检索结果-内蒙古大学图书馆

Asynchronous I/O Persistence for In-Memory Database Servers: Leveraging io_uring to Optimize Redis Persistence 17th

Asynchronous I/O Persistence for In-Memory Database Servers:...

17th International Conference on Cloud Computing, CLOUD 2024, Held as Part of the Services Conference Federation, SCF 2024

作者： Chen, Le-Gao Li, Yanzhi Laohakangvalvit, Tipporn Sugaya, Midori Innovative Global Program College of Engineering Shibaura Institute of Technology Tokyo Koto City Japan Department of Computer Science and Engineering College of Engineering Shibaura Institute of Technology Tokyo Koto City Japan

ISBN: (纸本)9783031771521

With constant hardware improvements allowing for increasingly large memory sizes, in-memory database servers have become an attractive option for various cloud applications. Even though in-memory database servers store all data in memory, there is still a need to persist data onto an I/O device for maintenance, updates, or protection against server crashes. In high throughput environments, persistence happens often, significantly hindering server throughput performance. Although popular in-memory database servers such as Redis or Dragonfly DB have adopted asynchronous I/O for socket operations, none have extended this approach for persistence. This results in significantly longer time taken for persistence, leading to prolonged reduced throughput. Given the recent introduction of io_uring, which has demonstrated significant performance improvements over past asynchronous I/O APIs, we have decided to implement it into Redis to evaluate its effectiveness in reducing these performance overheads. Our findings indicate that io_uring can significantly enhance performance in use cases with medium to large payload sizes but may hinder performances in use cases involving small payload sizes due to higher complexity and higher operation cost per datapoint. This method can likely be applied to other servers, such as Dragonfly DB and Memcached, to achieve similar benefits in appropriate scenarios. Additionally, in-memory database server persistence can serve as valuable benchmarks for further io_uring development and optimization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A Novel Flow Priority and Continuity Control Mechanism in SDN Network 1

A Novel Flow Priority and Continuity Control Mechanism in SD...

引用

1st International Conference on Innovative engineering sciences and Technological Research, ICIESTR 2024

作者： Yaseen, Fouad A. Alkhalidi, Nahlah Abdulrahman Al Wahaibi, Fawziya Nasser University of Baghdad College of Engineering Electronic and Communications Dept Iraq University of Baghdad College of Science Computer Science Dept. Iraq University of Technology and Applied Science College of Engineering Elecrical and Electronics Dept Oman

ISBN: (纸本)9798350348637

In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate precedence level for the data traffic flow. The control and modification of the DSCP bits directly impact the priority assigned to data packets, thereby shaping the traffic flow continuity accordingly. The evaluation and performance analysis of the proposed network were conducted using the Mininet simulator and the MATLAB platform. The outcomes of the comprehensive testing demonstrate that the implementation of our novel priority management technique has successfully reduced queuing delay and minimized packet loss. As a result, the overall data traffic continuity has been significantly enhanced. The obtained results demonstrate that the traffic flow continuity, handled by the Software-Defined Networking (SDN) controller with the support of DSCP modification, has increased by approximately 65% when implementing the proposed priority management based on DSCP bits modification in the SDN network. © 2024 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Ethical Framework for Multimodal AI Systems 1

Ethical Framework for Multimodal AI Systems

引用

1st International Conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Patkar, Uday Chandrakant Pitrubhakta, Vinit Sutar, Sanket Arora, Aria Jaiswal, Ritika Bhardwaj, Shikha Patil, Uday Shankar Bharati Vidyapeeth's College of Engineering Lavale Computer Department Pune India Bharati Vidyapeeth's College of Engineering Lavale Pune India Bharati Vidyapeeth's College of Engineering Lavale Department of Engineering science Pune India Bharati Vidyapeeth's College of Engineering Lavale Head of civil Engineering Department Pune India

ISBN: (纸本)9798350355611

As artificial intelligence (AI) systems converge on data from different modalities such as text, audio and images, this leads to a very unique ethical challenge. This research paper provides a theoretical framework to address the ethical implications of multimodal AI system. This paper focuses on three domains: privacy, fairness and consent. This paper reflects on various ways to protect sensitive data, mitigate biases across different modalities and ensure consent and transparency. These are accompanied by guidelines which are provided to support the best practices of responsible design and deployment of these systems. The aim of this paper is to help engineers develop multimodal AI technologies that are ethically sound and socially beneficial. © 2025 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Addressing Imbalance in Health Datasets: A New Method NR-Clustering SMOTE and Distance Metric Modification

