. This opens up the possibility of using sensors as used in wearable devices to effectively detect stress in our day-to-day lives. © 2023 Elsevier B.V.. All rights reserved.

关键词： Artificial intelligence

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Cyber Threat Analysis and Prediction Using Machine Learning 3

Cyber Threat Analysis and Prediction Using Machine Learning

引用

3rd international conference on Advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Singh, Kulvinder Jha, Sudan Chandigarh University Department of Computer Science and Engineering Punjab India

ISBN: (纸本)9781665438117

With the increase in cyber data attacks, the manual method of investigating cyber-attacks is more prone to errors and is time consuming. With the increase in advanced cyber threat attacks with the same patterns, timely investigation is not possible. There are many systems proposed which analyse and predict threats using various machine learning methods. In this model we applied machine learning algorithms to analyse and predict cyber-attacks. © 2021 IEEE.

关键词： Forecasting

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A Real-time AIS data computing Platform Based on Flink 3

A Real-time AIS Data Computing Platform Based on Flink

引用

3rd IEEE international conference on Frontiers Technology of Information and Computer, ICFTIC 2021

作者： Lv, Taizhi Zhang, Jun Chen, Yingying He, Chenyong Jiangsu Maritime Institute Department of Information Technology Nanjing China Nanjing Huihai Transportation Technology Company Limited Department of Research and Development Nanjing China

ISBN: (纸本)9781665406055

Ship AIS (automatic identification system) data is an important part of water traffic perception data. It covers the core elements of ship navigation, including the dynamic information about geographical location and the static information of ship. Only in in the Yangtze River Basin, tens of millions of AIS data are generated every day. The traditional way is to store AIS data by offline processing and analysis. With the application of smart maritime, more and more applications need to master the ship dynamics in real-time. In order to realize the real-time processing and analysis of AIS data, a real-time AIS data processing and analysis platform based on the streaming computing framework is proposed. Flink is an open-source distributed stream computing framework with high throughput and low latency. It is used to realize the operations of AIS data De duplication, analysis, statistics in real-time. Through the data visualization technology, the computing results are displayed in real-time. It realizes the effective tracking of ship status and the real-time statistics of ships under the jurisdiction. It is of practical significance to improve the efficiency of ship supervision and maritime management. © 2021 IEEE.

关键词： Big data

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Design of ATM Network Architecture that interoperate with Higher Level Protocols in 5G environment 3

Design of ATM Network Architecture that interoperate with Hi...

引用

3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Dubey, Deepty Singh, Thipendra Pal Bhattacharjee, Arup School of Computer Science University of Petroleum and Energy Studies Department of Computer Science Dehradun India National Institute of Technology Department of Computer Science and Engineering Assam Silchar India

ISBN: (纸本)9780738146270

A new architecture based on Synchronous Digital Hierarchy (SDH) technologies for a large number of satellite data transfer is proposed. The architecture is composed of terrestrial networks, inter-satellite satellites (ISLs), permanent and transportable earth stations, handheld terminals, portable terminals and satellite connections through SDH, IP, ATM or other network protocol. datagrams such as cell ATMs and packets for IPs may be carried using SDH networks between satellites in orbit, for example through asynchronized transfer mode (ATM). Satellites may be accessed directly by all sorts of ground terminals through IP or ATM. © 2021 IEEE.

关键词： Internet protocols

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A Study of Semi Supervised based approaches for Motor Imagery Signal Generation 3

A Study of Semi Supervised based approaches for Motor Imager...

引用

3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Raoof, Ifrah Gupta, Manoj Kumar School of Computer Science and Engineering Shri Mata Vaishno Devi University Katra Jammu and Kashmir182320 India

ISBN: (纸本)9780738146270

Brain-computer interface provides an alternative way to communicate between the human brain and the external devices. Deep learning approaches have been widely used in various fields for feature extraction and classification task. However, the deep learning method requires a lot of data for training purpose. Due to the hectic calibration process, it is very difficult to collect large amount of EEG data. In such situations, deep neural network has proven very challenging in practice. This paper provides a comprehensive review of the various semi supervised approaches that have been used till now for the augmentation of motor imagery EEG data. Further, this research work has discussed about various research challenges faced by this field. © 2021 IEEE.

关键词： Deep neural networks

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Devanagari Character Recognition using Deep Convolution Neural Networks 3

Devanagari Character Recognition using Deep Convolution Neur...

引用

3rd international conference on Advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Gupta, Akshat Jain, Aman Saifi, Jubair Singh, Ajay Kumar Meerut Institute of Engineering and Technology Computer Science and Engineering Meerut India

ISBN: (纸本)9781665438117

In the presented paper, a Deep Learning architecture for Devanagari handwritten character recognition is introduced. The dataset comprises of 94742 images of 58 distinct classes containing numerals, vowels and consonants from Devanagari script. Deep Convolution Neural Network (DCNN) have indicated better outcomes than traditional Machine Learning algorithms and Shallow networks in recognition tasks. The proposed algorithm achieved an accuracy of 99.20% on testing data with 98.31% accuracy on training data. © 2021 IEEE.

关键词： Computer vision

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Crime Analysis using DBSCAN Algorithm 3

Crime Analysis using DBSCAN Algorithm

引用

3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Mungekar, Devvrat Joshi, Himani Kankekar, Adinath Nair, Pratap Das, Poulami K.C. College of Engineering and Management Studies and Research Dept. of Computer Engineering Thane India

ISBN: (纸本)9780738146270

Today with the growth in the human population, the crime rate has also escalated. To mitigate the increasing crime rate, it is necessary to analyze this humongous data using data science and machine learning techniques. The existence of a system that makes it easier to analyze, visualize and predict criminal data is indispensable. In this paper a user-friendly web application has been proposed that investigates criminal data using data analysis and data visualization methods. Using this system, the user can understand the crime patterns, crime trends, identify the criminal hotspots by observing the results from the data visualization methods. Density based Spatial Clustering of Applications with Noise (DBSCAN) algorithms has been used to cluster the crimes according to the location. The Crime Analysis Web Application is developed using the open-source framework Streamlit and Google Cloud Platform's (GCP) BigQuery engine. © 2021 IEEE.

关键词： data visualization

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Privacy Protection Method for Experts' Evaluation Ability Calculation of Peer Review 3

Privacy Protection Method for Experts' Evaluation Ability Ca...

引用

3rd IEEE international conference on Communications, Information System and Computer Engineering, CISCE 2021

作者： Wang, Zisen Liang, Ying Xie, Xiaojie Liu, Zhengjun Research Center for Ubiquitous Computing Systems Institute of Computing Technology Chinese Academy of Science University of Chinese Academy of Sciences Beijing China Research Center for Ubiquitous Computing Systems Institute of Computing Technology Chinese Academy of Science Beijing China

ISBN: (纸本)9780738112152

Most of the existing calculation method of expert evaluation ability directly call data onto calculation, which leads to the risk of privacy leakage of expert review information and affects the peer review environment. With regard to this problem, a privacy protection method of experts' evaluation ability calculation of peer review is proposed. Privacy protection and data usability are adjusted according to privacy preferences. Using Gauss distribution and combining with the distributive law of real evaluation data, the virtual projects are generated, and the project data are anonymized according to the virtual projects. Laplace distribution is used to add noise to the evaluation sub score for perturbation, and the evaluation data are obfuscation according to the perturbation sub score. Based on the protected project data and evaluation data, the expert evaluation ability is calculated, and the review privacy is protected. The experimental results show that the proposed method can effectively balance the privacy protection and the accuracy of the calculation results. © 2021 IEEE.

关键词： data obfuscation

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