Design study of MovementSlicer : an interactive visualization of patterns and group meetings in 2D movement data

Movement data collected through GPS or other technologies is increasingly common, but is difficult to visualize due to overplotting and occlusion of movements when displayed on 2D maps. An additional challenge is the extraction of useful higher-level information (such as meetings) derived from the raw movement data. We present a design study of MovementSlicer, a tool for visualizing the places visited, and behaviors of, individual actors, and also the meetings between multiple actors. We first present a taxonomy of visualizations of movement data, and then consider tasks to support when analyzing movement data and especially meetings of multiple actors. We argue that Gantt charts have many advantages for understanding the movements and meetings of small groups of moving entities, and present the design of a Gantt chart that can nest people within locations or locations within people along the vertical axis, and show time along the horizontal axis. The rows of our Gantt chart are sorted by activity level and can be filtered using a weighted adjacency matrix showing meetings between people. Empty time intervals in the Gantt chart can be automatically folded, with smoothly animated transitions, yielding a multi-focal view. Case studies demonstrate the utility of our prototype

Advanced Biometrics with Deep Learning

Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others

Modelling biomolecules through atomistic graphs: theory, implementation, and applications

Describing biological molecules through computational models enjoys ever-growing popularity. Never before has access to computational resources been easier for scientists across the natural sciences. The need for accurate, efficient, and robust modelling tools is therefore irrefutable. This, in turn, calls for highly interdisciplinary research, which the thesis presented here is a product of. Through the successful marriage of techniques from mathematical graph theory, theoretical insights from chemistry and biology, and the tools of modern computer science, we are able to computationally construct accurate depictions of biomolecules as atomistic graphs, in which individual atoms become nodes and chemical bonds/interactions are represented by weighted edges. When combined with methods from graph theory and network science, this approach has previously been shown to successfully reveal various properties of proteins, such as dynamics, rigidity, multi-scale organisation, allostery, and protein-protein interactions, and is well poised to set new standards in terms of computational feasibility, multi-scale resolution (from atoms to domains) and time-scales (from nanoseconds to milliseconds). Therefore, building on previous work in our research group spanning over 15 years and to further encourage and facilitate research into this growing field, this thesis's main contribution is to provide a formalised foundation for the construction of atomistic graphs. The most crucial aspect of constructing atomistic graphs of large biomolecules compared to small molecules is the necessity to include a variety of different types of bonds and interactions, because larger biomolecules attain their unique structural layout mainly through weaker interactions, e.g. hydrogen bonds, the hydrophobic effect or π-π interactions. Whilst most interaction types are well-studied and have readily available methodology which can be used to construct atomistic graphs, this is not the case for hydrophobic interactions. To fill this gap, the work presented herein includes novel methodology for encoding the hydrophobic effect in atomistic graphs, that accounts for the many-body effect and non-additivity. Then, a standalone software package for constructing atomistic graphs from structural data is presented. Herein lies the heart of this thesis: the combination of a variety of methodologies for a range of bond/interaction types, as well as an implementation that is deterministic, easy-to-use and efficient. Finally, some promising avenues for utilising atomistic graphs in combination with graph theoretical tools such as Markov Stability as well as other approaches such as Multilayer Networks to study various properties of biomolecules are presented.Open Acces

Application of clustering analysis and sequence analysis on the performance analysis of parallel applications

