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: Integrative Biological Control; Ecostacking for Enha Yulin Gao,Heikki M. T. Hokkanen,Ingeborg Menzler-H Book 2020 Springer Nature Switzerla

[复制链接]
楼主: 联系
发表于 2025-3-25 05:16:17 | 显示全部楼层
发表于 2025-3-25 09:55:11 | 显示全部楼层
ewable energies) are analysed for assessment and quantification where data is available. The carbon footprint calculator includes the derived and influential activities that should be included in the application for the approval of urban planning instruments, within the ordinary or simplified strate
发表于 2025-3-25 14:33:57 | 显示全部楼层
发表于 2025-3-25 19:45:33 | 显示全部楼层
Adam Flöhr,Johan A. Stenberg,Paul A. Eganarine-sonar-monitoring levels of vigilance, as said by Jon Kabot-Zinn (1990, p. 23), “it would be incorrect to think of meditation as a passive process; it takes a good deal of energy and effort to regulate your attention and to remain genuinely calm and nonreactive.”
发表于 2025-3-25 21:52:16 | 显示全部楼层
发表于 2025-3-26 03:03:34 | 显示全部楼层
发表于 2025-3-26 08:10:26 | 显示全部楼层
发表于 2025-3-26 10:59:32 | 显示全部楼层
Pingyang Zhu,Zhongxian Lu,Guihua Chen,K. L. Heongsuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. .What You Will Learn.Build
发表于 2025-3-26 14:05:19 | 显示全部楼层
Chengyun Li,Jing Yang,Xiahong He,Shusheng Zhu,Youyong Zhusuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. .What You Will Learn.Build
发表于 2025-3-26 19:32:20 | 显示全部楼层
Ouyang Fang,Men XingYuan,Ge Fengsuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. .What You Will Learn.Build
 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 SITEMAP 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.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-8 08:16
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