Does speed matter? : the impact of the EU membership incentive on rule adoption in minority language rights protection

Denna avhandling tar sin utgångspunkt i ett ifrågasättande av effektiviteten i EU:s konditionalitetspolitik avseende minoritetsrättigheter. Baserat på den rationalistiska teoretiska modellen, External Incentives Model of Governance, syftar denna hypotesprövande avhandling till att förklara om tidsavståndet på det potentiella EU medlemskapet påverkar lagstiftningsnivån avseende minoritetsspråksrättigheter. Mätningen av nivån på lagstiftningen avseende minoritetsspråksrättigheter begränsas till att omfatta icke-diskriminering, användning av minoritetsspråk i officiella sammanhang samt minoriteters språkliga rättigheter i utbildningen. Metodologiskt används ett jämförande angreppssätt både avseende tidsramen för studien, som sträcker sig mellan 2003 och 2010, men även avseende urvalet av stater. På basis av det \"mest lika systemet\" kategoriseras staterna i tre grupper efter deras olika tidsavstånd från det potentiella EU medlemskapet. Hypotesen som prövas är följande: ju kortare tidsavstånd till det potentiella EU medlemskapet desto större sannolikhet att staternas lagstiftningsnivå inom de tre områden som studeras har utvecklats till en hög nivå. Studien visar att hypotesen endast bekräftas delvis. Resultaten avseende icke-diskriminering visar att sambandet mellan tidsavståndet och nivån på lagstiftningen har ökat markant under den undersökta tidsperioden. Detta samband har endast stärkts mellan kategorin av stater som ligger tidsmässigt längst bort ett potentiellt EU medlemskap och de två kategorier som ligger närmare respektive närmast ett potentiellt EU medlemskap. Resultaten avseende användning av minoritetsspråk i officiella sammanhang och minoriteters språkliga rättigheter i utbildningen visar inget respektive nästan inget samband mellan tidsavståndet och utvecklingen på lagstiftningen mellan 2003 och 2010.

3D roll-forming of hat-profile with variable depth and width

The use of roll-formed products in automotive, furniture, buildings etc. increases every year due to the low part-production cost and the complicated cross-sections that can be produced. The limitation with roll-forming until recent years is that one could only produce profiles with a constant cross-section in the longitudinal direction. About eight years ago ORTIC AB [1] developed a machine in which it was possible to produce profiles with a variable width (“3D roll-forming”) for the building industry. Experimental equipment was recently built for research and prototyping of profiles with variable cross-section in both width and depth for the automotive industry. The objective with the current study is to investigate the new tooling concept that makes it possible to roll-form hat-profiles, made of ultra high strength steel, with variable cross-section in depth and width. The result shows that it is possible to produce 3D roll-formed profiles with close tolerances.

A Note on Proxy Variables and Instrument Variable Regression

This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Extended local labor markets due to high speed trains : Visualization of estimations in the Swedish national travel demand forecasting tool, SAMPERS

Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.

The importance of body-mass exponent optimization for evaluation of performance capability in cross-country skiing

