Probabilistic models have been used extensively in the past to underpin classification algorithms in statistical pattern recognition. The most widely used model is the Gaussian distribution. However, signals of impulsive nature usually deviate from Gaussian and it is necessary to work with more realistic models. K-distribution is one of the long-tailed density which is known in the signal processing community for fitting the radar sea clutter accurately. The work presented in this thesis reflects the efforts made to model the background features, extracted from the sea images, by using a K-distribution. A novel approach for estimating the parameter of K-distribution is presented. The method utilises the empirical characteristic function, and is proven to perform better than any existing estimation technique. A classifier is then developed from the empirical characteristic function. This technique is applied to a problem of automatic target recognition with promising results.

This thesis describes the work carried out in the development and testing of parametric sonar systems for application in the fields of seabed sediment characterisation and classification, and the detection of seabed embedded objects. Parametric sonar systems offer a number of advantages over conventional sonar systems. This is especially true of the conflicting requirements of both seabed delineation and penetration required for a practical sub-seabed profiling system. Echoes from sub-bottom layers vary in strength dependent on both the boundary acoustic reflectivity and the absorption characteristics of the layer above. Absorption effects are usually frequency dependent, allowing better penetration to lower frequency signals.

The intent of this investigation is the determination of the values of the Cs-133 (n,2n)Cs-132 cross-section at neutron energies of 15.6 and 16.1 MeV. Neutrons of this energy are produced with comparative ease by means of the D-T reaction, in which deuterons of energy 500 and 750 keV, respectively, are impingent upon a tritium target.

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Previous research has shown that when observers hold a tool, they experience action-oriented visual biases in the area around this tool that are similar to visual biases that exist around the hands. Some researchers have theorized this effect is due to the tool being incorporated into the body schema following active tool use, while others argue that this effect may simply be due to the tool’s visual salience. The goal of the present study was to test these competing explanations of near-tool visual biases. In the first experiment, participants completed a target detection task under one of three conditions: 1) while holding a small rake next to one side of a monitor, preceded by an active object retrieval task; 2) while holding a rake next to a monitor, preceded by a passive looking task; or 3) with the rake placed next to a monitor by a researcher, preceded by a passive looking task. Participants detected targets near the rake faster than targets far from the rake in the first two conditions, but no target detection facilitation was seen in the third condition. Participants in Experiment 2 held a small rake next to a monitor after an active object retrieval task, but a paper shield blocked the tool from view, eliminating its visual salience. While the pattern of near-tool target detection facilitation did not significantly differ between shielded and unshielded conditions, the shield did reduce the magnitude of the near-tool effect. Taken together, these results suggest that near-tool effects cannot be driven by the visual presence of a tool alone, but they also indicate that a period of active use may not be necessary to introduce visual biases near tools.

Increased competition and increased costs of designing made it important for the firms to identify the right products and the right methods for manufacturing the products. Firms should focus on customers and identify customer demands accurately to design the right products. Several management methods and techniques that are currently available improve one or more functions or processes in an industry and do not take the complete product life cycle into consideration. On the other hand target costing is a method / philosophy that takes financial, manufacturing and customer aspects into consideration during designing phase and helps firms in making product design decisions to increase the profit / value of the company. It uses various techniques to identify customer demands, to decrease costs of manufacturing and finally to achieve strategic goals. Target costing does not replace any technique that is currently in practice for product design. But it forms an integral part of total product design / redesign based on strategic plans. The current report details the process of target costing along with some associated techniques and applies the process to the designing of the Caterpillar's D10 tractor in the late 70s / Master of Engineering

