Fuzzy Analysis of Speech Metrics to Estimate Conductor Alertness

2009 ◽  
Author(s):  
Parham Shahidi ◽  
Steve C. Southward ◽  
Mehdi Ahmadian
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Rule Base ◽  
Mathematical Framework ◽  
Human Knowledge ◽  
Knowledge Based ◽  
Single Output ◽  
Output System ◽  
Alertness Level ◽  
Different Levels

A Fuzzy Logic-based algorithm has been developed for processing a series of speech metrics with the ultimate goal of estimating train conductor alertness. The output is a single metric, which directly quantifies the alertness level of the conductor. The metrics were selected based on their correlation to alertness through processed speech, but without any interpretation of the spoken words or phrases. Metrics that are used include: speech duration, silence duration, word production rate and word intensity. The assessment of these metrics is an experience and human knowledge based task, which generates the need for a mathematical model to accommodate this special circumstance. The algorithm developed here uses Fuzzy Logic to cast the human knowledge base into a mathematical framework for the alertness estimation analysis. The core of this fuzzy system is a rule base consisting of fuzzy IF-THEN rules, which are derived from the existing knowledge about the effects of sleep deprivation on alertness such as Furthermore, the rules were inferred from actual voice recordings that were taken on board a train. This data was then used to create a classification scheme to determine which pattern in the speech indicates different levels of alertness from anxiety to fatigue. The simplicity of the underlying mathematical model in this approach enables this system to compute and output an alertness metric in real-time. The nature of this algorithm allows for the use of an arbitrary number of rules to classify the alertness level and therefore provides the ability to continuously develop and extend the rule base as new knowledge emerges. The resulting algorithm is a fast, multi-input, single-output system that is able to quantify the train conductor’s alertness level anytime speech is produced.

scholarly journals A Mixed Rough Sets/Fuzzy Logic Approach for Modelling Systemic Performance Variability with FRAM

2020 ◽  
Vol 12 (5) ◽  
pp. 1918
Author(s):  
Hussein Slim ◽  
Sylvie Nadeau
Keyword(s):  
Fuzzy Logic ◽  
Rough Sets ◽  
Assessment Model ◽  
Rule Base ◽  
Data Sets ◽  
Mathematical Framework ◽  
Real World Data ◽  
Second Stage ◽  
Fuzzy Logic Approach ◽  
Input Variables

The task to understand systemic functioning and predict the behavior of today’s sociotechnical systems is a major challenge facing researchers due to the nonlinearity, dynamicity, and uncertainty of such systems. Many variables can only be evaluated in terms of qualitative terms due to their vague nature and uncertainty. In the first stage of our project, we proposed the application of the Functional Resonance Analysis Method (FRAM), a recently emerging technique, to evaluate aircraft deicing operations from a systemic perspective. In the second stage, we proposed the integration of fuzzy logic into FRAM to construct a predictive assessment model capable of providing quantified outcomes to present more intersubjective and comprehensible results. The integration process of fuzzy logic was thorough and required significant effort due to the high number of input variables and the consequent large number of rules. In this paper, we aim to further improve the proposed prototype in the second stage by integrating rough sets as a data-mining tool to generate and reduce the size of the rule base and classify outcomes. Rough sets provide a mathematical framework suitable for deriving rules and decisions from uncertain and incomplete data. The mixed rough sets/fuzzy logic model was applied again here to the context of aircraft deicing operations, keeping the same settings as in the second stage to better compare both results. The obtained results were identical to the results of the second stage despite the significant reduction in size of the rule base. However, the presented model here is a simulated one constructed with ideal data sets accounting for all possible combinations of input variables, which resulted in maximum accuracy. The same should be further optimized and examined using real-world data to validate the results.

Fuzzy Logic Control of Low Cost Obstacle Climbing Robot

2014 ◽  
Vol 592-594 ◽  
pp. 2150-2154
Author(s):  
D. Elayaraja ◽  
S. Ramabalan
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fuzzy Logic Control ◽  
3D Model ◽  
Low Cost ◽  
Climbing Robot ◽  
Single Output ◽  
Logic Control ◽  
Output System ◽  
Solid Works

This paper deals with the design of wheeled mobile robot that will able to climb an obstacle and describes the fuzzy logic control of the obstacle climbing of the robot. The controller is 2 input and single output system. The controller is simulated in Mat lab. The 3D model of the mobile robot with eight wheels was designed using solid works and fabricated. The simulated result is compared with actual result.

scholarly journals Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

2015 ◽  
Vol 12 (2) ◽  
pp. 171-182 ◽  
Author(s):  
Dinesh Rana ◽  
Sudha Rani
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Fuzzy Logic Controller ◽  
Stress Factor ◽  
Innovative Technology ◽  
Rule Base ◽  
Single Output ◽  
On Line ◽  
Definition Of ◽  
Matlab Programming

Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC) for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

scholarly journals INVESTIGATING THE POTENTIAL CONSEQUENCES OF THE MEMBERSHIP FUNCTIONS IN A FUZZY LOGIC CONTROLLER-BASED OBSTACLE CLIMBING ROBOT

