Academic literature on the topic 'Global field root mean square'
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Journal articles on the topic "Global field root mean square"
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Apeh, O. I., E. C. Moka, and V. N. Uzodinma. "Evaluation of Gravity Data Derived from Global Gravity Field Models Using Terrestrial Gravity Data in Enugu State, Nigeria." Journal of Geodetic Science 8, no. 1 (December 1, 2018): 145–53. http://dx.doi.org/10.1515/jogs-2018-0015.
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Abstract Spherical harmonic expansion is a commonly applied mathematical representation of the earth’s gravity field. This representation is implied by the potential coeffcients determined by using elements/parameters of the field observed on the surface of the earth and/or in space outside the earth in the spherical harmonic expansion of the field. International Centre for Gravity Earth Models (ICGEM) publishes, from time to time, Global Gravity Field Models (GGMs) that have been developed. These GGMs need evaluation with terrestrial data of different locations to ascertain their accuracy for application in those locations. In this study, Bouguer gravity anomalies derived from a total of eleven (11) recent GGMs, using sixty sample points, were evaluated by means of Root-Mean-Square difference and correlation coeficient. The Root-Mean-Square differences of the computed Bouguer anomalies from ICGEMwebsite compared to their positionally corresponding terrestrial Bouguer anomalies range from 9.530mgal to 37.113mgal. Additionally, the correlation coe_cients of the structure of the signal of the terrestrial and GGM-derived Bouguer anomalies range from 0.480 to 0.879. It was observed that GECO derived Bouguer gravity anomalies have the best signal structure relationship with the terrestrial data than the other ten GGMs. We also discovered that EIGEN-6C4 and GECO derived Bouguer anomalies have enormous potential to be used as supplements to the terrestrial Bouguer anomalies for Enugu State, Nigeria.
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ARKIN, HANDAN. "STUDY OF ELASTIN SEQUENCES WITH SOLVENT INDUCED FORCE FIELD." International Journal of Modern Physics C 16, no. 09 (September 2005): 1339–46. http://dx.doi.org/10.1142/s0129183105007959.
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Conformational structures of two common repeat motifs Val1-Pro2-Gly3-Val4-Gly5 and Gly1-Leu2-Gly3-Gly4 of tropoelastin are investigated by using the multicanonical simulation procedure with solvation effects included energy force field. The effects of solvation energy term on the conformations are determined by analyzing Ramachandran plots. By minimizing the energy structures along the trajectory, the thermodynamically most stable low-energy microstates of the molecule in aqueous solution are determined and the root mean square deviations of these structures with respect to the global minimum are calculated.
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Arbuzov, Andrej B., and Alexander E. Pavlov. "Reduced conformal geometrodynamics." International Journal of Modern Physics A 35, no. 02n03 (January 30, 2020): 2040023. http://dx.doi.org/10.1142/s0217751x20400230.
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The global time in geometrodynamics is defined in a covariant under diffeomorphisms form. An arbitrary static background metric is taken in the tangent space. The global intrinsic time is identified with the mean value of the logarithm of the square root of the ratio of the metric determinants. The procedures of the Hamiltonian reduction and deparametrization of dynamical systems are implemented. The reduced Hamiltonian equations of motion of gravitational field in semi-geodesic coordinate system are written.
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Udompant, Kannapat, Ricardo Ospina, Yong-Joo Kim, and Noboru Noguchi. "Utilization of Quasi-Zenith Satellite System for Navigation of a Robot Combine Harvester." Agronomy 11, no. 3 (March 5, 2021): 483. http://dx.doi.org/10.3390/agronomy11030483.
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The purpose of this study is to evaluate the performance of a robot combine harvester by comparing the Centimeter Level Augmentation Service (CLAS) and the Multi-Global Navigation Satellite System (GNSS) Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) from the Quasi-Zenith Satellite System (QZSS) by using the Real Time Kinematic (RTK) positioning technique as a reference. The first section of this study evaluates the availability and the precision under static conditions by measuring the activation time, the reconnection time, and obtaining a Twice Distance Root Mean Square (2DRMS) of 0.04 m and 0.10 m, a Circular Error Probability (CEP) of 0.03 m and 0.08 m, and a Root Mean Square Error (RMSE) of 0.57 m and 0.54 m for the CLAS and MADOCA, respectively. The second section evaluates the accuracy under dynamic conditions by using a GNSS navigation-based combine harvester running in an experimental field. The results show that the RMSE of the lateral deviation is between 0.04 m and 0.69 m for MADOCA and between 0.03 m and 0.31 m for CLAS; which suggest that the CLAS positioning augmentation system can be utilized for the robot combine harvester if the user considers these accuracy and dynamic characteristics.
