An encoding approach was designed to track developmentally disabled clients through a continuum of services in a service delivery system. Exact matching offiles is ofprimary importance, as data files are linked together and used in decisions regarding client service plans. After four years of use, the reliability of the encoding system was evaluated and found to be an effective means of tracking clients through a service delivery system.
We present a color matching method that, given two different views of the same scene taken by two cameras with unknown settings and unknown internal parameter values, and encoded with unknown non-linear curves, is able to correct the colors of one of the images making it look as if it was captured under the other camera's settings. Our method is based on treating the in-camera color processing pipeline as a matrix multiplication followed by a non-linearity. This allows us to model a color stabilization transformation among the two shots by estimating several parameters. The method is fast and the results have no spurious colors. It outperforms the state-of-the-art both visually and according to several metrics, and can handle very challenging real-life examples. ; This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 761544 (project HDR4EU) and under grant agreement number 780470 (project SAUCE), and by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE).
Chemosensory pathways correspond to major signal transduction mechanisms and can be classified into the functional families flagellum-mediated taxis, type four pili-mediated taxis or pathways with alternative cellular functions (ACF). CheR methyltransferases are core enzymes in all of these families. CheR proteins fused to tetratricopeptide repeat (TPR) domains have been reported and we present an analysis of this uncharacterized family. We show that CheR-TPRs are widely distributed in GRAM-negative but almost absent from GRAM-positive bacteria. Most strains contain a single CheR-TPR and its abundance does not correlate with the number of chemoreceptors. The TPR domain fused to CheR is comparatively short and frequently composed of 2 repeats. The majority of CheR-TPR genes were found in gene clusters that harbor multidomain response regulators in which the REC domain is fused to different output domains like HK, GGDEF, EAL, HPT, AAA, PAS, GAF, additional REC, HTH, phosphatase or combinations thereof. The response regulator architectures coincide with those reported for the ACF family of pathways. Since the presence of multidomain response regulators is a distinctive feature of this pathway family, we conclude that CheR-TPR proteins form part of ACF type pathways. The diversity of response regulator output domains suggests that the ACF pathways form a superfamily which regroups many different regulatory mechanisms, in which all CheR-TPR proteins appear to participate. In the second part we characterize WspC of Pseudomonas putida, a representative example of CheR-TPR. The affinities of WspC-Pp for S-adenosylmethionine and Sadenosylhomocysteine were comparable to those of prototypal CheR, indicating that WspC-Pp activity is in analogy to prototypal CheRs controlled by product feed-back inhibition. The removal of the TPR domain did not impact significantly on the binding constants and consequently not on the product feed-back inhibition. WspC-Pp was found to be monomeric, which rules out a role of the TPR domain in self-association ; This work has been funded by research projects from the Andalusian regional government Junta de Andalucı´a (grants P09-RNM-4509 and CVI-7335 to T.K.), the Spanish Ministry for Economy and Competitiveness (grant Bio2010-16937 to T.K.) and from the BBVA Foundation (grant BIOCON08 185/09 to T.K.) ; Peer reviewed
Programa Oficial de Doutoramento en Computación . 5009V01 ; [Abstract] This thesis presents new methods for recasting dependency parsing as a sequence labeling task yielding a viable alternative to the traditional transition- and graph-based approaches. It is shown that sequence labeling parsers provide several advantages for dependency parsing, such as: (i) a good trade-off between accuracy and parsing speed, (ii) genericity which enables running a parser in generic sequence labeling software and (iii) pluggability which allows using full parse trees as features to downstream tasks. The backbone of dependency parsing as sequence labeling are the encodings which serve as linearization methods for mapping dependency trees into discrete labels, such that each token in a sentence is associated with a label. We introduce three encoding families comprising: (i) head selection, (ii) bracketing-based and (iii) transition-based encodings which are differentiated by the way they represent a dependency tree as a sequence of labels. We empirically examine the viability of the encodings and provide an analysis of their facets. Furthermore, we explore the feasibility of leveraging external complementary data in order to enhance parsing performance. Our