Spectral Values Research Articles

Effects of Higher Sloshing Modes on the Response of Rectangular Concrete Water Storage Tanks with Different Aspect Ratios to Near-Field Earthquakes

Near-field earthquakes have been shown to have different effects on structures than far-field events. This study examines the dynamic response of a rectangular concrete liquid storage tank with tapered walls to near-field ground motions, with particular emphasis on the effect of higher sloshing modes. The tank’s numerical modeling, calibrated using experimental results, was performed considering the tank’s wall flexibility. Seven selected near-field records were applied in each case, and the effects of the first five sloshing modes on the tank response at three different locations, including the corner, middle of the long wall, and middle of the short wall, were investigated. The effect of the earthquake incident angle on the tank’s response was also studied by applying major and minor horizontal earthquake components once along the longer and shorter tank walls, respectively, and vice versa. Results show that the tank corner may have a sloshing height up to 50% greater than the middle of the walls and that the maximum sloshing response is substantially influenced by the spectral acceleration value at the first sloshing period. Higher sloshing modes are found to affect the sloshing response, with a maximum R2 score of 0.95, depending on the excitation’s incidence angle.

Structural parameters of amphetamine: A DFT approach

The structural parameters of Amphetamine, a significant psychoactive drug, are investigated experimentally and computationally using spectroscopic and DFT methods. The molecule is subjected to optimization using the B3LYP functional with both 6-311+G (2d,p) and augmented cc-pVTZ basis sets. Resulting values are then compared against published crystal data for validation. Analysis of the Fourier Transform Infrared and Raman spectra is carried out with PED assignments and after scaling, the calculated spectral frequency values are verified with experimental spectra, revealing a favorable match between them. The NMR spectrum of the molecule is obtained using TD-DFT techniques. The quantum theory of atoms in molecules is employed to analyze the electron density distributions. The reactivity of the molecule is predicted using various tools including analysis of the molecular electrostatic potential surface, electron localized function, molecular graph, non-covalent interaction (NCI), Hirshfeld charge, frontier orbital as well as local and global reactivity descriptors. Natural bonding orbital analysis identifies the hybridization, charge transfer and correlation effects. The results of this study could be utilized for the development of novel chemical sensors for drug detection and to predict the correlation between the structure and pharmacological activity of various amphetamine derivatives.

Photometric correction of images obtained from Chandrayaan-2 Imaging Infra-Red Spectrometer (IIRS) data

India’s second mission to the Moon, Chandrayaan-2, carried one of the most advanced imaging spectrometers ever sent to image a planetary surface – the IIRS (Imaging Infra-Red Spectrometer) – a 250 band spectrometer developed at the Space Applications Centre (SAC), ISRO, India. In this study, IIRS data between 800 and 2000 nm have been used to derive photometrically corrected reflectance from calibrated radiance data supplied by ISRO’s online archive (Pradan) of Chandrayaan-2 data. Additionally, the photometric properties of three IIRS bands (950, 1500, and 1700 nm) have been studied in detail. Since the images obtained by IIRS are at different viewing geometry orientations, the purpose of performing a photometric correction on IIRS images is to re-project each pixel to a standard viewing geometry of incidence angle, i = 30°, emission angle, e = 0° and, phase angle, α = 30°. In order to correct the lunar limb darkening effect, a combination of the Lommel-Seeliger function and McEwen’s model was used. In addition, topographic data from the merged Digital Elevation Model of Lunar Reconnaissance Orbiter – Lunar Orbiter Laser Altimeter (LRO-LOLA) and SELENE Terrain Camera (TC) were utilized to remove effects from local topography. A photometric function was then applied on four images captured by IIRS which were included in the first public release of data in August 2021. Radiance and reflectance (obtained after implementing photometric correction on IIRS images) values were compared with L1 and L2 M3 (Moon Mineralogy Mapper) data from Chandrayaan-1. It was found that although IIRS images are much darker than M3, corrected IIRS reflectance images had a much smaller variation in terms of reflectance values with M3. Moreover, the associated spectral reddening and reflectance values are within range when compared with data from other lunar missions. In addition, the reflectance spectra derived from the corrected IIRS images have been plotted for each image. However, the spectra exhibit significantly deeper absorptions than their corresponding M3 data for the same pixel. Phase functions derived from three bands have a good correlation with the reflectance values and phase angles. Consequently, this function can be applied to all IIRS images as and when more data are released to the public.

Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and the protection of small-scale farmers’ practices. These issues are integral to food security and environmental health. Remote sensing technologies can assist precision agriculture in effectively addressing these complex problems by providing farmers with high-resolution lenses. The use of vegetation indices (VIs) is an essential component of remote sensing, which combines the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. A wide array of VIs can be used to classify the crops and evaluate their state and health. However, precisely this high number leads to difficulty in selecting the best VI and their combination for specific objectives. Without thorough documentation and analysis of appropriate VIs, users might find it difficult to use remote sensing data or obtain results with very low accuracy. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the effective use of VIs for the discrimination and monitoring of several important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities. The current review has shown that VIs appear to be suitable for mapping and monitoring agricultural crops, forage crops, meadows and pastures. Sentinel-1 and Sentinel-2 data were the most utilized sources, while some of the frequently used VIs were EVI, LAI, NDVI, GNDVI, PSRI, and SAVI. In most of the studies, an array of VIs needed to be employed to achieve a good discrimination of crops or prediction of yields. The main challenges in using VIs are related to the variation of the spectral characteristics during the vegetation period and to the similarities of the spectral signatures of various crops and semi-natural meadows. Thus, further studies are needed to establish appropriate models for the use of satellite data that would prove to have greater accuracy and provide more relevant information for the efficient monitoring of agricultural crops.

Assessing seismic risk in the built environment of Istanbul: High-resolution hazard mapping and ground motion analysis in the sea of Marmara region

This research scrutinizes the seismic threat looming over Istanbul, potentially subject to a substantial earthquake. We analyze six plausible earthquake scenarios, utilizing six ground motion prediction equations (GMPEs), to forge high-resolution seismic hazard maps. These maps reveal not only peak horizontal ground accelerations but also spectral acceleration values across varying temporal frames, integrating the amplification effects of softer sediments. Our approach delineates that Istanbul’s western shoreline faces heightened risk, with median spectral accelerations at 0.3 s approaching 1 g, signifying intense shaking potential. In contrast, the area encompassing the financial district exhibits lower values, around 0.3 g. The granularity of these findings lays bare the seismic vulnerabilities of the region, offering a window into the risks and potential damages facing this bustling metropolis. This enhanced understanding paves the way for strategic urban planning and risk mitigation efforts aimed at safeguarding Istanbul’s populace and infrastructure. This article succinctly condenses our study’s pivotal conclusions, presenting a clarion call for proactive measures to diminish earthquake impacts on this dynamic urban landscape.

HPLC-LED-Induced Fluorescence Analysis of Tear Fluids: An Objective Method for Primary Open Angle Glaucoma Diagnosis

PurposeThe study showcased the application of the lab-assembled HPLC-LED-IF system to analyze proteins in tear fluid samples collected from individuals diagnosed with primary open-angle glaucoma (POAG).MethodsClinical application of the said technique was evaluated by recording chromatograms of tear fluid samples from control and POAG subjects and by analyzing the protein profile using multivariate analysis. The data analysis methods involved are principal component analysis (PCA), Match/No-Match, and artificial neural network (ANN) based binary classification for disease diagnosis.ResultsMahalanobis distance and spectral residual values calculated using a standard calibration set of clinically confirmed POAG samples for the Match/No-Match test gave 86.9% sensitivity and 81.8% specificity. ANN with leaving one out procedure has given 87.1% sensitivity and 81.8% specificity.ConclusionThe results of the study revealed that the utilization of a 278 nm LED excitation in the HPLC system offers good sensitivity for detecting proteins at low concentrations allowing to obtain reliable protein profiles for the diagnosis of POAG.

Efficient PAPR Reduction in Cyclic Prefix with Enhanced Selection Strategy

The OFDM system’s selective mapping (SLM) technique for reducing Peak to Average Power Ratio (PAPR) seems promising. The fundamental principle of SLM is to create unique send sequences from the same data source and choose the transmit signal with the lowest PAPR. This study presents an enhanced cyclic prefix selection system with a lower PAPR by using selective mapping approaches. With the use of a signal multiplexing technique called orthogonal frequency division multiplexing (OFDM), the available bandwidth is divided into a range of frequencies called sounds. OFDMA technology can be employed anywhere that radio waves are used for data transmission. Input data is moved to the transmitter side for channel encoding. Using in-channel encoding, the digital signal is digitized and superfluous binary digits are eliminated. The signal is then connected to add and remove prefixes in a cyclical manner. Faults between these processes are eliminated by the AWGN channel followed by Hilbert Transform to lower the complexity of the entire process. Finally, by combining the clipping and SLM methods, improved outcomes are attaining in terms of spectral efficiency and PAPR reduction value, while maintaining the performance of channel estimation. MATLAB simulation is employed to evaluate the recommended method.