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Li, Zhongbing, Wei Pang, Haibo Liang, Guihui Chen, Hongming Duan, and Chuandong Jiang. "Fast Quantitative Modelling Method for Infrared Spectrum Gas Logging Based on Adaptive Step Sliding Partial Least Squares." Energies 15, no. 4 (February 12, 2022): 1325. http://dx.doi.org/10.3390/en15041325.
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Infrared spectroscopy (IR) quantitative analysis technology has shown excellent development potential in the field of oil and gas logging. However, due to the high overlap of the IR absorption peaks of alkane molecules and the offset of the absorption peaks in complex environments, the quantitative analysis of IR spectroscopy applied in the field puts forward higher requirements for modelling speed and accuracy. In this paper, a new type of fast IR spectroscopy quantitative analysis method based on adaptive step-sliding partial least squares (ASS-PLS) is designed. A sliding step control function is designed to change the position of the local PLS analysis model in the full spectrum band adaptively based on the relative change of the current root mean square error and the global minimum root-mean-square error for rapid modelling. The study in this paper reveals the influence of the position and width of the local modelling window on the performance, and how to quickly determine the optimal modelling window in an uncertain sample environment. The performance of the proposed algorithm has been compared with three typical quantitative analysis methods by experiments on an IR spectrum dataset of 400 alkane samples. The results show that this method has a fast quantitative modelling speed with high analysis accuracy and stability. It has important practical value for promoting IR spectroscopy gas-logging technology.
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Mäkinen, Antti, Ilkka Korpela, Timo Tokola, and Annika Kangas. "Effects of imaging conditions on crown diameter measurements from high-resolution aerial images." Canadian Journal of Forest Research 36, no. 5 (May 1, 2006): 1206–17. http://dx.doi.org/10.1139/x06-011.
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Imaging geometry, the structure of the forest, and certain tree properties can cause inaccuracy in image measurements of the crown dimensions of individual trees. Measurement error of the crown diameter was studied in relation to various factors to explain this error. A secondary aim was to generate calibration models for improving the accuracy of crown diameter image measurements. The crown diameters of a total of 715 sample trees in southern Finland were measured in the field and from aerial photographs at scales 1:6000, 1 : 12 000, and 1 : 16 000. The photo grammetric image measurement seemed to systematically underestimate the true crown diameter, and the major factor affecting the bias was tree species. The mean underestimation varied from 0.30 to 0.80 m, with root mean square errors of 0.951.10 m depending on the tree species. Linear regression analysis was employed to define the factors that had an effect on the image measurements, and calibration models in the form of linear regression models were generated. The calibration models worked reasonably well, and the root mean square error for the calibrated observations decreased by 22% for Scots pine (Pinus sylvestris L.), 53% for Norway spruce (Picea abies (L.) Karst), and 47% for silver birch (Betula pendula Roth).
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Wallerman, Jörgen, Steve Joyce, Coomaren P. Vencatasawmy, and Håkan Olsson. "Prediction of forest stem volume using kriging adapted to detected edges." Canadian Journal of Forest Research 32, no. 3 (March 1, 2002): 509–18. http://dx.doi.org/10.1139/x01-214.
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The modern techniques of the global positioning system and geographic information system enable many new approaches to forestry planning problems. Using these it is possible to efficiently geoposition, store, and analyze each field measurement in a spatial context. This work is directed towards the application of a dynamic forestry planning system based on a forest map with very high spatial resolution created from geopositioned field plot data, instead of the traditional forest stand map. The new dynamic system is dependent on accurate methods to create a high-resolution map from a set of field measurements. This problem may be solved using the kriging spatial prediction (interpolation) method. The aim of this paper is to present and empirically evaluate a new kriging method side-by-side with global and stratified kriging. The new method uses the output from an edge-detection algorithm, here applied to Landsat TM image data, to increase the prediction accuracy. Prediction evaluation was made in terms of mean forest stem volume per hectare measured on circular field plots of 10 m radius. The new method showed a prediction root mean square error of 41% of the mean volume, compared with corresponding results of global, 58%, and stratified kriging, 45%.
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Wang, Sijia, Yunhao Chen, Mingguo Wang, Yifei Zhao, and Jing Li. "SPA-Based Methods for the Quantitative Estimation of the Soil Salt Content in Saline-Alkali Land from Field Spectroscopy Data: A Case Study from the Yellow River Irrigation Regions." Remote Sensing 11, no. 8 (April 23, 2019): 967. http://dx.doi.org/10.3390/rs11080967.
