A Progressive Method to Monitor Power Using IoT

2021 ◽  
pp. 153-168
Author(s):  
S. Suriya ◽  
Agusthiyar Ramu ◽  
J. Shyamala Devi
Keyword(s):  
Author(s):  
O.A. Savkina ◽  
◽  
G.V. Ternovskoi ◽  
M.N. Lokachuk ◽  
E.N. Pavlovskaya ◽  
...  

1989 ◽  
Vol 9 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Geraldine Madden ◽  
Carl McGown

This study compared the effect of the Gallwey inner game method with the progressive method, as presented in the U.S. Volleyball Association Level 1 Technical Manual, on the learning of volleyball skills. The interaction of the methods with hemispheric dominance was also investigated. Hemisphericity was assessed using the Herrmann Participant Survey Form (HPSF). Volleyball skill was evaluated with a modification of the Barbarich (1980) Forearm Pass Test (BFPT) and a team game called cooperation. Undergraduate volunteers were divided into four groups. Two groups were taught by the inner game method and the other two groups were taught by the progressive method. Analysis of variance on the gain scores of the BFPT revealed no significant differences between the methods for forearm pass. There were also no differences on the team scores for cooperation, nor was there any significant interaction between brain dominance and either method. Thus, the prediction that right hemisphere dominant students would profit more if taught by the inner game method and that left hemisphere dominant students would profit more through the progressive method was not realized.


2017 ◽  
Vol 10 (3) ◽  
pp. 1-21
Author(s):  
Zekri Lougmiri

Skyline queries are important in many fields, especially for decision making. In this context, objects or tuples of databases are defined according to some numerical and non numerical attributes. The skyline operator acts on the numerical ones. The algorithms that implements this skyline operator are genrally of progressive or non progressive. The progressive ones return the skyline operator during its execution while non preogressive alogrithms return the result at the end of its execution. This paper presents a new progressive algorithm for computing the skyline points. This algorithm is based on sorting as a preprocessing of the input. The authors present new theorems for deducing promptly the first skyline points and reducing the candidate space. A new version of Divide-and-Conquer algorithm is used for computing the final skyline. Intensive experimentations on both real and synthetic datasets show that our algorithm presents best performance comparatively to other methods.


1928 ◽  
Vol 15 (2) ◽  
pp. 89-89
Author(s):  
Otto Merz
Keyword(s):  

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