检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Jiang, Ming Li, Yun Zhang, Feng Guo, Biao Qin, Ping Zhang, Shuo Lu, Yao School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Metaverse Application Engineering Center Guangxi Nanning530000 China Guangxi Institute of Digital Technology Guangxi Nanning530000 China School of Information Engineering Guangxi Polytechnic of Construction Nanning530000 China

ISBN: (纸本)9781665410205

In response to key challenges in federated learning, particularly those concerning the heterogeneity of locally distributed data which engenders client drift and the problematic occurrence of dimensionality collapse, we propose FedHiDiC: high-dimensional heterogeneous data condensation and distillation contrastive learning. A key idea of FedHiDiC is to integrate mean squared error, standard deviation, and covariance as regularization terms in local training to control parameter norm growth and bolster the capacity to handle high-dimensional, heterogeneous data. Another key idea is to utilize the similarity of representations between models to correct for local training, which reinforces intra-class compactness and inter-class distinction and reduces model variability through knowledge distillation from the global to local models, combined with contrastive strategies. Our experiments on CIFAR10 and CIFAR100 datasets show that FedHiDiC achieves significant performance improvements, surpassing FedAvg, FedProx, and MOON by 2.9% to 4.0% in accuracy, which confirms the effectiveness of FedHiDiC in tackling heterogeneity challenges. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Automated Self-Supervised Learning for Recommendation

Multi-Scale Automated Self-Supervised Learning for Recommend...

引用

2023 International Conference on Intelligent Management and Software Engineering, IMSE 2023

作者： Yan, Yuhang Gao, Yujie Tian, Liqin School of Computer Science Qinghai Normal University Xining China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining China School of Computer North China Institute of Science and Technology Yanjiao China

ISBN: (纸本)9798350394146

Automated self-supervised learning frameworks have shown significant results in the recommendation domain. However, existing methods such as AutoCF use graph convolutional networks and graph attention mechanisms that are limited to a single expression granularity and cannot fully capture the multi-granularity of user interests and product attributes. To address this problem, we propose MS-AutoCF, a multi-scale automated self-supervised learning recommender system that obtains user and product representations at different granularities through multi-layer graph convolution to match the global and local details of their interest preferences. Meanwhile, we design a query key value-based multi-head graph attention module that can adaptively aggregate and enhance the representations with different granularities. Experimental results show that the MS-AutoCF system achieves significant improvements over existing single-scale methods on several public datasets. ©2023 IEEE.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Optimizing Drug Dosage and Medication Management for Geriatric Patients with Artificial Neural Networks 3

Optimizing Drug Dosage and Medication Management for Geriatr...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Beemkumar, N. Singh, Daljeet Pal Ahmed, Zahid Faculty of Engineering and Technology Department of Mechanical Engineering Bagalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350343274

In this paper, we utilize ANNs to investigate how medicine dosing and management might be improved for the elderly population. The suggested strategy calls for the use of patient-specific data as inputs for the ANNs, such as age, renal and hepatic function, body mass index, and preexisting prescription profiles. The neural network model dynamically changes drug doses using the combination of the Multilayer Perceptron (MLP) algorithm, Backpropagation, and the Stochastic Gradient Descent (SGD) algorithm to maximize therapeutic benefits and reduce the likelihood of adverse drug events. The research highlights the improved accuracy, sensitivity, specificity, precision, and F1 score of the suggested technique compared to numerous conventional methods. As a result, the suggested system has great potential to revolutionize medication management for the elderly population since it is more personalized, flexible, patient-safe, effective, and efficient in its use of resources. © 2023 IEEE.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Leveraging AI to Unlock the Potential of Data Science 15

Leveraging AI to Unlock the Potential of Data Science

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Yadav, Rakesh Kumar Sudhamsu, Gadug Goyal, Manish Kumar Yuvaraj, S. Deshpande, Leena A. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

The application of synthetic Intelligence (AI) to records science has spread out a massive array of new possibilities. Via the combination of advanced evaluation strategies, effective understanding-pushed system gaining knowledge of algorithms, and modern computing architectures, AI is allowing researchers to quick and as it should be discover insights from huge and complicated datasets. Furthermore, AI tools are offering corporations with the ability to make higher and more knowledgeable choices from the evaluation of hundreds of thousands of statistics points. The skills of information technology powered by means of AI are revolutionizing industries which includes healthcare, finance, and manufacturing-producing savings, uncovering efficiencies, and identifying new opportunities. As AI-driven records technology maintains to strengthen, organizations that capitalize on its ability stand to gain precious insights and unlock new degrees of overall performance. © 2024 IEEE.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Sentiments Analysis on Amazon Product Reviews Using Supervised Machine Learning Algorithms

Sentiments Analysis on Amazon Product Reviews Using Supervis...