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The problem of soil salinization has always been a global problem involving resource, environmental, and ecological issues, and is closely related to the sustainable development of the social economy. Remote sensing provides an effective technical means for soil salinity identification and quantification research. This study focused on the estimation of the soil salt content in saline-alkali soils and applied the Successive Projections Algorithm (SPA) method to the estimation model; twelve spectral forms were applied in the estimation model of the spectra and soil salt content. Regression modeling was performed using the Partial Least Squares Regression (PLSR) method. Proximal-field spectral measurements data and soil samples were collected in the Yellow River Irrigation regions of Shizuishan City. A total of 60 samples were collected. The results showed that application of the SPA method improved the modeled determination coefficient (R2) and the ratio of performance to deviation (RPD), and reduced the modeled root mean square error (RMSE) and the percentage root mean square error (RMSE%); the maximum value of R2 increased by 0.22, the maximum value of RPD increased by 0.97, the maximum value of the RMSE decreased by 0.098 and the maximum value of the RMSE% decreased by 8.52%. The SPA–PLSR model, based on the first derivative of reflectivity (FD), the FD–SPA–PLSR model, showed the best results, with an R2 value of 0.89, an RPD value of 2.72, an RMSE value of 0.177, and RMSE% value of 11.81%. The results of this study demonstrated the applicability of the SPA method in the estimation of soil salinity, by using field spectroscopy data. The study provided a reference for a subsequent study of the hyperspectral estimation of soil salinity, and the proximal sensing data from a low distance, in this study, could provide detailed data for use in future remote sensing studies.
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Okpoko, J. S., and H. A. P. Audu. "Geostatistical Modelling and Mapping of the Concentration of Gaseous Pollutants." October 2018 2, no. 2 (October 2018): 219–32. http://dx.doi.org/10.36263/nijest.2018.02.0084.
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In this study, the prediction of the concentration of gaseous pollutants around Ughelli West gas flow station in Delta State of Nigeria was carried out using Geostatistical technique in GIS environment. Since air pollutants negatively affect quality of air, lives and the environment, there is therefore the need to frequently monitor air quality, have thorough understanding of the pollutants’ concentration and their spatial distribution in an environment. The gaseous pollutants data of volatile organic compounds (VOCs), methane (CH4), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ozone (O3), were obtained using Multi-parameter gas monitor while that of fine particulate matter (PM2.5) was obtained with SPM meter for a period of three months. Thermo Anemometer was used to obtain the values of wind speed, ambient temperature, atmospheric pressure and relative humidity. Artificial Neural Network designer software (Pythia) was used to validate the acquired field data; predict the concentration of the gaseous pollutants at selected distances from the flow station. The geospatial coordinates of the flow station were obtained using Global Navigation Satellite System (GNSS) receivers; the geospatial modelling and analysis were performed with ArcGIS software and ordinary kriging method of Geostatistical techniques. The results of the maximum concentration for the gaseous pollutants in the study area were 28.17 µg/m3, 19.44 µg/m3, 0.37 µg/m3, 49.81 µg/m3, 0.061 µg/m3 and 0.047µg/m3 for VOCs, CH4, NO2, PM2.5, O3 and SO2 respectively. The root mean square error for the concentration of the gaseous pollutants, ozone and sulphur (IV) oxide in the study area were 0.01618 and 0.008417 indicating a good interpolation model, while their root mean square standard errors, which show the reliability of the predicted values, were 0.70513551 and 0.8459251 respectively. These results conform with the report of other researchers that a better kriging method yields a smaller root mean square and a standard root mean square closer to one. The developed prediction maps for the gaseous pollutants in this study revealed that the study area will experience lower concentration of gaseous pollutants at a distance of 400 m and above.
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Li, Qi, and Ding Jun Wu. "Simulation and Field Test for Local Acceleration of an U-Shaped Girder." Advanced Materials Research 250-253 (May 2011): 2016–23. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.2016.
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The local vibration of a bridge under moving train is the source of low frequency noise radiated from the structure. Local vibration of bridges has not been widely studied compared to global vibration that leads to serviceability and safety problems. The local vibration of an urban rail transit U-shaped girder is simulated with the proposed mode superposition based train-track-bridge dynamic interaction model. The computed local acceleration responses under various train speeds are then verified by those obtained from field test, in terms of time-histories, spectra, peak-to-peak values and root mean square (RMS) values. It is founded that the main frequencies of the local acceleration of this girder are below 100 Hz. The proposed method and the computed local vibration could be further applied to predict the bridge-borne noise.
Dissertations / Theses on the topic "Global field root mean square"
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Jeans, Rhiannon. "Form perception and neural feedback: insights from V1 and V2." Thesis, 2014. http://hdl.handle.net/1885/12731.
