A corpus-driven error analysis of the oral and written production of Leaving Certificate Spanish learners

The Leaving Certificate (LC) is the national, standardised state examination in Ireland necessary for entry to third level education – this presents a massive, raw corpus of data with the potential to yield invaluable insight into the phenomena of learner interlanguage. With samples of official LC Spanish examination data, this project has compiled a digitised corpus of learner Spanish comprised of the written and oral production of 100 candidates. This corpus was then analysed using a specific investigative corpus technique, Computer-aided Error Analysis (CEA, Dagneaux et al, 1998). CEA is a powerful apparatus in that it greatly facilitates the quantification and analysis of a large learner corpus in digital format. The corpus was both compiled and analysed with the use of UAM Corpus Tool (O’Donnell 2013). This Tool allows for the recording of candidate-specific variables such as grade, examination level, task type and gender, therefore allowing for critical analysis of the corpus as one unit, as separate written and oral sub corpora and also of performance per task, level and gender. This is an interdisciplinary work combining aspects of Applied Linguistics, Learner Corpus Research and Foreign Language (FL) Learning. Beginning with a review of the context of FL learning in Ireland and Europe, I go on to discuss the disciplinary context and theoretical framework for this work and outline the methodology applied. I then perform detailed quantitative and qualitative analyses before going on to combine all research findings outlining principal conclusions. This investigation does not make a priori assumptions about the data set, the LC Spanish examination, the context of FLs or of any aspect of learner competence. It undertakes to provide the linguistic research community and the domain of Spanish language learning and pedagogy in Ireland with an empirical, descriptive profile of real learner performance, characterising learner difficulty.

A facile spin-cast route for cation exchange of multilayer perpendicularly-aligned nanorod assemblies

A facile spin cast route was developed to convert perpendicularly aligned nanorod assemblies of cadmium chalcogenides into their silver and copper analogues. The assemblies are rapidly cation exchanged without affecting either the individual rod dimensions or collective superlattice order extending over several multilayers.

Improving cross language information retrieval using corpus based query suggestion approach

Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach.

Droplet etching of deep nanoholes for filling with self-aligned complex quantum structures

Strain-free epitaxial quantum dots (QDs) are fabricated by a combination of Al local droplet etching (LDE) of nanoholes in AlGaAs surfaces and subsequent hole filling with GaAs. The whole process is performed in a conventional molecular beam epitaxy (MBE) chamber. Autocorrelation measurements establish single-photon emission from LDE QDs with a very small correlation function g (2)(0)≃ 0.01 of the exciton emission. Here, we focus on the influence of the initial hole depth on the QD optical properties with the goal to create deep holes suited for filling with more complex nanostructures like quantum dot molecules (QDM). The depth of droplet etched nanoholes is controlled by the droplet material coverage and the process temperature, where a higher coverage or temperature yields deeper holes. The requirements of high quantum dot uniformity and narrow luminescence linewidth, which are often found in applications, set limits to the process temperature. At high temperatures, the hole depths become inhomogeneous and the linewidth rapidly increases beyond 640 °C. With the present process technique, we identify an upper limit of 40-nm hole depth if the linewidth has to remain below 100 μeV. Furthermore, we study the exciton fine-structure splitting which is increased from 4.6 μeV in 15-nm-deep to 7.9 μeV in 35-nm-deep holes. As an example for the functionalization of deep nanoholes, self-aligned vertically stacked GaAs QD pairs are fabricated by filling of holes with 35 nm depth. Exciton peaks from stacked dots show linewidths below 100 μeV which is close to that from single QDs.