The present work investigates the applicability of Genetic Algorithms (GA) to the problem of signal propagation in Native Neuronal Networks (NNNs). These networks are comprised of neurons, some of which receive input signals. The signals propagate though the network by transmission between neurons. The research focuses on the regeneration of the output signal of the network without knowing the original input signal. The computational complexity of the problem is prohibitive for the exact computation. We propose to use a heuristic approach called Genetic Algorithm. Three algorithms are developed, based on the GA technique. The developed algorithms are tested on two different networks with varying input signals. The results obtained from the testing indicate significantly better performance of the developed algorithms compared to the Uniform Random Search (URS) technique, which is used as a control group. The importance of the research is in the demonstration of the ability of GA-based algorithms to successfully solve the problem at hand.

This thesis proposes a bearing condition monitoring system using acceleration and acoustic emission (AE) signals. Bearings are perhaps the most omnipresent machine elements and their condition is often critical to the success of an operation or process. Consequently, there is a great need for a timely knowledge of the health status of bearings. Generally, bearing monitoring is the prediction of the component's health or status based on signal detection, processing and classification in order to identify the causes of the problem. As the monitoring system uses both acceleration and acoustic emission signals, it is considered a multi-sensor system. This has the advantage that not only do the two sensors provide increased reliability they also permit a larger range of rotating speeds to be monitored successfully. When more than one sensor is used, if one fails to work properly the other is still able to provide adequate monitoring. Vibration techniques are suitable for higher rotating speeds whilst acoustic emission techniques for low rotating speeds. Vibration techniques investigated in this research concern the use of the continuous wavelet transform (CWT), a joint time- and frequency domain method, This gives a more accurate representation of the vibration phenomenon than either time-domain analysis or frequency- domain analysis. The image processing technique, called binarising, is performed to produce binary image from the CWT transformed image in order to reduce computational time for classification. The back-propagation neural network (BPNN) is used for classification. The AE monitoring techniques investigated can be categorised, based on the features used, into: 1) the traditional AE parameters of energy, event duration and peak amplitude and 2) the statistical parameters estimated from the Weibull distribution of the inter-arrival times of AE events in what is called the STL method. Traditional AE parameters of peak amplitude, energy and event duration are extracted from individual AE events. These events are then ordered, selected and normalised before the selected events are displayed in a three-dimensional Cartesian feature space in terms of the three AE parameters as axes. The fuzzy C-mean clustering technique is used to establish the cluster centres as signatures for different machine conditions. A minimum distance classifier is then used to classify incoming AE events into the different machine conditions. The novel STL method is based on the detection of inter-arrival times of successive AE events. These inter-arrival times follow a Weibull distribution. The method provides two parameters: STL and L63 that are derived from the estimated Weibull parameters of the distribution's shape (y), characteristic life (0) and guaranteed life (to). It is found that STL and 43 are related hyperbolically. In addition, the STL value is found to be sensitive to bearing wear, the load applied to the bearing and the bearing rotating speed. Of the three influencing factors, bearing wear has the strongest influence on STL and L63. For the proposed bearing condition monitoring system to work, the effects of load and speed on STL need to be compensated. These issues are resolved satisfactorily in the project.

Firms in highly dynamic environments focusing on innovation in their products and services, often encounter elevated amounts of uncertainty regarding the future direction of technological change. Finding reliable and imbedded information enhances a firm’s ability to tackle new markets and take advantage of possible hidden opportunities. To reduce uncertainty, obtain hidden knowledge, and gain competitive advantage, environmental scanning, which is one of the main components of foresight, is recommended by scholars of strategic management. The process of detecting weak signals for shedding light what one authority calls “blurry future zones” (Day & Schoemaker, 2005, p.1) has currently been receiving attention in environmental scanning studies. Some studies emphasize the importance of the subject; yet they offer few practical methodologies for actual cases. To help address this gap, this research introduces a new approach for detecting weak signals during Internet-based environmental scanning by applying the Cluto toolkit (see Section 4.7) plus using human judgment. This novel methodology is applied to the application of Micro Tiles, a recent innovative product of a digital display company located in Ontario, Canada, Christie Digital Company. In the conduct of this exploratory research, about 40,000 HTML pages were retrieved from the Internet in a search during 2009. To extract weak signals information from the retrieved unstructured texts, documents were grouped into a number of clusters by the CLUTO software. Two subject matter experts compared and evaluated the cluster results for the purpose of finding potentially relevant information in regard to the company’s strategic intent. Analyzing the clusters, the experts reduced the number of clustered documents from the original corpus into smaller sets with the goal of finding more relevant and unexpected documents (weak signals). The relevancy and expectedness of information in documents were two measurements as related to weak signals. The trends of the study indicate that as anticipated both experts found more unexpected documents in the smaller sets rather than the larger ones. Moreover, regarding one expert’s analysis, the smaller sets contain documents that are more relevant to the domain of interest. Overall, according to one expert, documents existing in the smaller sets display more weak signals. This emerging methodology offers a practical procedure to apply web-based information in the development of a company’s environmental scanning procedures. Using this methodology, managers can employ both computer tools and human sense-making methods to detect potential weak signals and reduce certain biases in the detection process.

