Darbo tikslas: atlikti šunų genetinių išteklių monitoringą, įvertinti panaudojimą ir vietinių šunų veislių išsaugojimą Lietuvoje. Darbo uždaviniai: 1. Surinkti ir išanalizuoti mokslinę literatūrą apie Lietuvoje veisiamas šunų veisles. 2. Surinkti duomenis apie šunų duomenų bazes Lietuvoje. 3. Surinkti duomenis ir atlikti registruotų šunų analizę už 2008 - 2012 metus iš RegiVet duomenų bazės. 4. Surinkti duomenis ir atlikti 2008 - 2012 metais registruotų šunų analizę iš LKD duomenų bazės. Darbo naujumas: Pirmą kartą buvo atliktas registruotų Lietuvoje auginamų šunų skaičiaus monitoringas ir identifikuotos labiausiai paplitusios veislės. Išvados: 1. Gyvūnų registravimo centre 2012 metais iš viso buvo registruota 33456 gyvūnai. Vilniuje registruoti 10844 gyvūnai, iš kurių 8722 šunys. Kaune atitinkamai registruoti 14136 registruoti gyvūnai, tarp jų 12058 šunys. Klaipėdoje šunų registruota gerokai mažiau – 4219. 2. RegiVet duomenų bazėje 2012 metais iš viso buvo registruota 5375 gyvūnai: iš jų 4531 šunys, 816 kačių ir 28 kiti gyvūnai. Lygint su 2008 registruotų gyvūnų padidėjo 34 procentais. 3. Registracijos pagausėjimą lėmė visuomenes švietimas, įstatymų įteisintas visų gyvūnų privalomas ženklinimas mikroschemomis ir migracija į užsienio šalis. 4. Lietuvos kinologų draugijos duomenų bazėje 2012 metais iš viso buvo registruota 5862 šunys. Lygint su 2008 m. registruotų šunų sumažėjo 21 procentų. 5. Registracijos sumažėjimą lėmė ekonominė situacija šalyje ir migracija į užsienio... [toliau žr. visą tekstą] / Object and tasks of work: Collect and analyze scientific literature on dogs breeds that are bred on Lithuania. Collect data of Lithuanian dog database. Collect data and do 2008-2012 registered dogs analyzis from RegiVet database. Collect data and do 2008-2012 registered dogs analyzis from LCS database. Research methodology: Analysis of scientific literature, scientific articles, and statistical data. Different articles and research material offering information on the issue under consideration were used as the basis for the research. Results and conclusions. In year 2012 there were 33456 registered animals in animal register. 10844 animals were registered in Vilnius, 8722 out of them were dogs. 14136 animals were registered in Kaunas, 12058 out of them were dogs. There were a lot less registered dogs in Klaipėda – only. In 2012 there were 5375 animals registered in RegiVet database: 4531 dogs, 816 cats and 28 other animals. There was a 34% rise in registered animal compared to 2008. This rise was caused by public education, a new law which required all animals to be microchipped and migration to other countries. In 2012, there were 5862 registered dogs in Lithuanian cynological societys database. Compared to 2008, there has been a a 21% fall. Decrease in registration was caused by economic situation in the country and migration. Most popular dogs breeds in 2008 – 2012 m. were German Shepherd Dog, Yorkshire Terrier, Labrador Retriever, West Siberian Laika, French Bulldog... [to full text]

Under international law, every state has the sovereign right to establish the conditions under which it will grant its nationality to a vessel. By consequence, different schemes for ship registration have been developed, traditionally the nationalist and open system. While the nationalist system imposes strict requirements regarding national ownership and manning, along with burdensome fiscal regimes for the shipping industry, the open system offered flexible requirements and a friendly taxation environment, that help shipowners to minimize their operation costs. / Open registries have been criticized for not complying with international accepted shipping standards in safety, environmental, and labour aspects. However, some of them have made great efforts to raise these standards, mainly obliged by the new demands of the shipping industry. Nonetheless, the shift to a new culture of quality shipping is not only a responsibility of flag states, but of all the actors of a maritime scenario.

The use of complementary non-invasive imaging modalities has been proposed to track disease progression, particularly cancer, while simultaneously evaluating therapeutic efficacy. A major obstacle is a limited ability to compare parameters obtained from different modalities, especially those from exogenous contrast agents or tracers. We hypothesize that combining Magnetic Resonance Imaging (MRI) and Ultrasound (US) will improve characterization of the tumour microenvironment. In this study, we describe a co-registration apparatus that facilitates the acquisition of a priori co-registered MR and US images in vivo. This apparatus was validated using phantom data and it was found that the US slices can be selected to an accuracy of +/- 100µm translationally and +/- 2 degrees rotationally. Additionally, it was shown that MRI and US may provide complimentary information about the tumour microenvironment, but more work needs to be done to assess repeatability of dynamic contrast enhanced MRI and US.