2021 ◽  
Vol 9 (1) ◽  
pp. 1294-1299
Author(s):  
K. Alhaf Malik, Dr.D.Elayaraja, Dr. S. Jafar Ali Ibrahim, Dr. N.S. Kalyan Chakravarthy
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Building Blocks ◽  
Vital Role ◽  
Autonomous Mobile Robots ◽  
Membership Functions ◽  
Climbing Robot ◽  
Single Output ◽  
Output System ◽  
Logic System

Autonomous mobile robots are the robots which can perform desired tasks in unstructured environment without continuous human guidance. This paper deals with the design of an Autonomous obstacle climbing robot that will able to climb an obstacle. This obstacle climbing navigation system is utilized by the intelligent fuzzy logic controller. The controller has 2 inputs and single output system. The inputs are slope and terrain type and the output is the speed of the robot. The membership functions are the building blocks of fuzzy logic system and play a vital role in the performance of mobile robot. This paper describes the effect of different membership functions namely triangular, trapezoidal membership functions are considered.

Study of the Hydraulic Mold System Basing on the Power Bond Graph

2012 ◽  
Vol 233 ◽  
pp. 135-141
Author(s):  
Liang Li ◽  
Kui Sheng Chen ◽  
Shu Guang Fu
Keyword(s):  
Mathematical Model ◽  
Dynamic Characteristic ◽  
System Optimization ◽  
Bond Graph ◽  
Single Output ◽  
Power Bond Graph ◽  
Output System ◽  
Single Input ◽  
Set Up ◽  
The Mathematical Model

This paper mainly introduces the structure and characteristics of the hydraulic mold system. By means of the power bond graph, the mathematical model of the servo system is set up. The analysis is not only to analyze single input and single output system (SISO) but also to analyze multi-input and multi-output system (MIMO).As result of it, it is widely applicable. Finally, we analyze the system dynamic characteristic basing on MATLAB SIMULINK. According to the simulation curves of the different parameters, we find out the system optimization measures.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

A model to account for the consequences of host nutrition on the outcome of gastrointestinal parasitism in sheep: model evaluation

Parasitology ◽  
2007 ◽  
Vol 134 (9) ◽  
pp. 1279-1289 ◽  
Author(s):  
D. VAGENAS ◽  
S. C. BISHOP ◽  
I. KYRIAZAKIS
Keyword(s):  
Mathematical Model ◽  
Worm Burden ◽  
Management Strategies ◽  
Sensitivity Analyses ◽  
Sheep Model ◽  
Host Nutrition ◽  
Gastrointestinal Parasitism ◽  
Different Characteristics ◽  
Nutritional Strategies ◽  
Different Levels

SUMMARYThis paper describes sensitivity analyses and expectations obtained from a mathematical model developed to account for the effects of host nutrition on the consequences of gastrointestinal parasitism in sheep. The scenarios explored included different levels of parasitic challenge at different planes of nutrition, for hosts differing only in their characteristics for growth. The model was able to predict the consequences of host nutrition on the outcome of parasitism, in terms of worm burden, number of eggs excreted per gram faeces and animal performance. The model outputs predict that conclusions on the ability of hosts of different characteristics for growth to cope with parasitism (i.e. resistance) depend on the plane of nutrition. Furthermore, differences in the growth rate of sheep, on their own, are not sufficient to account for differences in the observed resistance of animals. The model forms the basis for evaluating the consequences of differing management strategies and environments, such as breeding for certain traits associated with resistance and nutritional strategies, on the consequences of gastrointestinal parasitism on sheep.

scholarly journals Knowledge-based Lean Six Sigma maintenance system for sustainable buildings

2017 ◽  
Vol 8 (1) ◽  
pp. 109-130 ◽  
Author(s):  
Jasim Aldairi ◽  
M.K. Khan ◽  
J. Eduardo Munive-Hernandez
Keyword(s):  
Conceptual Framework ◽  
Six Sigma ◽  
Research Work ◽  
Lean Six Sigma ◽  
Rule Base ◽  
Sustainable Buildings ◽  
Sustainable Building ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Knowledge Based

Purpose This paper aims to develop a knowledge-based (KB) system for Lean Six Sigma (LSS) maintenance in environmentally sustainable buildings (Lean6-SBM). Design/methodology/approach The Lean6-SBM conceptual framework has been developed using the rule base approach of KB system and joint integration with gauge absence prerequisites (GAP) technique. A comprehensive literature review is given for the main pillars of the framework with a typical output of GAP analysis. Findings Implementation of LSS in the sustainable building maintenance context requires a pre-assessment of the organisation’s capabilities. A conceptual framework with a design structure is proposed to tackle this issue with the provision of an enhancing strategic and operational decision-making hierarchy. Research limitations/implications Future research work might consider validating this framework in other type of industries. Practical implications Maintenance activities in environmentally sustainable buildings must take prodigious standards into consideration, and, therefore, a robust quality assurance measure has to be integrated. Originality/value The significance of this research is to present a novel use of hybrid KB/GAP methodologies to develop a Lean6-SBM system. The originality and novelty of this approach will assist in identifying quality perspectives while implementing different maintenance strategies in the sustainable building context.

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