sequence labeling parser is endowed with two kinds of representations. First, we exploit the complementary nature of dependency and constituency parsing paradigms and enrich the parser with representations from both syntactic abstractions. Secondly, we use human language processing data to guide our parser with representations from eye movements. Overall, the results show that recasting dependency parsing as sequence labeling is a viable approach that is fast and accurate and provides a practical alternative for integrating syntax in NLP tasks. ; [Resumen] Esta tesis presenta nuevos métodos para reformular el análisis sintáctico de dependencias como una tarea de etiquetado secuencial, lo que supone una alternativa viable a los enfoques tradicionales basados en transiciones y grafos. Se demuestra que los analizadores de etiquetado secuencial ofrecen varias ventajas para el análisis sintáctico de dependencias, como por ejemplo (i) un buen equilibrio entre la precisión y la velocidad de análisis, (ii) la genericidad que permite ejecutar un analizador en un software genérico de etiquetado secuencial y (iii) la conectividad que permite utilizar el árbol de análisis completo como características para las tareas posteriores. El pilar del análisis sintáctico de dependencias como etiquetado secuencial son las codificaciones que sirven como métodos de linealización para transformar los árboles de dependencias en etiquetas discretas, de forma que cada token de una frase se asocia con una etiqueta. Introducimos tres familias de codificación que comprenden: (i) selección de núcleos, (ii) codificaciones basadas en corchetes y (iii) codificaciones basadas en transiciones que se diferencian por la forma en que representan un árbol de dependencias como una secuencia de etiquetas. Examinamos empíricamente la viabilidad de las codificaciones y ofrecemos un análisis de sus facetas. Además, exploramos la viabilidad de aprovechar datos complementarios externos para mejorar el rendimiento del análisis sintáctico. Dotamos a nuestro analizador sintáctico de dos tipos de representaciones. En primer lugar, explotamos la naturaleza complementaria de los paradigmas de análisis sintáctico de dependencias y constituyentes, enriqueciendo el analizador sintáctico con representaciones de ambas abstracciones sintácticas. En segundo lugar, utilizamos datos de procesamiento del lenguaje humano para guiar nuestro analizador con representaciones de los movimientos oculares. En general, los resultados muestran que la reformulación del análisis sintáctico de dependencias como etiquetado de secuencias es un enfoque viable, rápido y preciso, y ofrece una alternativa práctica para integrar la sintaxis en las tareas de PLN. ; [Resumo] Esta tese presenta novos métodos para reformular a análise sintáctica de dependencias como unha tarefa de etiquetaxe secuencial, o que supón unha alternativa viable aos enfoques tradicionais baseados en transicións e grafos. Demóstrase que os analizadores de etiquetaxe secuencial ofrecen varias vantaxes para a análise sintáctica de dependencias, por exemplo (i) un bo equilibrio entre a precisión e a velocidade de análise, (ii) a xenericidade que permite executar un analizador nun software xenérico de etiquetaxe secuencial e (iii) a conectividade que permite empregar a árbore de análise completa como características para as tarefas posteriores. O piar da análise sintáctica de dependencias como etiquetaxe secuencial son as codificacións que serven como métodos de linealización para transformar as árbores de dependencias en etiquetas discretas, de forma que cada token dunha frase se asocia cunha etiqueta. Introducimos tres familias de codificación que comprenden: (i) selección de núcleos, (ii) codificacións baseadas en corchetes e (iii) codificacións baseadas en transicións que se diferencian pola forma en que representan unha árbore de dependencia como unha secuencia de etiquetas. Examinamos empíricamente a viabilidade das codificacións e ofrecemos unha análise das súas facetas. Ademais, exploramos a viabilidade de aproveitar datos complementarios externos para mellorar o rendemento da análise sintáctica. O noso analizador sintáctico de etiquetaxe secuencial está dotado de dous tipos de representacións. En primeiro lugar, explotamos a natureza complementaria dos paradigmas de análise sintáctica de dependencias e constituíntes e enriquecemos o analizador sintáctico con representacións de ambas abstraccións sintácticas. En segundo lugar, empregamos datos de procesamento da linguaxe humana para guiar o noso analizador con representacións dos movementos oculares. En xeral, os resultados mostran que a reformulación da análise sintáctico de dependencias como etiquetaxe de secuencias é un enfoque viable, rápido e preciso, e ofrece unha alternativa práctica para integrar a sintaxe nas tarefas de PLN. ; This work has been carried out thanks to the funding from the European Research Council (ERC), under the European Union's Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150).
