scholarly journals Error Analysis of NOMA-Based VLC Systems With Higher Order Modulation Schemes

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 2792-2803
Author(s):  
Esam M. Almohimmah ◽  
Mohammed T. Alresheedi
Keyword(s):  
Error Analysis ◽  
Higher Order ◽  
Modulation Schemes

Time-discrete higher order ALE formulations: a priori error analysis

2013 ◽  
Vol 125 (2) ◽  
pp. 225-257 ◽  
Author(s):  
Andrea Bonito ◽  
Irene Kyza ◽  
Ricardo H. Nochetto
Keyword(s):  
Error Analysis ◽  
A Priori ◽  
Higher Order ◽  
A Priori Error Analysis

Higher order two-scale finite element error analysis for thermoelastic problem in quasi-periodic perforated structure

2017 ◽  
Vol 28 (07) ◽  
pp. 1750097
Author(s):  
Mingxiang Deng ◽  
Yongping Feng
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Error Analysis ◽  
Thermal Behavior ◽  
Higher Order ◽  
Numerical Results ◽  
Thermoelastic Problem ◽  
Asymptotic Expressions ◽  
Element Error ◽  
Element Method

In this paper, one new coupled higher order two-scale finite element method (TSFEM) for thermoelastic problem in composites is proposed. Firstly, some new two-scale asymptotic expressions and homogenization formulations for the problem are briefly given. Next, some high–low coupled approximate errors corresponding to TSFEM are analyzed. Finally, some numerical results of the displacement and the increment of temperature are presented, which show that TSFEM is an effective method for predicting the mechanical and the thermal behavior of composites in quasi-periodic perforated structure.

scholarly journals Higher-order thinking skills based on Marzano taxonomy in basic biology I course

2019 ◽  
Vol 5 (3) ◽  
Author(s):  
Metri Dian Insani ◽  
Novida Pratiwi ◽  
M. Muhardjito
Keyword(s):  
Decision Making ◽  
Error Analysis ◽  
Deductive Reasoning ◽  
Inductive Reasoning ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Optimal Level ◽  
Higher Order ◽  
Moderate Level ◽  
Higher Order Thinking Skills

This research was aimed at profiling student’s thinking skills in dealing with Higher-Order Thinking Skills (HOTS) questions based on Marzano taxonomy by referring to 13 indicators. This pre-experimental research employed pretest-posttest design. The indicators included were comparison, classification, deductive reasoning, inductive reasoning, error analysis, construction, analysis perspective, abstraction, decision making, investigation, problem solving, inquiry experiment, and innovation finding. The instrument used was a 13-essay question (r-Pearson= 0.79 and Cronbach alpha = 0.68). The data gained from 98 students of Natural Science Education was then analyzed using paired t-test. The results showed the significant different between pre-test and posttest (sig. <0.01). As many as four HOTS indicators (i.e. deductive reasoning, error analysis, construction, and abstraction) were categorized as low level. Meanwhile, the eighth HOTS indicators were categorized as moderate level, namely: comparison, inductive reasoning, analysis perspective, decision making, investigation, solving problem, inquiry experiment, and innovative finding. In addition, the classification indicator was considered in high level in the end of the course. It can be concluded that, in general, students’ HOTS are still in moderate level. Thus, the proper strategies should be designed to improve this condition into the optimal level.

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