High Performance Computing and Supercomputing is the high end area of the computing science that studies and develops the most powerful computers available. Current supercomputers are extremely complex so are the applications that run on them. To take advantage of the huge amount of computing power available it is strictly necessary to maximize the knowledge we have about how these applications behave and perform. This is the mission of the (parallel) performance analysis. In general, performance analysis toolkits oUer a very simplistic manipulations of the performance data. First order statistics such as average or standard deviation are used to summarize the values of a given performance metric, hiding in some cases interesting facts available on the raw performance data. For this reason, we require the Performance Analytics, i.e. the application of Data Analytics techniques in the performance analysis area. This thesis contributes with two new techniques to the Performance Analytics Veld. First contribution is the application of the cluster analysis to detect the parallel application computation structure. Cluster analysis is the unsupervised classiVcation of patterns (observations, data items or feature vectors) into groups (clusters). In this thesis we use the cluster analysis to group the CPU burst of a parallel application, the regions on each process in-between communication calls or calls to the parallel runtime. The resulting clusters obtained are the diUerent computational trends or phases that appear in the application. These clusters are useful to understand the behaviour of computation part of the application and focus the analyses to those that present performance issues. We demonstrate that our approach requires diUerent clustering algorithms previously used in the area. Second contribution of the thesis is the application of multiple sequence alignment algorithms to evaluate the computation structure detected. Multiple sequence alignment (MSA) is technique commonly used in bioinformatics to determine the similarities across two or more biological sequences: DNA or roteins. The Cluster Sequence Score we introduce applies a Multiple Sequence Alignment (MSA) algorithm to evaluate the SPMDiness of an application, i.e. how well its computation structure represents the Single Program Multiple Data (SPMD) paradigm structure. We also use this score in the Aggregative Cluster Re-Vnement, a new clustering algorithm we designed, able to detect the SPMD phases of an application at Vne-grain, surpassing the cluster algorithms we used initially. We demonstrate the usefulness of these techniques with three practical uses. The Vrst one is an extrapolation methodology able to maximize the performance metrics that characterize the application phases detected using a single application execution. The second one is the use of the computation structure detected to speedup in a multi-level simulation infrastructure. Finally, we analyse four production-class applications using the computation characterization to study the impact of possible application improvements and portings of the applications to diUerent hardware conVgurations. In summary, this thesis proposes the use of cluster analysis and sequence analysis to automatically detect and characterize the diUerent computation trends of a parallel application. These techniques provide the developer / analyst an useful insight of the application performance and ease the understanding of the application’s behaviour. The contributions of the thesis are not reduced to proposals and publications of the techniques themselves, but also practical uses to demonstrate their usefulness in the analysis task. In addition, the research carried out during these years has provided a production tool for analysing applications’ structure, part of BSC Tools suite

3D seismic analysis of the geometry and development of a deep water fold and thrust belt

This thesis uses industry 3D seismic to investigate the nature and distribution of strain in a deep water fold and thrust belt and describes the complex fault plane and stratal geometries that result from fold and thrust linkage. The principal aim is to gain a better understanding of the structural architecture and evolution of toe-of-slope compressional settings. To this end, the project represents a logical series of arguments involving the study of individual structures and fold and fault pairs, to considering a fold belt as a whole. The outer thrust belt of the Niger Delta is observed to comprise of synthetic and antithetic faults that interact and link along strike. A preliminary geometric classification is proposed for antithetic thrust fault linkage zones based on observations of fault surface and stratal geometries. The relationship between fault interaction and fold characteristics is also investigated. The connectivity of stratigraphic horizons across fault surfaces and through transfer zones is shown to vary with the type of linkage and with depth. Conclusions drawn on the along strike variability of fault network density, orientation and vertical extent are shown to have significant application to modelling of fluid flow. The concept of numerous and geometrically distinct thrust fault linkages forming through-going folds is developed through the investigation of a single isolated fold that comprises a number of linking forethrusts and backthrusts. This case study, involving the quantification of the development of this relatively simple structure, allows conclusions to be drawn on fold growth that are later applied to a more complex and closely spaced fold belt. The internal structural geometry of faults and stratigraphic horizons within the single fold are described though detailed three-dimensional mapping. The analysis of the distribution of fault and fold strain, both on individual thrusts within the fold and for the structure as a whole, suggest efficient displacement transfer between numerous linking faults that accommodated shortening as a coherent unit. In addition to this, variations in the magnitude of fault heave are compensated by complementary trends in fold strain. A study of syn-kinematic units demonstrates that the single structural culmination present today was initially made up of a number of folds with local structural highs. Major thrust surfaces within the fold are also interpreted to be the product of the along strike linkage and amalgamation of initially distinct faults. These observations made on the isolated fold are applied to a complex, closely spaced fold belt. The relative timing of individual faults and folds agree with established models of a progressive foreland propagating sequence of thrust faults but also display out-of-sequence events. Findings demonstrate a significant period of synchronous development between all structures in the fold belt. Aggregation of fault and fold shortening profiles indicate that displacement transfer occurs along strike and also in a dip-parallel direction between within the fold belt. Bulk shortening is thus conserved along strike within the syn-kinematic units and low lateral heave gradients suggest efficient displacement transfer between all constituent structures. The evidence presented here shows that all elements of a fold belt can be kinematically linked during growth. Irregularities in the distribution of deformation in pre-kinematic units corroborate findings that the folds are the product of along strike linkage of discrete segments, in a similar manner to that documented in extensional systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