引用

computers, Materials & Continua 2025年第2期82卷 2931-2949页

作者： Hairani Hairani Triyanna Widiyaningtyas Didik Dwi Prasetya Afrig Aminuddin Department of Electrical Engineering and Informatics Faculty of EngineeringUniversitas Negeri MalangMalang65145Indonesia Department of Computer Science Universitas BumigoraMataram83127Indonesia Department of Computer Graphic and Multimedia Faculty of ComputingCollege of Computing and Applied SciencesUniversiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared t

关键词： SMOTE modification Clustering-SMOTE manhattan distance

来源：评论

学校读者我要写书评

暂无评论

Blockchain for Patient-Centric Solutions Using Distributed Ledger Technology 2

Blockchain for Patient-Centric Solutions Using Distributed L...

引用

2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Sandhya, G. Vaishnavi, T. Subashree, M. Naveen Kumar, A. Sri Krishna College of Technology Computer Science and Engineering Tamil Nadu India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505745

Blockchain technology, with its decentralized and tamper-resistant nature, has the potential to revolutionize healthcare by improving data security, reliability, and interoperability. By leveraging encryption methods such as Attribute-Based Encryption (ABE), patient records can be securely stored and protected from unauthorized modifications or breaches. Additionally, the integration of smart contracts and standardized data formats enables seamless communication across diverse healthcare systems, fostering a more connected and efficient ecosystem. This patient-focused model enhances data privacy while granting individuals greater control over their medical information. However, the adoption of blockchain in healthcare encounters several challenges, including regulatory hurdles, scalability issues, implementation costs, and acceptance by users. Moreover, integrating blockchain with existing infrastructures and ensuring cooperation among stakeholders adds further complexity. Despite these obstacles, research underscores blockchain's potential to redefine healthcare data management. Addressing these challenges can pave the way for a more secure, interoperable, and patientdriven healthcare system in the future. © 2025 IEEE.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Evaluating Self-Supervised Learning Models for Multi-Label Pathology Detection: A Benchmark Against Supervised Learning 2

Evaluating Self-Supervised Learning Models for Multi-Label P...

引用

2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Agarwal, Nidhi Pooja Kumar, Nitish Anushka Garg, Yashica Department of Computer Science Engineering Galgotias University Greater Noida India School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of Information Technology Bharati Vidyapeeth College of Engineering New Delhi India Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for Women New Delhi India

ISBN: (纸本)9798331530389

The analysis and objective of the current work is to check the performance of SSL Models in multi-label classification on the available dataset of NIH Chest X-ray images which is a large-scale medical imaging dataset. The performance of SSL models, Dino_v_bl6, Dino with ResNet-50, and MoCo (Momentum Contrast) has been evaluated against the supervised model ResNet. These models are supposed to train to detect multiple pathologies using chest X-ray images. We also note that self-supervised embedding models outperform traditional supervised learning to a significant extent, achieving similar or higher performance on a number of quantitative metrics when compared to the softmax supervised ResNet model. This also draws attention to the possibilities of using SSL for biosignal-specific medical images. Furthermore, SSL approaches offer a promising solution in scenarios where there is an overabundance of annotated datasets available for training models such as deep neural networks. The effectiveness of SSL approaches in addressing the problem of data annotation is also emphasized by this study. © 2025 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Online Sales Prediction in E-Commerce Market Using Machine Learning 4

Online Sales Prediction in E-Commerce Market Using Machine L...

引用

4th International Conference on Signal Processing and Communication, ICSPC 2023

作者： Ajaykrishna, S. Suganya, T.S. Rao, Beema Pughazendi, N. Computer Science and Engineering Panimalar Engineering College India Srm Institute of Science and Technology Ramapuram Campus India

ISBN: (纸本)9798350300772

Product sales anticipation assumes a key part in upgrading idealness of item conveyance in E-Commerce. Among numerous heterogeneous provisions pertinent to sales estimating, advancement crusades held in E-Commerce and contending connection amid substitutable items would significantly muddle the substance. Unlikely, these variables are typically neglected in the current research;since the regular time-series investigation-based procedures principally believe the business records unaided. In this article, we make use of the previous data in online trade market to build up the framework to anticipate sales. As stated by the qualities of diverse data, 3-sorts of expectation techniques are: Incentive-Auto-Regressive-Integrated-Moving-Average (I-ARIMA), Long-Short-Term-Memory (LSTM) and Artificial-Neural-Network (ANN). These 3-techniques can handle the concern with diverse exactness necessities and various data types. Broad investigations are led more than two genuine datasets in diverse areas from E-Commerce. Outcomes reveal that the LSTM gets munificent implementation attain over others and modern intense learning choices as far as anticipating precision. This research considers the benefits and inconveniences of the three kinds of strategies on diverse informational repositories and gives considerable rules to traders on their advertising methodologies. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

