检索结果-内蒙古大学图书馆

13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Laohakanniyom, Pakorn Ichikawa, Kohei Iida, Hajimu Leelaprute, Pattara Manaskasemsak, Bundit Rungsawang, Arnon Kasetsart University Department of Computer Engineering Bangkok Thailand Nara Institute of Science and Technology Nara Japan

ISBN: (纸本)9798350368086

The exponential growth in networked systems, such as entertainment streaming services, has necessitated advancements in network performance. Traditional singlepath routing often results in bottlenecks and inefficiencies, whereas multipath routing can significantly enhance bandwidth utilization and accommodate diverse user demands. This study explores the integration of SRv6 (Segment Routing over IPv6) with MPTCP (Multipath TCP) to leverage multiple network routes concurrently. SRv6 offers a scalable routing architecture by embedding routing information within IPv6 headers, while MPTCP distributes traffic across multiple paths, enhancing both network performance and reliability. We conducted experiments using two network topologies: a synthetic topology with 7 nodes and 11 links, and the Internet2 OS3E topology with 34 nodes and 42 links. Throughput measurements were taken under four scenarios: single-path TCP without SRv6, single-path TCP with SRv6, MPTCP without SRv6, and MPTCP with SRv6. The experimental results confirmed that the integration of SRv6 with MPTCP achieved the expected improvements in network performance, demonstrating enhanced throughput and better resource utilization compared to single-path TCP configurations. The implications of this research indicate that SRv6 and MPTCP integration enhances throughput, network reliability, and efficiency. This approach provides additional perspective for further scalable solutions that can be applied across various network topologies, and addressing modern network demands. However, this research also identifies potential challenges such as throughput fluctuations when SRv6 and MPTCP are combined, which may affect the performance of realtime applications. Future research should explore these challenges to optimize the integration of SRv6 and MPTCP. © 2024 IEEE.

关键词： Integration

来源：评论

学校读者我要写书评

暂无评论

P-IOC-FPMine: an association rule mining algorithm for item constraints based on the MapReduce framework

引用

International Journal of Wireless and Mobile Computing 2022年第1期23卷 57-66页

作者： Chu, Zenan Wang, Wei Department of Computer Science and Information Engineering Anyang Institute of Technology Henan Anyang China

In the application of big data, one of the most challenging problems is how to consider the requirements of users. To avoid this problem, we proposed IOC-FP-growth. This added user-defined pre-term or post-item constraints into the classic FP-growth algorithm. What’s more, a parallel data mining algorithm based on MapReduce, namely P-IOC-FPMine was proposed, which was a low-memory fast association rule mining algorithm. Finally, by evaluating the effectiveness of the method in the public data. The results showed that the IOC-FP-growth method can consider the user’s needs for association rules easily. Compared with the FP-growth, Recorder and PNARCMC, we only need to meet the requirements of users to extract accurate rules, which will bring huge advantages for data mining. After parallelisation, the performance of the P-IOC-FPMine was better than FP-growth on the data set. The results showed that the P-IOC-FPMine was more appropriate for handling large-scale data sets. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： MapReduce

来源：评论

学校读者我要写书评

暂无评论

Facial recognition using grey wolf optimization

引用

Materials Today: Proceedings 2022年 58卷 273-285页

作者： Barman, Bhaswati Dewang, Rupesh Kumar Mewada, Arvind Computer Science and Engineering Department Motilal Nehru Institute of Technology Allahabad Prayagraj India

Nowadays, multimedia data on social media platforms of the Internet, especially images, are proliferating, due to which image retrieval systems based on content are one of the major research areas. Despite the introduction of various content-based images retrieval approaches, face recognition remains a problematic task. Consequently, this paper developed a face recognition framework using modifying the bag-of-features (BOF) from a grey wolf optimisation (GWO) algorithm in which a variable weight is used. Variable weight proposes a sine cos function to find the best score. The convergence behaviour of the variable weight GWO algorithm is performed over some benchmark functions. Furthermore, it has been used to get the histograms fed into training and testing function to get the model accuracy using the Yale face database. © 2022

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Voice command-integrated AR-based E-commerce Application for Automobiles

Voice command-integrated AR-based E-commerce Application for...