Automatic Detection of Maintenance Scenarios for Equipment and Control Systems in Industry

The well-known methods of scene extraction on video are focused on analyzing the similarity between frames. However, they do not all analyze the composition of the image scene, which may remain the same during maintenance. Therefore, this paper proposes an algorithm for equipment maintenance scene detection based on human hand tracking. It is based on the assumption that, when servicing technological equipment, it is possible to determine the change in repair action by the position of the service engineer’s hands. Thus, certain information and the algorithm that processes these changes allow us to segment the video into actions performed during the service. We process the time series obtained by moving the hand position using spectral singular value decomposition for multivariate time series. To verify the algorithm, we performed maintenance on the control cabinet of a mining conveyor and recorded the work on a first-person video, which was processed using the developed method. As a result, we obtained some scenes corresponding to opening the control cabinet, de-energizing the unit, and checking the contacts with a multimeter buzzer test. A third-person video of motor service was similarly processed. The algorithm demonstrated the results in separate scenes of removing screws, working with a multimeter, and disconnecting and replacing motor parts.

Neurointerventions on two generations of angiography systems: Recent systems reduce radiation exposure by half

PurposeFluoroscopically-guided neurointervention may be associated with prolonged procedure time and substantial radiation exposure to the patient and staff. This study sought to examine technological features affecting the potential radiation exposure reduction of new angiography systems, compared to older systems, for neurointerventional procedures. MethodsConsecutive neurointerventional patients (2020–2022) were retrospectively analyzed. The air kerma at the reference point (Ka,r) and kerma-area product (KAP) were compared between Artis icono and Artis zee (Siemens) using statistical analyses (two-tailed t tests), where P < 0.05 is considered significant. X-ray tube potential and copper filtration were examined. Tests with an anthropomorphic phantom (Sun Nuclear) on Artis icono were conducted and entrance skin exposure and x-ray spectral half value layer were measured. Effective spectral filtration was characterized by x-ray spectral modeling. ResultsThe number of procedures was 1158 [median (range) age, 59 (7–95) years] on Artis zee and 1087 [60 (1–95) years] on Artis icono, without significant difference in age (p = 0.059) between cohorts. Ka,r was 925.4 (890.6–960.1) mGy [mean (95 % CI)] and KAP was 119.8 (115–124.5) Gy∙cm2 on Artis zee. The measures were 48–50 % lower on Artis icono, 440.5 (411.7–469.4) mGy (Ka,r) and 59.5 (55.4–63.6) Gy∙cm2 (KAP); while the difference in fluoroscopic time between the two generations of angiography systems was insignificant (p = 0.55). ConclusionsThe newer angiography system, with updated hardware and software, was found to result in half the radiation exposure compared to older technology of the same manufacturer, even though fluoroscopic time was similar.

Theoretical determination of electronic, geometric and spectroscopic properties of some 1,2,4-triazol derivatives

In this study, molecular geometric optimization of five 4,5-dihydro-1H-1,2,4-triazol-5-one derivative compounds was obtained using Density Functional Theory, (DFT, B3LYP)/ Hartree Fock, (HF, B3LYP) methods on the basis set of 6-311G (d,p) in order to find the most stable geometric shape of the studied compounds. FT-IR and UV-vis spectral values were performed by using gauge independent atomic orbital (GIAO) methods with Gaussian G09W package program. IR frequency datas of investigated five compounds were calculated in gas phases and are multiplied with appropriate scala factors. The identification of the calculated IR data was performed in the veda4f program. Additionally, bond angles, bond lengths, dipole moments, highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO) energy and total energy, mulliken charges and molecular electrostatic potential (MEP) of five compounds were calculated using same methods and set.

