Search results for " Process"
showing 10 items of 17204 documents
Energy-based fluid–structure model of the vocal folds
2020
AbstractLumped elements models of vocal folds are relevant research tools that can enhance the understanding of the pathophysiology of many voice disorders. In this paper, we use the port-Hamiltonian framework to obtain an energy-based model for the fluid–structure interactions between the vocal folds and the airflow in the glottis. The vocal fold behavior is represented by a three-mass model and the airflow is described as a fluid with irrotational flow. The proposed approach allows to go beyond the usual quasi-steady one-dimensional flow assumption in lumped mass models. The simulation results show that the proposed energy-based model successfully reproduces the oscillations of the vocal …
TIME-MINIMAL CONTROL OF DISSIPATIVE TWO-LEVEL QUANTUM SYSTEMS: THE INTEGRABLE CASE
2009
The objective of this article is to apply recent developments in geometric optimal control to analyze the time minimum control problem of dissipative two-level quantum systems whose dynamics is governed by the Lindblad equation. We focus our analysis on the case where the extremal Hamiltonian is integrable.
Using the Analytic Hierarchy Process (AHP) in Evaluating the Decision of Moving to a Manufacturing Process Based Upon Continuous 5 Axes CNC Machine-t…
2016
Abstract This paper represents the second part of the work described in the paper with the title “Decision-making tool for moving from 3-axes to 5-axes CNC machine-tool”. The problem of using either 3 axes CNC machine-tools or 5 axes CNC machine tools was presented in the first part, together with a fuzzy logic based decision support tool. This time, an AHP approach is used in order to evaluate the decision of moving to a manufacturing process based upon 5 axes machine tools. Three variants were taken into consideration and analysed. The consistency of the proposed approach was evaluated and a sensitivity analysis was also introduced.
Assembly Assistance System with Decision Trees and Ensemble Learning
2021
This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …
Collaboration and Decision-Making in Context
2016
The goal of this chapter is to provide a historical account of the evolutions in the domain of the book and to set the stage for the concepts and solutions to be presented in the following chapters, including the introduction of the terminology adopted to be used throughout this text. Consequently, we aim at providing the answers to a series of questions, such as: (a) “How the organizations have been evolving over the last decades?”, (b) “Which have been the corresponding trends of the management and control schemes?”, (c) “How management and control functions are allocated to human and automation equipment?”, (d) “Which are the desirable properties of the information processing tools meant…
Density Flow in Dynamical Networks via Mean-Field Games
2016
Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic a…
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
A Fractional-Order Control Approach to Ramp Tracking with Memory-Efficient Implementation
2020
We investigate the fractional-order (FO) control of arbitrary order LTI systems. We show that, for ramp tracking or input disturbance rejection, it is advantageous to include an FO integrator to the open-loop if we have to increase the order of integration further than one. With the lower phase-loss of the FO integrator it is easier to guarantee a desired phase margin. Furthermore the flat phase response around the crossover-frequency (iso-damping property) can be achieved for a wider frequency range such that the closed-loop is more robust wrt. amplitude and phase margins. The drawback of the FO approach is the increased implementation effort and the algebraic decay, which slows down the t…
Detection of algorithmically generated malicious domain names using masked N-grams
2019
Abstract Malware detection is a challenge that has increased in complexity in the last few years. A widely adopted strategy is to detect malware by means of analyzing network traffic, capturing the communications with their command and control (C&C) servers. However, some malware families have shifted to a stealthier communication strategy, since anti-malware companies maintain blacklists of known malicious locations. Instead of using static IP addresses or domain names, they algorithmically generate domain names that may host their C&C servers. Hence, blacklist approaches become ineffective since the number of domain names to block is large and varies from time to time. In this paper, we i…
Enhancing Disaster Response for Hazardous Materials Using Emerging Technologies: The Role of AI and a Research Agenda
2019
Despite all efforts like the introduction of new training methods and personal protective equipment, the need to reduce the number of First Responders (FRs) fatalities and injuries remains. Reports show that advances in technology have not yet resulted in protecting FRs from injuries, health impacts, and odorless toxic gases effectively. Currently, there are emerging technologies that can be exploited and applied in emergency management settings to improve FRs protection. The aim of this paper is threefold: First, to conduct scenario analysis and situations that currently threat the first responders. Second, to conduct gap analysis concerning the new technology needs in relations to the pro…