As the capabilities of autonomous vehicles increase, their use in situations that are dangerous or dull for humans is becoming more popular. Autonomous systems are currently being used in several military and civilian domains, including search and rescue operations, disaster relief coordination, infrastructure inspection and surveillance missions. In order to perform high level mission autonomy tasks, a method is required for the vehicle to localize itself, as well as generate a map of the environment. Algorithms which allow the vehicle to concurrently localize and create a map of its surroundings are known as solutions to the Simultaneous Localization and Mapping (SLAM) problem. Certain high level tasks, such as drivability analysis and obstacle avoidance, benefit from the use of a dense map of the environment, and are typically generated with the use of point cloud data. The point cloud data is incorporated into SLAM algorithms with scan registration techniques, which determine the relative transformation between two sufficiently overlapping point clouds. The Normal Distributions Transform (NDT) algorithm is a promising method for scan registration, however many issues with the NDT approach exist, including a poor convergence basin, discontinuities in the NDT cost function, and unreliable pose estimation in sparse, outdoor environments. This thesis presents methods to overcome the shortcomings of the NDT algorithm, in both 2D and 3D scenarios. To improve the convergence basin of NDT for 2D scan registration, the Multi-Scale k-Means NDT (MSKM-NDT) algorithm is presented, which divides a 2D point cloud using k-means clustering and performs the scan registration optimization over multiple scales of clustering. The k-means clustering approach generates fewer Gaussian distributions when compared to the standard NDT algorithm, allowing for evaluation of the cost function across all Gaussian clusters. Cost evaluation across all the clusters guarantees that the optimization will converge, as it resolves the issue of discontinuities in the cost function found in the standard NDT algorithm. Experiments demonstrate that the MSKM-NDT approach can be used to register partially overlapping scans with large initial transformation error, and that the convergence basin of MSKM-NDT is superior to NDT for the same test data. As k-means clustering does not scale well to 3D, the Segmented Greedy Cluster NDT (SGC-NDT) method is proposed as an alternative approach to improve and guarantee convergence using 3D point clouds that contain points corresponding to the ground of the environment. The SGC-NDT algorithm segments the ground points using a Gaussian Process (GP) regression model and performs clustering of the non ground points using a greedy method. The greedy clustering extracts natural features in the environment and generates Gaussian clusters to be used within the NDT framework for scan registration. Segmentation of the ground plane and generation of the Gaussian distributions using natural features results in fewer Gaussian distributions when compared to the standard NDT algorithm. Similar to MSKM-NDT, the cost function can be evaluated across all the clusters in the scan, resulting in a smooth and continuous cost function that guarantees convergence of the optimization. Experiments demonstrate that the SGC-NDT algorithm results in scan registrations with higher accuracy and better convergence properties than other state-of-the-art methods for both urban and forested environments.

Medical imaging has become the key to access inside human body for the purpose of diagnosis and treatment planning. In order to understand the effectiveness of planned treatment following the diagnosis, treated body part may have to be monitored several times during a period of time. Information gained from successive imaging of body part provides guidance to next step of treatment. Comparison of images or datasets taken at different times requires registration of these images or datasets since the same conditions may not be provided at all times. Accurate segmentation of the body part under treatment is needed while comparing medical images to achieve quantitative and qualitative measurements. This segmentation task enables two dimensional and three dimensional visualizations of the region which also aid in directing the planning strategy. In this thesis, several segmentation algorithms are investigated and a hybrid segmentation algorithm is developed in order to segment bone tissue out of head CT slices for orthodontic treatment planning. Using the developed segmentation algorithm, three dimensional visualizations of segmented bone tissue out of head CT slices of two patients are obtained. Visualizations are obtained using the MATLAB Computer software&amp / #8217 / s visualization library. Besides these, methods are developed for automatic registration of twodimensional and three-dimensional CT images taken at different time periods. These methods are applied to real and synthetic data. Algorithms and methods used in this thesis are also implemented in MATLAB computer program.

&Ouml / YP processes are complex due to four different types of actors and many interdependent stages it involves. All the registration, application and placement stages are performed using a paper-based information system and the number of actors involved increases each year. As a consequence of this, collecting, storing and processing the required information becomes more difficult, error prone and insufficient. In this study, to enhance &Ouml / YP processes and to eliminate the errors and difficulties of the paper-based information system in use, a computer-based information system consisting of a web-based tool was developed, implemented and evaluated.