Classification of Sugarcane Area Using Landsat 8 and Random Forest based on Phenology Knowledge

Indonesia is one of the largest countries globally with an area for planting sugarcane. The current problem is that determining the planting area of sugarcane is still done conventionally; this is very limited and wastes time. Thus, knowing the sugarcane planting area becomes essential for policymaking through Remote Sensing technology. However, the challenge of Remote Sensing is the limited data due to weather and the spectral variability of other plants. So, it is necessary to classify based on phenological knowledge. The study aims to classify sugarcane areas based on phenological knowledge using Remote Sensing and Machine Learning. This application finished on the cloud platform Google Earth Engine (GEE) through Landsat 8 satellite imagery data. The knowledge of sugarcane phenology was built based on the Normalized Difference Vegetation Index (NDVI) spectral value and built with the harmonic model. In addition, classification is accomplished by object-oriented (OO) methods for segmentation classification. Object-oriented is solved by the Simple Non-Iterative Clustering (SNIC) algorithm for spatial cluster identification, the Gray-Level Co-occurrence Matrix (GLCM) for texture extraction, and the Random Forest algorithm for Land Use-Land Cover (LULC) classification. The results of the accuracy analysis using the confusion matrix and the classification of sugar cane areas based on phenological knowledge obtained the best results with an overall accuracy of 95.9% with a Kappa coefficient of 0.92. It can be concluded that a classification approach with knowledge of plant phenology can help better classify the availability of land for plantations in the future.

Hyperspectral data and vegetative indices for paddy: A case study in Kerala, India

This paper reports the result of first attempt to study the variation in spectral signature of rice grown at different altitude and nutrient management practices using spectroradiometer in Kerala, India. Multiple experiments were conducted in Wayanad, Kozhikode, and Alappuzha districts, capturing essential spectral and agronomic data. The spectral data from Wayanad and Alappuzha plots at different growth stages revealed significant influences due to soil type and altitudinal variations. Furthermore, distinct spectral signatures emerged during different rice growth stages. The calculation of 15 indices, encompassing vegetative and water indices, yielded noteworthy variations at various physiological stages. Notably, the Leaf Area Index in Wayanad surpassed that in Alappuzha, maintaining this trend from panicle initiation to harvest stage. The spectral signatures also provided clear indications of water stress in the rice fields, with severity and mechanical processes were apparent through vegetative and water indices. Validation through conventional analysis of relative water content and membrane leakage corroborated these findings. Field experiment results confirmed the significant differences in spectral reflectance based on planting methods and nutrient management treatments. The spectral signature exhibited a robust correlation with rice yield (r = 0.94), capturing variations in management practices statistically. Regression analysis revealed a strong correlation between spectral and lab-analyzed values for different physiological and nutrient parameters. In conclusion, the developed spectral library for the rice cultivar Uma, along with the derived indices, proves instrumental in comprehending crop growth stages, identifying water or nutrient stress, and predicting the paddy yield during growing seasons, which will help for sustaining the rice production.

Mg-Al layered double hydroxides film coating for efficient biomimetic stealth

Most biomimetic stealth materials have difficulty in achieving the “homochromatic and homospectral” of green vegetation and therefore have low spectral similarity to green vegetation and are easily detected and identified by hyperspectral imaging techniques. Hence, there is an urgent need to develop “homochromatic and homospectral” bionic materials for the hyperspectral stealth. Based on the generation mechanism of spectral curves of green vegetation in the 400–2500 nm band, environmentally friendly functional fillers with excellent weather resistance and stealth coatings with Mg-Al layered double hydroxide films were prepared. The cosine value of the near-infrared spectrum of stealth coatings and plant leaves reached 0.997, achieving the “same color and spectrum” as the green vegetation. The spectral cosine values of the 30 days outdoor stealth coatings and green leaves can still reach 0.984, demonstrating excellent weather resistance. These stealth coatings provide new insights into the application of hyperspectral materials in biomimetic camouflage.

Response- and probability-based evaluation of spectrally matched ground motion selection strategies for bi-directional dynamic analysis of low- to mid-rise RC buildings

In this study, the effect of different strategies which consider various levels of constraints for spectrally matched ground motion (GM) selection on seismic responses of the buildings was evaluated. For this, six different three-dimensional buildings and three different local soil classes were considered. Various GM record sets were used for each strategy and local soil class pair to perform bi-directional nonlinear dynamic analyses of the buildings and maximum global and maximum inter-story drift ratio demands were obtained. To evaluate the efficiency of proposed strategies, the mean and dispersion of the demands were investigated. Then, the differences among the means of the seismic demands obtained for the strategies were evaluated using the analysis of variance method. Moreover, probability curves of the demands were constructed and compared. The results indicate that i) the mean of the demands generally used for code-based performance assessment can be estimated more consistently by the proposed strategies; ii) the supplemental constraints about spectral matching allow to control the dispersion of the spectral acceleration values of selected GMs and hence the dispersion of the demands; iii) using the appropriate one of the proposed strategies, GMs with desired dispersion of spectral accelerations can be acquired for probability-based performance assessment.

