Results 271 to 280 of about 6,303,262 (343)

Vanadium Doped Magnetic MoS2 Monolayers of Improved Electrical Conductivity as Spin‐Orbit Torque Layer

Advanced Functional Materials, EarlyView.
Electrically conductive and room temperature magnetic atomically thin (≈0.8 nm) vanadium doped MoS2 (V‐MoS2) is demonstrated for its spintronic applications. Here, the spin transport at the interface of permalloy (Py) and high spin‐orbit coupling V‐MoS2 magnetic monolayers is shown.
Krishna Rani Sahoo, Manoj Talluri, Dipak Maity, Suman Mundlia, Ashique Lal, M. S. Devapriya, Arabinda Haldar, Chandrasekhar Murapaka, Tharangattu N. Narayanan   +8 more
wiley   +1 more source

Advanced Nano‐Fibrillated Cellulose/Modified MXene Janus Membrane for Continuous 24‐h Water‐Power Co‐Generation

Advanced Functional Materials, EarlyView.
The Janus membrane integrates a superhydrophilic CNF@CTAB‐MXene layer with a superhydrophobic PTFE layer, enabling efficient solar‐driven water evaporation and electricity generation. It achieves an evaporation rate of 1.51 kg m−2 h−1 with excellent salt resistance and long‐term stability.
Yinan Li, Liulian Huang, Zhibin He, Jianguo Li, Chenglong Fu, Qinghong Zheng, Lihui Chen, Yonghao Ni   +7 more
wiley   +1 more source

Some of the next articles are maybe not open access.

Related searches:

GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification

IEEE Transactions on Knowledge and Data Engineering, 2020
Feature reduction is an important aspect of Big Data analytics on today’s ever-larger datasets. Rough sets are a classical method widely applied in attribute reduction.
Shuyin Xia, Zhao Zhang, Wenhua Li, Guoyin Wang, Elisabeth Giem, Zizhong Chen   +5 more
semanticscholar   +1 more source

Active Incremental Feature Selection Using a Fuzzy-Rough-Set-Based Information Entropy

IEEE transactions on fuzzy systems, 2020
Feature selection is a popular technique of preprocessing data. In order to deal with dynamic or large data, incremental feature selection has been developed, in which the features selected from existing data are integrated with those mined from both ...
Xiao Zhang, Changlin Mei, De-gang Chen, Yanyan Yang, Jinhai Li   +4 more
semanticscholar   +1 more source

Rough Set Theory [PDF]

ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems, 2017
This chapter discusses the basic preliminaries of rough set theory (RST). Since its inception, RST has been a prominent tool for data analysis due to its analysis friendly nature. RST provides a range of data structures, e.g. information systems, decision systems and approximations, to represent the real-world data.
S. Tsumoto, Hiroshi Tanaka
semanticscholar   +2 more sources

ROUGH FUZZY SETS AND FUZZY ROUGH SETS*

International Journal of General Systems, 1990
The notion of a rough set introduced by Pawlak has often been compared to that of a fuzzy set, sometimes with a view to prove that one is more general, or, more useful than the other. In this paper we argue that both notions aim to different purposes.
Dubois, Didier, Prade, Henri
openaire   +3 more sources

Selection of Rich Model Steganalysis Features Based on Decision Rough Set $\alpha$ -Positive Region Reduction

IEEE transactions on circuits and systems for video technology (Print), 2019
Steganography detection based on Rich Model features is a hot research direction in steganalysis. However, rich model features usually result a large computation cost.
Yuanyuan Ma, Xiangyang Luo, Xiaolong Li, Z. Bao, Yi Zhang   +4 more
semanticscholar   +1 more source

Intuitionistic Fuzzy Rough Set-Based Granular Structures and Attribute Subset Selection

IEEE transactions on fuzzy systems, 2019
Attribute subset selection is an important issue in data mining and information processing. However, most automatic methodologies consider only the relevance factor between samples while ignoring the diversity factor.
Anhui Tan, Weizhi Wu, Y. Qian, Jiye Liang, Jinkun Chen, Jinjin Li   +5 more
semanticscholar   +1 more source