Comparative Effects of Chemical Pretreatments on Mechanical Properties of Sustainable Rubberized Concrete

Tue, 13 Dec 2022 00:00:00 +0000

Publication date: 13 December 2022
Source: International Journal of Engineering and Applied Technologies Vol. 22
Author(s): Ahmad Ali, Raheel Zafar, Tayyaba Bibi
Chemical pretreatments are known to have significant influence over mechanical properties of concrete and being able to quantify the effect of chemical pretreatments will be of great help in trying to anticipate the rubberized concrete’s possible mechanical properties. This paper presents an experimental study that was conducted on cylindrical concrete samples prepared by using different proportions of natural coarse aggregates (NCAs) replaced by pretreated; with different concentrations of chemicals, rubber coarse aggregates (RCAs). The aim was to ameliorate the mechanical properties of concrete using sustainable alternative; rubber coarse aggregate. After chemical treatment, washing and air drying, RCAs were first coated with cement paste and then dried and cured for 28 days to enhance their bonding behavior in concrete. The results confirmed the efficiency of pretreated RCAs, in improving the mechanical properties of rubberizes concrete especially the compressive strength. Key words: Compressive strength, Rubber coarse aggregates, Rubberized concrete, Pretreatment, Sustainability corresponding author: pc.ahmadali@gmail.com

Noise Removal from Images Using Adaptive Neuro/Network-Fuzzy Interface Systems

Tue, 13 Dec 2022 00:00:00 +0000

Publication date: 13 December 2022
Source: International Journal of Engineering and Applied Technologies Vol. 22
Author(s): Krishna Prasad Pulipaka, K. Sathish Kumar, K. Geethali Apoorva, Rohith Rao, K. Radha Krishna
Any Information signal is best desirable without any external noise/ disturbances. Noise in any signal is the undesirable quantity present which deteriorates the signal's quality, thus compromising the information. Any signal, be it an image signal (2-D) or else a video signal (3-D) in the field of communication, if not always but most number of times prone to noise. In this paper, we would be dealing with removing types of noise on an image, using various filter techniques such as vector median filter, vector directional filter. Using the image processing tools in MATLAB, we could achieve this quite effortlessly. Looking at the prior approaches and keeping those factors in understanding, this paper would intend to path a more thoughtful way to bifurcate the image from its noise using the techniques of the neural networks. With thorough scrutiny and understanding of filters, this paper ensemble the performance of filters, through which we would be applying the most suitable filter out of the lot with the neural networks.