Faculty Opinions recommendation of Antibody domain exchange is an immunological solution to carbohydrate cluster recognition.

Author(s):  
Sachdev Sidhu
Keyword(s):  
Author(s):  
Chloe Chun-wing Lo ◽  
Markus Hollander ◽  
Freda Wan ◽  
Alexis-Walid Ahmed ◽  
Nikki Bernobić ◽  
...  
Keyword(s):  

Author(s):  
David B. Boles

Can training of a task be achieved using a different task drawing on the same mental resources? Subjects performed 5 successive blocks of trials, with bargraph recognition required in Blocks 1, 4, and 5. Blocks 2 and 3 either involved bargraph recognition (Group 1, n = 13), dot cluster recognition (Group 2, n = 14), or word number recognition (Group 3, n= 14). The majority of the practice effect across blocks was found to be due to practice within a previously identified “spatial quantitative” perceptual resource, regardless of whether the resource was instantiated in bargraph or dot cluster recognition. These results suggest that (a) training should focus on the target task's perceptual resources, and (b) training can use tasks different from the target task as long as the same resources are used. If these findings generalize, substantial savings in training costs may be achievable by using different, simplified tasks during training.


2012 ◽  
Vol 16 (4) ◽  
pp. 653-673 ◽  
Author(s):  
Carmen Vega Orozco ◽  
Marj Tonini ◽  
Marco Conedera ◽  
Mikhail Kanveski

2005 ◽  
Vol 44 (21) ◽  
pp. 7540-7546 ◽  
Author(s):  
P. S. Lakshminarayanan ◽  
D. Krishna Kumar ◽  
Pradyut Ghosh

2006 ◽  
Vol 20 (4) ◽  
pp. 443-452 ◽  
Author(s):  
Ioannis K. Brilakis ◽  
Lucio Soibelman ◽  
Yoshihisa Shinagawa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaohui Wang ◽  
Qiyuan Tang ◽  
Zhaozhong Chen ◽  
Youyi Luo ◽  
Hongyu Fu ◽  
...  

AbstractThe uniformity of the rice cluster distribution in the field affects population quality and the precise management of pesticides and fertilizers. However, there is no appropriate technical system for estimating and evaluating the uniformity at present. For that reason, a method based on unmanned aerial vehicle (UAV images) is proposed to estimate and evaluate the uniformity in this present study. This method includes rice cluster recognition and location determination based on the RGB color characteristics of the seedlings of aerial images, region segmentation considering the rice clusters based on Voronoi Diagram, and uniformity index definition for evaluating the rice cluster distribution based on the variation coefficient. The results indicate the rice cluster recognition attains a high precision, with the precision, accuracy, recall, and F1-score of rice cluster recognition reaching > 95%, 97%, 97%, 95%, and 96%, respectively. The rice cluster location error is small and obeys the gamma (3.00, 0.54) distribution (mean error, 1.62 cm). The uniformity index is reasonable for evaluating the rice cluster distribution verified via simulation. As a whole process, the estimating method is sufficiently high accuracy with relative error less than 0.01% over the manual labeling method. Therefore, this method based on UAV images is feasible, convenient, technologically advanced, inexpensive, and highly precision for the estimation and evaluation of the rice cluster distribution uniformity. However, the evaluation application indicates that there is much room for improvement in terms of the uniformity of mechanized paddy field transplanting in South China.


Sign in / Sign up

Export Citation Format

Share Document