A Scalable and Extensible Framework for Superposition-Structured Models

In many learning tasks, structural models usually lead to better interpretability and higher generalization performance. In recent years, however, the simple structural models such as lasso are frequently proved to be insufficient. Accordingly, there has been a lot of work on "superposition-structured" models where multiple structural constraints are imposed. To efficiently solve these "superposition-structured" statistical models, we develop a framework based on a proximal Newton-type method. Employing the smoothed conic dual approach with the LBFGS updating formula, we propose a scalable and extensible proximal quasi-Newton (SEP-QN) framework. Empirical analysis on various datasets shows that our framework is potentially powerful, and achieves super-linear convergence rate for optimizing some popular "superposition-structured" statistical models such as the fused sparse group lasso

Scene integration for online VR advertising clouds

This paper presents a scene composition approach that allows the combinational use of standard three dimensional objects, called models, in order to create X3D scenes. The module is an integral part of a broader design aiming to construct large scale online advertising infrastructures that rely on virtual reality technologies. The architecture addresses a number of problems regarding remote rendering for low end devices and last but not least, the provision of scene composition and integration. Since viewers do not keep information regarding individual input models or scenes, composition requires the consideration of mechanisms that add state to viewing technologies. In terms of this work we extended a well-known, open source X3D authoring tool

Management and Visualisation of Non-linear History of Polygonal 3D Models

The research presented in this thesis concerns the problems of maintenance and revision control of large-scale three dimensional (3D) models over the Internet. As the models grow in size and the authoring tools grow in complexity, standard approaches to collaborative asset development become impractical. The prevalent paradigm of sharing files on a file system poses serious risks with regards, but not limited to, ensuring consistency and concurrency of multi-user 3D editing. Although modifications might be tracked manually using naming conventions or automatically in a version control system (VCS), understanding the provenance of a large 3D dataset is hard due to revision metadata not being associated with the underlying scene structures. Some tools and protocols enable seamless synchronisation of file and directory changes in remote locations. However, the existing web-based technologies are not yet fully exploiting the modern design patters for access to and management of alternative shared resources online. Therefore, four distinct but highly interconnected conceptual tools are explored. The first is the organisation of 3D assets within recent document-oriented No Structured Query Language (NoSQL) databases. These "schemaless" databases, unlike their relational counterparts, do not represent data in rigid table structures. Instead, they rely on polymorphic documents composed of key-value pairs that are much better suited to the diverse nature of 3D assets. Hence, a domain-specific non-linear revision control system 3D Repo is built around a NoSQL database to enable asynchronous editing similar to traditional VCSs. The second concept is that of visual 3D differencing and merging. The accompanying 3D Diff tool supports interactive conflict resolution at the level of scene graph nodes that are de facto the delta changes stored in the repository. The third is the utilisation of HyperText Transfer Protocol (HTTP) for the purposes of 3D data management. The XML3DRepo daemon application exposes the contents of the repository and the version control logic in a Representational State Transfer (REST) style of architecture. At the same time, it manifests the effects of various 3D encoding strategies on the file sizes and download times in modern web browsers. The fourth and final concept is the reverse-engineering of an editing history. Even if the models are being version controlled, the extracted provenance is limited to additions, deletions and modifications. The 3D Timeline tool, therefore, implies a plausible history of common modelling operations such as duplications, transformations, etc. Given a collection of 3D models, it estimates a part-based correspondence and visualises it in a temporal flow. The prototype tools developed as part of the research were evaluated in pilot user studies that suggest they are usable by the end users and well suited to their respective tasks. Together, the results constitute a novel framework that demonstrates the feasibility of a domain-specific 3D version control

MULTI-X, a State-of-the-Art Cloud-Based Ecosystem for Biomedical Research

With the exponential growth of clinical data, and the fast development of AI technologies, researchers are facing unprecedented challenges in managing data storage, scalable processing, and analysis capabilities for heterogeneous multisourced datasets. Beyond the complexity of executing data-intensive workflows over large-scale distributed data, the reproducibility of computed results is of paramount importance to validate scientific discoveries. In this paper, we present MULTIX, a cross-domain research-oriented platform, designed for collaborative and reproducible science. This cloud-based framework simplifies the logistical challenges of implementing data analytics and AI solutions by providing pre-configured environments with ad-hoc scalable computing resources and secure distributed storage, to efficiently build, test, share and reproduce scientific pipelines. An exemplary use-case in the area of cardiac image analysis will be presented together with the practical application of the platform for the analysis of ~20.000 subjects of the UK-Biobank database

A survey of secure middleware for the Internet of Things

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area