引用

2023 International Conference on Integration of Computational Intelligent System, ICICIS 2023

作者： Gore, Ramdas D. Borole, Vipin Y. Gupta, Rohit S. Sonaje, Viabhav Chaudhari, Prafulla Gawali, Bharti W. SOCSE Sandip University Department of Computer Science and Application Nashik422213 India Nashik422213 India Dr. Babasaheb Ambedkar Marathwada University Department of Computer Science and Information Technology Aurangabad431001 India

ISBN: (纸本)9798350318784

To determine the sentiment or emotion indicated in a text, such as a review, tweet, or piece of customer feedback, sentiment analysis, also known as opinion mining, uses computational linguistics, machine learning, and natural language processing techniques. Sentiment analysis seeks to determine whether the automatic sentiment expressed in the text is positive, negative, neutral, or occasionally more nuanced emotions like joy, sadness, rage, etc. The Apple iPhone 14 Pro Max (1 TB, Gold) evaluations from 160 Amazon consumers were used in this study. We used tokenization, stop word removal, stemming, and punctuation mark removal for preprocessing. Positive and negative word analysis is done using word clouds. We received favourable and unfavourable feedback about the Apple iPhone 14 Pro Max. Dynamic, good, improving, lovely, fantastic, great, etc., are positive evaluations. Additionally, unfavourable reviews are a costly, stuck gimmicky, gimmicky hesitant, heck of many complaints, bug bumpy and alarming, break dissatisfied, etc. We used Naive Bayes, Support Vector Machines (SVM), and Logistic Regression, among other machine learning approaches. We got 90%, 91%, and 94% accuracy for Logistic Regression, Support Vector Machines (SVM), and Naive Bayes, respectively. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

An Evaluation of Interactive Communication Media Algorithms and Their Usage for Networking applications 5th

An Evaluation of Interactive Communication Media Algorithms ...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Kudari, Jayashree M. Yadav, Rakesh Kumar Yadav, Surendra Kapse, Vinod Mansiram Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

This paper evaluates using interactive conversation media algorithms inside the context of networking applications. Exceptional forms of algorithms are mentioned, which includes media movement algorithms, interactive conversation protocols, recording algorithms, and video compression protocols. The overall performance of those algorithms is classified and evaluated thru a quantitative analysis that includes measurements of common latency and packet loss. Additionally, the paper investigates using interactive communication media algorithms for one of kind programs together with video conferencing, on line gaming, and voice over IP offerings. Sooner or later, a contrast of various algorithms is made, with hints for the fine answers primarily based on the evaluated performance and application necessities.. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Video conferencing

来源：评论

学校读者我要写书评

暂无评论

Autonomous and Adaptive Communications Systems in Mobile Ad-Hoc Networks 5th

Autonomous and Adaptive Communications Systems in Mobile Ad-...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： J, Bhuvana Yadav, Dhyan Chandra Goyal, Manish Kumar Sharma, Himanshu Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Luckow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

Protocols, enabling communication, manipulation, and coordination among cell nodes. Those techniques can efficiently use the community topology, connectivity, to-be-had assets, and consumer requirements to alter communication parameters and path selection for record transmissions robotically. Self-sufficient/adaptive systems also manage user requests and sensor measurements in real-time to dynamically regulate verbal exchange protocols and network configurations for higher verbal exchange performance. Furthermore, those structures also provide capabilities, including self-configuration, self-organization, fault-tolerance, and communique reliability. Various mechanisms may permit autonomous and adaptive verbal exchange in MANETs, including geo-vicinity-based total routing, location-established network coding, allotted garages, energy-conscious communication protocols, and allotted coordination techniques. Additionally, simulated annealing and particle swarm optimization can be used to optimize conversation and routing protocols. Self-sufficient and adaptive communications systems in cellular ad hoc networks have become a need in today’s international, as cell gadgets are used extra often and for more complex tasks. These structures are essential for preserving a clean float of verbal exchange without a centralized infrastructure or constant direction topologies. Self-reliant communications systems offer sturdy, self-configuring, self-healing, and self-organizing communication networks. Such structures are designed to constantly alter parameters primarily based on facts amassed from community resources and a person’s desired preference. Adaptive systems, on the other hand, dynamically create a superior topology by way of considering to-be-had assets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Investigating Wireless Networks with Network Coding Algorithms 5th