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In the brain, every cortical inter-area feedforward projection shares a reciprocal feedback connection. Despite its pervasive nature in the brain, our understanding of the functional role of neural feedback in form perception remains incomplete, particularly in behaving animals. This problem is addressed in humans with a novel form completion paradigm. Seven subjects (5 female) had their EEG waveforms analysed using three linear models showing non-significant differences between stimulus conditions designed to produce differences by manipulating neural feedback to V1. Two of these subjects (one female), in addition to EEG waveforms, had combined magnetic resonance imaging (MRI) and functional MRI (fMRI) cortical maps that allowed anatomically close areas such as V1 and V2 to have their signals decomposed and neural feedback inferred. Differences between stimulus conditions arose once signals had been divided into V1 and V2. Significant differences (p < .05) for one subject in V1 and V2 suggests cortical interactions at 100ms and 350ms. This suggests the form completion paradigm has utility at investigating the influence of the V2 far receptive field surround on V1, given future given signal to noise issues are resolved.
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PÁLENÍKOVÁ, Lenka. "Geodetické práce v investiční výstavbě." Master's thesis, 2009. http://www.nusl.cz/ntk/nusl-51158.
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The accuracy appraisal and its evaluation with what the results of geodetic work are being achieved will be shown in this graduation thesis. As well as the related legislation and economic point of view of the price setting in comparison to other geodetic companies. One of the major surveyed area is testing of the used instruments - confrontation of achieved values with the values stated by manufacturer, accuracy analysis of the used methods and allignment of independent measurements of equal magnitude.
Book chapters on the topic "Global field root mean square"
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Keller, Reto B. "Decibel." In Design for Electromagnetic Compatibility--In a Nutshell, 23–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14186-7_3.
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AbstractThis chapter introduces the topic decibel in a compact form. Decibel is defined as the ratio of two quantities, typically power, voltage, or current. In the field of EMC, the decibel must be understood. One advantage of decibels is that a gain of 10 dB means a gain of 10 dB for current, voltage, and power likewise. This fact helps to prevent misinterpretations and helps to simplify things. This is the main reason why EMC and high-frequency system engineers like to work with decibels.This chapter assumes that values of voltages V [V], currents I [A], power P [W], electric field strengths E [V/m], and magnetic field strength H [A/m] are given as root-mean-square (RMS) values.
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Pinsky, Mark. "Commentary on: [L 33] The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction [L 34] A Heuristic Exposition of Wiener’s Mathematical Theory of Prediction and Filtering [L 69] Limiting Theorems for Galton-Watson Branching Process [L 70] Limiting Theorems for Age-Dependent Branching Process [L 81] (with H. P McKean, Jr.) Weighted Trigonometrical Approximation on R1 with Application to the Germ Field of a Stationary Gaussian Noise." In Selected Papers of Norman Levinson, 160–62. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-5335-8_15.
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Adnan, Muhammad, Rana Muhammad Adnan, Shiyin Liu, Muhammad Saifullah, Yasir Latif, and Mudassar Iqbal. "Prediction of Relative Humidity in a High Elevated Basin of Western Karakoram by Using Different Machine Learning Models." In Weather Forecasting [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98226.
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Accurate and reliable prediction of relative humidity is of great importance in all fields concerning global climate change. The current study has employed Multivariate Adaptive Regression Spline (MARS) and M5 Tree (M5T) models to predict the relative humidity in the Hunza River basin, Pakistan. Both the models provided the best prediction for the input scenario S6 (RHt-1, RHt-2, RHt-3, Tt-1, Tt-2, Tt-3). The statistical analysis displayed that the MARS model provided a better prediction of relative humidity as compared to M5T at all meteorological stations, especially, at Ziarat followed by Khunjerab and Naltar. The values of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) were (5.98%, 5.43%, and 0.808) for Khunjerab; (6.58%, 5.08%, and 0.806) for Naltar; and (5.86%, 4.97%, 0.815) for Ziarat during the testing of MARS model whereas, the values were (6.14%, 5.56%, and 0.772) for Khunjerab; (6.19%, 5.58% and 0.762) for Naltar and (6.08%, 5.46%, 0.783) for Ziarat during the testing of M5T model. Both the models performed slightly better in training as compared to the testing stage. The current study encourages future research to be conducted at high altitude basins for the prediction of other meteorological variables using machine learning tools.
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Schulman, L. S. "Ferromagnetism." In When Things Grow Many, 50–62. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780198861881.003.0005.
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Abstract Magnetism and order parameters are discussed in both mean field theory and exact treatments. An example of stochastic dynamics for the Ising model is given. The Curie–Weiss model is defined as a system in which mean field theory is exact. For this system (consisting of N spins) the fluctuations at the critical point are the fourth root of N, rather than the square root as is the case when the variables are independent.