3D seismic analysis of the geometry and development of a deep water fold and thrust belt

This thesis uses industry 3D seismic to investigate the nature and distribution of strain in a deep water fold and thrust belt and describes the complex fault plane and stratal geometries that result from fold and thrust linkage. The principal aim is to gain a better understanding of the structural architecture and evolution of toe-of-slope compressional settings. To this end, the project represents a logical series of arguments involving the study of individual structures and fold and fault pairs, to considering a fold belt as a whole. The outer thrust belt of the Niger Delta is observed to comprise of synthetic and antithetic faults that interact and link along strike. A preliminary geometric classification is proposed for antithetic thrust fault linkage zones based on observations of fault surface and stratal geometries. The relationship between fault interaction and fold characteristics is also investigated. The connectivity of stratigraphic horizons across fault surfaces and through transfer zones is shown to vary with the type of linkage and with depth. Conclusions drawn on the along strike variability of fault network density, orientation and vertical extent are shown to have significant application to modelling of fluid flow. The concept of numerous and geometrically distinct thrust fault linkages forming through-going folds is developed through the investigation of a single isolated fold that comprises a number of linking forethrusts and backthrusts. This case study, involving the quantification of the development of this relatively simple structure, allows conclusions to be drawn on fold growth that are later applied to a more complex and closely spaced fold belt. The internal structural geometry of faults and stratigraphic horizons within the single fold are described though detailed three-dimensional mapping. The analysis of the distribution of fault and fold strain, both on individual thrusts within the fold and for the structure as a whole, suggest efficient displacement transfer between numerous linking faults that accommodated shortening as a coherent unit. In addition to this, variations in the magnitude of fault heave are compensated by complementary trends in fold strain. A study of syn-kinematic units demonstrates that the single structural culmination present today was initially made up of a number of folds with local structural highs. Major thrust surfaces within the fold are also interpreted to be the product of the along strike linkage and amalgamation of initially distinct faults. These observations made on the isolated fold are applied to a complex, closely spaced fold belt. The relative timing of individual faults and folds agree with established models of a progressive foreland propagating sequence of thrust faults but also display out-of-sequence events. Findings demonstrate a significant period of synchronous development between all structures in the fold belt. Aggregation of fault and fold shortening profiles indicate that displacement transfer occurs along strike and also in a dip-parallel direction between within the fold belt. Bulk shortening is thus conserved along strike within the syn-kinematic units and low lateral heave gradients suggest efficient displacement transfer between all constituent structures. The evidence presented here shows that all elements of a fold belt can be kinematically linked during growth. Irregularities in the distribution of deformation in pre-kinematic units corroborate findings that the folds are the product of along strike linkage of discrete segments, in a similar manner to that documented in extensional systems

Novel class discovery meets foundation models for 3D semantic segmentation

The task of Novel Class Discovery (NCD) in semantic segmentation entails training a model able to accurately segment unlabelled (novel) classes, relying on the available supervision from annotated (base) classes. Although extensively investigated in 2D image data, the extension of the NCD task to the domain of 3D point clouds represents a pioneering effort, characterized by assumptions and challenges that are not present in the 2D case. This paper represents an advancement in the analysis of point cloud data in four directions. Firstly, it introduces the novel task of NCD for point cloud semantic segmentation. Secondly, it demonstrates that directly transposing the only existing NCD method for 2D image semantic segmentation to 3D data yields suboptimal results. Thirdly, a new NCD approach based on online clustering, uncertainty estimation, and semantic distillation is presented. Lastly, a novel evaluation protocol is proposed to rigorously assess the performance of NCD in point cloud semantic segmentation. Through comprehensive evaluations on the SemanticKITTI, SemanticPOSS, and S3DIS datasets, the paper demonstrates substantial superiority of the proposed method over the considered baselines.Comment: arXiv admin note: substantial text overlap with arXiv:2303.1161