Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

El paisaje cultural inisecular : construcción ad hoc de metodología para análisis de valor productivo del paisaje en la producción de vivienda masiva en Mendoza, Argentina

Fil: Zalazar, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas

MIRACLE’s Ad-Hoc and Geographical IR Approaches for CLEF 2006

This paper presents the 2006 Miracle team’s approaches to the Ad-Hoc and Geographical Information Retrieval tasks. A first set of runs was obtained using a set of basic components. Then, by putting together special combinations of these runs, an extended set was obtained. With respect to previous campaigns some improvements have been introduced in our system: an entity recognition prototype is integrated in our tokenization scheme, and the performance of our indexing and retrieval engine has been improved. For GeoCLEF, we tested retrieving using geo-entity and textual references separately, and then combining them with different approaches.

MIRACLE at Ad-Hoc CLEF 2005: Merging and Combining Without Using a Single Approach

This paper presents the 2005 Miracle’s team approach to the Ad-Hoc Information Retrieval tasks. The goal for the experiments this year was twofold: to continue testing the effect of combination approaches on information retrieval tasks, and improving our basic processing and indexing tools, adapting them to new languages with strange encoding schemes. The starting point was a set of basic components: stemming, transforming, filtering, proper nouns extraction, paragraph extraction, and pseudo-relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. Second-order combinations were also tested, by averaging or selective combination of the documents retrieved by different approaches for a particular query. In the multilingual track, we concentrated our work on the merging process of the results of monolingual runs to get the overall multilingual result, relying on available translations. In both cross-lingual tracks, we have used available translation resources, and in some cases we have used a combination approach.

An energy efficient adaptive HELLO algorithm for mobile ad hoc networks

HELLO protocol or neighborhood discovery is essential in wireless ad hoc networks. It makes the rules for nodes to claim their existence/aliveness. In the presence of node mobility, no fix optimal HELLO frequency and optimal transmission range exist to maintain accurate neighborhood tables while reducing the energy consumption and bandwidth occupation. Thus a Turnover based Frequency and transmission Power Adaptation algorithm (TFPA) is presented in this paper. The method enables nodes in mobile networks to dynamically adjust both their HELLO frequency and transmission range depending on the relative speed. In TFPA, each node monitors its neighborhood table to count new neighbors and calculate the turnover ratio. The relationship between relative speed and turnover ratio is formulated and optimal transmission range is derived according to battery consumption model to minimize the overall transmission energy. By taking advantage of the theoretical analysis, the HELLO frequency is adapted dynamically in conjunction with the transmission range to maintain accurate neighborhood table and to allow important energy savings. The algorithm is simulated and compared to other state-of-the-art algorithms. The experimental results demonstrate that the TFPA algorithm obtains high neighborhood accuracy with low HELLO frequency (at least 11% average reduction) and with the lowest energy consumption. Besides, the TFPA algorithm does not require any additional GPS-like device to estimate the relative speed for each node, hence the hardware cost is reduced.

Terminología bilingüe y documentación ad hoc para intérpretes de conferencias. Una aproximación metodológica basada en corpus

El intérprete de conferencias debe llevar a cabo un trabajo documental antes, durante y después de los eventos en los que presta sus servicios, independientemente de su subcompetencia extralingüística. Desafortunadamente, pocas son las propuestas metodológicas que se hayan planteado para que este profesional pueda realizar esta tarea de manera sistemática. En el presente artículo, repasamos algunos de los trabajos que se han referido a las posibilidades que tiene el intérprete de satisfacer sus necesidades informativas. Una vez reseñada la mencionada escasez de propuestas, presentamos, en un estudio de caso, una aproximación metodológica a este trabajo de documentación, fundamentada en la compilación de corpus paralelos ad hoc y la extracción terminológica en forma de glosarios.

La Oscilación del Mediterráneo Occidental: un patrón de teleconexión ad hoc para el este de la Península Ibérica

Se presenta el origen y la historia de la propuesta de un nuevo patrón de teleconexión, la Oscilación del Mediterráneo Occidental (WeMO), presentado por el autor en 2002 y aceptado internacionalmente en 2006. El índice de la WeMO, como diferencia de las presiones atmosféricas en superficie, previamente estandarizadas, de Cádiz-San Fernando y Padua, ofrece mejores correlaciones con la precipitación en la fachada oriental de la Península Ibérica que la NAO. En la actualidad medio centenar de artículos en revistas indexadas internacionalmente, de especialidades científicas diversas, no solo de Climatología, han hecho uso del nuevo patrón o lo han referenciado. Para la Península Ibérica, la WeMO es el patrón más explicativo de la precipitación torrencial desde el nordeste al sur.