Establishing Equivalence Relations Using a Respondent-Type Training Procedure

1996 ◽  
Vol 46 (4) ◽  
pp. 685-706 ◽  
Author(s):  
Geraldine Leader ◽  
Dermot Barnes ◽  
Paul M. Smeets
Keyword(s):  
Equivalence Relations ◽  
Training Procedure

Establishing Equivalence Relations Using a Respondent-Type Training Procedure III

2000 ◽  
Vol 50 (1) ◽  
pp. 63-78 ◽  
Author(s):  
Geraldine Leader ◽  
Dermot Barnes-Holmes ◽  
Paul M. Smeets
Keyword(s):  
Equivalence Relations ◽  
Training Procedure

The influence of training procedure and stimulus valence on the long-term maintenance of equivalence relations

2021 ◽  
Vol 185 ◽  
pp. 104343
Author(s):  
Marcelo V. Silveira ◽  
Julio C. Camargo ◽  
Natália M. Aggio ◽  
Giovan W. Ribeiro ◽  
Mariéle Diniz Cortez ◽  
...  
Keyword(s):  
Equivalence Relations ◽  
Training Procedure ◽  
Stimulus Valence ◽  
Term Maintenance

Task-Switching Training and Transfer

2018 ◽  
Vol 32 (3) ◽  
pp. 106-130 ◽  
Author(s):  
Zsófia Anna Gaál ◽  
István Czigler
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Training ◽  
Task Switching ◽  
Difficulty Level ◽  
Training Procedure ◽  
Far Transfer ◽  
Near Transfer ◽  
Related Potentials ◽  
Transfer Tasks

Abstract. We used task-switching (TS) paradigms to study how cognitive training can compensate age-related cognitive decline. Thirty-nine young (age span: 18–25 years) and 40 older (age span: 60–75 years) women were assigned to training and control groups. The training group received 8 one-hour long cognitive training sessions in which the difficulty level of TS was individually adjusted. The other half of the sample did not receive any intervention. The reference task was an informatively cued TS paradigm with nogo stimuli. Performance was measured on reference, near-transfer, and far-transfer tasks by behavioral indicators and event-related potentials (ERPs) before training, 1 month after pretraining, and in case of older adults, 1 year later. The results showed that young adults had better pretraining performance. The reference task was too difficult for older adults to form appropriate representations as indicated by the behavioral data and the lack of P3b components. But after training older adults reached the level of performance of young participants, and accordingly, P3b emerged after both the cue and the target. Training gain was observed also in near-transfer tasks, and partly in far-transfer tasks; working memory and executive functions did not improve, but we found improvement in alerting and orienting networks, and in the execution of variants of TS paradigms. Behavioral and ERP changes remained preserved even after 1 year. These findings suggest that with an appropriate training procedure older adults can reach the level of performance seen in young adults and these changes persist for a long period. The training also affects the unpracticed tasks, but the transfer depends on the extent of task similarities.

The effect of a simple training procedure on the judgment of visual number.

1951 ◽  
Author(s):  
E. L. Kaufman ◽  
A. L. Minturn ◽  
T. W. Reese
Keyword(s):  
Training Procedure ◽  
Visual Number

Weakly precomplete equivalence relations in the Ershov hierarchy

2019 ◽  
Vol 58 (3) ◽  
pp. 297-319
Author(s):  
N. A. Bazhenov ◽  
B. S. Kalmurzaev
Keyword(s):  
Equivalence Relations ◽  
Ershov Hierarchy

Equivalence relations among inequalities for some relative operator entropies

Positivity ◽  
2020 ◽  
Vol 24 (5) ◽  
pp. 1503-1518
Author(s):  
Ismail Nikoufar ◽  
Maryam Fazlolahi
Keyword(s):  
Equivalence Relations

scholarly journals Evaluation of Mixed Deep Neural Networks for Reverberant Speech Enhancement

Biomimetics ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 1 ◽  
Author(s):  
Michelle Gutiérrez-Muñoz ◽  
Astryd González-Salazar ◽  
Marvin Coto-Jiménez
Keyword(s):  
Neural Networks ◽  
Short Term Memory ◽  
Computational Cost ◽  
Real Life ◽  
Fixed Number ◽  
Training Procedure ◽  
Statistical Validation ◽  
Significant Drop ◽  
Training Time ◽  
Important Solution