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Cluis, D. A. "Global Variance and Root Mean Square Error Associated with Linear Interpolation of a Markovian Time-Series." In Statistical Aspects of Water Quality Monitoring, Proceedings of the Workshop held at the Canada Centre for Inland Waters, 335–46. Elsevier, 1986. http://dx.doi.org/10.1016/s0167-5648(08)70804-9.
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Sohor, Andrii. "A PRIORI RESEARCH RELATED TO THE CALCULATION OF THE REGIONAL ELLIPSOID FOR UKRAINE AND ITS EFFECTIVENESS." In Theoretical and practical aspects of the development of modern scientific research. Publishing House “Baltija Publishing”, 2022. http://dx.doi.org/10.30525/978-9934-26-195-4-13.
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Despite the high accuracy of global geodetic reference systems and their widespread use in GPS measurements, regional (local) geodetic systems are becoming more widely used. For example, the World Geodetic System 1984 (WGS84) has 83 such local systems. The emergence of the latter is caused by the emergence of new problems of physical geodesy. These are the so-called regional problems, which make it possible to study in more detail both the geometric and gravimetric (physical) properties of the studied region (territory). For example, the tasks of constructing a high-precision regional geoid (quasi-geoid), regional ellipsoid, determining the regional normal formula of gravity, and others are becoming increasingly important. That is why at present both national and regional reference ellipsoids are accepted for processing geodetic data on a regional scale (for example, for a specific country), and for global research – a general terrestrial reference ellipsoid GRS80 or, when processing GPS data – a general terrestrial reference ellipsoid WGS84.In principle, any reference ellipsoid that represents a generalized figure of the Earth with appropriate accuracy can be used to process geodetic information. The deviations of the geoid from such an ellipsoid can determine the corrections that must be made in the results of geodetic measurements to bring the latter to the surface of this ellipsoid. However, with large deviations of the geoid from the reference ellipsoid, there are large corresponding reductions of geodetic measurements, which are burdened with significant errors due to the linearization of the main problem of geodesy and, consequently, the problem of bringing geodetic measurements to the ellipsoid. Therefore, from a practical point of view, to reduce the impact of these linearization errors and obtain methodologically optimal results of geodetic data processing, it is expedient and even necessary to use a reference ellipsoid that best describes the generalized geoid surface in the region of specific geodetic works.Given the above, the question arose about the national reference coordinate system, as such a system has some advantages over the national system in the process of practical processing of mass geodetic measurements, especially linear. In this regard, the issues of building a national reference system, namely, the definition of a regional ellipsoid, are very important and relevant. Therefore, the scope of our research is the construction of a national reference system based on data on the regional gravitational field of Ukraine. The methodology of such research is that the task of determining the regional ellipsoid is practically reduced to finding some corrections to the known, accepted by us, the general terrestrial ellipsoid GRS80. The regional ellipsoid for the territory of Ukraine should be the one that would best represent the geoid (quasi-geoid) of the region. That is, the heights of the geoid relative to the regional ellipsoid within the territory of Ukraine should be as small as possible. These questions are reflected in this monograph, the purpose of which is to investigate a priori calculations to determine the parameters of the internal orientation of the regional ellipsoid according to its gravitational field in Ukraine. Thus, based on the results of the above a priori studies, the following can be noted. Determining all five parameters of a regional ellipsoid leads to a strong functional dependence of the parameters. This dependence (correlation) is quite well demonstrated on the values of root mean square errors, which are proportional to the obtained parameters and even exceed the latter. Taking into account these remarks, we can conclude that the joint calculation of all five parameters by the method of least squares on the territory of Ukraine does not give us the expected good results. This is well seen from a priori calculations based on the heights of the geoid, presented in the form of a spheroidal trapezoid, which describes the territory of Ukraine. In contrast to this solution, studies to determine only the parameters of the internal orientation of the ellipsoid at a given major half-axis and compression of this ellipsoid, make it possible to choose a terrestrial regional ellipsoid that would best represent a geoid (quasi-geoid) built in Ukraine.
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Ben Amira, Bilel, Mariem Ammar, Ahmad Kaffel, Zied Driss, and Mohamed Salah Abid. "The Effects of Curved Blade Turbine on the Hydrodynamic Structure of a Stirred Tank." In Vortex Dynamics Theories and Applications. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.92394.