Use of modern traffic signal coordination has now been proved by its performance to reduce the total delay, increase driving speed and provide the smoothness of driving significantly. To provide more possibility of success in any traffic development including traffic signal coordination, traffic analytical and modelling software packages are now the best answer. This thesis illustrates the practical using of aaSIDRA and PARAMICS in development of traffic signal coordination on Sri-Jan Road, Khon Kaen City Thailand. The fixed-time signal plan with bandwidth maximization strategy is selected for the studied corridor. Two essential steps in the development are: determination of signal plans and cycle times using Version 2.1 aaSIDRA Micro-analytical software package; and determination of coordination offsets by using Version 5.1 PARAMICS Micro-simulation software package. The PARAMICS is also using in the evaluation of actual and improved traffic condition on Sri-Jan corridor. The results show that the newly proper signal plans and offsets produces significant improvements on the traffic conditions of the Sri-Jan Road. Recommendations on the motorcycle impacts and the projection of future traffic condition have also been provided for further study. / Thesis (MTransportSysEngineering)--University of South Australia, 2006.

Transport systems can be modelled and analysed with two techniques namely analytical and simulation. Until recently, aaSIDRA was the leader in the traffic modelling and analysis software based on analytical theory at micro scale. However, it cannot be used for more than one intersection. Meanwhile, the PARAMICS, AIMSUN NG and VISSIM are micro simulation software which are widely used in modelling and analysing transport systems. Further, CUBE Dynasim is also micro simulation software. It is created by Dynalogic in France and integrated in CUBE by Citilabs, UK. However, this software is relatively new compared to PARAMICS, AIMSUN NG or VISSIM. It is able to model multi nodes and multi modals transport system. The version of software used in this research is CUBE Dynasim 1.4.9 released in 2004 aaSIDRA 2.0 version 2.0.0.205. / Thesis (MTransportSysEngineering)--University of South Australia, 2005.

Problems in the demodulation of one, two, and three-dimensional signals are investigated. In one-dimensional linear systems the analytic signal and the Hilbert transform are central to the understanding of both modulation and demodulation. However, it is shown that an efficient nonlinear algorithm exists which is not explicable purely in terms of an approximation to the Hilbert transform. The algorithm is applied to the problem of finding the envelope peak of a white light interferogram. The accuracy of peak location is then shown to compare favourably with conventional, but less efficient, techniques. In two dimensions (2-D) the intensity of a wavefield yields to a phase demodulation technique equivalent to direct phase retrieval. The special symmetry of a Helmholtz wavefield allows a unique inversion of an autocorrelation. More generally, a 2-D (non-Helmholtz) fringe pattern can be demodulated by an isotropic 2-D extension of the Hilbert transform that uses a spiral phase signum function. The range of validity of the new transform is established using the asymptotic method of stationary phase. Simulations of the algorithm confirm that deviations from the ideal occur where the fringe pattern curvature is larger than the fringe frequency. A new self-calibrating algorithm for arbitrary sequences of phase-shifted interferograms is developed using the aforementioned spiral phase transform. The algorithm is shown to work even with discontinuous fringe patterns, which are known to seriously hamper other methods. Initial simulations of the algorithm indicate an accuracy of 5 milliradians is achievable. Previously undocumented connections between the demodulation techniques are uncovered and discussed.

Thesis (Ph. D.)--Ohio University, June, 1998. / Title from PDF t.p.

Dissertation (Ph.D.) -- University of Texas Southwestern Medical Center at Dallas, 2008. / Vita. Bibliography: p. 141-151.

Thesis (M.S.)--University of Alabama at Birmingham, 2008. / Description based on contents viewed Feb. 10, 2009; title from PDF t.p. Includes bibliographical references (p. 55-58).

Thesis (M.S.)--University of Alabama at Birmingham, 2008. / Description based on contents viewed Oct. 8, 2008; title from PDF t.p. Includes bibliographical references (p. 58-60).