Review of Computer Engineering Research

Published by: Conscientia Beam
Online ISSN: 2410-9142
Print ISSN: 2412-4281
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No. 2

Real-Time Car Parking System Using Arduino Control

Pages: 41-63
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Real-Time Car Parking System Using Arduino Control

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DOI: 10.18488/journal.76.2021.82.41.63

Ahmed Raza Moshin , Maira Khalid , Muhammad Awais , Kinza Ahmad

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Ahmed Raza Moshin , Maira Khalid , Muhammad Awais , Kinza Ahmad (2021). Real-Time Car Parking System Using Arduino Control. Review of Computer Engineering Research, 8(2): 41-63. DOI: 10.18488/journal.76.2021.82.41.63
In the ongoing examination of metropolitan areas, the increment in population produces high vehicle density on roads. Consequently, this prompts irritating issue for the drivers to leave their vehicles as it is hard to discover a leaving space. This paper introduces web based automatic smart parking system for vehicles. In this paper we have proposed a system which can easily manage parking system through networks of different sensors. This system can easily find a parking space and check whether the user parked the vehicle or not. In addition, this system can create unlimited locations and add slots to these locations. This is multi-user parking system where a single application can work for multiple locations. This parking system will improve the probability of successful parking and minimizes the waiting time of user. Moreover, this parking management system will encourage users to track parking slots and make the parking process a hassle-free experience.
Contribution/ Originality
This study contributes to the existing IoT literature that uses devices to provide a better parking system. This study investigated IoT with web-based applications and finds the slots for the user with direction provided on screen using map view. This Study shows the documentation of the real time parking system.

Two-Stage Model with Rough Cluster and Salp Optimization Technique for Epistasis Detection

Pages: 27-40
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Two-Stage Model with Rough Cluster and Salp Optimization Technique for Epistasis Detection

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DOI: 10.18488/journal.76.2021.82.27.40

S Priya , R Manavalan

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S Priya , R Manavalan (2021). Two-Stage Model with Rough Cluster and Salp Optimization Technique for Epistasis Detection. Review of Computer Engineering Research, 8(2): 27-40. DOI: 10.18488/journal.76.2021.82.27.40
The discovery of gene-gene interactions to identify complex diseases is one of the primary challenges in genome-wide association studies (GWAS). Genetic interactions (Epistasis) are typically seen as interactions between various single nucleotide polymorphisms (SNPs). Genetic interactions discovery can assist the researchers in identifying gene pathways, recognizing gene activity, and discovering potential drug targets. Rough Cluster based Salp Optimization for Epistasis detection (RCSalp-Epi) is a two-stage epistasis model that has been evaluated on a variety of simulated disease models. In the screening stage, the rough clustering algorithm is employed to partition the genotype data into different clusters. The selection stage presents Salp optimization with a single objective function (SalpEpi-SO) and multiple objective functions (SalpEpi-MO) over the clusters to find disease-related SNP combinations. RCSalp-performance Epi's is evaluated in comparison with SalpEpi-SO and SalpEpi-MO. The outcome of the experimental analysis revealed that RCSalp-Epi-MO is superior to SalpEpi-SO and SalpEpi-MO in terms of power and execution time.
Contribution/ Originality
The paper's primary contribution is finding the higher order genetic interactions with high detection power and minimal computational effort.