983 resultados para Cost predictors


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Aquesta tesi forma part d'un projecte destinat a predir el rendiment acadèmic dels estudiants de doctorat portat a terme per l'INSOC (International Network on Social Capital and Performance). El grup de recerca INSOC està format per les universitats de Girona (Espanya), Ljubljana (Eslovènia), Giessen (Alemanya) i Ghent (Bèlgica). El primer objectiu d'aquesta tesi és desenvolupar anàlisis quantitatius comparatius sobre el rendiment acadèmic dels estudiants de doctorat entre Espanya, Eslovènia i Alemanya a partir dels resultats individuals del rendiment acadèmic obtinguts de cada una de les universitats. La naturalesa internacional del grup de recerca implica la recerca comparativa. Vam utilitzar variables personal, actitudinals i de xarxa per predir el rendiment. El segon objectiu d'aquesta tesi és entendre de manera qualitativa perquè les variables de xarxa no ajuden quantitativament a predir el rendiment a la universitat de Girona (Espanya). En el capítol 1, definim conceptes relacionats amb el rendiment i donam un llistat de cada una de les variables independents (variables de xarxa, personals i actitudinals), resumint la lliteratura. Finalment, explicam com s'organitzen els estudis de doctorat a cada un dels diferents països. A partir d'aquestes definicions teòriques, en els pròxims capítols, primer presentarem els qüestionaris utilitzats a Espanya, Eslovènia i Alemanya per mesurar aquests diferents tipus de variables. Després, compararem les variables que són relevants per predir el rendiment dels estudiants de doctorat a cada país. Després d'això, fixarem diferents models de regressió per predir el rendiment entre països. En tots aquests models les variables de xarxa fallen a predir el rendiment a la Universitat de Girona. Finalment, utilitzem estudis qualitatius per entendre aquests resultats inesperats. En el capítol 2, expliquem com hem dissenyat i conduït els qüestionaris en els diferents països amb l'objectiu d'explicar el rendiment dels estudiants de doctorat obtinguts a Espanya, Eslovènia i Alemanya. En el capítol 3, cream indicadors comparables però apareixen problemes de comparabilitat en preguntes particulars a Espanya, Eslovènia i Alemanya. En aquest capítol expliquem com utilitzem les variables dels tres països per crear indicadors comparables. Aquest pas és molt important perquè el principal objectiu del grup de recerca INSOC és comparar el rendiment dels estudiants de doctorat entre els diferents països. En el capítol 4 comparem models de regressió obtinguts de predir el rendiment dels estudiants de doctorat a les universitats de Girona (Espanya) i Eslovènia. Les variables són característiques dels grups de recerca dels estudiants de doctorat enteses com una xarxa social egocèntrica, característiques personals i actitudinals dels estudiants de doctorat i algunes carecterístiques dels directors. Vam trobar que les variables de xarxa egocèntriques no predien el rendiment a la Universitat de Girona. En el capítol 5, comparem dades eslovenes, espanyoles i alemnayes, seguint la metodologia del capítol 4. Concluïm que el cas alemany és molt diferent. El poder predictiu de les variables de xarxa no millora. En el capítol 6 el grup de recerca dels estudiants de doctorat és entès com una xarxa duocèntrica (Coromina et al., 2008), amb l'objectiu d'obtendre informació de la relació mútua entre els estudiants i els seus directors i els contactes d'ambdós amb els altres de la xarxa. La inclusió de la xarxa duocèntrica no millora el poder predictiu del model de regressió utilitzant les variales egocèntriques de xarxa. El capítol 7 pretèn entendre perquè les variables de xarxa no predeixen el rendiment a la Universitat de Girona. Utilitzem el mètode mixte, esperant que l'estudi qualitatiu pugui cobrir les raons de perquè la qualitat de la xarxa falla en la qualitat del treball dels estudiants. Per recollir dades per l'estudi qualitatiu utilitzem entrevistes en profunditat.

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One of the main challenges for developers of new human-computer interfaces is to provide a more natural way of interacting with computer systems, avoiding excessive use of hand and finger movements. In this way, also a valuable alternative communication pathway is provided to people suffering from motor disabilities. This paper describes the construction of a low cost eye tracker using a fixed head setup. Therefore a webcam, laptop and an infrared lighting source were used together with a simple frame to fix the head of the user. Furthermore, detailed information on the various image processing techniques used for filtering the centre of the pupil and different methods to calculate the point of gaze are discussed. An overall accuracy of 1.5 degrees was obtained while keeping the hardware cost of the device below 100 euros.

