No abstract

The paper contains a survey of mobile scanning systems for measuring the railway clearance gauge. The research was completed as part of the project carried out for the PKP (PKP Polish Railway Lines S.A., Warsaw, Poland) in 2011–2013. The authors conducted experiments, including a search for the latest solutions relating to mobile measurement systems that meet the basic requirement. At the very least, these solutions needed to be accurate and have the ability for quick retrieval of data. In the paper, specifications and the characteristics of the component devices of the scanning systems are described. Based on experiments, the authors did some examination of the selected mobile systems to be applied for measuring the clearance gauge. The Riegl (VMX-250) and Z+F (Zoller + Fröhlich) Solution were tested. Additional test measurements were carried out within a 30-kilometer section of the Warsaw-Kraków route. These measurements were designed so as to provide various elements of the railway infrastructure, the track geometry and the installed geodetic control network. This ultimately made it possible to reduce the time for the preparation of geodetic reference measurements for the testing of the accuracy of the selected systems. Reference measurements included the use of the polar method to select profiles perpendicular to the axis of the track. In addition, the coordinates selected were well defined as measuring points of the objects of the infrastructure of the clearance gauge. All of the tested systems meet the accuracy requirements initially established (within the range of 2 cm as required by the PKP). The tested systems have shown their advantages and disadvantages.

No abstract

KEY WORDSchronic obstructive pulmonary disease, computed tomography, emphysema score, endobronchial ultrasound, markers of remodelling ABSTRACT INTRODUCTION Airway remodeling plays an important role in the development of chronic obstructive pulmonary disease (COPD). Imaging methods, such as computed tomography (CT) and endobronchial ultrasound (EBUS), may be useful in the assessment of structural alterations in the lungs.OBJECTIVES The aim of this study was to evaluate a relationship between the severity of emphysema assessed by chest CT, the thickness of bronchial wall layers measured by EBUS, and the markers of remodeling in bronchoalveolar lavage fluid (BALF) in patients with COPD. PATIENTS AND METHODSThe study included 33 patients with COPD who underwent pulmonary function tests, emphysema score assessment by chest CT, as well as bronchofiberoscopy with EBUS in order to measure the total bronchial wall thickness and, separately, layers L 1 , L 2 , and L 3-5 . Selected remodeling (matrix metalloproteinase 9 [MMP-9], tissue inhibitor of metalloproteinase 1, transforming growth factor β 1 [TGF-β 1 ]) and inflammatory markers (neutrophil elastase, eosinophil cationic protein) were measured in BALF samples using an enzyme-linked immunosorbent assay.RESULTS MMP-9 levels in BALF were significantly higher in patients with very severe bronchial obstruction than in those with moderate and mild bronchial obstruction (P = 0.02), and showed a negative correlation with forced expiratory volume in 1 second (r = -0.538, P = 0.002). The thickness of L 1 and L 2 , which histologically correspond to the mucosa, submucosa, and smooth muscle, demonstrated a positive correlation with TGF-β 1 levels in BALF (r = 0.366, P = 0.046 and r = 0.425, P = 0.02) and the thickness of L 1 showed a negative association with neutrophil elastase levels (r = -0.508, P = 0.004). There was no significant correlation between the analyzed markers in BALF and the emphysema score. CONCLUSIONS Significant correlations of TGF-β 1 and elastase with the thickness of bronchial wall layers, and of MMP-9 with the severity of obstruction, may suggest the involvement of these markers in airway remodeling in patients with COPD.

The study presents the analysis of the possible use of limited number of the Sentinel-2 and Sentinel-1 to check if crop declarations that the EU farmers submit to receive subsidies are true. The declarations used in the research were randomly divided into two independent sets (training and test). Based on the training set, supervised classification of both single images and their combinations was performed using random forest algorithm in SNAP (ESA) and our own Python scripts. A comparative accuracy analysis was performed on the basis of two forms of confusion matrix (full confusion matrix commonly used in remote sensing and binary confusion matrix used in machine learning) and various accuracy metrics (overall accuracy, accuracy, specificity, sensitivity, etc.). The highest overall accuracy (81%) was obtained in the simultaneous classification of multitemporal images (three Sentinel-2 and one Sentinel-1). An unexpectedly high accuracy (79%) was achieved in the classification of one Sentinel-2 image at the end of May 2018. Noteworthy is the fact that the accuracy of the random forest method trained on the entire training set is equal 80% while using the sampling method ca. 50%. Based on the analysis of various accuracy metrics, it can be concluded that the metrics used in machine learning, for example: specificity and accuracy, are always higher then the overall accuracy. These metrics should be used with caution, because unlike the overall accuracy, to calculate these metrics, not only true positives but also false positives are used as positive results, giving the impression of higher accuracy. Correct calculation of overall accuracy values is essential for comparative analyzes. Reporting the mean accuracy value for the classes as overall accuracy gives a false impression of high accuracy. In our case, the difference was 10–16% for the validation data, and 25–45% for the test data.