Computer vision tasks such as three dimensional (3D) registration, 3D modelling, and 3D object recognition are becoming more and more useful in industry, and have application such as reverse CAD engineering, and robot navigation. Each of these applications use correspondence algorithms as part of their processes. Correspondence algorithms are required to compute accurate mappings between artificial surfaces that represent actual objects or scenes. In industry, inaccurate correspondence is related to factors such as expenses in time and labour, and also safety. Therefore, it is essential to select an appropriate correspondence algorithm for a given surface matching task. However, current research in the area of surface correspondence is hampered by an abundance of applications specific algorithms, and no uniform terminology of consistent model for selecting and/or comparing algorithms. This dissertation presents a correspondence framework for surface matching algorithms. The framework is a conceptual model that is implementable. It is designed to assist in the analysis, comparison, development, and implementation of correspondence algorithms, which are essential tasks when selecting or creating an algorithm for a particular application. The primary contribution of the thesis is the correspondence framework presented as a conceptual model for surface matching algorithms. The model provides a systematic method for analysing, comparing, and developing algorithms. The dissertation demonstrates that by dividing correspondence computation into five stages: region definition, feature extraction, feature representation, local matching, and global matching, the task becomes smaller and more manageable. It also shows that the same stages of different algorithms are directly comparable. Furthermore, novel algorithms can be created by simply connecting compatible stages of different algorithms. Finally, new ideas can be synthesised by creating only the stages to be tested, without developing a while new correspondence algorithm. The secondary contribution that is outlined is the correspondence framework presented as a software design tool for surface matching algorithms. The framework is shown to reduce the complexity of implementing existing algorithms within the framework. This is done by encoding algorithms in a stage-wise procedure, whereby an algorithm is separated into the five stages of the framework. The software design tool is shown to validate the integrity of restructuring existing algorithms within it, and also provide an efficient basis for creating new algorithms. The third contribution that is made is the specification of a quality metric for algorithms comparison. The metric is used to assess the accuracy of the outcomes of a number of correspondence algorithms, which are used to match a wide variety of input surface pairs. The metric is used to demonstrate that each algorithm is application specific, and highlight the types of surfaces that can be matched by each algorithm. Thus, it is shown that algorithms that are implemented within the framework can be selected for particular surface correspondence tasks. The final contribution made is this dissertation is the expansion of the correspondence framework beyond the surface matching domain. The correspondence framework is maintained in its original form, and is used for image matching algorithms. Existing algorithms from three image matching applications are implemented and modified using the framework. It is shown how the framework provides a consistent means and uniform terminology for developing both surface and image matching algorithms. In summary, this thesis presents a correspondence framework for surface matching algorithms. The framework is general, encompassing a comprehensive set of algorithms, and flexible, expanding beyond surface matching to major image matching applications.

This thesis presents research that was conducted to develop anatomically realistic finite element models of breast deformation under a variety of gravity loading conditions to assist clinicians in tracking suspicious tissues across multiple imaging modalities. Firstly, the accuracy of the modelling framework in predicting deformations of a homogeneous body was measured using custom designed silicon gel phantoms. The model predicted surface deformations with an average RMS error of 1.5 mm +/- 0.2 mm and tracked internal marker locations with an average RMS error of 1.4 mm +/- 0.7 mm. A novel method was then developed to determine the reference configuration of a body, when given its mechanical properties, boundary conditions and a deformed configuration. The theoretical validity of the technique was confirmed with an analytic solution. The accuracy of the method was also measured using silicon gel experiments, predicting the reference configuration surface with an average RMS error of 1.3 mm +/- 0.1 mm, and tracking internal marker locations with an average error of 1.5 mm +/- 0.8 mm. Silicon gel composites were then created to measure the accuracy of standard techniques to model heterogeneity. The models did not match the experimentally recorded deformations. This highlighted the need for further validation exercises on modelling heterogeneity before modelling them in the breast. A semi-automated algorithm was developed to fit finite element models to the skin and muscle surfaces of each individual, which were segmented from breast MR images. The code represented the skin with an average RMS error of 1.46 mm +/- 0.32 mm and the muscle with an average RMS error of 1.52 mm +/- 0.3 mm. The framework was then tested using images of the breast obtained under different gravity loading conditions and neutral buoyancy. A homogeneous model was first developed using the neutral buoyancy images as a representation of the reference configuration. The model did not accurately capture the regional deformations of the breast under gravity loading. However, the gross shape of the breast was reproduced, indicating that a biomechanical model of the breast could be useful to reliably track tissues across multiple images for cancer diagnosis. / This research was sponsored by the Top Achiever Doctoral Scholarship and the University of Auckland Doctoral Scholarship. Extra funding for travel was provided by the Graduate Research Fund and the John Logan Campbell Trust Fund.