LeNet with Bidirectional Long Short-Term Memory for Signal Detection in Underwater Optical Communication 1

LeNet with Bidirectional Long Short-Term Memory for Signal D...

引用

1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Subhashini, S. Al-Farouni, Mohammed Kumar, B. Satish Sharmiladevi, D. Anita Sofia Liz, D.R. B S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science and Engineering Chennai India The Islamic University Department of Computers Techniques Engineering College of Technical Engineering Najaf Iraq Maisammaguda Department of Electronics and Communication Engineering Hyderabad India Sona College of Technology Department of Electronics and Communication Engineering Salem India New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350352931

Underwater optical signal detection performance suffers from occlusion and turbidity in degraded environments. Due to complex underwater environment the high directionality of light beam and vibration transceiver incident optical power usually spans a very wide dynamic range. This paper, proposed LeNet with Bidirectional Long Short-Term Memory (BiLSTM) technique performed efficiently in the signal detection in under water optical communication by effectively extracting spatial features and capturing temporal dependencies. The data collected for this research includes data bits of 72 vectors of transmitted signals through the Gulf seawater. The LeNet approach process the received optical communication signals and extract spatial features from convolutional layer, converting them into relevant signal to enhance the communication of underwater. The combination of LeNet feature extraction capabilities and Bi-LSTM sequential learning the signal then enhances the model ability leading to achieve better performance in signal detection. The performance of proposed method is evaluated with various metrics such as accuracy, precision, recall, f1-score and Bit Error Rate (BER) metrics based on sea water. © 2024 IEEE.

关键词： Error statistics

来源：评论

学校读者我要写书评

暂无评论

User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

引用

computer Systems science & engineering 2022年第8期42卷 605-618页

作者： S.Godfrey Winster A.Siva Kumar R.Ramesh Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyChengalpattu603203India Department of Information Technology Sri Sai Ram Engineering CollegeChennai600044India Department of Electronics and Communication Engineering Saveetha Engineering CollegeChennai602105India

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient *** advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any *** to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient *** improve the performance in data security,the block chains are used for securing the data in the cloud ***,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the *** this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud *** proposed approach performs data transaction by employing the block *** proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud *** proposed protocol is implemented in real time using Java programming language and uses IBM *** implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.

关键词： Cloud blockchain data security ABE block-level

来源：评论

学校读者我要写书评

暂无评论

Back propagation artificial neural network for diagnose of the heart disease

引用

Journal of Reliable Intelligent Environments 2023年第1期9卷 57-85页

作者： Kaur, Jagmohan Khehra, Baljit S. Singh, Amarinder IKG Punjab Technical University Punjab Jalandhar144103 India Computer Science and Engineering BBSB Engineering College Punjab Fatehgarh Sahib140407 India Department of Applied Sciences BBSB Engineering College Punjab Fatehgarh Sahib140407 India

Nowadays, coronary heart disease is one of the most fatal disease globally. Many researchers and medical technicians have developed and designed various computer-aided diagnosis systems using various machine learning models such as random forest, linear regression, rough set, naive bayes, artificial neural network, support vector machine, multivariate adaptive regression splines, K-nearest neighbor and decision tree to name a few. This era of digital health domain demands early prediction of heart disease which is the crucial need to control the global mortality rate of this particular disease. Commonly used methods for heart disease detection are clinical and expert dependant which makes them costly and inaccessible to the masses. In this paper, an efficient-cum-automated coronary heart disease diagnosis model is being proposed using multi-layered artificial neural network with back propagation algorithm. The proposed model compares the variation caused by different number of neurons used in the hidden layers for different transfer functions. The model has been implemented on Kaggle and Statlog heart disease dataset with thirteen clinical parameters. The experimental results attained an accuracy of 99.92% using six hidden layers with tan-hyperbolic transfer function. The results have been substantiated through statistical parameters and k-fold cross validation. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Nearest neighbor search

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：