Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

PDF

Series

Artificial Neural Networks

Articles 1 - 7 of 7

Full-Text Articles in Physical Sciences and Mathematics

A Technical Perspective On Integrating Artificial Intelligence To Solid-State Welding, Sambath Yaknesh, Natarajan Rajamurugu, Prakash K. Babu, Saravanakumar Subramaniyan, Sher A. Khan, C. Ahamed Saleel, Mohammad Nur-E-Alam, Manzoore E. M. Soudagar Jan 2024

A Technical Perspective On Integrating Artificial Intelligence To Solid-State Welding, Sambath Yaknesh, Natarajan Rajamurugu, Prakash K. Babu, Saravanakumar Subramaniyan, Sher A. Khan, C. Ahamed Saleel, Mohammad Nur-E-Alam, Manzoore E. M. Soudagar

Research outputs 2022 to 2026

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes …

Go to article

Utilizing Neural Networks And Wearables To Quantify Hip Joint Angles And Moments During Walking And Stair Ascent, Megan V. Mccabe Jun 2020

Utilizing Neural Networks And Wearables To Quantify Hip Joint Angles And Moments During Walking And Stair Ascent, Megan V. Mccabe

ENGS 88 Honors Thesis (AB Students)

Wearable sensors were leveraged to develop two methods for computing hip joint angles and moments during walking and stair ascent that are more portable than the gold standard. The Insole-Standard (I-S) approach replaced force plates with force-measuring insoles and achieved results that match the curvature of results from similar studies. Peaks in I-S kinetic results are high due to error induced by applying the ground reaction force to the talus. The Wearable-ANN (W-A) approach combines wearables with artificial neural networks to compute the same results. Compared against the I-S, the W-A approach performs well (average rRMSE = 18%, R2 …

Go to article

Monitoring And Evaluating The Influences Of Class V Injection Wells On Urban Karst Hydrology, James Adam Shelley Oct 2018

Monitoring And Evaluating The Influences Of Class V Injection Wells On Urban Karst Hydrology, James Adam Shelley

Masters Theses & Specialist Projects

The response of a karst aquifer to storm events is often faster and more severe than that of a non-karst aquifer. This distinction is often problematic for planners and municipalities, because karst flooding does not typically occur along perennial water courses; thus, traditional flood management strategies are usually ineffective. The City of Bowling Green (CoBG), Kentucky is a representative example of an area plagued by karst flooding. The CoBG, is an urban karst area (UKA), that uses Class V Injection Wells to lessen the severity of flooding. The overall effectiveness, siting, and flooding impact of Injection Wells in UKA’s is …

Go to article

Timing Attack Detection On Bacnet Via A Machine Learning Approach, Michael N. Johnstone, Matthew Peacock, J I. Den Hartog Jan 2015

Timing Attack Detection On Bacnet Via A Machine Learning Approach, Michael N. Johnstone, Matthew Peacock, J I. Den Hartog

Australian Information Security Management Conference

Building Automation Systems (BAS), alternatively known as Building Management Systems (BMS), which centralise the management of building services, are often connected to corporate networks and are routinely accessed remotely for operational management and emergency purposes. The protocols used in BAS, in particular BACnet, were not designed with security as a primary requirement, thus the majority of systems operate with sub-standard or non-existent security implementations. As intrusion is thus likely easy to achieve, intrusion detection systems should be put in place to ensure they can be detected and mitigated. Existing intrusion detection systems typically deal only with known threats (signature-based approaches) …

Go to article

Applying Feature Selection To Reduce Variability In Keystroke Dynamics Data For Authentication Systems, Mark Abernethy, Shri Rai Dec 2012

Applying Feature Selection To Reduce Variability In Keystroke Dynamics Data For Authentication Systems, Mark Abernethy, Shri Rai

Australian Information Warfare and Security Conference

Authentication systems enable the verification of claimed identity. Password-based authentication systems are ubiquitous even though such systems are amenable to numerous attack vectors and are therefore responsible for a large number of security breaches. Biometrics has been increasingly researched and used as an alternative to password-based systems. There are a number of alternative biometric characteristics that can be used for authentication purposes, each with different positive and negative implementation factors. Achieving a successful authentication performance requires effective data processing. This study investigated the use of keystroke dynamics for authentication purposes. A feature selection process, based on normality statistics, was applied …

Go to article

Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow Dec 2010

Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, first a novel decentralized state feedback stabilization controller is introduced for a class of nonlinear interconnected discrete-time systems in affine form with unknown subsystem dynamics, control gain matrix, and interconnection dynamics by employing neural networks (NNs). Subsequently, the optimal control problem of decentralized nonlinear discrete-time system is considered with unknown internal subsystem and interconnection dynamics while assuming that the control gain matrix is known. For the near optimal controller development, the direct neural dynamic programming technique is utilized to solve the Hamilton-Jacobi-Bellman (HJB) equation forward-in-time. The decentralized optimal controller design for each subsystem utilizes the critic-actor structure …

Go to article

(Teff,Log G,[Fe/H]) Classification Of Low-Resolution Stellar Spectra Using Artificial Neural Networks, Shawn Snider, Yuan Qu, Carlos Allende Prieto, Ted Von Hippel, Timothy C. Beers, Christopher Sneden, David L. Lambert, Silvia Rossi Dec 1999

(Teff,Log G,[Fe/H]) Classification Of Low-Resolution Stellar Spectra Using Artificial Neural Networks, Shawn Snider, Yuan Qu, Carlos Allende Prieto, Ted Von Hippel, Timothy C. Beers, Christopher Sneden, David L. Lambert, Silvia Rossi

Publications

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic analysis are no longer practical. New tools are required that are capable of extracting quickly and with reasonable accuracy important basic stellar parameters coded in the spectra. Recent analyses of Artificial Neural Networks (ANNs) applied to the classification of astronomical spectra have demonstrated the ability of this concept to derive estimates of temperature and luminosity. We have adapted the back-propagation ANN technique developed by von Hippel et al. (1994) to predict …

Go to article