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This work is aimed at studying the hydrodynamic structure in a cylindrical stirred vessel equipped with an eight-curved blade turbine. Flow fields were measured by two-dimensional particle image velocimetry (PIV) to evaluate the effect of the curved blade turbine. Velocity field, axial and radial velocity distribution, root mean square (rms) of the velocity fluctuations, vorticity, and turbulent kinetic energy were presented. Therefore, two recirculation loops were formed close to the free surface and in the bottom of the tank. Moreover, the highest value area of the vorticity is localized in the upper region of the tank which follows the same direction of the first circulation loop. The turbulent kinetic energy is maximum at the blade tip following the trailing vortices.
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Lagerlund, Terrence D. "Instrumentation and Electricity for Clinical Neurophysiology." In Clinical Neurophysiology, edited by Devon I. Rubin, 1019–32. 5th ed. Oxford University PressNew York, 2021. http://dx.doi.org/10.1093/med/9780190067854.003.0058.
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Abstract This chapter reviews the basic principles of electricity and how they apply to electrical circuits. Electrical properties such as electric field, electric potential, electromotive force, electric current, current density, resistance, conductance, resistivity, conductivity, capacitance, inductance, frequency, reactance, and impedance are defined, along with their measurement units and formulas for calculation. Electrical circuit components such as seats of electromotive force (batteries and generators), resistors, capacitors, coils (inductors), diodes, and transistors are described, as well as example circuits containing these components. Key concepts of electrical circuits such as direct current and alternating current, root mean square measurements, time constant, cutoff frequency, resonance, forward and reverse biasing, gain (amplification), and common mode rejection ratio are discussed. High-pass and low-pass filter circuits and differential amplifier circuits are also described and their usage is illustrated.
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Mishra, Shashwati, and Mrutyunjaya Panda. "Medical Image Thresholding Using Genetic Algorithm and Fuzzy Membership Functions." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 896–916. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch045.
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Thresholding is one of the important steps in image analysis process and used extensively in different image processing techniques. Medical image segmentation plays a very important role in surgery planning, identification of tumours, diagnosis of organs, etc. In this article, a novel approach for medical image segmentation is proposed using a hybrid technique of genetic algorithm and fuzzy logic. Fuzzy logic can handle uncertain and imprecise information. Genetic algorithms help in global optimization, gives good results in noisy environments and supports multi-objective optimization. Gaussian, trapezoidal and triangular membership functions are used separately for calculating the entropy and finding the fitness value. CPU time, Root Mean Square Error, sensitivity, specificity, and accuracy are calculated using the three membership functions separately at threshold levels 2, 3, 4, 5, 7 and 9. MRI images are considered for applying the proposed method and the results are analysed. The experimental results obtained prove the effectiveness and efficiency of the proposed method.
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Mishra, Bikram Keshari, and Amiya Kumar Rath. "An Enhanced Clustering Method for Image Segmentation." In Exploring Critical Approaches of Evolutionary Computation, 325–43. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5832-3.ch016.
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The findings of image segmentation reflect its expansive applications and existence in the field of digital image processing, so it has been addressed by many researchers in numerous disciplines. It has a crucial impact on the overall performance of the intended scheme. The goal of image segmentation is to assign every image pixels into their respective sections that share a common visual characteristic. In this chapter, the authors have evaluated the performances of three different clustering algorithms used in image segmentation: the classical k-means, its modified k-means++, and proposed enhanced clustering method. Brief explanations of the fundamental working principles implicated in these methods are presented. Thereafter, the performance which affects the outcome of segmentation are evaluated considering two vital quality measures, namely structural content (SC) and root mean square error (RMSE). Experimental result shows that the proposed method gives impressive result for the computed values of SC and RMSE as compared to k-means and k-means++. In addition to this, the output of segmentation using the enhanced technique reduces the overall execution time as compared to the other two approaches irrespective of any image size.
Conference papers on the topic "Global field root mean square"
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Noel, Adam, Dimitrios Makrakis, and Andrew W. Eckford. "Root Mean Square Error of Neural Spike Train Sequence Matching with Optogenetics." In 2017 IEEE Global Communications Conference (GLOBECOM 2017). IEEE, 2017. http://dx.doi.org/10.1109/glocom.2017.8255060.
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Kumar, Ashutosh. "Transformer-Based Deep Learning Models for Well Log Processing and Quality Control by Modelling Global Dependence of the Complex Sequences." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208109-ms.
