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

共 907 条记录，以下是171-180 订阅

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

Proceedings - 2021 3rd International Conference on Advances ...

引用

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

ISBN: (纸本)9781665438117

The proceedings contain 403 papers. The topics discussed include: a modified data clustering algorithm for uncertain data in peer to peer networks;concept drift detection for social media: a survey;voice feature analysis for speaker recognition to improve content management;analysis and prediction of drugs using machine learning techniques;text summarization using extractive techniques;an analysis and research on sentiments of twitter data;advancements of lab on chip in reducing human intervention: a study;an open air outdoor environment for children in urban residential precinct;analysis of online media content using data science techniques;a machine learning approach for predicting dengue outbreak;analysis of student performance and requirement using data science;analytical study of stochastic trends of non-performing assets of public and private commercial banks in india;a critical analysis of diabetes detection using machine learning algorithms;and recommendation system with exploratory data analytics using machine learning.

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Deep Learning Techniques to Improve Radio Resource Management in Vehicular Communication Network 1

引用

3rd international conference on Sustainable Advanced computing, ICSAC 2021

作者： Agarwal, Vartika Sharma, Sachin Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9789811690129

ISBN: (纸本)9789811690112

This paper investigates the deep learning techniques to improve radio resource management (RRM) in vehicular communication network (VCN). In this paper, the deep learning algorithms are highlighted which are used for RRM. Deep learning technique in RRM is basically used to train the model using various algorithms of resource management including network data. Various machine learning tools will be helpful to get best solutions for resource allocation in a large cellular network. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Resource allocation

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A Survey of Machine Learning-Based Approaches for Missing Value Imputation 3

A Survey of Machine Learning-Based Approaches for Missing Va...

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

作者： Gond, Vikesh Kumar Dubey, Aditya Rasool, Akhtar Maulana Azad National Institute of Technology Department of Computer Science and Engineering Bhopal India

ISBN: (纸本)9780738146270

Missing values create issues during the analysis of the dataset. Learning algorithms in an asymmetrical dataset can generate an overrated classification accuracy due to a bias towards the majority class at the expense of the minority class. Missing values in the dataset have a negative impact on the imputation of accuracy;therefore, it could lead to a different output. Some algorithms cannot handle missing values properly, while some techniques give efficient results to estimate the missing values. It is very important to handle missing data because many machine learning algorithm performances reduces due to missing values. It might be possible that the original datasets have some missing data for many factors like data were not kept in a file, data had been corrupted, etc. In this paper, some techniques are discussed which are employed to impute the missing data, and these techniques are compared using their merits and drawbacks. © 2021 IEEE.

关键词： Decision trees

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Edge computing Power Optimization Method in Container Cloud Environment

Edge Computing Power Optimization Method in Container Cloud ...

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

作者： Yuchao Zhao Tianhui Jiang Xiamen Ocean Vocational College Xiamen China

Due to slow CPU speed and small battery capacity, intelligent mobile devices cannot perform computing themselves, which causes many problems such as resource scheduling security technology. To reduce these problems, edge computing techniques are needed. However, moving some computing tasks from mobile devices to edge servers increases the additional energy consumption of transport and server computation. Considering the four factors affecting mobile devices and servers, as well as the energy consumption of data transmission, a particle swarm optimization algorithm based on hierarchical learning was proposed to solve the problems of computing speed, power consumption of downloaded data, and computing security of mobile devices. The proposed algorithm optimizes these four parameters for each mobile device to allocate computing resources more rationally, minimize the total energy consumption, and ensure security during scheduling. When modeling computing resources, the maximum energy consumption, computation cycle, storage, bandwidth, and delay constraints are also considered. Compared to the other algorithms in the container cloud, the proposed particle swarm optimization algorithm optimized by hierarchical learning can get the optimal solution of resource scheduling satisfying the constraints faster, with lower energy consumption and higher security.

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An Overview: Exploratory data Analytics on E-Commerce dataset 3

An Overview: Exploratory Data Analytics on E-Commerce Datase...

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

作者： Panwar, Manu Wadhwa, Amit Pippal, Sanjeev GL.Bajaj Institute of Technology Computer Science and Engineering Gr.Noida India

ISBN: (纸本)9781665438117

Its not news that people have been increasingly relying on digital technologies in recent years. As a result of this consumption, humans and machines are producing more data. On the other hand, these tools imply that organizations are complex. Furthermore, as the volume of data generated by users grows as a result of improved internet connections around the world, the issues of handling that data grow as well. As a result, techniques like machine learning (ML) can assist firms in managing and utilizing data supplied by users. Further, the focus of this work is to give insights in the field of exploratory data analysis to e-commerce system by applying probable machine learning based model. © 2021 IEEE.

关键词： data Analytics

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Security Attacks in Cloud computing: A Systematic Review 3

Security Attacks in Cloud Computing: A Systematic Review

引用

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

作者： Sansanwal, Suman Jain, Nitin Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9780738146270

These days cloud computing plays very major role in the world of computers. On demand services via Internet is provided by cloud computing using large amount of virtual storage. Its most important feature is that user has no need to establish costly computing infrastructure and pay very less for its services. Virtualization is the backbone of resource sharing provided by cloud computing. Security is huge challenge of cloud computing. Cloud computing allows the user to access resources anywhere anytime via internet which is actually the main reason behind the multiple varieties of attacks. Generally at different cloud layers various threats functioning like data breach, data leakage and unauthorized data access. Even there is constant implementation and improvement occurring regarding security issues and its countermeasures over cloud computing with the growth of time, unfortunately security is still a big challenge. This paper includes a examination based on a theoretical survey on cloud computing that communicated various possible threats and also taxonomy model where at each layer a number of various security attacks enter from the usage of different cloud services, moreover for these attacks proposed mechanisms and the solutions available earlier. © 2021 IEEE.

