Results 251 to 260 of about 592,656 (330)

Bio‐Inspired Magnetically Tunable Structural Colors from Elliptical Self‐Assembled Block Copolymer Microparticles

Advanced Functional Materials, EarlyView.
Cephalopod‐inspired photonic microparticles with dynamic structural coloration are fabricated via confined self‐assembly of linear block copolymers into ellipsoids containing stacked lamellae. Embedded superparamagnetic nanoparticles enable rapid magnetic alignment, restoring vivid, angle‐dependent color.
Gianluca Mazzotta, Simone Bertucci, Jose Mendoza‐Carreño, Agustín Mihi, Paola Lova, Davide Comoretto, Ullrich Steiner, Marco Lattuada, Andrea Dodero   +8 more
wiley   +1 more source

Nucleation‐Controlled Reconstruction of CuOx for Selective CO2 Electroreduction

Advanced Functional Materials, EarlyView.
The ratio of oxygen vacancies (Ov) and exposed Cu2O (111)/(200) of CuOx precatalyst is modulated by nucleation control of Cu(OH)2 precursor. Low Ov ratio and high ratio of Cu2O (111)/(200) in slow‐nucleated CuOx reconstructs to high‐coordinated oxide‐derived copper (OD‐Cu) during electrochemical CO2 reduction reaction (CO2RR) and exhibits enhanced ...
Ying Ying Ch'ng, Zhipeng Ma, Ming Zhang, Shujie Zhou, Varun Kundi, Priyank Vijaya Kumar, Wenyu Zhong, Yuwei Yang, Jitraporn Vongsvivut, Qinfen Gu, Xiaoxuan Luo, Lixue Jiang, Rahman Daiyan, Zhaojun Han, Rose Amal   +14 more
wiley   +1 more source

Dual‐Site Ru Single‐Atoms and RuP Nanoclusters on N, P, and B Co‐Doped Porous Carbon for Efficient Alkaline HER and AEM Water Electrolysis

Advanced Functional Materials, EarlyView.
Ru single atoms and RuP nanoclusters are co‐anchored in N, P, and B co‐doped porous carbon nanospheres via in situ carbonization/phosphidation of a boronate polymer precursor. RuP activates water, while nearby Ru single atoms accelerate H2 formation through H* transfer. The catalyst delivers low overpotential and high durability in alkaline HER and AEM
Xiaohong Wang, Juguo Dai, Dongxu Li, Jianghua Wu, Hucheng Fu, Yiting Xu, Xueqiang Qi, Qian Xue, Yanbin Shen, Xiaoqing Pan, Conghui Yuan, Shuifen Xie, Andreu Cabot, Lizong Dai   +13 more
wiley   +1 more source

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Forecasting of customer demands for production planning by local k-nearest neighbor models

, 2021
Demand forecasting is of major importance for manufacturing companies since it provides a basis for production planning. However, demand forecasting can be a difficult task because customer demands often fluctuate due to several influences.
M. Kück, M. Freitag
semanticscholar   +1 more source

A new locally adaptive k-nearest neighbor algorithm based on discrimination class

Knowledge-Based Systems, 2020
The k -nearest neighbor (kNN) rule is a classical non-parametric classification algorithm in pattern recognition, and has been widely used in many fields due to its simplicity, effectiveness and intuitiveness.
Z. Pan, Yikun Wang, Yiwei Pan
semanticscholar   +1 more source

Improved k-nearest neighbor classification

Pattern Recognition, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Yingquan, Ianakiev, Krassimir, Govindaraju, Venu   +2 more
openaire   +2 more sources

SVkNN: Efficient Secure and Verifiable k-Nearest Neighbor Query on the Cloud Platform*

IEEE International Conference on Data Engineering, 2020
With the boom in cloud computing, data outsourcing in location-based services is proliferating and has attracted increasing interest from research communities and commercial applications.
Ningning Cui, Xiaochun Yang, Bing Wang, Jianxin Li, Guoren Wang   +4 more
semanticscholar   +1 more source

Quantum K‐Nearest Neighbor Classification Algorithm via a Divide‐and‐Conquer Strategy

Advanced Quantum Technologies
The K‐nearest neighbor algorithm is one of the most frequently applied supervised machine learning algorithms. Similarity computing is considered to be the most crucial and time‐consuming step among the classical K‐nearest neighbor algorithm. A quantum K‐
Li‐Hua Gong, W. Ding, Zi-Ming Li, Yuan‐Zhi Wang, Nan-Run Zhou   +4 more
semanticscholar   +1 more source

A generalized mean distance-based k-nearest neighbor classifier

Expert systems with applications, 2019
K-nearest neighbor (KNN) rule is a well-known non-parametric classifier that is widely used in pattern recognition. However, the sensitivity of the neighborhood size k always seriously degrades the KNN-based classification performance, especially in the ...
Jianping Gou, Hongxing Ma, Weihua Ou, Shaoning Zeng, Yunbo Rao, Hebiao Yang   +5 more
semanticscholar   +1 more source