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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
Electronic Theses and Dissertations
Early identification and detection of abnormal time series patterns is vital for a number of manufacturing. Slide shifts and alterations of time series patterns might be indicative of some anomaly in the production process, such as machinery malfunction. Usually due to the continuous flow of data monitoring of manufacturing processes requires automated Control Chart Pattern Recognition(CCPR) algorithms. The majority of CCPR literature consists of supervised classification algorithms. Less studies consider unsupervised versions of the problem. Despite the profound advantage of unsupervised methodology for less manual data labeling their use is limited due to the fact that their performance is not …
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
Electronic Theses and Dissertations
In recent years, the advancement of neurobiologically plausible models and computer networking has resulted in new ways of implementing control systems on robotic platforms. The work presents a control approach based on vertebrate neuromodulation and its implementation on autonomous robots in the open-source, open-access environment of robot operating system (ROS). A spiking neural network (SNN) is used to model the neuromodulatory function for generating context based behavioral responses of the robots to sensory input signals. The neural network incorporates three types of neurons- cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for rewards- and …