Downscaling Gridded DEMs Using the Hopfield Neural Network

A new Hopfield neural network (HNN) model for downscaling a digital elevation model in grid form (gridded DEM) is proposed. The HNN downscaling model works by minimizing the local semivariance as a goal, and by matching the original coarse spatial resolution elevation value as a constraint. The HNN model is defined such that each pixel of the original coarse DEM is divided into f × f subpixels, represented as network neurons. The elevation of each subpixel is then derived iteratively (i.e., optimized) based on minimizing the local semivariance under the coarse elevation constraint. The proposed HNN model was tested against three commonly applied alternative benchmark methods (bilinear resampling, bicubic and Kriging resampling methods) via an experiment using both degraded and sampled datasets at 20-, 60-, and 90-m spatial resolutions. For this task, a simple linear activation function was used in the HNN model. Evaluation of the proposed model was accomplished comprehensively with visual and quantitative assessments against the benchmarks. Visual assessment was based on direct comparison of the same topographic features in different downscaled images, scatterplots, and DEM profiles. Quantitative assessment was based on commonly used parameters for DEM accuracy assessment such as the root mean square error, linear regression parameters m and b, and the correlation coefficient R. Both visual and quantitative assessments revealed the much greater accuracy of the HNN model for increasing the grid density of gridded DEMs

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Zastosowanie metod estymacji odpornej w sieciach geodezyjnych zintergrowanych z 3D obserwacjami GNSS– studium przypadku w kamieniołomie Lang Son

Recently, in Vietnam, the detection of geodetic measurements that contain rough errors as well as such data processing method has been considered as a key step in geodetic data processing, especially for large geodetic networks with many different types of measurements like 3D - Global Navigation Satellite Systems (GNSS) network. On the other hand, mines in Vietnam often have complex terrains, so it is necessary to apply modern and flexible surveying methods in combination with ground and space measurements to build 3D coordinates control networks for management and exploitation to ensure sustainable development. Therefore, this research developed a Robust estimation method based on empirical weighting function for establishing 3D geodetic network combining terrestrial observation and GNSS vectors. The experiment on processing the combined network in Lang Son limestone quarry, Vietnam showed that the proposed method could be an effective solution for processing 3D terrestrial – GNSS geodetic network for mine surveying in Vietnam.Niezawodność osnowy geodezyjnej wynika z niezawodności układu obserwacyjnego, który tę osnowę wyznacza oraz wyraża możliwość jego kontroli na wypadek zaistnienia błędów grubych, szczególnie w przypadku dużych osnów składających się z tradycyjnych sieci zintegrowanych z GNSS obserwacjami. Z drugiej strony, ponieważ tereny kopalni odkrywkowych w Wietnamie są często o silnie zróżnicowanej morfologii utworzone w wyniku eksploatacji górniczej a sieci kontrolne na obszarach górniczych powstawały w różnych okresach o różnych figurach geometrycznych i różnych metodach pomiarowych, wiec jest zintegrowanie klasycznych sieci z GNSS obserwacjami zostało koniecznym zagadnieniem. W artykule, przedstawiono wyniki badania nad zastosowaniem metod estymacji odpornej w sieciach geodezyjnych zintergrowanych z 3D obserwacjami GNSS w kamieniołomie Lang Son. Eksperyment dotyczący przetwarzania połączonej sieci w kamieniołomie wapienia Lang Son (Wietnamie) wykazał, że proponowana metoda jest odpowiednim rozwiązaniem do przetwarzania tradycyjnej naziemnej sieci z 3D GNSS-owskimi obserwacjami w osnowie geodezyjnej służącej skutecznie do prac geodezyjnych w kamieniołomie Lang Son a w innych kopalniach odkrywkowych generalnie mówiąc

Porównanie metod ponownego próbkowania dla skalowanego w dół zmniejszania DEM

In this paper, a comparison and evaluation of three resampling methods for gridded DEM is implemented. The evaluation was based on the results of bilinear resampling, bi-cubic and Kriging resampling methods for an experiment using both degraded and sampled datasets at 20 m and 60 m spatial resolutions. The evaluation of the algorithms was accomplished comprehensively with visual and quantitative assessments. The visual assessment process was based on direct comparison of the same topographic features in different downscaled images, scatterplots and profiles. The quantitative assessment was based on the most commonly used parameters for DEM accuracy assessment such as root mean square errors (RMSEs), linear regression parameters m and b, and correlation coefficient R. Both visual and quantitative assessment revealed greater accuracy of the Kriging over the other two conventional methods

Accuracy assessment of mine walls’ surface models derived from terrestrial laser scanning

Abstract The monitoring of highwall slopes at open-pit mines is an important task to ensure safe mining. For this reason, several techniques such as total station, radar, terrestrial Light Detection and Ranging (LIDAR) can be employed for surface measurement. The objective of this study is to investigate mesh algorithms, which can be used to interpolate 3D models of pit walls. Experiments were carried out at Coc Sau open-pit mine at Quang Ninh province of Vietnam, and at experimental mine of Akademia Górniczo-Hutnicza University of Science and Technology in Cracow, Poland. First, 3D point cloud data for the study area was acquired by using terrestrial LIDAR, then was used to generate mesh surfaces using three algorithms—Delaunay 2.5D XY Plane, Delaunay 2.5D Best Fitting Plane, and Mesh from Points. After that, the results were rectified and optimized. Subsequently, the optimized meshes were used for generation of non-uniform rational basis spline (NURBS) surfaces. Then, the NURBS surface accuracy was assessed. The results showed that the average distance between surface and point cloud was within range of 5.6–5.8 mm with deviation of 6.2–6.8 mm, depending on the used mesh. Additionally, the quality of surfaces depends on the quality of input data set and the algorithm used to generate mesh network, and the accuracy of computed NURBS surfaces fitting into pointset was 4–5 times lower than that of optimized mesh fitting. However, the accuracy of the final product allows determining displacements on the level of centimeters

An Experimental Study of Roughness Elements to Design Fixed-Bed Hydraulic Model—A Step-by-Step Process and an Application in Vietnam

The calibration of the water level in a hydraulic model experiment is a time-consuming task. In this study, the authors proposed a guide to adjust the water level in the fixed-bed hydraulic experiment, by establishing a connection between the water level increase (ΔZ) in the model with other factors such as roughness diameter (d), roughness density (s), and flow velocity (v). Based on the results of 105 model experiments with different d, s, and v, the study also suggested a process to design a model experiment. The results of the study were used to build a fixed-bed hydraulic experiment for a river section passing through the Ialy hydropower plant in Vietnam. The results showed that after 01 time of implementation, the water level in the experiment was close to the observed water level. The differences between the calculated and measured water levels have been significantly reduced, from 0.027–0.036 m to 0.003–0.008 m. This finding shows that the approach of the study saves time and effort in the process of setting up a hydraulic experiment