Abstract
The Portuguese General Directorate for Book, Archives and Libraries (DGLAB) has selected CIDOC CRM as the basis for its next-generation digital archive management software. Given the ontological foundations of the Conceptual Reference Model (CRM), a graph database or a triplestore was seen as the best candidate to represent a CRM-based data model for the new software. We thus decided to compare several of these databases, based on their maturity, features, performance in standard tasks and, most importantly, the Object-Graph Mappers (OGM) available to interact with each database in an object-oriented way. Our conclusions are drawn not only from a systematic review of related works but from an experimental scenario. For our experiment, we designed a simple CRM-compliant graph designed to test the ability of each OGM/database combination to tackle the so-called diamond-problem in Object-Oriented Programming (OOP) to ensure that property instances follow domain and range constraints. Our results show that (1) ontological consistency enforcement in graph databases and triplestores is much harder to achieve than in a relational database, making them more suited to an analytical rather than a transactional role; (2) OGMs are still rather immature solutions; and (3) neomodel, an OGM for the Neo4j graph database, is the most mature solution in the study as it satisfies all requirements, although it is also the least performing.

Abstract
In parallel ray tracing, techniques fall into one of two camps: imageparallel techniques aim at increasing frame rate by replicating scene data across nodes and splitting the rendering work across different ranks, and data-parallel techniques aim at increasing the size of the model that can be rendered by splitting the model across multiple ranks, but typically cannot scale much in frame rate. We propose and evaluate a hybrid approach that combines the advantages of both by splitting a set of N x M ranks into M islands of N ranks each and using data-parallel rendering within each island and image parallelism across islands. We discuss the integration of this concept into four wildly different parallel renderers and evaluate the efficacy of this approach based on multiple different data sets.

Abstract
Programs with a continuous state space or that interact with physical processes often require notions of equivalence going beyond the standard binary setting in which equivalence either holds or does not hold. In this paper we explore the idea of equivalence taking values in a quantale V, which covers the cases of (in)equations and (ultra)metric equations among others. Our main result is the introduction of a V-equational deductive system for linear ?-calculus together with a proof that it is sound and complete (in fact, an internal language) for a class of enriched autonomous categories. In the case of inequations, we get an internal language for autonomous categories enriched over partial orders. In the case of (ultra)metric equations, we get an internal language for autonomous categories enriched over (ultra)metric spaces. We use our results to obtain examples of inequational and metric equational systems for higher-order programs that contain real-time and probabilistic behaviour.

Abstract
The prevalence and availability of cloud infrastructures has made them the de facto solution for storing and archiving data, both for organizations and individual users. Nonetheless, the cloud's wide spread adoption is still hindered by dependability and security concerns, particularly in applications with large data collections where efficient search and retrieval services are also major requirements. This leads to an increased tension between security, efficiency, and search expressiveness. In this article we tackle this tension by proposing BISEN, a new provably-secure boolean searchable symmetric encryption scheme that improves these three complementary dimensions by exploring the design space of isolation guarantees offered by novel commodity hardware such as Intel SGX, abstracted as Isolated Execution Environments (IEEs). BISEN is the first scheme to support multiple users and enable highly expressive and arbitrarily complex boolean queries, with minimal information leakage regarding performed queries and accessed data, and verifiability regarding fully malicious adversaries. Furthermore, BISEN extends the traditional SSE model to support filter functions on search results based on generic metadata created by the users. Experimental validation and comparison with the state of art shows that BISEN provides better performance with enriched search semantics and security properties.

Abstract

Abstract