979 resultados para Semantic differential
Resumo:
Driven by new network and middleware technologies such as mobile broadband, near-field communication, and context awareness the so-called ambient lifestyle will foster innovative use cases in different domains. In the EU project Hydra high-level security, trust and privacy concerns such as loss of control, profiling and surveillance are considered at the outset. At the end of this project the. Hydra middleware development platform will have been designed so as to enable developers to realise secure ambient scenarios. This paper gives a short introduction to the Hydra project and its approach to ensure security by design. Based on the results of a focus group analysis of the user domain "building automation" typical threats are evaluated and their risks are assessed. Then, specific security requirements with respect to security, privacy, and trust are derived in order to incorporate them into the Hydra Security Meta-Model. How concepts such as context, semantic resolution of security, and virtualisation support the overall Hydra approach will be introduced and illustrated on the basis of it technical building automation scenario.
Resumo:
Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.
Resumo:
Differential Evolution (DE) is a tool for efficient optimisation, and it belongs to the class of evolutionary algorithms, which include Evolution Strategies and Genetic Algorithms. DE algorithms work well when the population covers the entire search space, and they have shown to be effective on a large range of classical optimisation problems. However, an undesirable behaviour was detected when all the members of the population are in a basin of attraction of a local optimum (local minimum or local maximum), because in this situation the population cannot escape from it. This paper proposes a modification of the standard mechanisms in DE algorithm in order to change the exploration vs. exploitation balance to improve its behaviour.
Resumo:
Increasingly, distributed systems are being used to host all manner of applications. While these platforms provide a relatively cheap and effective means of executing applications, so far there has been little work in developing tools and utilities that can help application developers understand problems with the supporting software, or the executing applications. To fully understand why an application executing on a distributed system is not behaving as would be expected it is important that not only the application, but also the underlying middleware, and the operating system are analysed too, otherwise issues could be missed and certainly overall performance profiling and fault diagnoses would be harder to understand. We believe that one approach to profiling and the analysis of distributed systems and the associated applications is via the plethora of log files generated at runtime. In this paper we report on a system (Slogger), that utilises various emerging Semantic Web technologies to gather the heterogeneous log files generated by the various layers in a distributed system and unify them in common data store. Once unified, the log data can be queried and visualised in order to highlight potential problems or issues that may be occurring in the supporting software or the application itself.
Resumo:
Search engines exploit the Web's hyperlink structure to help infer information content. The new phenomenon of personal Web logs, or 'blogs', encourage more extensive annotation of Web content. If their resulting link structures bias the Web crawling applications that search engines depend upon, there are implications for another form of annotation rapidly on the rise, the Semantic Web. We conducted a Web crawl of 160 000 pages in which the link structure of the Web is compared with that of several thousand blogs. Results show that the two link structures are significantly different. We analyse the differences and infer the likely effect upon the performance of existing and future Web agents. The Semantic Web offers new opportunities to navigate the Web, but Web agents should be designed to take advantage of the emerging link structures, or their effectiveness will diminish.
Resumo:
A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models.
Resumo:
We investigate the spectrum of certain integro-differential-delay equations (IDDEs) which arise naturally within spatially distributed, nonlocal, pattern formation problems. Our approach is based on the reformulation of the relevant dispersion relations with the use of the Lambert function. As a particular application of this approach, we consider the case of the Amari delay neural field equation which describes the local activity of a population of neurons taking into consideration the finite propagation speed of the electric signal. We show that if the kernel appearing in this equation is symmetric around some point a= 0 or consists of a sum of such terms, then the relevant dispersion relation yields spectra with an infinite number of branches, as opposed to finite sets of eigenvalues considered in previous works. Also, in earlier works the focus has been on the most rightward part of the spectrum and the possibility of an instability driven pattern formation. Here, we numerically survey the structure of the entire spectra and argue that a detailed knowledge of this structure is important within neurodynamical applications. Indeed, the Amari IDDE acts as a filter with the ability to recognise and respond whenever it is excited in such a way so as to resonate with one of its rightward modes, thereby amplifying such inputs and dampening others. Finally, we discuss how these results can be generalised to the case of systems of IDDEs.
Resumo:
Transforming growth factor-β (TGF-β) is synthesised as an inactive precursor protein; this is cleaved to produce the mature peptide and a latency associated protein (LAP), which remains associated with the mature peptide until activation by LAP degradation. Isoform specific antibodies raised against the LAPs for TGF-β2and -β3were used to determine the myocardial levels of LAP (activatable TGF-β) and full length precursor (inactive TGF-β) forms during post-natal development in the rat. TGF-β2was present predominantly as the precursor in 2 day old myocardium. There was an age-dependent shift from precursor protein to LAP between 2 and 28 days. A corresponding increase in the level of mature (activatable) TGF-β2was found. TGF-β3was detected in significant quantities only as LAP. However, a four-fold increase in the expression of TGF-β3LAP was observed between 2 and 28 days. The substantial increases in activatable forms of TGF-β2and -β3that occur in myocardium during the first 28 days of life in the rat support a role for these proteins in post-natal cardiac development.
Resumo:
The transforming growth factorβ(TGFβ) superfamily plays an important role in the myocardial response to hypertrophy. We have investigated the protein expression of TGFβ1,β2andβ3in left ventricular tissue, and determined their subcellular distribution in myocytes by immunoblotting and immunocytochemistry during the development of left ventricular hypertrophy (LVH), using isoform specific antibodies to TGFβ1,β2andβ3. LVH was produced in rats by aortic constriction (AC) and LV tissue was obtained at days (d)0, 1, 3, 7, 14, 21 and 42 following operation. Compared with age matched sham-operated controls (SH), TGFβ1levels in LV tissue of AC rats increased significantly from d1–d14 (P<0.03) concomitant with the adaptive growth of LV tissue. In contrast, TGFβ3levels decreased in LV tissue of AC rats from d3 post-operation (significant from d14–d42,P<0.03). No significant difference in TGFβ2levels were observed from SH and AC rats after operation. Antibodies to TGFβ1stained intercalated disks, sarcolemmal membranes and cytoplasm, but not nuclei, of cardiomyocytes on LV sections from untreated and SH rats. However, a trans-localisation of TGFβ1to the nuclei of cardiomyocytes was observed in AC hearts. Antibodies to TGFβ3stained T tubules, cytoplasm and the nuclei of cardiomyocytes from untreated and SH rats. However, by d7 post-AC operation, TGFβ3expression was lost rapidly from nuclei of cardiomyocytes followed by a reduction in total TGFβ3immunofluorescence in myocytes. Antibodies to TGFβ2stained sarcolemmal membranes of cardiomyocytes from both SH and AC rats without significant difference between groups. Thus, the differential pattern of protein expression and subcellular distribution of TGFβ1,β2andβ3in myocytes during the development of LVH suggests that these molecules play different roles in the response of cardiomyocytes to LVH.