Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

Mechanical Strength Enhancement of 3D Printed Acrylonitrile Butadiene Styrene Polymer Components Using Neural Network Optimization Algorithm

Abstract: Fused filament fabrication (FFF), a portable, clean, low cost and flexible 3D printing technique, finds enormous applications in different sectors. The process has the ability to create ready to use tailor-made products within a few hours, and acrylonitrile butadiene styrene (ABS) is extensively employed in FFF due to high impact resistance and toughness. However, this technology has certain inherent process limitations, such as poor mechanical strength and surface finish, which can be improved by optimizing the process parameters. As the results of optimization studies primarily depend upon the efficiency of the mathematical tools, in this work, an attempt is made to investigate a novel optimization tool. This paper illustrates an optimization study of process parameters of FFF using neural network algorithm (NNA) based optimization to determine the tensile strength, flexural strength and impact strength of ABS parts. The study also compares the efficacy of NNA over conventional optimization tools. The advanced optimization successfully optimizes the process parameters of FFF and predicts maximum mechanical properties at the suggested parameter settings.

A Novel Binary Spider Monkey Optimization Algorithm for Thinning of Concentric Circular Antenna Arrays

Abstract: This paper presents a novel binary algorithm named as binary spider monkey optimization (binSMO) for thinning of concentric circular antenna arrays (CCAA). The proposed algorithm has been adapted from a recently developed nature inspired optimization method, spider monkey optimization (SMO). SMO works in continuous domain and as such is not suitable for application to binary optimization problems. The binSMO algorithm has been proposed with inclusion of logical operators in SMO for binary thinning problem. Thinning of an antenna array reduces the maximum side lobe level (SLL) as well as cost and size of antenna array. Thinning of CCAA can be modelled as 0–1 binary integer optimization problem. The proposed binSMO is used to synthesize CCAA in order to reduce the SLL and at the same time keeping the percentage of thinning equal to or more than the desired level. Simulation examples of two ring and ten ring CCAA have been considered. The novel method binSMO gives reduced SLL as compared to the resul...

Distance-Based Residual Energy-Efficient Stable Election Protocol for WSNs

Abstract: Wireless sensor networks (WSNs) comprise nodes with restricted battery power that are deployed to observe some physical event within the sensor field. Information gathering is typical, but an important operation in several applications of WSNs. It is important to control the sensor network for longer period of time in an energy-efficient manner for gathering information. Hence, it is perpetually fascinating to design protocols that are energy efficient, have prolonged lifetime and can support event-driven applications. This paper proposes a protocol referred to as distance-based residual energy-efficient stable election protocol (DRESEP) that is nearly optimal for event-driven information gathering applications in sensor networks. The key idea of DRESEP is moving gathered information from sensor nodes to cluster head (CH) depending upon perceived changes. Dual-hop communication between CHs and base station is introduced to achieve energy minimization. Further, the results demonstrate that the proposed algorithm significantly outperforms existing algorithms in terms of energy optimization and system lifetime.