INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 932 authors who have published 2618 publications receiving 37658 citations.

An ontology-based approach to conflict resolution in Home and Building Automation Systems

Abstract: Ambient intelligent systems such as Home and Building Automation Systems (HBAS) are becoming evermore accepted and capable of actuating automatically on behalf of users to fulfil their requests or enable activities. However, when multiple users interact with such systems, the requirements of activities often interfere resulting in conflicting actuations which HBAS ought to automatically detect and resolve. Yet, despite recent advances in HBAS, no ambient intelligent solution has been reported that is adequately grounded on knowledge analysis. The contributions of this article are twofold. First, it reviews relevant literature on Ambient Intelligence, conflict detection, conflict resolution and knowledge representation in HBAS. Second, it proposes and validates an ontological framework for conflict detection and resolution backed by knowledge-based analysis. Effectively, the proposed solution performs automatic environment actuations maximizing users comfort and energy efficiency.

Exploiting Phone Log-Likelihood Ratio Features for the Detection of the Native Language of Non-Native English Speakers.

Abstract: Detecting the native language (L1) of non-native English speakers may be of great relevance in some applications, such as computer assisted language learning or IVR services. In fact, the L1 detection problem closely resembles the problem of spoken language and dialect recognition. In particular, log-likelihood ratios of phone posterior probabilities, known as Phone LogLikelihood Ratios (PLLR), have been recently introduced as features for spoken language recognition systems. This representation has proven to be an effective way of retrieving acousticphonotactic information at frame-level, which allows for its use in state-of-the-art systems, that is, in i-vector systems. In this paper, we explore the use of PLLR-based i-vector systems for L1 native language detection. We also investigate several linear and non-linear L1 classification schemes on top of the PLLR ivector front-ends. Moreover, we compare PLLR based systems with both conventional phonotactic systems based on n-gram modelling of phoneme sequences and acoustic-based i-vector systems. Finally, the potential complementarity of the different approaches is investigated based on a set of system fusion experiments.

Using a Grid for Digital Preservation

Abstract: Digital preservation aims at maintaining digital objects and data accessible over long periods of time. Data grids provide several functionalities required by digital preservation systems, especially when massive amounts of data must be preserved, as in e-Science domains. We propose the use of existing data grid solutions to build frameworks for digital preservation. In this paper we survey the main threats to digital preservation, which are used to identify a central point of failure in the metadata catalog of the iRODS data grid solution. We propose three extensions to the iRODS framework, to overcome the shortcomings of iRODS when used as a digital preservation system.

Exploiting Total Order Multicast in Weakly Consistent Transactional Caches

Abstract: Nowadays, distributed in-memory caches are increasingly used as a way to improve the performance of applications that require frequent access to large amounts of data. In order to maximize performance and scalability, these platforms typically rely on weakly consistent partial replication mechanisms. These schemes partition the data across the nodes and ensure a predefined (and typically very small) replication degree, thus maximizing the global memory capacity of the platform and ensuring that the cost to ensure replica consistency remains constant as the scale of the platform grows. Moreover, even though several of these platforms provide transactional support, they typically sacrifice consistency, ensuring guarantees that are weaker than classic 1-copy serializability, but that allow for more efficient implementations. This paper proposes and evaluates two partial replication techniques, providing different (weak) consistency guarantees, but having in common the reliance on total order multicast primitives to serialize transactions without incurring in distributed deadlocks, a main source of inefficiency of classical two-phase commit (2PC) based replication mechanisms. We integrate the proposed replication schemes into Infinispan, a prominent open-source distributed in-memory cache, which represents the reference clustering solution for the well-known JBoss AS platform. Our performance evaluation highlights speed-ups of up to 40x when using the proposed algorithms with respect to the native Infinispan replication mechanism, which relies on classic 2PC-based replication.