Submit Paper @IJSTE Feb 2018

IJSTE Journal – Call for Papers
Vol. 4 Issue 8 Feb 2018
Index Copernicus Value= 62.78 | Impact Factor : 4.753
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IJSTE | Effect of #Blend Ratio of Plastic Pyrolysis Oil and Diesel Fuel on the Performance of Single Cylinder CI Engine


Depleting quantity of Conventional Fuel has been focused as a greater problem these days. Day by day, quantity of Petroleum, Crude Oil has more utilisation and lesser production. Increasing use of Petrol & Diesel has made the people of the world to think for some alternative way for energy resources. At the same time. Other rising problem against the people of the world is increase in plastic waste and recycling of the same. Both of the issues are focused and efforts are made to get optimum solution. An experimental setup has been prepared for Plastic Pyrolysis oil and Diesel Blend to be used in single cylinder, 4-stroke CI engine. Plastic Pyrolysis oil is obtained from plastic waste by pyrolysis process. Pyrolysis process is a thermo-chemical decomposition of organic matter in absence of oxygen. Blending of pyrolysis oil with diesel helps to reduce the consumption of diesel fuel. The variation in the Blending ratio of Plastic Pyrolysis Oil and Diesel fuel affects the engine performance as well as exhaust emission data. To understand the variation in Engine performance, different Blends of Plastic Pyrolysis Oil and Diesel Fuel were prepared and experimentations were done by running these blends separately in engine with various loads at Injection Pressure of 190 bar. Blends were prepared for 10%, 20%, 30% and 50% of Plastic Pyrolysis Oil with 90%, 80%, 70% and 50% of Diesel Fuel respectively. Effect of Engine performance of each were compared by Graphical representation of different performance parameters.

#PlasticPyrolysisOil, #BlendRatio, #EnginePerformance, #DieselFuel, #CI #Engine


  1. Kagdi Dhruvin Nileshkumar , L. D. COLLEGE OF ENGINEERING
  3. Tushar M. Patel, LDRP – ITR
  4. Gaurav P. Rathod, LDRP – ITR

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IJSTE (International Journal of Science Technology and Engineering)

ISSN (Online) : 2349-784X

Call for Papers Subject Category : Engineering Science and Technology

Call for Papers Frequency : Monthly, 12 issues per year

IMPACT FACTOR: 4.753 | Index Copernicus Value: 69.90

Submission Last Date: 25-Dec-17
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Neuromorphic Technology. #IJSTE Journal#

Title: Neuromorphic Technolog:   Computer Chips that Mimic the Human Brain

Even today’s best supercomputers cannot rival the sophistication of the human brain. Computers are linear, moving data back and forth between memory chips and a central processor over a high-speed backbone. The brain, on the other hand, is fully interconnected, with logic and memory intimately cross-linked at billions of times the density and diversity of that found in a modern computer. Neuromorphic chips aim to process information in a fundamentally different way from traditional hardware, mimicking the brain’s architecture to deliver a huge increase in a computer’s thinking and responding power.


Miniaturization has delivered massive increases in conventional computing power over the years, but the bottleneck of shifting data constantly between stored memory and central processors uses large amounts of energy and creates unwanted heat, limiting further improvements. In contrast, neuromorphic chips can be more energy efficient and powerful, combining data-storage and data-processing components into the same interconnected modules. In this sense, the system copies the networked neurons that, in their billions, make up the human brain.

Neuromorphic technology will be the next stage in powerful computing, enabling vastly more rapid processing of data and a better capacity for machine learning. IBM’s million-neuron TrueNorth chip, revealed in prototype in August 2014, has a power efficiency for certain tasks that is hundreds of times superior to a conventional CPU (Central Processing Unit), and more comparable for the first time to the human cortex. With vastly more compute power available for far less energy and volume, neuromorphic chips should allow more intelligent small-scale machines to drive the next stage in miniaturization and artificial intelligence.

Potential applications include: drones better able to process and respond to visual cues, much more powerful and intelligent cameras and smartphones, and data-crunching on a scale that may help unlock the secrets of financial markets or climate forecasting. Computers will be able to anticipate and learn, rather than merely respond in pre-programmed ways.

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