引用

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2023

作者： Krishnamurthy, Vallidevi Jafrin Rosary, B. Oliver Joel, G. Balasubramanian, Surendiran Kumari, Sakshi Vellore Institute of Technology School of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Mechanical Engineering Chennai India National Institute of Technology Puducherry Department of Computer Science and Engineering Puducherry India

ISBN: (纸本)9798350312126

This research work aims to create an Augmented Reality (AR) based android app that can project the dimensions of an automobile in the real world and recognize voice commands to operate functions like opening car doors and changing colors. The app uses a combination of augmented reality, machine learning technology, Unity game engine, C# script, Google speech recognition API and Vuforia SDK to superimpose images of the car in the real world and allow control through voice commands. The initial focus is on cars, but the solution can also be used to create AR-enabled brochures for marketing companies to enhance sales and provide customers with a better understanding of the product before purchase. © 2023 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Eye Disease Detection Through Image Classification Using Federated Learning

引用

SN computer Science 2023年第6期4卷 836页

作者： Kaushal, Vishal Hada, Nishant Singh Sharma, Sangeeta Computer Science and Engineering Department National Institute of Technology Himachal Pradesh Hamirpur 177005 India

In recent years, the fields of artificial intelligence and deep learning have had a significant impact on the field of ocular imaging. One area where deep learning has been particularly useful is in identifying and categorizing different eye diseases through the analysis of retinal photographs, optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA) images. However, traditional methods of training deep learning models often require large and diverse datasets from multiple locations, which can raise concerns about data security and patient privacy. To address these concerns, researchers have begun to explore the use of federated learning, a method of distributed, collaborative learning that allows multiple parties to work together without needing to share sensitive data. This paper implements four popular deep learning algorithms: VGG16, MobileNet, ResNet50, and InceptionV3, in a federated learning environment for ocular imaging datasets. The objective is to explore the effectiveness of these algorithms in terms of accuracy, privacy, and other performance parameters. The results demonstrate that implementing these algorithms in a federated learning environment can lead to significant improvements in performance and privacy compared to traditional centralized learning methods. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks Fundus imaging Ophthalmological disease detection Transfer learning

来源：评论

学校读者我要写书评

暂无评论

STC (Sketch To Code)-An Enhanced Html & CSS Autocode Generator from Handwritten Text and Image Using Deep Learning 2

STC (Sketch To Code)-An Enhanced Html & CSS Autocode Generat...

引用

2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Srinath, R. Siva Prasath, K.R. Varun Raj, S. Vinith, W. Srinivasan, L. Dr. N.G.P. Institute of Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350365269

This paper presents an innovative solution for automating the transformation of hand-drawn sketches into HTML and CSS code. The process unfolds in four distinct phases: Pre-processing optimizes input sketches, Segmentation identifies key regions using Region Proposal Networks (RPN), Feature Extraction employs Line Drawing Prediction (LDP) for detailed interpretation, and Classification categorizes features into HTML and CSS elements. The integrated use of RPN and LDP ensures precise recognition of design elements and layout, streamlining the conversion process. This approach not only enhances accuracy but also enables a seamless transition from creative ideation to web development, reducing the manual effort traditionally associated with coding. © 2024 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

A Data Privacy-Preserving Model driven on Differential Approach in Cloud Environment

A Data Privacy-Preserving Model driven on Differential Appro...

引用

2023 International Conference on Green Energy, Computing and Intelligent technology, GEn-CITy 2023

作者： Gupta, Rishabh Saxena, Deepika Singh, Ashutosh Kumar Department of Computer Science and Engineering The University of Aizu Aizuwakamatsu Japan Department of Computer Applications National Institute of Technology Kurukshetra India

ISBN: (纸本)9781839539596

With the wide range of cloud services, including flexibility, high scalability, and the least upfront capital investment, it also offers machine learning services that are utilized in various applications, such as medical diagnosis, risk analysis, and product recommendation. Since it has many advantages, many organizations move their data to the cloud platform for storage, processing, and distribution intentions. The classification service is offered by the cloud service provider so that owners can assess their data. It gathers the data from the owners' side for training the machine learning model and accomplishing the classification task. The cloud servers handled by a third party might not be totally trusted by the data owners. However, data privacy is a significant challenge among the critical barriers to preserving data while distributing it. A novel data protection model is proposed, driven on machine learning and differential approaches that carry out classification tasks while protecting the owners' data through noise addition. The model enables the different owners to store, share, and utilize data on the cloud platform. The experiments are carried out on Cleveland, New-Thyroid, and SA-Heart datasets to determine the effectiveness of the model in terms of accuracy, precision, recall, and F1-score. The results show that it achieves high accuracy, precision, recall, and F1-score up to 88.37%, 83.28%, 98.41%, and 82.91%, respectively. © The Institution of engineering & technology 2023.

