Detection of Behavioral Data Based on Recordings from Energy Usage Sensor

2016 ◽  
pp. 137-146
Author(s):  
Piotr Augustyniak
Keyword(s):  
Behavioral Data ◽  
Energy Usage

Development of Reading Remediation for Dyslexic Individuals

2016 ◽  
Vol 224 (4) ◽  
pp. 240-246 ◽  
Author(s):  
Mélanie Bédard ◽  
Line Laplante ◽  
Julien Mercier
Keyword(s):  
20Th Century ◽  
Scientific Literature ◽  
Behavioral Data ◽  
Educational Neuroscience ◽  
Reading Remediation ◽  
Functional Brain ◽  
Neurophysiological Data ◽  
Brain Correlates ◽  
Research Questions ◽  
The Brain

Abstract. Dyslexia is a phenomenon for which the brain correlates have been studied since the beginning of the 20th century. Simultaneously, the field of education has also been studying dyslexia and its remediation, mainly through behavioral data. The last two decades have seen a growing interest in integrating neuroscience and education. This article provides a quick overview of pertinent scientific literature involving neurophysiological data on functional brain differences in dyslexia and discusses their very limited influence on the development of reading remediation for dyslexic individuals. Nevertheless, it appears that if certain conditions are met – related to the key elements of educational neuroscience and to the nature of the research questions – conceivable benefits can be expected from the integration of neurophysiological data with educational research. When neurophysiological data can be employed to overcome the limits of using behavioral data alone, researchers can both unravel phenomenon otherwise impossible to document and raise new questions.

Behavioral data in the design of aircrew training devices

1975 ◽  
Author(s):  
B. W. Cream ◽  
F. T. Eggemeier ◽  
G. A. Klein
Keyword(s):  
Behavioral Data

Energy usage is crucial social issue

1981 ◽  
Author(s):  
Stuart Oskamp
Keyword(s):  
Social Issue ◽  
Energy Usage

Energy Efficiency Analysis in ERA using NFL-BA Algorithm

2020 ◽  
pp. 340-348
Author(s):  
Palky Mehta ◽  
H. L. Sharma
Keyword(s):  
Cluster Head ◽  
Vital Role ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Cluster Heads ◽  
Comparison Results ◽  
Current Scenario ◽  
Energy Efficiency Analysis ◽  
Selection Of

In the current scenario of Wireless Sensor Network (WSN), power consumption is the major issue associated with nodes in WSN. LEACH technique plays a vital role of clustering in WSN and reduces the energy usage effectively. But LEACH has its own limitation in order to search cluster head nodes which are randomly distributed over the network. In this paper, ERA-NFL- BA algorithm is being proposed for selects the cluster heads in WSN. This algorithm help in selection of cluster heads can freely transform from global search to local search. At the end, a comparison has been done with earlier researcher using protocol ERA-NFL, which clearly shown that proposed Algorithm is best suited and from comparison results that ERA-NFL-BA has given better performance.

SOME TRENDS IN GRASSLAND FARMING IN EUROPE

1977 ◽  
pp. 5-19
Author(s):  
R.W. Brougham
Keyword(s):  
Land Use ◽  
Crude Protein ◽  
Energy Usage ◽  
Hill Country ◽  
Wide Range

IN an assessment such as this, one could cover a wide range of topics fairly shallowly or a lesser number in a bit more depth. I have opted for the latter. The topics discussed will embrace some trends in dairying, beef farming, sheep farming, hill country farming, and land use generally, species and variety usage in grassland farming, use of crude protein produced from pasture, and some implications of energy usage.

Developing Multi-Tier Network Design for Effective Energy Consumption of Cluster Head Selection in WSN

2016 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Wan Isni Sofiah Wan Din ◽  
Saadiah Yahya ◽  
Mohd Nasir Taib ◽  
Ahmad Ihsan Mohd Yassin ◽  
Razulaimi Razali
Keyword(s):  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Energy Usage ◽  
Network Cluster ◽  
Fuzzy Logic Approach ◽  
The Stability

Clustering in Wireless Sensor Network (WSN) is one of the methods to minimize the energy usage of sensor network. The design of sensor network itself can prolong the lifetime of network. Cluster head in each cluster is an important part in clustering to ensure the lifetime of each sensor node can be preserved as it acts as an intermediary node between the other sensors. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. Thus, this paper presents an improvement of clustering algorithm for two-tier network as we named it as Multi-Tier Algorithm (MAP). For the cluster head selection, fuzzy logic approach has been used which it can minimize the energy usage of sensor nodes hence maximize the network lifetime. MAP clustering approach used in this paper covers the average of 100Mx100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. It is concluded that, MAP dominant the lifetime of WSN compared to LEACH and SEP protocols. For the future work, the stability of this algorithm can be verified in detailed via different data and energy. 

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