找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Disruptive Technologies for Big Data and Cloud Applications; Proceedings of ICBDC J. Dinesh Peter,Steven Lawrence Fernandes,Amir H. Confer

[復制鏈接]
查看: 8609|回復: 62
樓主
發(fā)表于 2025-3-21 19:11:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Disruptive Technologies for Big Data and Cloud Applications
副標題Proceedings of ICBDC
編輯J. Dinesh Peter,Steven Lawrence Fernandes,Amir H.
視頻videohttp://file.papertrans.cn/282/281602/281602.mp4
概述Gathers peer-reviewed proceedings of the International Conference on Big Data and Cloud Computing.Presents not only state of the art in cloud computing technologies and big data.Provides recent innova
叢書名稱Lecture Notes in Electrical Engineering
圖書封面Titlebook: Disruptive Technologies for Big Data and Cloud Applications; Proceedings of ICBDC J. Dinesh Peter,Steven Lawrence Fernandes,Amir H.  Confer
描述.This book provides a written record of the synergy that already exists among the research communities and represents a solid framework in the advancement of big data and cloud computing disciplines from which new interaction will result in the future. This book is a compendium of the International Conference on Big Data and Cloud Computing (ICBDCC 2021). It includes recent advances in big data analytics, cloud computing, the Internet of nano things, cloud security, data analytics in the cloud, smart cities and grids, etc. This book primarily focuses on the application of knowledge that promotes ideas for solving the problems of society through cutting-edge technologies. The articles featured in this book provide novel ideas that contribute to the growth of world-class research and development. The contents of this book are of interest to researchers and professionals alike..
出版日期Conference proceedings 2022
關(guān)鍵詞Big Data; Data Analytics; Cloud Infrastructure for Big Data; Resource Scheduling; Data Models; Machine Le
版次1
doihttps://doi.org/10.1007/978-981-19-2177-3
isbn_ebook978-981-19-2177-3Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Disruptive Technologies for Big Data and Cloud Applications影響因子(影響力)




書目名稱Disruptive Technologies for Big Data and Cloud Applications影響因子(影響力)學科排名




書目名稱Disruptive Technologies for Big Data and Cloud Applications網(wǎng)絡公開度




書目名稱Disruptive Technologies for Big Data and Cloud Applications網(wǎng)絡公開度學科排名




書目名稱Disruptive Technologies for Big Data and Cloud Applications被引頻次




書目名稱Disruptive Technologies for Big Data and Cloud Applications被引頻次學科排名




書目名稱Disruptive Technologies for Big Data and Cloud Applications年度引用




書目名稱Disruptive Technologies for Big Data and Cloud Applications年度引用學科排名




書目名稱Disruptive Technologies for Big Data and Cloud Applications讀者反饋




書目名稱Disruptive Technologies for Big Data and Cloud Applications讀者反饋學科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:17:13 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:53:04 | 只看該作者
1876-1100 d computing technologies and big data.Provides recent innova.This book provides a written record of the synergy that already exists among the research communities and represents a solid framework in the advancement of big data and cloud computing disciplines from which new interaction will result in
地板
發(fā)表于 2025-3-22 08:03:40 | 只看該作者
5#
發(fā)表于 2025-3-22 08:55:47 | 只看該作者
6#
發(fā)表于 2025-3-22 12:59:55 | 只看該作者
7#
發(fā)表于 2025-3-22 20:53:07 | 只看該作者
8#
發(fā)表于 2025-3-22 23:21:14 | 只看該作者
A Statistical Performance Analysis of GPU WAH Range Querying,raphical processing units (GPUs) can process bitmap index queries more efficiently than CPUs in many instances. This paper presents a statistical performance analysis of a GPU bitmap query engine applied to range queries. The results of this analysis provide insights for future GPU query engine design.
9#
發(fā)表于 2025-3-23 01:58:47 | 只看該作者
10#
發(fā)表于 2025-3-23 06:51:18 | 只看該作者
The Instrumental Method in Psychologyrning is that these models can create features without a?human intervention. The performance of five different models for forest fire classification is analyzed in this paper: VGG-16, ResNet-50-V2, MobileNet-V2, Inception-V2, and Xception. MobileNet-V2 performed the best among all the architectures with an accuracy of 96.84% on the dataset.
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-12 19:01
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復 返回頂部 返回列表
东辽县| 阿尔山市| 徐水县| 平泉县| 呼伦贝尔市| 延边| 江城| 永新县| 哈尔滨市| 锦屏县| 新绛县| 松阳县| 南城县| 封丘县| 铜梁县| 永顺县| 嘉义县| 花莲县| 大同县| 峨山| 社旗县| 永泰县| 绥中县| 崇义县| 河北区| 襄樊市| 阜新市| 永仁县| 沭阳县| 腾冲县| 扬州市| 天峻县| 汉中市| 孝昌县| 井研县| 扎囊县| 辉南县| 兖州市| 铜川市| 澜沧| 临夏县|