关键词： Risk analysis

来源：评论

学校读者我要写书评

暂无评论

Using Micro Services Architecture to Improve Scalability, Flexibility, and Performance in E-Learning Platforms 15

Using Micro Services Architecture to Improve Scalability, Fl...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Johnson, J.G. Abylin Caleb Andrew, H. Department of computer science and engineering Karunya Institute of Technology and Sciences Karunya Nagar Coimbatore641114 India

ISBN: (纸本)9798331300579

A revolutionary approach for creating and executing scalable, adaptable, and robust software systems is microservices architecture. Microservices present a strong answer to the problems with traditional monolithic designs in the context of e-learning platforms, where performance, scalability, and adaptability are critical requirements. This paper provides a thorough analysis of how microservices are transforming e-learning platforms, emphasizing how they can improve performance, scalability, and flexibility. First, we give a summary of microservices architecture, emphasizing its main ideas and advantages. Next, we explore the particular uses of microservices in e-learning platforms, talking about how they facilitate fault isolation, modularization, and independent scaling. Through dissecting e-learning platform architectures into discrete microservices and analyzing their essential elements, we demonstrate how microservices enable effective user administration, content distribution, analytics, and more vital features. We also discuss scalability and performance issues, showing how the microservices design allows for horizontal scaling and providing guidance on how to maximize performance using asynchronous processing, load balancing, and caching. We discuss frequent issues that arise while introducing microservices in e-learning platforms and offer solutions throughout the article. Lastly, we highlight new technologies and areas for more study and invention as we go over future trends and directions in microservices for e-learning. © Grenze Scientific Society, 2024.

关键词： Scalability

来源：评论

学校读者我要写书评

暂无评论

Improved Deepmaxoutmodel for Disease Prediction in Healthcare IoT Cloud System 3

Improved Deepmaxoutmodel for Disease Prediction in Healthcar...

引用

3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Preetha, P. Packialatha, A. Vels Institute of Science Technology and Advanced Studies Department of Computer Science Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350374643

The Internet of Medical Things IoMT has grown rapidly due to the growing popularity of wearable technology and its applications in health monitoring systems. The IoMT significantly reduces the death rate by facilitating early sickness identification. Predicting cardiac disease is among the most significant issues with clinical dataset analysis. Finding the key components of heart disease prediction is the goal of the suggested investigation, which makes use of machine learning techniques. Despite several studies on the issue, the accuracy of the findings on the diagnosis of heart illness is low. The purpose of this paper is to provide an innovative framework for healthcare monitoring that includes the following phases. Data preprocessing, feature extraction, acquisition of data, and prediction are the primary stages. The process of acquiring data is at the IoTs layer. The medical data is considered in this case (benchmark datasets of different illnesses). The data pre-processing operations of data cleaning and data filtering at the cloud layer are applied to the data obtained from the IoT sensors (considering the dataset), where the data normalization process will take place. Subsequently, statistical features and raw features are extracted. The multi-layered Deepmaxout model will predict the diseases during in the prediction phase. Lastly, the evaluation of the suggested approach is compared to existing methods using several types of metrics. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning Algorithms for Emotion Classification 7

Comparative Analysis of Machine Learning Algorithms for Emot...

引用

7th IEEE Pune Section International Conference, PuneCon 2024

作者： Deshmukh, Ashish Dhage, Aniket Gadapa, Ritika Butle, Sanika Yenkikar, Anuradha Sable, Nilesh P. Vishwakarma Institute of Information Technology Department of Cse - Artificial Intelligence Pune India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798331527822

In this generation, social media platforms such as Twitter, Instagram and also e-commerce websites have become an integral part of our society. Social media is used for communication and it is also a platform where the users can express their thoughts and feelings. Also, users share their reviews on e-commerce websites. To analyze what exactly is the emotion of the user our machine learning models explores the sentiment analysis techniques for predicting emotions from the given text data. It follows a series of steps, starting with importing libraries, acquiring datasets, visualization, pre-processing, and model building. The data is used to train on a variety of models, including LSTM, Naive Bayes, Random Forest, Gradient Boosting, and SVM. The performance of each model is evaluated using metrics like accuracy, precision, recall, and F1-score. Comparative analysis is conducted to determine the most effective model for emotion prediction. Furthermore, the research investigates emotion prediction for huge datasets and provides a procedure for exporting trained models for future usage. It provides insights into the performance of various machine learning algorithms in sentiment analysis, hence contributing to the understanding and interpreting emotions from textual data on various platforms. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：