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Abstract A single well from any mature field produces approximately 1.7 million Measurement While Drilling (MWD) data points. We either use cross-correlation and covariance measurement, or Long Short-Term Memory (LSTM) based Deep Learning algorithms to diagnose long sequences of extremely noisy data. LSTM's context size of 200 tokens barely accounts for the entire depth. Proposed work develops application of Transformer-based Deep Learning algorithm to diagnose and predict events in complex sequences of well-log data. Sequential models learn geological patterns and petrophysical trends to detect events across depths of well-log data. However, vanishing gradients, exploding gradients and the limits of convolutional filters, limit the diagnosis of ultra-deep wells in complex subsurface information. Vast number of operations required to detect events between two subsurface points at large separation limits them. Transformers-based Models (TbMs) rely on non-sequential modelling that uses self-attention to relate information from different positions in the sequence of well-log, allowing to create an end-to-end, non-sequential, parallel memory network. We use approximately 21 million data points from 21 wells of Volve for the experiment. LSTMs, in addition to auto-regression (AR), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) conventionally models the events in the time-series well-logs. However, complex global dependencies to detect events in heterogeneous subsurface are challenging for these sequence models. In the presented work we begin with one meter depth of data from Volve, an oil-field in the North Sea, and then proceed up to 1000 meters. Initially LSTMs and ARIMA models were acceptable, as depth increased beyond a few 100 meters their diagnosis started underperforming and a new methodology was required. TbMs have already outperformed several models in large sequences modelling for natural language processing tasks, thus they are very promising to model well-log data with very large depth separation. We scale features and labels according to the maximum and minimum value present in the training dataset and then use the sliding window to get training and evaluation data pairs from well-logs. Additional subsurface features were able to encode some information in the conventional sequential models, but the result did not compare significantly with the TbMs. TbMs achieved Root Mean Square Error of 0.27 on scale of (0-1) while diagnosing the depth up to 5000 meters. This is the first paper to show successful application of Transformer-based deep learning models for well-log diagnosis. Presented model uses a self-attention mechanism to learn complex dependencies and non-linear events from the well-log data. Moreover, the experimental setting discussed in the paper will act as a generalized framework for data from ultra-deep wells and their extremely heterogeneous subsurface environment.
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Kokamägi, Kaupo, Natalja Liba, Kristo Must, and Martin Sirk. "Accuracy Assessment of Mobile Laser Scanning Elevation Data in Different Vegetation Areas." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.202.
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Due to the overall development of technology, laser scanning has reached a new level. During the last decade, all the different technologies necessary for mobile laser scanning, have been developed. Due to the fact that mobile laser scanning brings the need to process very large amounts of data, development of computers and software is also very important. The aim of current research was to assess the accuracy of mobile laser scanning elevation data in different vegetation areas and to explore if mobile laser scanning could be used as an alternative to aerial laser scanning. This article only covers the data collecting, processing and accuracy assessment aspects of the research. Data used in current study was collected in summer of 2015, during mobile laser scanning of Põltsamaa-Kärevere section of E263 route (Tallinn-Tartu-Võru-Luhamaa). Three smaller, differently vegetated, sections were picked from the large project to study the accuracy of elevation data. For accuracy assessment, the mobile laser scanning elevation data was compared to the checkpoints measured with GNSS (Global Navigation Satellite Systems) device. Ground profiles were drawn based on mobile laser scanning data. For objective assessment, accuracy of mobile laser scanning elevation data was compared to accuracy of ground profile elevation data and aerial laser scanning elevation data. The study found that the RMSE (Root Mean Square Error) in the I section, which was a field vegetated with 1 metre high crop, was 0,98 metres. RMSE in the II section, which was a pasture with low and sparse vegetation, was 0,23 metres. RMSE in the III section, which contained a bushy ditch and a field behind it, was 0,61 metres. Results show that the accuracy of mobile laser scanning elevation data depends substantially on the density of vegetation in scanned areas and that drawing ground profiles reduced the RMSE of mobile laser scanning elevation data. Results show that the accuracy of mobile laser scanning elevation data depends substantially on the density of vegetation in scanned areas. On this basis it can be concluded, that the most reasonable time to conduct mobile laser scanning would be during a season, when vegetation is the sparsest. It can also be concluded that drawing ground profiles makes mobile laser scanning data more accurate.
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Esmailzadeh, Mitra, and Aouni A. Lakis. "Turbulence-Induced Vibration Analysis of an Open Curved Thin Shell." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30383.
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A method is presented to predict the root mean square displacement response of an open curved thin shell structure subjected to a turbulent boundary-layer-induced random pressure field. The basic formulation of the dynamic problem is an efficient approach combining classic thin shell theory and the finite element method. The displacement functions are derived from Sanders’ thin shell theory. A numerical approach is proposed to obtain the total root mean square displacements of the structure in terms of the cross-spectral density of random pressure fields. The cross-spectral density of pressure fluctuations in the turbulent pressure field is described using the Corcos formulation. Exact integrations over surface and frequency lead to an expression for the total root mean square displacement response in terms of the characteristics of the structure and flow. An in-house program based on the presented method was developed. The total root mean square displacements of a curved thin blade subjected to turbulent boundary layers were calculated and illustrated as a function of free stream velocity and damping ratio. A numerical implementation for the vibration of a cylinder excited by fully developed turbulent boundary layer flow was presented. The results compared favorably with those obtained using software developed by Lakis et al.