Investigating Wireless Networks with Network Coding Algorith...

引用

5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Ahmed, Zahid Gupta, Anjali Preethi, D. Singh, Akhilendra Pratap Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electrical and Electronic Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Community coding algorithms had been demonstrated to have capability to improve the performance of wireless networks. This paper offers a research, assessment, and implementation of community coding algorithms for Wi-Fi networks. The paper affords an overview of community coding algorithms and discusses the related blessings, drawbacks, and tradeoffs that have to be taken into account while evaluating the performance of these algorithms. Furthermore, simulation outcomes are offered to assess the overall performance of one of a kind network coding algorithms while implemented in a wireless community surroundings. Ultimately, the paper outlines the hardware and software elements required to correctly put into effect and test those algorithms in an operational wireless community. The promising consequences of the experiments imply that these community coding algorithms can be used to efficiently improve the overall performance of Wi-Fi networks within the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

Icon-to-Icon Translation using Pixel-Level Weight Adversarial Networks

Journal of Network Intelligence

引用

Journal of Network Intelligence 2022年第1期7卷 147-160页

作者： Pan, Yao-Ming Lin, Kai-Biao Chen, Chin-Ling School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Engineering Research Center of Big Data Application in Private Health Medicine Fujian Provincial University Putian351100 China School of Information Engineering Changchun Sci-Tech University Changchun130600 China Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung41349 Taiwan

We investigate image-to-image translation as a solution to icon-to-icon translation problems. Icon-to-icon translation aims to translate the input icon to appear like the target domain’s icons and simultaneously preserve the original icon’s information (e.g., application logo, text and background color). We present a novel approach to trans-lating icons to the version with the target style intelligently. By observing many icons with various styles, we propose a pixel-level weight matrix to calculating the weighted losses. These losses guide the generator to focus on the critical regions of the icon. People can clearly get the original icon’s information from the proposed method’s results, while the existing state-of-the-art image-to-image translation methods may fail to do this. © 2022, Taiwan Ubiquitous information CO LTD. All rights reserved.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Disease Detection Using Ensemble Model in Machine Learning

引用

SN computer Science 2025年第3期6卷 1-15页

作者： Mohapatra, Rojalin Giri, Parimala Kumar Sayyad, Irfan Sahu, Amaresh Brahma, Biswajit Kamila, Nilayam Kumar Department of Computer Science and Engineering Gandhi Institute for Technological Advancement Odisha Bhubaneswar India Department of Information Technology and Computer Application Vignan’s Foundation for Science Technology and Research (Deemed to be University) Andhra Pradesh Vadlamudi India Department of MCA Ajay Binay Institute of Technology Odisha Cuttack India McKesson Corporation San Francisco CA United States Capital One Wilmington DE United States

Disease detection is a vital issue in the healthcare system. Few diseases need to be tested early if any patient discovers any disease-related symptoms in their body. Although various methods are used to test several diseases based on the symptoms, it is necessary to improve the experimental testing for disease detection through various machine learning (ML) methods. Thus, the ensemble ML Model is proposed to enhance the experimental performance per the methods. Different machine learning methods such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Gaussian Naive Bayes (GNB) and Logistic Regression (LR) are used to make ensemble models based on the combination of two or three methods. The experiment is demonstrated on the proposed ensemble model using a diabetes data set and performed with various evaluation metrics. As per the performance of the ensemble method, (SVM + RF) performed well than other methods with an accuracy of 99%. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ensemble model Logistic regression Machine learning Naïve Bayes Random forest SVM Voting classifier

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：