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Effect of Ti4+ and Sn4+ co-incorporation on the catalytic performance of CeO2 -MnOx catalyst for low temperature NH3-SCR 期刊论文
APPLIED SURFACE SCIENCE, 2019, 卷号: 476, 页码: 283-292
作者:  Chen, Li;  Yao, Xiaojiang;  Cao, Jun;  Yang, Fumo;  Tang, Changjin;  Dong, Lin
Adobe PDF(4668Kb)  |  收藏  |  浏览/下载：269/0  |  提交时间：2019/03/25
CeO2-MnOx-TiO2-SnO2 catalyst  Ti4+ and Sn4+ co-incorporation  Low-temperature NH3-SCR  Catalytic performance  By-product N2O  
Autonomic decentralized elasticity based on a reinforcement learning controller for cloud applications 期刊论文
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 卷号: 94, 页码: 765-780
作者:  Nouri, Seyed Mohammad Reza;  Li, Han;  Venugopal, Srikumar;  Guo, Wenxia;  He, MingYun;  Tian, Wenhong
Adobe PDF(2063Kb)  |  收藏  |  浏览/下载：148/0  |  提交时间：2019/04/18
Cloud computing  Autonomic decentralized elasticity  Reinforcement learning  Resource provisioning  Cloud applications  
Characteristics of single atmospheric particles in a heavily polluted urban area of China: size distributions and mixing states 期刊论文
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2019, 卷号: 26, 期号: 12, 页码: 11730-11742
作者:  Li, Li;  Wang, Qiyuan;  Zhang, Xu;  She, Yuanyuan;  Zhou, Jiamao;  Chen, Yang;  Wang, Ping;  Liu, Suixin;  Zhang, Ting;  Dai, Wenting;  Han, Yongming;  Cao, Junji
Adobe PDF(671Kb)  |  收藏  |  浏览/下载：252/0  |  提交时间：2019/06/24
Single particle  Chemical composition  Size distribution  Mixing state  SPAMS  Biomass burning  
A comprehensive review on current status, mechanism, and possible sources of arsenic contamination in groundwater: a global perspective with prominence of Pakistan scenario 期刊论文
ENVIRONMENTAL GEOCHEMISTRY AND HEALTH, 2019, 卷号: 41, 期号: 2, 页码: 737-760
作者:  Ali, Watiar;  Rasool, Atta;  Junaid, Muhammad;  Zhang, Hua
Adobe PDF(1650Kb)  |  收藏  |  浏览/下载：215/0  |  提交时间：2019/06/24
Arsenic  Groundwater  Sources  Mechanisms  Isotope evidence  Comparison  Health effects  
Characterization of urban amine-containing particles in southwestern China: seasonal variation, source, and processing 期刊论文
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2019, 卷号: 19, 期号: 5, 页码: 3245-3255
作者:  Chen, Yang;  Tian, Mi;  Huang, Ru-Jin;  Shi, Guangming;  Wang, Huanbo;  Peng, Chao;  Cao, Junji;  Wang, Qiyuan;  Zhang, Shumin;  Guo, Dongmei;  Zhang, Leiming;  Yang, Fumo
Adobe PDF(3672Kb)  |  收藏  |  浏览/下载：221/0  |  提交时间：2019/04/18
A multi-key SMC protocol and multi-key FHE based on some-are-errorless LWE 期刊论文
SOFT COMPUTING, 2019, 卷号: 23, 期号: 5, 页码: 1735-1744
作者:  Wang, Huiyong;  Feng, Yong;  Ding, Yong;  Tang, Shijie
Adobe PDF(545Kb)  |  收藏  |  浏览/下载：154/0  |  提交时间：2019/03/25
LWE  FHE  Key homomorphism  SMC  
Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product 期刊论文
RENEWABLE ENERGY, 2019, 卷号: 132, 页码: 221-232
作者:  Chen, Ji-Long;  He, Lei;  Chen, Qiao;  Lv, Ming-Quan;  Zhu, Hong-Lin;  Wen, Zhao-Fei;  Wu, Sheng-Jun
Adobe PDF(900Kb)  |  收藏  |  浏览/下载：404/0  |  提交时间：2018/12/13
Diffuse radiation  Direct beam radiation  Models  MODIS  
Elastic-net regularized latent factor analysis-based models for recommender systems 期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 66-74
作者:  Wang, Dexian;  Chen, Yanbin;  Guo, Junxiao;  Shi, Xiaoyu;  He, Chunlin;  Luo, Xin;  Yuan, Huaqiang
Adobe PDF(1965Kb)  |  收藏  |  浏览/下载：213/0  |  提交时间：2019/01/17
Big data  Recommender systems  Collaborative filtering  Latent factor analysis  Elastic-net  Regularization  Latent factor distribution  
Joint Operator Scaling and Placement for Distributed Stream Processing Applications in Edge Computing 会议论文
17th International Conference on Service-Oriented Computing, ICSOC 2019, Toulouse, France, October 28, 2019 - October 31, 2019
作者:  Peng, Qinglan;  Xia, Yunni;  Wang, Yan;  Wu, Chunrong;  Luo, Xin;  Lee, Jia
收藏  |  浏览/下载：173/0  |  提交时间：2020/02/18
DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 60186-60198
作者:  Wang, Qingxian;  Peng, Binbin;  Shi, Xiaoyu;  Shang, Tianqi;  Shang, Mingsheng
Adobe PDF(4751Kb)  |  收藏  |  浏览/下载：144/0  |  提交时间：2019/06/24
Recommender systems  collaborative filtering  rating prediction  denoising autoencoders  multi layered perceptron