42 research outputs found
Second-Order Belief Hidden Markov Models
Hidden Markov Models (HMMs) are learning methods for pattern recognition. The
probabilistic HMMs have been one of the most used techniques based on the
Bayesian model. First-order probabilistic HMMs were adapted to the theory of
belief functions such that Bayesian probabilities were replaced with mass
functions. In this paper, we present a second-order Hidden Markov Model using
belief functions. Previous works in belief HMMs have been focused on the
first-order HMMs. We extend them to the second-order model
The rise of policy coherence for development: a multi-causal approach
In recent years policy coherence for development (PCD) has become a key principle in international development debates, and it is likely to become even more relevant in the discussions on the post-2015 sustainable development goals. This article addresses the rise of PCD on the Western donors’ aid agenda. While the concept already appeared in the work of Organisation for Economic Co-operation and Development (OECD) in the early 1990s, it took until 2007 before PCD became one of the Organisation’s key priorities. We adopt a complexity-sensitive perspective, involving a process-tracing analysis and a multi-causal explanatory framework. We argue that the rise of PCD is not as contingent as it looks. While actors such as the EU, the DAC and OECD Secretariat were the ‘active causes’ of the rise of PCD, it is equally important to look at the underlying ‘constitutive causes’ which enabled policy coherence to thrive well
Solvent-surface interactions control the phase structure in laser-generated iron-gold core-shell nanoparticles
This work highlights a strategy for the one-step synthesis of FeAu nanoparticles by the pulsed laser ablation of alloy targets in the presence of different solvents. This method allows particle generation without the use of additional chemicals; hence, solvent-metal interactions could be studied without cross effects from organic surface ligands. A detailed analysis of generated particles via transmission electron microscopy in combination with EDX elemental mapping could conclusively verify that the nature of the used solvent governs the internal phase structure of the formed nanoparticles. In the presence of acetone or methyl methacrylate, a gold shell covering a non-oxidized iron core was formed, whereas in aqueous media, an Au core with an Fe3O4 shell was generated. This core-shell morphology was the predominant species found in >90% of the examined nanoparticles. These findings indicate that fundamental chemical interactions between the nanoparticle surface and the solvent significantly contribute to phase segregation and elemental distribution in FeAu nanoparticles. A consecutive analysis of resulting Fe@Au core-shell nanoparticles revealed outstanding oxidation resistance and fair magnetic and optical properties. In particular, the combination of these features with high stability magnetism and plasmonics may create new opportunities for this hybrid material in imaging applications
Four challenges in the field of alternative, radical and citizens’ media research
In January 1994 the Zapatista movement in southern Mexico inaugurated a new era of media use for dissent. Since that time, an array of dissenting collectives and individuals have appropriated media technologies in order to make their voices heard or to articulate alternative identities. From Zapatista media to the Arab Spring, social movements throughout the world are taking over, hybridizing, recycling, and adapting media technologies. This new era poses a new set of challenges for academics and researchers in the field of Communication for Social Change (CfSC). Based on examples from Mexico, Lebanon, and Colombia, this article highlights and discusses four such research challenges: accounting for historical context; acknowledging the complexity of communication processes; anchoring analysis in a political economy of information and communication technologies; and positioning new research in relation to existing knowledge and literature within the field of communication and social change.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline
Anxiety Disorders in Children and Adolescents with Autistic Spectrum Disorders: A Meta-Analysis
There is considerable evidence that children and adolescents with autistic spectrum disorders (ASD) are at increased risk of anxiety and anxiety disorders. However, it is less clear which of the specific DSM-IV anxiety disorders occur most in this population. The present study used meta-analytic techniques to help clarify this issue. A systematic review of the literature identified 31 studies involving 2,121 young people (aged <18 years) with ASD, and where the presence of anxiety disorder was assessed using standardized questionnaires or diagnostic interviews. Across studies, 39.6% of young people with ASD had at least one comorbid DSM-IV anxiety disorder, the most frequent being specific phobia (29.8%) followed by OCD (17.4%) and social anxiety disorder (16.6%). Associations were found between the specific anxiety disorders and ASD subtype, age, IQ, and assessment method (questionnaire versus interview). Implications for the identification and treatment of anxiety in young people with ASD are discussed
Anxiety Levels in Children with Autism Spectrum Disorder:A Meta-Analysis
The aim of the current study was to meta-analytically examine whether anxiety levels in children with autism spectrum disorders (ASD) are elevated. A total of 83 articles were selected from a systematic literature search and were included in the meta-analyses. Results demonstrated that children with ASD had higher anxiety levels compared to typically developing children, and this difference increased with IQ. Youth with ASD also tended to have higher anxiety levels compared to clinically referred children, and this difference increased with age. Children with ASD had higher anxiety levels compared to youth with externalizing or developmental problems, but not when compared to youth with internalizing problems. The study findings highlight the importance of more research in order to fully understand the nature and development of anxiety in children with ASD. More specifically, the results suggest that especially high-functioning adolescents with ASD may be at risk for developing anxiety disorders. Therefore, it seems important to carefully follow and monitor children with ASD transcending to adolescenc
A second-order hidden markov model for part-of-speech tagging
This paper describes an extension to the hidden Markov model for part-of-speech tagging using second-order approximations for both contex-tual and lexical probabilities. This model in-creases the accuracy of the tagger to state of the art levels. These approximations make use of more contextual information than standard statistical systems. New methods of smoothing the estimated probabilities are also introduced to address the sparse data problem.