Application of remote sensing methods for statistical estimation of organic matter in soils

The availability of reliable information on the physicochemical properties of soils is a necessary tool for maintaining and improving fertility and effective optimization of agricultural land management in many countries. However, ground-based research methods require significant financial and time resources. It has been established that methods based on remote sensing data are an efficient, accurate, and less costly solution for studying different types of soil cover parameters. This work aims to determine the predicted indicator of humus content in soils in selected regions of the Kyiv region (Ukraine) with the corresponding soil types. For this, the spectral properties of chernozem soils were investigated based on Landsat 8 OLI satellite images. A mosaic of the mean spectral reflectance values for the study period (2013-2015) was created using the Google Earth Engine. The vegetation indices NDSI, NDWI, NDBI, MSAVI, and NDVI were used to identify bare soils. Using multiple linear regression, an optimal F-Comparing Nested Model was created for predicting humus content in soils, including seven parameters. The model's accuracy was estimated with such indicators R=0.95, R2= 0.90, σy = 0.16 %. The approach based on the proposed model can be used to support the adoption of the necessary management decisions to improve soil fertility and maintain balanced land use.

Recommendation of new design spectra for Iran using modified Newmark method

The Newmark design spectra are commonly adopted in seismic codes to calculate design spectra, while these spectra generally differ from the statistically driven ones. This study aims to re-construct the Iranian design spectra by implementing a modified Newmark method on an extensive database of previous earthquakes in Iran. Three sets of recorded earthquakes are considered to evaluate the effects of parameters such as source-to-site distance, magnitude of ground motion, and shear-wave velocity. Considering that the selected earthquakes have different frequency contents, the suitable frequency ranges for each earthquake category are obtained. Subsequently, a statistical approach is adopted to calculate amplification factors and spectral bounds of the site design spectrum of Iran for three different site categories as a function of ground motion's magnitude. The calculated coefficients can be used to modify the Newmark spectral values in displacement, velocity, and acceleration-sensitive regions to obtain suitable design spectra. The results indicate that, in general, the proposed design spectra can provide a better representative of the earthquakes in Iran compared to the current Iranian seismic design code.

Offshore near-fault pulse-like ground motions: An insight into the DONET1 seafloor ground motions from the 2016 Mw6.0 Off-Mie earthquake in Japan

Offshore near-fault ground motions were obtained by the DONET1 seafloor seismic network during the 2016 Off-Mie Mw6.0 earthquake that occurred in the Nankai Trough of Japan. These data provide an opportunity for exploring the characteristics of offshore near-fault ground motions, especially pulse-like ground motions. A comparison of the offshore and onshore near-fault ground motions indicates that the recorded offshore spectral acceleration (SA) in the period of 0.5–5.0 s and peak ground velocity (PGV) for this earthquake are higher than those of the onshore values, and the observed maximum spectral value (βmax) of the offshore near-fault ground motions in this event is underestimated by the design spectra in the seismic codes of China, the United States, and Japan. Based on the Hilbert-Huang transform method, eight offshore pulse-like ground motion records are identified and extracted in the Off-Mie earthquake. The primary analysis indicates that the pulse-like ground motion may be caused by the directivity effect and the radiation pattern. Comparing the pulse parameters, time-frequency parameters, and response spectra of offshore and onshore pulse-like ground motions, the findings demonstrate that within the context of this earthquake event, approximately half of the offshore pulse amplitude (Vp) exceeds the predicted values of onshore models; the low-frequency components of offshore pulse-like ground motions of this event are more pronounced, constituting a larger portion of the total ground motion energy; offshore pulse-like ground motions exhibit a tendency to possess higher maximum instantaneous energy (Einst) compared to onshore pulse-like ground motions with similar rupture distances. Moreover, the βmax of offshore pulse-like ground motions is found to be greater than that of onshore pulse-like ground motions in medium to long periods (>0.5 s). The identified and characteristic recognition of offshore near fault pulse-like ground motion revealed by this earthquake event raises new concerns about seismic design for offshore engineering.

The closed-loop control method based on dual-port adaptive internal model control for fine image stabilization of space telescopes.