The purpose of this dissertation is to investigate the feasibility of using neural networks in conjunction with the Fourier Modified Direct Mellin Transform (FMDMT) for the recognition of ship targets. The FMDMT is a modification of the Direct Mellin Transform for digital implementations, and is applied to the magnitudes of the Discrete Fourier Transforms (DFT) of range profiles of ships. Necessity for the use of the FMDMT is corroborated by the fact that features can be extracted from the range profiles of targets, regardless of target aspect angle. Variation in aspect angle results in variation of the independent variable. Feature extraction is made possible by the scale invariant properties of the Mellin Transform. Substantial emphasis was placed on preprocessing techniques applied in the implementation of the FMDMT on simulated range profiles and in particular, real ship profiles. The FMDMT was thus examined extensively and utilised as it was developed and demonstrated in [20]. At the completion of this examination, the recognition procedures and methods were applied on simulated data with the aid of a radar simulator developed and adapted for this dissertation. Results of the recognition of simulated ship targets were scrutinized closely and recorded. Employment of this procedure afforded the ability to compare the recognition results for real ship data with those of simulated ship data at a later stage. Acquisition of a large database of ship profiles was made successful by a ship target data capture plan implemented at the Institute for Maritime Technology (IMT) in Simon's Town. The database included the radar range profile data for the SAS Protea and the Outeniqua, which carried out several successful full circular manoeuvres in the line of sight of the search radar utilised (Raytheon). The relevant ships performed these circular manoeuvres in order that the acquired data incorporate radar range profiles of the relevant ships at most aspect angles from 0 degrees to 360 degrees. Extensive and thorough testing of the performance of the FMDMT would thus be possible since every possible aspect angle would be scrutinized. Preprocessing of data and recognition of targets was implemented in exactly the same manner and order as was the case with the simulated ship data. Extensive examination of the FMDMT revealed that the MDMT should only be applied to one side of a real and even Fourier Transform of a ship target. Literature on the FMDMT had failed to elaborate on this point. Comparison of the recognition results for real and simulated data, indicates a great similarity in success, thus validating the methods and procedures described theoretically and adopted practically for preprocessing of the radar range profiles and recognition of the targets. In order to demonstrate the feasibility of ship target recognition using the procedures and methods incorporated in the dissertation, real ship data for an entire range of different ships should be acquired in the same manner as indicated above. Bibliography: pages 117-118.

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Target tracking refers to the process of estimating the state of a moving object from remote and noisy measurements. In this thesis we consider the Bayesian filtering framework to perform target tracking under nonlinear models, a target moving in continuous time, and measurements that are available in discrete time intervals (known as continuous-discrete). The Bayesian filtering theory establishes the mathematical basis to obtain the posterior probability density function of the state, given the measurement history. This probability density function contains all the information required about the state of the target. It is well documented that there is no exact solution for posterior density under the models mentioned. Hence, the approximation of such density functions have been studied for over four decades. The literature demonstrates that this has led to the development of multiple filters. In target tracking, due to the remote sensing performed, an additional complication emerges. The measurements received are not always from the desired target and could have originated from unknown sources, thus making the tracking more difficult. This problem is known as a measurement origin uncertainty. Additionally to the filters, different methods have been proposed to address the measurement origin uncertainty due to its negative impact, which could cause a false track. Unfortunately, a final solution has yet to be achieved. The first proposal of this thesis is a new approximate Bayesian filter for continuous-discrete systems. The new filter is a higher accuracy version of the cubature Kalman filter. This filter is developed using a fifth-degree spherical radial cubature rule and the Ito-Taylor expansion of order 1.5 for dealing with stochastic differential equations. The second proposal is an improved version of the probabilistic data association method. The proposed method utilizes the maximum likelihood values for selecting the measurements that are used for the data association. In the first experiment, the new filter is tested in a challenging 3-dimensional turn model, demonstrating superiority over other existing filters. In a second and third experiments, the proposed data association method is tested for target tracking in a 2-dimensional scenarios under heavy measurement origin uncertainty conditions. The second and third experiments demonstrate the superiority of the proposed data association method compared to the probabilistic data association. / Thesis / Doctor of Philosophy (PhD)

The workshop is organized by the Nuclear Physics Institute of Academy of Sciences of the Czech Republic, public research institution, together with the Institute of Radiopharmaceutical Cancer Research of Helmholtz-Center Dresden-Rossendorf and in cooperation with the International Atomic Energy Agency (IAEA) and the support of many private sponsors. It is rather symbolic that Czech and German research institutions joined now freely their powers in order to organize this event.