scholarly journals Effects of Commission Errors during Noncontingent Reinforcement

2020 ◽  
Author(s):  
Stephanie Hope Jones
2021 ◽  
Vol 36 (2) ◽  
pp. 514-521
Author(s):  
Jeanne Luis ◽  
Yanerys Leon ◽  
Claudia Campos

1995 ◽  
Vol 20 (3) ◽  
pp. 190-196 ◽  
Author(s):  
Bobby Newman ◽  
Dawn M. Buffington ◽  
Mairead A. O'grady ◽  
Mary E. Mcdonald ◽  
Claire L. Poulson ◽  
...  

A multiple baseline across students design was used to investigate the effects of a self-management package on schedule following by three teenagers with autism. During baseline conditions, noncontingent reinforcement was provided. In the treatment phase, students contingently self-reinforced the verbal identification of transition times. Systematic increases in accurate identification of transitions were observed across all students. Accurate identification of transition time and self-reinforcement were maintained in a one-month follow-up.


2017 ◽  
Vol 47 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Olívia Bueno da COSTA ◽  
Eraldo Aparecido Trondoli MATRICARDI ◽  
Marcos Antonio PEDLOWSKI ◽  
Mark Alan COCHRANE ◽  
Luiz Cláudio FERNANDES

ABSTRACT Although soybean production has been increasing in the state of Rondônia in the last decade, soybean planted area has been estimated indirectly using secondary datasets, which has limited understanding of its spatiotemporal distribution patterns. This study aimed to map and analyze spatial patterns of soybean expansion in Rondônia. We developed a classification technique based on Spectral Mixture Analysis (SMA) derived from Landsat imagery and Decision Tree Classification to detect and map soybean plantations in 2000, 2005, 2010, and 2014. The soybean classification map showed 93% global accuracy, 23% omission and 0% of commission errors for soybean crop fields. The greatest increases of soybean cropped area in the state of Rondônia were observed between 2000-2005 and 2005-2010 time-periods (33,239 ha and 59,628 ha, respectively), mostly located in Southern Rondônia. The expansion of soybean areas to Northern Rondônia (25,627 ha) has mostly occurred in the 2010-2014 time period. We estimate that 95.4% of all newly created soybean plantations, detected by 2014, were established on lands deforested nine or more years earlier. We concluded that the incursion of soybean plantations on lands deforested for other land uses (e.g. ranching) is contributing to their displacement (pastures) from older colonization zones toward more remote frontier areas of the Amazon, exacerbating new deforestation there.


2021 ◽  
Vol 13 (19) ◽  
pp. 4012
Author(s):  
Panpan Xu ◽  
Nandin-Erdene Tsendbazar ◽  
Martin Herold ◽  
Jan G. P. W. Clevers

The monitoring of Global Aquatic Land Cover (GALC) plays an essential role in protecting and restoring water-related ecosystems. Although many GALC datasets have been created before, a uniform and comprehensive GALC dataset is lacking to meet multiple user needs. This study aims to assess the effectiveness of using existing global datasets to develop a comprehensive and user-oriented GALC database and identify the gaps of current datasets in GALC mapping. Eight global datasets were reframed to construct a three-level (i.e., from general to detailed) prototype database for 2015, conforming with the United Nations Land Cover Classification System (LCCS)-based GALC characterization framework. An independent validation was done, and the overall results show some limitations of current datasets in comprehensive GALC mapping. The Level-1 map had considerable commission errors in delineating the general GALC distribution. The Level-2 maps were good at characterizing permanently flooded areas and natural aquatic types, while accuracies were poor in the mapping of temporarily flooded and waterlogged areas as well as artificial aquatic types; vegetated aquatic areas were also underestimated. The Level-3 maps were not sufficient in characterizing the detailed life form types (e.g., trees, shrubs) for aquatic land cover. However, the prototype GALC database is flexible to derive user-specific maps and has important values to aquatic ecosystem management. With the evolving earth observation opportunities, limitations in the current GALC characterization can be addressed in the future.


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