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Irrespective of whether an airline has high or low operating costs, a thorough knowledge and breakdown of them is vital in order for management to: • monitor performance (to check if targets / budgets are being met. If not, remedial action can be taken) • set appropriate fares and tariffs • evaluate new routes, aircraft acquisition and outsourcing opportunities

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Outline • How Low cost airlines have changed the EU? • Maturity in Europe? • Market Substitution or generation? • Are LCCs culpable for increasing aviation's carbon footprint? • What makes a successful low cost airline? • LCCs and the long haul market

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Estimates of the Cost difference “The evidence suggests that low-cost no-frills operations can achieve unit costs as low as half those of a major network carrier” CAP 685 Single European Aviation Market: The First Five Years (June 1998)

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LCC Market Development - In 1996 low cost airlines (LCCs) accounted for only 1.4% of intra-European Union capacity. By the end of 2002, low cost airlines had captured 12% of all intra-EU capacity - Currently LCCs have a 30% market share of scheduled European point-to-point passengers. According to AEA forecasts, the LC market is expected to increase to 43% of European traffic by 2011. - In 2006 140 million passengers were carried by LCCs. - Low-fare airlines have increased their presence from 13% of city pairs in 2003 to 26% in 2007. 96% of new city-pairs between 2005 and 2007 were added by LCCs. - The United Kingdom still sees the highest number of low-cost flights, followed by Spain, which has been making up a lot of ground over the last year. This is followed by Italy and Germany with slightly fewer flights. These four countries contribute to roughly three quarters of low-cost departures. France is fifth in this list with only 5% of LC flights. - easyJet and Ryanair continue to be the biggest players in the European LCC market accounting for about 40% of all LCC capacity. The top two are followed by Airberlin, which contributes another 10% leaving three carriers in control of half the European low-cost market.

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This paper is a review of a study on perception and comprehension of speech using syntactic, visual and acoustic information.

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This paper reviews a study to determine the applicabilty of the Wechsler-Bellevue and the Wechsler Intelligence Scale for severely hearing impaired children.

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Chronic pesticide poisoning is difficult to detect. We sought to develop a low-cost test battery for settings such as Ecuador’s floriculture industry. First we had to develop a case definition; as with all occupational diseases a case had to have both sufficient effective dose and associated health effects. For the former, using canonical discriminant analysis, we found that adding measures of protection and overall environmental stressors to occupational category and duration of exposure was useful. For the latter, factor analysis suggested three distinct manifestations of pesticide poisoning. We then determined sensitivity and specificity of various combinations of symptoms and simple neurotoxicity tests from the Pentox questionnaire, and found that doing so increased sensitivity and specificity compared to use of acethylcholinesterase alone – the current screening standard. While sensitivity and specificity varied with different case definitions, our results support the development of a low-cost test battery for screening in such settings.

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Sectoral shifts, such as shrinkage of low labour productivity and the low-wage construction sector, can lead to apparent increased aggregate average labour productivity and average wages, especially when capital intensity differs across sectors. For 11 main sectors and 13 manufacturing sub-sectors, we quantify the compositional effects on productivity, wages and unit labour costs (ULCs) based and real effective exchange rates (REER), for 24 EU countries. Compositional effects are greatest in Ireland, where the pharmaceutical sector drives the growth of output and productivity, but other sectors have suffered greatly and have not yet recovered. Our new ULC-REER measurements, which are free from compositional effects, correlate well with export performance. Among the countries facing the most severe external adjustment challenges, Lithuania, Portugal and Ireland have been the most successful based on five indicators, and Latvia, Estonia and Greece the least successful. There is evidence of downward wage flexibility in some countries, but wage cuts have corrected just a small fraction of pre-crisis wage rises and came with massive reductions in employment even in the business sector excluding construction and real estate, highlighting the difficulty of adjusting wages downward.

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As a background document for Bruegel Policy Contribution 2012/11 ‘Compositional effects on productivity, labour cost and export adjustment’, this working paper presents detailed results for 24 EU countries on: • The sectoral changes in the economy; • The unit labour costs (ULC) based real effective exchange rate (REER) and its main components; • Export performance. • The ULC-REERs are calculated: • For the total economy, the business sector (excluding agriculture, construction and real estate activities), and some main sectors; • Using both actual aggregates and fixed-weight aggregates, as the latter are free from the impacts of compositional changes; • Against 30 trading partners and against three subsets of trading partners: euro-area, non-euro area EU, non-EU.