IntroductionDiagnostic codes, such as the ICD-10, may be considered as sensitive information. If such codes have to be encoded using current methods for data linkage, all hierarchical information given by the code positions will be lost. We present a technique (HPBFs) for preserving the hierarchical information of the codes while protecting privacy. The new method modifies a widely used Privacy-preserving Record Linkage (PPRL) technique based on Bloom filters for the use with hierarchical codes.
Objectives and ApproachAssessing the similarities of hierarchical codes requires considering the code positions of two codes in a given diagnostic hierarchy. The hierarchical similarities of the original diagnostic code pairs should correspond closely to the similarity of the encoded pairs of the same code.
Furthermore, to assess the hierarchy-preserving properties of an encoding, the impact on similarity measures from differing code positions at all levels of the code hierarchy can be evaluated. A full match of codes should yield a higher similarity than partial matches.
Finally, the new method is tested against ad-hoc solutions as an addition to a standard PPRL setup. This is done using real-world mortality data with a known link status of two databases.
ResultsIn all applications for encoded ICD codes where either categorical discrimination, relational similarity or linkage quality in a PPRL setting is required, HPBFs outperform other known methods. Lower mean differences and smaller confidence intervals between clear-text codes and encrypted code pairs were observed, indicating better preservation of hierarchical similarities. Finally, using these techniques allows for much better hierarchical discrimination for partial matches.
ConclusionThe new technique yields better linkage results than all other known methods to encrypt hierarchical codes. In all tests, comparing categorical discrimination, relational similarity and PPRL linkage quality, HPBFs outperformed methods currently used.
Abstract We analyze the description of the polite language in the early 17th century Japanese grammars, mainly the 'large' grammar (1604–1608) by the missionaries João Rodrigues 'Tçuzu' [the interpreter], S.J. (1562–1633), and the Japanese grammar (1632) by Diego Collado, O.P. (late 16th century–1638). Over 350 years of the Pragmatics established as a linguistic domain, one of the first Japanese dictionaries (1603–1604) introduced the designation of honorific particles and honored verbs. Rodrigues developed this terminology considerably, having analyzed accurately social and linguistic relationships and ways of Japanese reverence and politeness. He proposed an innovative linguistic terminology, inexistent in former European grammars and dictionaries, of which a part was followed by Collado: honorific and humble or humiliative particles, honored and humble verbs, honorable or honorific and low pronouns. Rodrigues also paid special attention to the women's specific forms of address, describing their own 'particles'. To sum up, the earlier 17th century Japanese grammars described pioneeringly what nowadays has been called as the Politeness Principle of Japanese or the honorific language of Japanese, termed as Keigo (respect language) or, academically, Taigū Hyōgen (treatment expressions).
AbstractThe present experiments focused on how orthographic processing develops during reading acquisition. Specifically, a large, cross‐sectional sample of children from grade 2 to grade 4 was exposed to pairs of words, pseudowords, digit strings, and pseudo‐letter (Armenian) strings while their sensitivity to transpositions (T) and substitutions (S) of internal characters was investigated in a perceptual matching task. The results showed that the development of identity and position decoding diverged between the four stimulus categories. Most importantly, sensitivity improved with longer exposure to formal education and higher reading level to both S and T pairs for digit strings, but only to S pairs for words and pseudowords. The results were successfully reproduced in two small independent samples. We propose a general framework, the Adaptive Specialization Hypothesis, to accommodate the results. According to this hypothesis, the transposed‐letter effect is not a hard‐wired feature of the orthographic processing system but an adaptive response of the developing orthographic system to the constraints of lexical access in several orthographies.