In view of the complex working environment of space astronomical telescopes, the influence of various disturbance sources on the imaging quality cannot be ignored. This paper focuses on compensating for the space telescope line-of-sight (LOS) deviation and suppressing the low-frequency disturbance problem in astronomical observation. A closed-loop control method based on dual-port adaptive internal model control (AIMC) for the fine image stabilization system (FISS) was proposed. To be specific, the fine guidance sensor (FGS) as the high-precision detection unit of the FISS calculates the telescope LOS deviation and sends it to the controller unit in real time. The controller unit drives the large-aperture fast steering mirror (FSM), which performs high-precision two-dimensional rotation to compensate for the telescope LOS deviation, according to the dual-port AIMC control algorithm. Moreover, the dual-port AIMC control method adds an AIMC loop on the basis of the feedback loop and adjusts the filter parameters adaptively according to the target angular velocity of the FSM, achieving higher disturbance suppression capability. The experimental results verify that the control method proposed can effectively compensate for the LOS deviation and suppress the composite frequency disturbance. In the 0-8Hz frequency band, the power spectral density integral values of the star centroid deviation in the X and Y directions of the FGS are, respectively, suppressed by 97.38% and 98.38%.

The influence of combined effects of hyperbaria and hyperoxia on human heart rate variability during exercise strain

With the participation of 8 male volunteers, the dynamics of values of heart rate autonomic regulation were studied at response to physical load on a bicycle ergometer twice: both respirating by the room air under normobaric environment and simulating effects of the altered hyperoxic respiratory gas mixture (HRGM) by the rebreathe respiration methods from a rebreather at the high-pressure chamber (at «depth» 7 m). The devices and methods of Holter electrocardiogram monitoring were used under 24 hours research. The specialized software to analyze the data was used. The electrocardiogram (ECG) and calculated time series of cardiac intervals data obtained were subjected to mathematical processing to calculate statistical and spectral values of heart rate variability (HRV). Additionally, the geometric and nonlinear analysis methods of HRV were investigated. It has been established that influencing factors (compound and pressure of the HRGM) affect the autonomic regulation of heartbeats both at rest and during physical load. Clinical practitioners the HRV values are studied at rest and during strictly regulated tests, i.e. in stationary conditions. The analysis of non-stationary processes, for example, when it is necessary to continuously analyze data, the so-called transient processes under increasing psychological stress, to assess changes in the autonomic regulation of the heart during breathing of gas mixtures with different compositions (hypoxic therapy, hyperbaric oxygenation, etc.), and, especially during physically upload are used the methods of nonlinear and geometric analysis of HRV that are independent of the degree of nonstationary processes and, to some extent, of artifactual cardiac intervals. During the breathing the respiratory gas mixtures with an increased substance of O2 under conditions of high pressure, the activity of the parasympathetic branches of the autonomic nervous system (ANS) significantly increases. The nonlinear dynamics indexes reflect significant differences in the activity of autonomic components under experimental conditions in the direction of strengthening the parasympathetic links of the ANS. The use of nonlinear analysis values is more acceptable when evaluating obtained of non-stationary processes. In general, the study confirms that the regulatory response to the effects of hyperbaria and hyperoxia when performing a bicycle ergometer test with stepwise increase exercise strain is manifested by the prevalence of the activity of the parasympathetic part of the ANS autonomic regulation of cardiac rhythm compared to regular room air and barometric pressure.

CHALLENGES IN PREPARING DATASETS FOR SUPER-RESOLUTION ON THE EXAMPLE OF SENTINEL-2 AND PLANET SCOPE IMAGES

Abstract. Benchmark datasets is an significant aspect in in many areas such as computer vision, deep learning, geospatial data as they serve as standardized test sets for evaluating the performance of models. Among many techniques of image processing, there is super-resolution (SR) which is aimed at reconstructing a low-resolution (LR) image into a high-resolution (HR) image. For training and validation SR models as a dataset the pairs of HR and LR images are needed, which should be the same apart from resolution. There is a lot of benchmark datasets for super-resolution methods, but they usually include conventional photographs of an common objects, while remote sensing data have different characteristic in general. This paper focuses on the process of preparing datasets for super-resolution in satellite images, where high-resolution and low-resolution image data come from different sources. The case of the single-image super-resolution method was considered. The experiment was performed on Sentinel-2 and PlanetScope data, but the assumptions can also be transferred to data obtained from other satellites. The procedure on how to make the pairs of HR and LR images consistent in terms of time, location and spectral values was proposed. The impact of the processes carried out was measured using image similarity measurement methods such as PSNR, SSIM and SCC.