找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Cyber Warfare, Security and Space Computing; Second International Sandeep Joshi,Amit Kumar Bairwa,Anton Pljonkin Conference proceedings 202

[复制链接]
楼主: Jurisdiction
发表于 2025-3-26 23:47:32 | 显示全部楼层
发表于 2025-3-27 02:01:02 | 显示全部楼层
发表于 2025-3-27 08:34:19 | 显示全部楼层
Secure Data Management Using BlockChain,rading their understanding of the capabilities and imperatives of blockchain-related information administration frameworks. It moreover advocates for the advancement of combination frameworks custom fitted to a differing cluster of viable needs.
发表于 2025-3-27 12:41:11 | 显示全部楼层
发表于 2025-3-27 16:07:46 | 显示全部楼层
An Empirical Analysis of Neighborhood-Based Approaches for Trustworthy Recommendations with Apache F methods as implemented in the Mahout. Finally, the accuracy of UBCF methods is measured in terms of two metrics: Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Empirically obtained results demonstrate that an RS can provide trustworthy recommendations to its end users by increasing
发表于 2025-3-27 19:47:20 | 显示全部楼层
Multilingual Sentiment Analysis over Real-Time Voice, of this paper include developing a flexible system that can accommodate multiple languages – namely – English, Hindi and Telugu. Additionally, it seeks to offer real-time sentiment feedback, which is a useful function in several fields, such as social media monitoring, voice assistant technologies,
发表于 2025-3-27 23:18:13 | 显示全部楼层
Identity Verification: A Decentralized KYC Approach Using Blockchain,the AES encryption algorithm, and the hash of the encrypted data is provided to the user and stored on the blockchain. This decentralized and secure KYC system minimizes redundancy, enhances user control, and fortifies data security.
发表于 2025-3-28 05:09:13 | 显示全部楼层
S-Defender: A Smishing Detection Approach in Mobile Environment, content and employs a Naive Bayesian classifier to categorize the message as either smishing or ham. Additionally, our approach normalizes and converts Lingo language text messages into their standard form to improve classification accuracy. The model’s validation, conducted using the English SMS dataset, resulted in an overall accuracy of 94.72%.
发表于 2025-3-28 08:54:47 | 显示全部楼层
发表于 2025-3-28 14:26:49 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 吾爱论文网 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
QQ|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-8-25 10:26
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表