IR-thermography for Quality Prediction in Selective Laser Deburring

AbstractSelective Laser Deburring (SLD) is an innovative edge-refinement process being developed at the Laser Zentrum Nord (LZN) in Hamburg. It offers a wear-free processing of defined radii and bevels at the edges as well as the possibility to deburr several materials with the same laser source.Sheet metal parts of various applications need to be post-processed to remove sharp edges and burrs remaining from the initial production process. Thus, SLD will provide an extended degree of automation for the next generation of manufacturing facilities.This paper investigates the dependence between the deburring result and the temperature field in- and post-process. In order to achieve this, the surface temperature near to the deburred edge is monitored with IR-thermography. Different strategies are discussed for the approach using the IR-information as a quality assurance. Additional experiments are performed to rate the accuracy of the quality prediction method in different deburring applications

Performance of IMPACT, CRASH and Nijmegen models in predicting six month outcome of patients with severe or moderate TBI: An external validation study

Background: External validation on different TBI populations is important in order to assess the generalizability of prognostic models to different settings. We aimed to externally validate recently developed models for prediction of six month unfavourable outcome and six month mortality. Methods: The International Neurotrauma Research Organization - Prehospital dataset (INRO-PH) was collected within an observational study between 2009-2012 in Austria and includes 778 patients with TBI of GCS < = 12. Three sets of prognostic models were externally validated: the IMPACT core and extended models, CRASH basic models and the Nijmegen models developed by Jacobs et al - all for prediction of six month unfavourable outcome and six month mortality. The external validity of the models was assessed by discrimination (Area Under the receiver operating characteristic Curve, AUC) and calibration (calibration statistics and plots). Results: Median age in the validation cohort was 50 years and 44% had an admission GSC motor score of 1-3. Six-month mortality was 27%. Mortality could better be predicted (AUCs around 0.85) than unfavourable outcome (AUCs around 0.80). Calibration plots showed that the o

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km(2)) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m(-2) yr(-1), respectively) compared to tundra (average annual NEE +10 and -2 g C m(-2) yr(-1)). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE

Glasgow Coma Scale Motor Score and Pupillary Reaction To Predict Six-Month Mortality in Patients with Traumatic Brain Injury: Comparison of Field and Admission Assessment

The Glasgow Coma Scale (GCS) and pupillary reactivity are well-known prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the GCS motor score and pupillary reactivity assessed in the field and at hospital admission and assess their prognostic value for 6-month mortality in patients with moderate or severe TBI. We studied 445 patients with moderate or severe TBI from Austria enrolled to hospital in 2009–2012. The area under the curve (AUC) and Nagelkerke's R(2) were used to evaluate the predictive ability of GCS motor score and pupillary reactivity assessed in the field and at admission. Uni- and multi-variable analyses—adjusting for age, other clinical, and computed tomography findings—were performed using combinations of field and admission GCS motor score and pupillary reactivity. Motor scores generally deteriorated from the field to admission, whereas pupillary reactivity was similar. GCS motor score assessed in field (AUC=0.754; R(2)=0.273) and pupillary assessment at admission (AUC=0.662; R(2)=0.214) performed best as predictors of 6-month mortality in the univariate analysis. This combination also showed best performance in the adjusted analyses (AUC=0.876; R(2)=0.508), but the performance of both predictors assessed at admission was not much worse (AUC=0.857; R(2)=0.460). Field GCS motor score and pupillary reactivity at hospital admission, compared to other combinations of these parameters, possess the best prognostic value to predict 6-month mortality in patients with moderate-to-severe TBI. Given that differences in prognostic performance are only small, both the field and admission values of GCS motor score and pupillary reaction may be reasonable to use in multi-variable prediction models to predict 6-month outcome

Epidemiology and Patterns of Transport-Related Fatalities in Austria 1980–2012

<div><p><b>Objectives:</b> Transport-related accidents remain the largest single cause of death among people aged 15 to 29 in the European Union, and despite the decrease in number of fatalities from 1990 onwards they remain a significant public health problem. The aim of this article was to analyze the long-term trends and patterns of transport-related fatalities, identify the anatomic distribution of most significant injuries in different road users, and identify the primary populations at risk of transport-related death in Austria between 1980 and 2013.</p><p><b>Methods:</b> Data on transport-related fatalities based on death certificates were obtained from Statistics Austria for the analyzed period. Crude and age-standardized mortality rates per 100,000 were calculated and broken down by age, gender, and month of death, and the anatomic distribution of most significant injuries were identified. Potential years of life lost before age 75 (PYLL-75) were used as a measure of public health impact.</p><p><b>Results:</b> A total of 39,709 transport-related fatalities were identified for the studied years; 74% were males and the mean age was 42.1 years (range 0–103). A decrease in the number of fatalities (from 2018 in 1980 to 554 in 2012), mortality rates (from 26 in 1980 to 7 in 2012), and PYLL-75 (from 68,960 in 1980 to 14,931 in 2012) was observed. Introduction of major prevention milestones (compulsory use of seat belts or child restraints) may have contributed to this decrease. Men 16–24 years old were at the highest risk of transport-related death. Pedestrian victims were more likely to be women and car drivers and motorcyclists were more often men. Most fatal transport accidents occurred between the months of May and October and prevailingly in towns of fewer than 20,000 inhabitants. Injuries to the head were the most significant injuries in all user groups (>50% of cases in all road user types). Reduced mortality rates could translate into higher prevalence of long-term disabilities in survivors of transport accidents.</p><p><b>Conclusions:</b> Despite the decreasing trend observed, transport-related fatalities remain a serious public health issue in Austria. An increase in the mortality of motor vehicle drivers warrants more preventive action in this group. Further research is needed on other outcomes of transport accidents such as long-term disabilities to elucidate the true public health burden of transport accidents.</p></div