4 resultados para active principle
em Dalarna University College Electronic Archive
Resumo:
Prosodic /template Morphology, that "draws heavily on the theoretical apparatus and formalisms of the generative phonology model known as autosegmental phonology" (Katamba, F. 1993: 154), is the best analysis that can handle Arabic morphology. Verbs in Arabic are represented on three independent tiers: root tier, the skeletal tier and the vocalic melody tier (Katamba, F. 1993). Vowel morphemes, which are represented by diacritics, are inserted within the consonant morphemes, which are represented by primary symbols, to form words. The morpheme tier hypothesis paves the way to understand the nonconcatenative Arabic morphology. This paper analyzes gender in perfect active and passive 3rd person singular verbs on the basis of PM. The focus of the analysis shall be drawn heavily on the most common Arabic verbs; triconsonantal verbs, with brief introduction of the less common verbs; quadriconsonantal perfect active and passive masculine and feminine 3rd person singular verbs. I shall, too, cast the light on some vowel changes that some verbs undergo when voice changes.
Resumo:
A series of measurements on the performance of solar cell string modules with low-concentrating CPC reflectors with a concentration factor C ˜ 4X have been carried out. To minimise the reduction in efficiency due to high cell temperatures, the modules were cooled. Four different way of cooling were tested:1) The thermal mass of the module was increased, 2) passive air cooling was used by introducing a small air gap between the module and the reflector, 3) the PV cells were cooled by a large cooling fin, 4) the module was actively cooled by circulating cold water on the back. The best performance was given with the actively cooled PV module which gave 2,2 times the output from a reference module while for the output from the module with a cooling fin the value was 1,8.Active cooling is also interesting due to the possibility of co-generation of thermal and electrical energy which is discussed in the paper. Simulations, based on climate data from Stockholm, latitude 59.4°N, show that there are good prospects for producing useful temperatures of the cooling fluid with only a slightly reduced performance of the electrical fraction of the PV thermal hybrid system.
Resumo:
This paper analyzes Japanese language classes at Dalarna University in Sweden that are held through a web conferencing system. It discusses how students’ learning and language acquisition can be supported by making better use of the available features of using a web conferencing system for language lessons. Of particular interest is the existence of an “information gap” among students, created because of the limits posed by distance communication. Students who take Japanese courses at Dalarna University usually access classes from their home, which are located all over Sweden or even abroad. This fact can be utilized in language classes because the “information gap” can lead to interactions that are essential for language learning. In order to make use of this natural “information gap” and turn it into an opportunity for communication, our classes used a teaching method called “personalization” [Kawaguchi, 2004]. “Personalization” aims to persuade students to express their own ideas, opinions, feelings and preferences. The present analysis suggests that “personalization” in web-based language classes is a surprisingly effective teaching method. By making students explain about things at home (why they have them, what they use them for, or why they are important), students become motivated to express themselves in Japanese. This makes communication meaningful and enhances students’ interest in improving their vocabulary. Furthermore, by knowing each other, it becomes easier to create a ”supportive classroom environment” [Nuibe, 2001] in which students feel able to express themselves. The analysis suggests that that web-based education can be seen not simply as a supplement to traditional face-to face classroom education, but as a unique and effective educational platform in itself.
Resumo:
Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic. The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.