Speech signals are degraded in real-life environments, as a product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One of the conditions that make adverse quality difficult to handle in those systems is reverberation, produced by sound wave reflections that travel from the source to the microphone in multiple directions. To enhance signals in such adverse conditions, several deep learning-based methods have been proposed and proven to be effective. Recently, recurrent neural networks, especially those with long short-term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as speech. One of the most challenging aspects of LSTM networks is the high computational cost of the training procedure, which has limited extended experimentation in several cases. In this work, we present a proposal to evaluate the hybrid models of neural networks to learn different reverberation conditions without any previous information. The results show that some combinations of LSTM and perceptron layers produce good results in comparison to those from pure LSTM networks, given a fixed number of layers. The evaluation was made based on quality measurements of the signal’s spectrum, the training time of the networks, and statistical validation of results. In total, 120 artificial neural networks of eight different types were trained and compared. The results help to affirm the fact that hybrid networks represent an important solution for speech signal enhancement, given that reduction in training time is on the order of 30%, in processes that can normally take several days or weeks, depending on the amount of data. The results also present advantages in efficiency, but without a significant drop in quality.

scholarly journals Micromagnetic Characterization of Operation-Induced Damage in Charpy Specimens of RPV Steels

2021 ◽  
Vol 11 (7) ◽  
pp. 2917
Author(s):  
Madalina Rabung ◽  
Melanie Kopp ◽  
Antal Gasparics ◽  
Gábor Vértesy ◽  
Ildikó Szenthe ◽  
...  
Keyword(s):  
Neutron Irradiation ◽  
Pressure Vessel ◽  
Operating Conditions ◽  
Magnetic Characteristics ◽  
Pressure Vessel Steel ◽  
Training Procedure ◽  
Vessel Steel ◽  
Before And After ◽  
The Individual ◽  
Magnetic Adaptive Testing

The embrittlement of two types of nuclear pressure vessel steel, 15Kh2NMFA and A508 Cl.2, was studied using two different methods of magnetic nondestructive testing: micromagnetic multiparameter microstructure and stress analysis (3MA-X8) and magnetic adaptive testing (MAT). The microstructure and mechanical properties of reactor pressure vessel (RPV) materials are modified due to neutron irradiation; this material degradation can be characterized using magnetic methods. For the first time, the progressive change in material properties due to neutron irradiation was investigated on the same specimens, before and after neutron irradiation. A correlation was found between magnetic characteristics and neutron-irradiation-induced damage, regardless of the type of material or the applied measurement technique. The results of the individual micromagnetic measurements proved their suitability for characterizing the degradation of RPV steel caused by simulated operating conditions. A calibration/training procedure was applied on the merged outcome of both testing methods, producing excellent results in predicting transition temperature, yield strength, and mechanical hardness for both materials.

Fundamental relations and identities of fuzzy hyperalgebras

2021 ◽  
pp. 1-10
Author(s):  
Narjes Firouzkouhi ◽  
Abbas Amini ◽  
Chun Cheng ◽  
Mehdi Soleymani ◽  
Bijan Davvaz
Keyword(s):  
Universal Algebra ◽  
Equivalence Relation ◽  
Polynomial Function ◽  
Equivalence Relations ◽  
Fundamental Relation ◽  
Term Function ◽  
Biological Phenomena ◽  
Definition Of

Inspired by fuzzy hyperalgebras and fuzzy polynomial function (term function), some homomorphism properties of fundamental relation on fuzzy hyperalgebras are conveyed. The obtained relations of fuzzy hyperalgebra are utilized for certain applications, i.e., biological phenomena and genetics along with some elucidatory examples presenting various aspects of fuzzy hyperalgebras. Then, by considering the definition of identities (weak and strong) as a class of fuzzy polynomial function, the smallest equivalence relation (fundamental relation) is obtained which is an important tool for fuzzy hyperalgebraic systems. Through the characterization of these equivalence relations of a fuzzy hyperalgebra, we assign the smallest equivalence relation α i 1 i 2 ∗ on a fuzzy hyperalgebra via identities where the factor hyperalgebra is a universal algebra. We extend and improve the identities on fuzzy hyperalgebras and characterize the smallest equivalence relation α J ∗ on the set of strong identities.

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