Geometric morphometry serves biologists and anthropologists to rigorously and quantitatively describe shapes. These representations can be treated as a statistical sample, allowing the researchers to study its variability within groups and correlate it to other features. Geometric morphometry uses landmarks as the proxy for shape, with consistent semantics in each specimen. General triangle meshes do not have this property, and as such, semantically consistent remeshes must be created artificially. This thesis deals with the design of an algorithm that consistently resamples a set of surface models for the purpose of statistical analysis. Coherent point drift was employed to perform nonrigid registration, whose result is then used to generate a semantically consistent remeshes. This approach was successfully applied in a number of studies. As CPD is compute-intensive, we propose methods of accelerating both its initialization and processing phases. Also, an extension was introduced, that can map the deviation of the surfaces from perfect bilateral symmetry and analyze it in a sample, which is significant, among others, for quantification of pathologies. Manual trimming of the surfaces and merging datasets results in outlier regions in the individual surfaces and potentially large differences in their vertex...

Complex systems are designed using the model-based design paradigm in which mathematical models of systems are created and checked against specifications. Cyber-physical systems (CPS) are complex systems in which the physical environment is sensed and controlled by computational or cyber elements possibly distributed over communication networks. Various aspects of CPS design such as physical dynamics, software, control, and communication networking must interoperate correctly for correct functioning of the systems. Modeling formalisms, analysis techniques and tools for designing these different aspects have evolved independently, and remain dissimilar and disparate. There is no unifying formalism in which one can model all these aspects equally well. Therefore, model-based design of CPS must make use of a collection of models in several different formalisms and use respective analysis methods and tools together to ensure correct system design. To enable doing this in a formal manner, this thesis develops a framework for multi-model verification of cyber-physical systems based on behavioral semantics. Heterogeneity arising from the different interacting aspects of CPS design must be addressed in order to enable system-level verification. In current practice, there is no principled approach that deals with this modeling heterogeneity within a formal framework. We develop behavioral semantics to address heterogeneity in a general yet formal manner. Our framework makes no assumptions about the specifics of any particular formalism, therefore it readily supports various formalisms, techniques and tools. Models can be analyzed independently in isolation, supporting separation of concerns. Mappings across heterogeneous semantic domains enable associations between analysis results. Interdependencies across different models and specifications can be formally represented as constraints over parameters and verification can be carried out in a semantically consistent manner. Composition of analysis results is supported both hierarchically across different levels of abstraction and structurally into interacting component models at a given level of abstraction. The theoretical concepts developed in the thesis are illustrated using a case study on the hierarchical heterogeneous verification of an automotive intersection collision avoidance system.