Application of second and higher order subspace tracking in multichannel data analysis

2013 ◽  
Author(s):  
Marzieh Fatemi ◽  
Reza Sameni
Keyword(s):  
Data Analysis ◽  
Higher Order ◽  
Subspace Tracking ◽  
Multichannel Data

READING EXERCISES FOR VIII GRADE STUDENTS BASED ON BLOOM’S TAXONOMY

2017 ◽  
Vol 6 (3) ◽  
Author(s):  
Intan Permata Sari And Indra Hartoyo
Keyword(s):  
Data Analysis ◽  
Lower Order ◽  
Bloom's Taxonomy ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Higher Order ◽  
Critical Thinking Skills ◽  
Thinking Skill ◽  
Level Of Education ◽  
Bloom’S Taxonomy

This study is aimed at (1) analyzing reading exercises based Bloom’s taxonomy for VIII grade in English on Sky textbook. (2) Found the distribution of the lower and higher order thinking skill in reading exercises. (3) To reason for level reading exercises. After analyzed the data, the result of the data analysis also infers that the six levels of Bloom’s taxonomy in reading exercises weren’t applied totally. The creating skill doesn’t have distribution in reading exercise, and the understanding – remembering level more dominant than another levels. The distribution of the higher order thinking level was lower than the lower order thinking level and the six levels are not appropriate with the proportion for each level of education based Bloom’s taxonomy, such as the distribution of the creating level in the reading exercise must be a concern because no question that belong to the creating level. It was concluded that reading exercises in English on Sky textbook cannot improve students' critical thinking skills for VIII grade.

scholarly journals Development of worksheet based on high-order thinking skills to improve high-order thinking skills of the students

2018 ◽  
Vol 2 (1) ◽  
pp. 37
Author(s):  
Yennita Yennita ◽  
Isra Khasyyatillah ◽  
Gibran Gibran ◽  
Mitri Irianti
Keyword(s):  
Data Analysis ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Higher Order ◽  
High Order ◽  
Average Score ◽  
Thinking Skill ◽  
Ability Test ◽  
Higher Level Thinking ◽  
High Order Thinking

This research aimed to develop high order thinking skills  workheet in momentum, impulse, and collision topic for senior high school This type of research is Research and Development  follow 4D models, includes : define, design, develop and disseminate. Data collection instruments used validation sheets for given to 5 validator, Aspects assessed include graphic, presentation, language, and the contents of workheet. Based on the result of data analysis showed that all aspects got average score in the range of 3.4 to 4 with categories of  very high. Thus, high order thinking skills was valid. For the purposes of testing the worksheet is given on 68 students. to measure the effectiveness of worksheet used  Higher Level Thinking Ability Test that amounts to 12 items. Based on the result of data analysis indicate, There is difference of higher order thinking skill of students who use HOTS worksheet than who are not use HOTS worksheet, where the average Higher Order Thinking Skill on students who use HOTS worksheet higher

SAS Nonlinear Models or Artificial Higher Order Neural Network Nonlinear Models?

2021 ◽  
pp. 174-217
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Data Analysis ◽  
Learning Algorithm ◽  
Nonlinear Models ◽  
Higher Order ◽  
Model Order ◽  
Higher Order Neural Networks ◽  
Parameter Values ◽  
Better Than

This chapter delivers general format of higher order neural networks (HONNs) for nonlinear data analysis and six different HONN models. Then, this chapter mathematically proves that HONN models could converge and have mean squared errors close to zero. Moreover, this chapter illustrates the learning algorithm with update formulas. HONN models are compared with SAS nonlinear (NLIN) models, and results show that HONN models are 3 to 12% better than SAS nonlinear models. Finally, this chapter shows how to use HONN models to find the best model, order, and coefficients without writing the regression expression, declaring parameter names, and supplying initial parameter values.

Joint decorrelation, a versatile tool for multichannel data analysis

NeuroImage ◽  
2014 ◽  
Vol 98 ◽  
pp. 487-505 ◽  
Author(s):  
Alain de Cheveigné ◽  
Lucas C. Parra
Keyword(s):  
Data Analysis ◽  
Multichannel Data ◽  
Versatile Tool

scholarly journals Topological Information Data Analysis

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 869 ◽  
Author(s):  
Pierre Baudot ◽  
Monica Tapia ◽  
Daniel Bennequin ◽  
Jean-Marc Goaillard
Keyword(s):  
Data Analysis ◽  
Statistical Tests ◽  
Biological Systems ◽  
Higher Order ◽  
Information Storage ◽  
Structure Characteristic ◽  
Order Structure ◽  
Data Set ◽  
Topological Information ◽  
Statistical Interactions

This paper presents methods that quantify the structure of statistical interactions within a given data set, and were applied in a previous article. It establishes new results on the k-multivariate mutual-information ( I k ) inspired by the topological formulation of Information introduced in a serie of studies. In particular, we show that the vanishing of all I k for 2 ≤ k ≤ n of n random variables is equivalent to their statistical independence. Pursuing the work of Hu Kuo Ting and Te Sun Han, we show that information functions provide co-ordinates for binary variables, and that they are analytically independent from the probability simplex for any set of finite variables. The maximal positive I k identifies the variables that co-vary the most in the population, whereas the minimal negative I k identifies synergistic clusters and the variables that differentiate–segregate the most in the population. Finite data size effects and estimation biases severely constrain the effective computation of the information topology on data, and we provide simple statistical tests for the undersampling bias and the k-dependences. We give an example of application of these methods to genetic expression and unsupervised cell-type classification. The methods unravel biologically relevant subtypes, with a sample size of 41 genes and with few errors. It establishes generic basic methods to quantify the epigenetic information storage and a unified epigenetic unsupervised learning formalism. We propose that higher-order statistical interactions and non-identically distributed variables are constitutive characteristics of biological systems that should be estimated in order to unravel their significant statistical structure and diversity. The topological information data analysis presented here allows for precisely estimating this higher-order structure characteristic of biological systems.

scholarly journals A Learning Design to Improve Higher Order Thinking Skills (HOTS)

2021 ◽  
Vol 3 (2) ◽  
pp. 34-41
Author(s):  
Ocy Dwi Rismi
Keyword(s):  
Data Analysis ◽  
Research Method ◽  
Implementation Process ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Higher Order ◽  
Learning Design ◽  
Higher Order Thinking Skills ◽  
Learning Mathematics ◽  
Descriptive Method

The purpose of this research is to describe the learning design aimed at improving students' higher-order thinking skills (HOTS) in learning mathematics and describe the obstacles encountered in the implementation process. The research method used in this study is a literature review. Data analysis uses a descriptive method, which describes the results of the research and then draws conclusions.

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