Integrating Learning And Visualization Technologies In Orthopaedics:- Establishing The Virtual Orthopaedic European University

Digital technologies offer a working environment for familiarisation with new surgical procedures and management of clinical case audit. Our aim is to provide a novel route for access to educational material that more closely resembles the working practice of the arthroscopist. This is to support higher surgical training and life long learning. The proof of concept has been the development of a shoulder arthroscopy simulation model as an interface for the surgical trainee to access multimedia based educational orthopaedic modules. This demonstrates a human-computer interface that more closely resembles the process of factual knowledge association during clinical procedures, moving toward the ultimate goal of seamless integration of knowledge repositories with clinical intervention operative video information, integrating the structured surgical course model with the multimedia educational orthopaedic modules, generated for the learning of shoulder surgery

Adaptive Compressed Sensing for Support Recovery of Structured Sparse Sets

This paper investigates the problem of recovering the support of structured signals via adaptive compressive sensing. We examine several classes of structured support sets, and characterize the fundamental limits of accurately recovering such sets through compressive measurements, while simultaneously providing adaptive support recovery protocols that perform near optimally for these classes. We show that by adaptively designing the sensing matrix we can attain significant performance gains over non-adaptive protocols. These gains arise from the fact that adaptive sensing can: (i) better mitigate the effects of noise, and (ii) better capitalize on the structure of the support sets.Comment: to appear in IEEE Transactions on Information Theor

Beyond Good and Evil: Formalizing the Security Guarantees of Compartmentalizing Compilation

Compartmentalization is good security-engineering practice. By breaking a large software system into mutually distrustful components that run with minimal privileges, restricting their interactions to conform to well-defined interfaces, we can limit the damage caused by low-level attacks such as control-flow hijacking. When used to defend against such attacks, compartmentalization is often implemented cooperatively by a compiler and a low-level compartmentalization mechanism. However, the formal guarantees provided by such compartmentalizing compilation have seen surprisingly little investigation. We propose a new security property, secure compartmentalizing compilation (SCC), that formally characterizes the guarantees provided by compartmentalizing compilation and clarifies its attacker model. We reconstruct our property by starting from the well-established notion of fully abstract compilation, then identifying and lifting three important limitations that make standard full abstraction unsuitable for compartmentalization. The connection to full abstraction allows us to prove SCC by adapting established proof techniques; we illustrate this with a compiler from a simple unsafe imperative language with procedures to a compartmentalized abstract machine.Comment: Nit

Corrupted Sensing with Sub-Gaussian Measurements

This paper studies the problem of accurately recovering a structured signal from a small number of corrupted sub-Gaussian measurements. We consider three different procedures to reconstruct signal and corruption when different kinds of prior knowledge are available. In each case, we provide conditions for stable signal recovery from structured corruption with added unstructured noise. The key ingredient in our analysis is an extended matrix deviation inequality for isotropic sub-Gaussian matrices.Comment: To appear in Proceedings of IEEE International Symposium on Information Theory 201

Branch-coverage testability transformation for unstructured programs

Test data generation by hand is a tedious, expensive and error-prone activity, yet testing is a vital part of the development process. Several techniques have been proposed to automate the generation of test data, but all of these are hindered by the presence of unstructured control flow. This paper addresses the problem using testability transformation. Testability transformation does not preserve the traditional meaning of the program, rather it deals with preserving test-adequate sets of input data. This requires new equivalence relations which, in turn, entail novel proof obligations. The paper illustrates this using the branch coverage adequacy criterion and develops a branch adequacy equivalence relation and a testability transformation for restructuring. It then presents a proof that the transformation preserves branch adequacy