Robust ASR using Support Vector Machines

The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-margin training paradigm have led us to suggest them as a good technique for robust speech recognition. However, important shortcomings have had to be circumvented, the most important being the normalisation of the time duration of different realisations of the acoustic speech units. In this paper, we have compared two approaches in noisy environments: first, a hybrid HMM–SVM solution where a fixed number of frames is selected by means of an HMM segmentation and second, a normalisation kernel called Dynamic Time Alignment Kernel (DTAK) first introduced in Shimodaira et al. [Shimodaira, H., Noma, K., Nakai, M., Sagayama, S., 2001. Support vector machine with dynamic time-alignment kernel for speech recognition. In: Proc. Eurospeech, Aalborg, Denmark, pp. 1841–1844] and based on DTW (Dynamic Time Warping). Special attention has been paid to the adaptation of both alternatives to noisy environments, comparing two types of parameterisations and performing suitable feature normalisation operations. The results show that the DTA Kernel provides important advantages over the baseline HMM system in medium to bad noise conditions, also outperforming the results of the hybrid system.Publicad

Explaining Support Vector Machines: A Color Based Nomogram.

PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models. OBJECTIVE: In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto) not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables. RESULTS: Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant). When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable. CONCLUSIONS: This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method

Agents in decentralised information ecosystems: the DIET approach

The complexity of the current global information infrastructure requires novel means of understanding and exploiting the dynamics of information. One means may be through the concept of an information ecosystem. An information ecosystem is analo gous to a natural ecosystem in which there are flo ws of materials and energy analo gous to information flow between many interacting individuals. This paper describes a multi-agent platform, DIET (Decentralised Information Ecosystem Technologies) that can be used to implement open, robust, adaptive and scalable ecosystem-inspired systems. We describe the design principles of the DIET software architecture, and present a simple example application based upon it. We go on to consider how the DIET system can be used to develop information brokering agents, and how these can contribute to the implementation of economic interactions between agents, as well as identifying some open questions relating to research in these areas. In this way we show the capacity of the DIET system to support applications using information agents.Future and Emerging Technologies arm of the IST Programme of the European Union, under the FET Proactive Initiative – Universal Information Ecosystems (FET, 1999), through project DIET (IST -1999-10088), BTexaCT Intelligent Systems Laboratory for stimulating discussion and comment

Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

<p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K_d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P²= 0.67-0.73; for new kinases it ranged P²_kin= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P²= 0.47, P²_kin= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p

International lower limb collaborative (INTELLECT) study: a multicentre, international retrospective audit of lower extremity open fractures

Trauma remains a major cause of mortality and disability across the world1, with a higher burden in developing nations2. Open lower extremity injuries are devastating events from a physical3, mental health4, and socioeconomic5 standpoint. The potential sequelae, including risk of chronic infection and amputation, can lead to delayed recovery and major disability6. This international study aimed to describe global disparities, timely intervention, guideline-directed care, and economic aspects of open lower limb injuries

Ética Profesional y Responsabilidad Social Universitaria

este libro compila reflexiones y experiencias en responsabilidad social y ética profesional desde instituciones de Educación Superior. La responsabilidad social universitaria, como ámbito de investigación y de desarrollo conceptual y metodológico es transversal a las universidades, tanto desde el punto de vista organizacional, como desde el misional e investigativo. Quienes impulsen la responsabilidad social, requieren de ética profesional, que debe ser la clave para la construcción de principios que guíen a empresarios, políticos, gestores sociales, investigadores, entre otros, para lograr consensuar el a veces difícil equilibrio entre el bien común y el desarrollo personal

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Gestión del conocimiento. Perspectiva multidisciplinaria. Volumen 8

El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, volumen 8, de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro es una publicación internacional, seriada, continua, arbitrada de acceso abierto a todas las áreas del conocimiento, que cuenta con el esfuerzo de investigadores de varios países del mundo, orientada a contribuir con procesos de gestión del conocimiento científico, tecnológico y humanístico que consoliden la transformación del conocimiento en diferentes escenarios, tanto organizacionales como universitarios, para el desarrollo de habilidades cognitivas del quehacer diario. La gestión del conocimiento es un camino para consolidar una plataforma en las empresas públicas o privadas, entidades educativas, organizaciones no gubernamentales, ya sea generando políticas para todas las jerarquías o un modelo de gestión para la administración, donde es fundamental articular el conocimiento, los trabajadores, directivos, el espacio de trabajo, hacia la creación de ambientes propicios para el desarrollo integral de las instituciones