This thesis presents research that was conducted to develop anatomically realistic finite element models of breast deformation under a variety of gravity loading conditions to assist clinicians in tracking suspicious tissues across multiple imaging modalities. Firstly, the accuracy of the modelling framework in predicting deformations of a homogeneous body was measured using custom designed silicon gel phantoms. The model predicted surface deformations with an average RMS error of 1.5 mm +/- 0.2 mm and tracked internal marker locations with an average RMS error of 1.4 mm +/- 0.7 mm. A novel method was then developed to determine the reference configuration of a body, when given its mechanical properties, boundary conditions and a deformed configuration. The theoretical validity of the technique was confirmed with an analytic solution. The accuracy of the method was also measured using silicon gel experiments, predicting the reference configuration surface with an average RMS error of 1.3 mm +/- 0.1 mm, and tracking internal marker locations with an average error of 1.5 mm +/- 0.8 mm. Silicon gel composites were then created to measure the accuracy of standard techniques to model heterogeneity. The models did not match the experimentally recorded deformations. This highlighted the need for further validation exercises on modelling heterogeneity before modelling them in the breast. A semi-automated algorithm was developed to fit finite element models to the skin and muscle surfaces of each individual, which were segmented from breast MR images. The code represented the skin with an average RMS error of 1.46 mm +/- 0.32 mm and the muscle with an average RMS error of 1.52 mm +/- 0.3 mm. The framework was then tested using images of the breast obtained under different gravity loading conditions and neutral buoyancy. A homogeneous model was first developed using the neutral buoyancy images as a representation of the reference configuration. The model did not accurately capture the regional deformations of the breast under gravity loading. However, the gross shape of the breast was reproduced, indicating that a biomechanical model of the breast could be useful to reliably track tissues across multiple images for cancer diagnosis. / This research was sponsored by the Top Achiever Doctoral Scholarship and the University of Auckland Doctoral Scholarship. Extra funding for travel was provided by the Graduate Research Fund and the John Logan Campbell Trust Fund.

Detecting regions of change while reducing unimportant changes in multiple outdoor images of the same scene containing fence wires (i.e., a chain-link mesh fence) acquired by a mobile camera from slightly different viewing positions, angles and at different times is a very difficult problem. Regions of change include appearing of new objects and/or disappearing of old objects behind fence wires, breaches in the integrity of fence wires and attached objects in front of fence wires. Unimportant changes are mainly caused by camera movement, considerable background clutter, illumination variation, tiny sizes of fence wires and non-uniform illumination that occurs across fence wires. There are several issues that arise from these kinds of multiple outdoor images. The issues are: (1) parallax (the apparent displacement of an object as seen from two different positions that are not on a line with the object) among objects in the scene, (2) changing in size of same objects as a result of camera movement in forward or backward direction, (3) background clutter of outdoor scenes, (4) thinness of fence wires and (5) significant illumination variation that occurs in outdoor scenes and across fence wires. In this dissertation, an automated change detection method is proposed for these kinds of multiple outdoor images. The change detection method is composed of two distinct modules, which are a module for detecting object presence and/or absence behind fence wires and another module for detecting breaches in the integrity of fence wires and/or attached objects in front of fence wires. The first module consist of five main steps: (1) automated image registration, (2) confidence map image production by the Zitnick and Kanade algorithm, (3) occlusion map image generation, (4) significant or unimportant changes decision by the first hybrid decision-making system and (5) false positives reduction by the template subtraction approach. The second module integrates: (1) the Sobel edge detector combined with an adaptive thresholding technique in extracting edges of fence wires, (2) an area-based measuring in separating small and big objects based on their average areas determined once in the calibration process and (3) the second hybrid decision-making system in classifying objects as significant or unimportant changes. Experimental results demonstrate that the change detection method can identify and indicate approximate locations and possible percentages of significant changes whilst reducing unimportant changes in these kinds of multiple outdoor images. The study has utilized occluded regions in a confidence map image produced by the Zitnick and Kanade algorithm as potential significant changes in the image change detection research. Moreover, the study proves that the use of the Sobel edge detector combined with an adaptive thresholding technique is applicable in extracting edges of outdoor fence wires. In the future, the method could be integrated into patrol robots in order to provide assistance to human guards in protecting outdoor perimeter security. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1522689 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2010