Introduction Performance in cross-country skiing is influenced by the skier’s ability to continuously produce propelling forces and force magnitude in relation to the net external forces. A surrogate indicator of the “power supply” in cross-country skiing would be a physiological variable that reflects an important performance-related capability, whereas the body mass itself is an indicator of the “power demand” experienced by the skier. To adequately evaluate an elite skier’s performance capability, it is essential to establish the optimal ratio between the physiological variable and body mass. The overall aim of this doctoral thesis was to investigate the importance of body-mass exponent optimization for the evaluation of performance capability in cross-country skiing. Methods In total, 83 elite cross-country skiers (56 men and 27 women) volunteered to participate in the four studies. The physiological variables of maximal oxygen uptake (V̇O2max) and oxygen uptake corresponding to a blood-lactate concentration of 4 mmol∙l-1 (V̇O2obla) were determined while treadmill roller skiing using the diagonal-stride technique; mean oxygen uptake (V̇O2dp) and upper-body power output (Ẇ) were determined during double-poling tests using a ski-ergometer. Competitive performance data for elite male skiers were collected from two 15-km classical-technique skiing competitions and a 1.25-km sprint prologue; additionally, a 2-km double-poling roller-skiing time trial using the double-poling technique was used as an indicator of upper-body performance capability among elite male and female junior skiers. Power-function modelling was used to explain the race and time-trial speeds based on the physiological variables and body mass. Results The optimal V̇O2max-to-mass ratios to explain 15-km race speed were V̇O2max divided by body mass raised to the 0.48 and 0.53 power, and these models explained 68% and 69% of the variance in mean skiing speed, respectively; moreover, the 95% confidence intervals (CI) for the body-mass exponents did not include either 0 or 1. For the modelling of race speed in the sprint prologue, body mass failed to contribute to the models based on V̇O2max, V̇O2obla, and V̇O2dp. The upper-body power output-to-body mass ratio that optimally explained time-trial speed was Ẇ ∙ m-0.57 and the model explained 63% of the variance in speed. Conclusions The results in this thesis suggest that V̇O2max divided by the square root of body mass should be used as an indicator of performance in 15-km classical-technique races among elite male skiers rather than the absolute or simple ratio-standard scaled expression. To optimally explain an elite male skier’s performance capability in sprint prologues, power-function models based on oxygen-uptake variables expressed absolutely are recommended. Moreover, to evaluate elite junior skiers’ performance capabilities in 2-km double-poling roller-skiing time trials, it is recommended that Ẇ divided by the square root of body mass should be used rather than absolute or simple ratio-standard scaled expression of power output.

Physiological demands of competitive elite cross-country skiing

Introduction Researchers have, for decades, contributed to an increased collective understanding of the physiological demands in cross-country skiing; however, almost all of these studies have used either non-elite subjects and/or performances that emulate cross-country skiing. To establish the physiological demands of cross-country skiing, it is important to relate the investigated physiological variables to the competitive performance of elite skiers. The overall aim of this doctoral thesis was, therefore, to investigate the external validity of physiological test variables to determine the physiological demands in competitive elite cross-country skiing. Methods The subjects in Study I – IV were elite male (I – III) and female (III – IV) cross-country skiers. In all studies, the relationship between test variables (general and ski-specific) and competitive performances (i.e. the results from competitions or the overall ski-ranking points of the International Ski Federation (FIS) for sprint (FISsprint) and distance (FISdist) races) were analysed. Test variables reflecting the subject’s general strength, upper-body and whole-body oxygen uptake, oxygen uptake and work intensity at the lactate threshold, mean upper-body power, lean mass, and maximal double-poling speed were investigated. Results The ability to maintain a high work rate without accumulating lactate is an indicator of distance performance, independent of sex (I, IV). Independent of sex, high oxygen uptake in whole-body and upper-body exercise was important for both sprint (II, IV) and distance (I, IV) performance. The maximal double-poling speed and 60-s double-poling mean power output were indicators of sprint (IV) and distance performance (I), respectively. Lean mass was correlated with distance performance for women (III), whereas correlations were found between lean mass and sprint performance among both male and female skiers (III). Moreover, no correlations between distance performance and test variables were derived from tests of knee-extension peak torque, vertical jumps, or double poling on a ski-ergometer with 20-s and 360-s durations (I), whereas gross efficiency while treadmill roller skiing showed no correlation with either distance or sprint performance in cross-country skiing (IV). Conclusion The results in this thesis show that, depending on discipline and sex, maximal and peak oxygen uptake, work intensity at the lactate threshold, lean mass, double-poling mean power output, and double-poling maximal speed are all externally valid physiological test variables for evaluation of performance capability among elite cross-country skiers; however, to optimally indicate performance capability different test-variable expressions should be used; in general, the absolute expression appears to be a better indicator of competitive sprint performance whereas the influence of body mass should be considered when evaluating competitive distance performance capability of elite cross-country skiers.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

INVASIVE AQUATIC INVASION: THE SPREAD OF VARIABLE LEAF MILFOIL IN MAINE

http://digitalcommons.colby.edu/atlasofmaine2009/1033/thumbnail.jpg