Cyclic preparation of two-qubit state in two noisy environments

2022 ◽  
Vol 21 (1) ◽  
Author(s):  
Yi-Ru Sun ◽  
Xiu-Bo Chen ◽  
Jun Shao ◽  
Song Han ◽  
Haibo Hong ◽  
...  
Keyword(s):  
Qubit State ◽  
Noisy Environments

Joint Remote Preparation of an Arbitrary Two-Qubit State in Noisy Environments

2014 ◽  
Vol 53 (7) ◽  
pp. 2236-2245 ◽  
Author(s):  
Xiao-Wei Guan ◽  
Xiu-Bo Chen ◽  
Li-Chen Wang ◽  
Yi-Xian Yang
Keyword(s):  
Qubit State ◽  
Noisy Environments ◽  
Remote Preparation

SMART IDENTIFICATION OF POWER QUALITY EVENTS USING NEW STOCKWELL TRANSFORM AND MACHINE LEARNING ALGORITHM

2019 ◽  
Vol XVI (4) ◽  
pp. 95-113
Author(s):  
Muhammad Tariq ◽  
Tahir Mehmood
Keyword(s):  
Machine Learning ◽  
Power Quality ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Noisy Environments ◽  
Satisfactory Performance ◽  
Feature Values ◽  
Learning Machine ◽  
Stockwell Transform ◽  
Electrical Utilities

Accurate detection, classification and mitigation of power quality (PQ) distortive events are of utmost importance for electrical utilities and corporations. An integrated mechanism is proposed in this paper for the identification of PQ distortive events. The proposed features are extracted from the waveforms of the distortive events using modified form of Stockwell’s transform. The categories of the distortive events were determined based on these feature values by applying extreme learning machine as an intelligent classifier. The proposed methodology was tested under the influence of both the noisy and noiseless environments on a database of seven thousand five hundred simulated waveforms of distortive events which classify fifteen types of PQ events such as impulses, interruptions, sags and swells, notches, oscillatory transients, harmonics, and flickering as single stage events with their possible integrations. The results of the analysis indicated satisfactory performance of the proposed method in terms of accuracy in classifying the events in addition to its reduced sensitivity under various noisy environments.

An Asynchronous Anycast Cross-layer Protocol for WSN Suited to Noisy Environments

2021 ◽  
Author(s):  
Tales Heimfarth ◽  
João Carlos Giacomin ◽  
Bruno de Oliveira Schneider
Keyword(s):  
Cross Layer ◽  
Noisy Environments

Do primary school libraries affect teenagers’ attitudes towards leisure reading?

IFLA Journal ◽  
2021 ◽  
pp. 034003522098335
Author(s):  
Pamela McKirdy
Keyword(s):  
High School ◽  
Primary School ◽  
Family Background ◽  
School Libraries ◽  
First Year ◽  
Noisy Environments ◽  
Primary School Students ◽  
School Students ◽  
Leisure Reading ◽  
Reading For Pleasure

This study explores how New Zealand primary school students’ experiences of school libraries affected their attitudes towards reading for pleasure once they entered secondary school. Two hundred and seventy-six students in their first year at high school completed a survey asking about their primary school libraries. The students were asked to self-identify as keen readers, occasional readers or non-readers. The results were analysed in a spreadsheet, considering variables such as attitude to reading, former school and family background. The students were mainly positive about their libraries, but were bothered by cramped and noisy environments and books they perceived as babyish. Students from schools with a librarian were more positive about reading for fun than those from schools where the library was not prioritised. Students from a family background where reading was encouraged were more likely to maintain a positive attitude to reading by the time they reached high school.

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