Thinking and acting both globally and locally : The Field School in intercultural education as a model for action-research training and civic learning.

We present the Field School model of intercultural civic education, service-learning, action research training, and collaboration (with local academic and community partners) based on field work in applied anthropology. Theoretical and methodological foundations of the Field School also include experiential learning and immersive pedagogy, multiculturalism and cross-cultural communication, international education and study abroad programs, collaborative international development, participatory research, and in-depth knowledge in one’s own specific discipline. The primary goals of these intensive, short-term action research projects in other, less-developed countries or regions are benefits for community partners that are as sustainable as possible and to foster and assess learning experiences of students. The Peabody-Vanderbilt Field School in Intercultural Education began in Ecuador and Argentina, but we focus on Field Schools in China, rural New Mexico, and South Africa. In Guangxi, P.R.C., U.S. and Chinese students learned to navigate political and cultural complexities to study migration, community needs and assets assessment, and health effects of changing diet on children, and assisted English language learning in schools, a university and a factory. Native American students from Gallup, NM, and students from Nashville, TN, travelled to each other’s locale to study the impact of diabetes in each culture and develop health education and other prevention strategies. In Cape Town, SA, students worked on health and education projects in three townships; we focus here on a collaboration with high school staff to study and reduce the high dropout rate. We analyze Field School impacts on local community partners and student-researchers

Spoken term detection ALBAYZIN 2014 evaluation: overview, systems, results, and discussion

The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1186/s13636-015-0063-8Spoken term detection (STD) aims at retrieving data from a speech repository given a textual representation of the search term. Nowadays, it is receiving much interest due to the large volume of multimedia information. STD differs from automatic speech recognition (ASR) in that ASR is interested in all the terms/words that appear in the speech data, whereas STD focuses on a selected list of search terms that must be detected within the speech data. This paper presents the systems submitted to the STD ALBAYZIN 2014 evaluation, held as a part of the ALBAYZIN 2014 evaluation campaign within the context of the IberSPEECH 2014 conference. This is the first STD evaluation that deals with Spanish language. The evaluation consists of retrieving the speech files that contain the search terms, indicating their start and end times within the appropriate speech file, along with a score value that reflects the confidence given to the detection of the search term. The evaluation is conducted on a Spanish spontaneous speech database, which comprises a set of talks from workshops and amounts to about 7 h of speech. We present the database, the evaluation metrics, the systems submitted to the evaluation, the results, and a detailed discussion. Four different research groups took part in the evaluation. Evaluation results show reasonable performance for moderate out-of-vocabulary term rate. This paper compares the systems submitted to the evaluation and makes a deep analysis based on some search term properties (term length, in-vocabulary/out-of-vocabulary terms, single-word/multi-word terms, and in-language/foreign terms).This work has been partly supported by project CMC-V2 (TEC2012-37585-C02-01) from the Spanish Ministry of Economy and Competitiveness. This research was also funded by the European Regional Development Fund, the Galician Regional Government (GRC2014/024, “Consolidation of Research Units: AtlantTIC Project” CN2012/160)

Synchronization patterns in LIF neuron networks: merging nonlocal and diagonal connectivity

Abstract: The effects of nonlocal and reflecting connectivities have been previously investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which assimilate the exchange of electrical signals between neurons. In this work, we investigate the effect of diagonal coupling inspired by findings in brain neuron connectivity. Multi-chimera states are reported both for the simple diagonal and combined nonlocal–diagonal connectivities, and we determine the range of optimal parameter regions where chimera states appear. Overall, the measures of coherence indicate that as the coupling range increases (below all-to-all coupling) the emergence of chimera states is favored and the mean phase velocity deviations between coherent and incoherent regions become more prominent. A number of novel synchronization phenomena are induced as a result of the combined connectivity. We record that for coupling strengths σ < 1 the synchronous regions have mean phase velocities lower than the asynchronous, while the opposite holds for σ > 1. In the intermediate regime, σ ~ 1, the oscillators have common mean phase velocity (i.e., are frequency-locked) but different phases (i.e., they are phase-asynchronous). Solitary states are recorded for small values of the coupling strength, which grow into chimera states as the coupling strength increases. We determine parameter values where the combined effects of nonlocal and diagonal coupling generate chimera states with two different levels of synchronous domains mediated by asynchronous regions. © 2018, EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature

On the Minimization of Concave Information Functionals for Unsupervised Classification via Decision Trees Abstract

A popular method for unsupervised classification of high-dimensional data via decision trees is characterized as minimizing the empirical estimate of a concave information functional. It is shown that minimization of such functionals under the true distributions leads to perfect classification. Key words: Decision trees, clustering, unsupervised classification, information functionals, disjoint supports