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All Journal Bulletin of Electrical Engineering and Informatics Journal La Multiapp
Hussien, Nadia Mahmood
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering

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Journal : Journal La Multiapp

 1 
Automated Chemical Equation Balancing Using the Apriori Algorithm Mohialden, Yasmin Makki; Hussien, Nadia Mahmood; Al-Rada, Walaa A Abd
Journal La Multiapp Vol. 4 No. 3 (2023): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v4i3.852

Abstract

Chemical equations must be balanced to maintain mass conservation. Traditional chemists employed manual processes with meticulous investigation and trial-and-error iterations. Automating and enhancing this difficult process is becoming more popular as machine learning (ML) progresses. We provide a novel Apriori algorithm-based chemical equation balancing method in this paper. Our solution uses the Apriori algorithm to find common itemsets of balanced reactions and translates unbalanced equations into machine-readable language. After that, it reconstructs balanced equations, automating a tedious task.
Enhancing User Authentication with Facial Recognition and Feature-Based Credentials Mohialden, Yasmin Makki; Hussien, Nadia Mahmood; Ali, Doaa Muhsin Abd
Journal La Multiapp Vol. 4 No. 6 (2023): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v4i6.903

Abstract

This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition.
Co-Authors Akawee, Mustafa Mahmood Al-Rada, Walaa A Abd Ali, Doaa Muhsin Abd Mohammed, Mostafa Abdulghafoor Mohialden, Yasmin Makki