IIR modeling of interpositional transfer functions with a genetic algorithm aided by an adaptive filter for the purpose of altering free-field sound localization

The psychoacoustic process of sound localization is a system of complex analysis. Scientists have found evidence that both binaural and monaural cues are responsible for determining the angles of elevation and azimuth which represent a sound source. Engineers have successfully used these cues to build mathematical localization systems. Research has indicated that spectral cues play an important role in 3-d localization. Therefore, it seems conceivable to design a filtering system which can alter the localization of a sound source, either for correctional purposes or listener preference. Such filters, known as Interpositional Transfer Functions, can be formed from division in the z-domain of Head-related Transfer Functions. HRTF’s represent the free-field response of the human body to sound processed by the ears. In filtering applications, the use of IIR filters is often favored over that of FIR filters due to their preservation of resolution while minimizing the number of required coefficients. Several methods exist for creating IIR filters from their representative FIR counterparts. For complicated filters, genetic algorithms (GAs) have proven effective. The research summarized in this thesis combines the past efforts of researchers in the fields of sound localization, genetic algorithms, and adaptive filtering. It represents the initial stage in the development of a practical system for future hardware implementation which uses a genetic algorithm as a driving engine. Under ideal conditions, an IIR filter design system has been demonstrated to successfully model several IPTF pairs which alter sound localization when applied to non-minimum phase HRTF’s obtained from free-field measurement

Multi-Objective Optimization of Nonlinear Quarter Car Suspension System - PID and LQR Control

This paper presents modeling, control and optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car along with seat and driver is developed and simulated in Matlab/Simulink® environment. Input road condition is taken as class C road and vehicle travelling at 80kmph. Active control of suspension system is achieved using PID and LQR control actions. Instead of guessing and or trial and error method to determine the PID and LQR control parameters, a GA based optimization algorithm is implemented. The optimization function is modeled as multi-objective problem comprising of frequency weighted RMS acceleration, VDV, suspension space, tyre deflection and controller force. It is observed that optimized parameters gives better control as compared to the classical parameters and passive suspension system. Further simulations are carried out on suspension system with seat and driver model. The PID controller gives better ride comfort by reducing RMS head acceleration and VDV. Results are presented in time and frequency domain

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 140

This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1975

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

Studies on binaural and monaural signal analysis methods and applications

Sound signals can contain a lot of information about the environment and the sound sources present in it. This thesis presents novel contributions to the analysis of binaural and monaural sound signals. Some new applications are introduced in this work, but the emphasis is on analysis methods. The three main topics of the thesis are computational estimation of sound source distance, analysis of binaural room impulse responses, and applications intended for augmented reality audio. A novel method for binaural sound source distance estimation is proposed. The method is based on learning the coherence between the sounds entering the left and right ears. Comparisons to an earlier approach are also made. It is shown that these kinds of learning methods can correctly recognize the distance of a speech sound source in most cases. Methods for analyzing binaural room impulse responses are investigated. These methods are able to locate the early reflections in time and also to estimate their directions of arrival. This challenging problem could not be tackled completely, but this part of the work is an important step towards accurate estimation of the individual early reflections from a binaural room impulse response. As the third part of the thesis, applications of sound signal analysis are studied. The most notable contributions are a novel eyes-free user interface controlled by finger snaps, and an investigation on the importance of features in audio surveillance. The results of this thesis are steps towards building machines that can obtain information on the surrounding environment based on sound. In particular, the research into sound source distance estimation functions as important basic research in this area. The applications presented could be valuable in future telecommunications scenarios, such as augmented reality audio

Investigation of a non-linear suspension in a quarter car model

This thesis presents the study of a quarter car model which consists of a two-degree-of-freedom (2 DOF) with a linear spring and a nonlinear spring configuration. In this thesis, the use of non-linear vibration attachments is briefly explained, and a survey of the research done in this area is also discussed. The survey will show what have been done by the researches in this new field of nonlinear attachments. Also, it will be shown that this topic was not extensively researched and is a new type of research where no sufficient experimental work has been applied. As an application, a quarter car model was chosen to be investigated. The aim of the Thesis is to validate theoretically and experimentally the use of nonlinear springs in a quarter car model. Design the new type of suspension and insert it in the experimental set up, built from the ground up in the laboratory. A novel criterion for optimal ride comfort is the root mean square of the absolute acceleration specified by British standards ISO 2631-1997. A new way to reduce vibrations is to take advantage of nonlinear components. The mathematical model of the quarter-car is derived, and the dynamics are evaluated in terms of the main mass displacement and acceleration. The simulation of the car dynamics is performed using Matlab® and Simulink®. The realization of vibration reduction through one-way irreversible nonlinear energy localization which requires no pre-tuning in a quarter car model is studied for the first time. Results show that the addition of the nonlinear stiffness decreases the vibration of the sprung mass to meet optimal ride comfort standards. As the passenger is situated above the sprung mass, any reduction in the sprung mass dynamics will directly have the same effect on the passenger of the vehicle. The future is in the use of a nonlinear suspension that could provide improvement in performance over that realized by the passive, semi active and active suspension. The use of a quarter car model is simple compared to a half car model or a full car model, furthermore in the more complex models you can study the heave and the pitch of the vehicle. For the initial study of the nonlinear spring the quarter car model was sufficient enough to study the dynamics of the vehicle. Obtaining an optimum suspension system is of great importance for automotive and vibration engineer involved in the vehicle design process. The suspension affects an automobile’s comfort, performance, and safety. In this thesis, the optimization of suspension parameters which include the spring stiffness and damper coefficient is designed to compromise between the comfort and the road handling. Using Genetic algorithm an automated optimization of suspension parameters was executed to meet performance requirements specified. Results show that by optimizing the parameters the vibration in the system decreases immensely