Approach for Energy Saving and Pollution Reducing by Fueling Diesel Engines with Emulsified Biosolution/Biodiesel/Diesel Blends

2008 ◽  
Vol 42 (10) ◽  
pp. 3849-3855 ◽  
Author(s):  
Yuan-Chung Lin ◽  
Wen-Jhy Lee ◽  
How-Ran Chao ◽  
Shu-Li Wang ◽  
Tsui-Chun Tsou ◽  
...  
Keyword(s):  
Energy Saving ◽  
Diesel Engines

An overview: Energy saving and pollution reduction by using green fuel blends in diesel engines

2015 ◽  
Vol 159 ◽  
pp. 214-236 ◽  
Author(s):  
John Kennedy Mwangi ◽  
Wen-Jhy Lee ◽  
Yu-Cheng Chang ◽  
Chia-Yang Chen ◽  
Lin-Chi Wang
Keyword(s):  
Energy Saving ◽  
Diesel Engines ◽  
Pollution Reduction ◽  
Fuel Blends ◽  
Green Fuel

Synthesis of new aluminum nano hybrid composite liner for energy saving in diesel engines

2015 ◽  
Vol 98 ◽  
pp. 440-448 ◽  
Author(s):  
N. Tiruvenkadam ◽  
P.R. Thyla ◽  
M. Senthilkumar ◽  
M. Bharathiraja ◽  
A. Murugesan
Keyword(s):  
Energy Saving ◽  
Diesel Engines ◽  
Hybrid Composite ◽  
Composite Liner

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

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