关键词： Virtualization

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Impact of COVID-19 Variants Using Multi-Criteria Selection Approach

Impact of COVID-19 Variants Using Multi-Criteria Selection A...

引用

2024 international conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Sagar, Shrddha Kumar, Avadhesh Singh, Sofia Shukla, Garima Upadhyay, Diwakar School of Computer Science and Engineering Galgotias University Uttar Pradesh India Amity School of Engineering and Technology Amity University Department of Artificial Intelligence Uttar Pradesh Noida India Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Maharashtra Mumbai India School of Computing Graphic Era Hill University Haldwani India

ISBN: (纸本)9798331517953

The aim of the proposed work is related to the detailed study of various types of COVID-19 along with its symptoms. This study utilized a retrospective approach to the COVID data from 2019 to 2021 to assess the severity level of the various types of COVID-19. After a detailed analysis, we have identified seven symptoms which are as follows: breathing, chest pain, fever, body ache, sore throat and cough, tiredness, and loss of taste/smell. In this study, the prediction of the COVID-19 severity level is made using a fuzhzy multi-objective optimization based on ratio analysis (fuzzy MOORA) approach. The proposed model simultaneously predicts the severity level of COVID-19 with multiple criteria. The severity levels listed on government-approved websites for various types of COVID-19 are considered for validating the proposed methodology's result. The highest overall performance index value is used to decide. As a result, the overall performance index value has been achieved and moreover, we can predict the severity level of different forms of COVID-19 using this strategy. After the implementation of our proposed approach, we got the overall performance index value of delta T4 (0.433086). The Coronavirus Virus 2019 (COVID-19) pandemic is on the increase for over two years. The World Health Organization (WHO) statistics show that approximately 260 million confirmed cases have been documented, with over five million deaths. In our work, we have implemented a fuzzy MOORA approach for predicting the severity level of the different types of COVID-19. The overall performance index value of each COVID-19 is shown in the table. Table 1.2 demonstrates that Delta T4 is ranked 1st, Gamma T3 is ranked 2nd, Beta T2 is ranked 3rd, Alpha T1 4th and Omicron T5 has the least rank. © 2024 IEEE.

关键词： COVID-19

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Design of Enterprise Cost Budget Management Platform Based on Amoeba Model and CUDA data Analysis 3

Design of Enterprise Cost Budget Management Platform Based o...

引用

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

作者： Yu, Zhiye Guangdong University of Science and Technology Guangdong Dongguan523000 China

ISBN: (纸本)9780738146270

Cost budgeting is an important link in enhancing the competitiveness of an enterprise and realizing the optimal configuration of enterprise production. With the development of computer and information technology, there is an urgent need for cost budget management information systems to control costs for enterprises, enhance management levels, and achieve the purpose of improving economic benefits. The research method of this thesis is case analysis combined with innovative scheme design. Based on the author's research on the Amoeba model in the work of a consulting company, as well as the analysis and conclusions of the problems and problems collected in the actual investigation of Company A, according to the theory of Amoeba's business model and cost management, and the company The actual application process is combined. © 2021 IEEE.

关键词： Budget control

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A Weibo Recommendation Algorithm Integrating User Interests 3

A Weibo Recommendation Algorithm Integrating User Interests

引用

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

作者： Zhu, Xiaojing College of Intelligent Science and Engineering Yunnan Technology and Business University Yunnan Kunming651701 China

ISBN: (纸本)9780738146270

A Weibo recommendation algorithm integrating user interests is studied in this manuscript. Among the algorithms based on content similarity recommendation, the LDA algorithm is one of the most used and classic algorithms. Therefore, this paper uses the LDA algorithm to mine the user interest distribution and uses the cosine similarity algorithm to calculate the similarity between the general microblog to be recommended and the user's interest. The proposed algorithm is designed by considering the similarity of user interest based on the semantic level and the similarity of the social relationship based on the follow relationship are then considered, a better recommendation effect can be achieved. To validate the model, the proposed algorithm is simulated on the data collected from the Weibo. The accuracy is higher than before. © 2021 IEEE.

关键词： Semantics

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A Novel Big data Cleaning Algorithm Based On Edge computing In Industrial Internet of Things 3

A Novel Big Data Cleaning Algorithm Based On Edge Computing ...

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2021年第三届先进计算机技术、信息科学与通信国际会议(CTISC2021)

作者： Mao Chen Wen Chen Yongqi Zhu College of Information Science and Technology Donghua University

ISBN: (纸本)9781665418683

The Industrial Internet of Things(IIoT) is a revolution that is changing the face of industry. It brings opportunities and also challenges. Due to the harsh sensor environment in the industry, the collected big data is not credible, which seriously affects the judgment and feedback of the cloud. Traditional data cleaning relying on sensor nodes is not enough to process big data, while mobile edge computing can provide a good *** paper proposes a data cleaning solution based on mobile edge nodes. First,we obtain the training data of the cleaning ***, we use the isolation forest(iForest) anomaly detection method at the edge nodes. Experimental results show that the scheme improves the efficiency of data cleaning and also ensures the reliability and integrity of the data.

关键词： Industries Information science Image edge detection Training data Forestry Big data Cleaning

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