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He, Tao, Liwei Liu, Chaobang Yao, Dakui Feng, and Xianzhou Wang. "Large-Eddy Simulation of Vortex Flow Field of the Cylinder With Variable Cross Section." In ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/omae2022-79795.
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Abstract In recent years, some scholars have proposed a pontoon tension leg platform, whose tension leg is in the form of variable cross section, but there is little research on vortex flow field of variable cross-section structure at high Reynolds number. Therefore, it is of great significance to study the vortex flow field of structures with variable cross section. In this study, the vortex flow field of the cylinder with variable cross section are studied in detail by large-eddy simulations. Structured grid is used for computation, and SIMPLEC algorithm is used to solve the pressure and velocity. Large-eddy simulation of flow past circular cylinder is carried out, and the simulation results accord well with the published experimental results, which shows that the numerical method is accurate enough. Large-eddy simulations are performed for flow past the wavy cylinders at Reynolds number of 61000. The lift and drag characteristics, pressure field structure and vortex field of the cylinder with variable cross section are analyzed. The results show that the mean drag coefficients and r.m.s (root-mean-square) of the lift coefficients of the wavy cylinders are less than those of a corresponding circular cylinder. The wavy cylinder changes the pressure field and vortex field relative to the circular cylinder.
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MOZGERIS, Gintautas, Ina BIKUVIENĖ, and Donatas JONIKAVICIUS. "THE OPPORTUNITIES AND CHALLENGES OF USING AIRBORNE LASER SCANNING FOR FOREST INVENTORIES IN LITHUANIA." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.023.
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The aim of this study was to test the usability of airborne laser scanning (ALS) data for stand-wise forest inventories in Lithuania based on operational approaches from Nordic countries, taking into account Lithuanian forest conditions and requirements for stand-wise inventories, such as more complex forests, unified requirements for inventory of all forests, i.e. no matter the ownership, availability of supporting material from previous inventories and high accuracy requirements for total volume estimation. Test area in central part of Lithuania (area 2674 ha) was scanned using target point density 1 m-2 followed by measurements of 440 circular field plots (area 100–500 m2). Detailed information on 22 final felling areas with all trees callipered (total area 42.7 ha) was made available to represent forest at mature age. Updated information from conventional stand-wise inventory was made available for the whole study area, too. A two phase sampling with nonparametric Most Similar Neighbor estimator was used to predict point-wise forest characteristics. Total volume of the stand per 1 ha was predicted with an root mean square error of 18.6 %, basal area – 17.7 %, mean diameter – 13.6 %, mean height – 7.9 % and number of tree – 42.8 % at plot-level with practically no significant bias. However, the relative root mean square errors increased 2–4 times when trying to predict forest characteristics by three major groups of tree species – pine, spruce and all deciduous trees taken together. Main conclusion of the study was that accuracy of predicting volume using ALS data decreased notably when targeting forest characteristics by three major groups of tree species.
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Kazankova, Irina, Irina Kazankova, Elena Vasechkina, and Elena Vasechkina. "INDIVIDUAL VARIATION OF GROWTH AND FILTRATION RATES OF MUSSELS MYTILUS GALLOPROVINCIALIS LAM." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b93b7b86624.98126617.
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Research on individual variation of the filtration and growth rates of mussels was based both on the authors’ field and laboratory experiments and literature data analysis. High individual variability of these characteristics was recorded during the tests. The coefficient of variation grew up as the mean rate diminished. Under low specific growth rate the coefficient of variation (ratio of root-mean-square deviation to the sample mean) could exceed 100 %. Tests revealed the power-law relation of the coefficient of variation from the average for studied characteristics. That relation could be seen in filtration and growth rate charts; it was also true for estimates of production energy and metabolic costs. The exponent varied from -0.36 to -0.77. Individual growth rate variation of mussels was concluded to be an important criterion of the favorability of environmental conditions.
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Kazankova, Irina, Irina Kazankova, Elena Vasechkina, and Elena Vasechkina. "INDIVIDUAL VARIATION OF GROWTH AND FILTRATION RATES OF MUSSELS MYTILUS GALLOPROVINCIALIS LAM." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b43172e2145.
Full textAbstract:
Research on individual variation of the filtration and growth rates of mussels was based both on the authors’ field and laboratory experiments and literature data analysis. High individual variability of these characteristics was recorded during the tests. The coefficient of variation grew up as the mean rate diminished. Under low specific growth rate the coefficient of variation (ratio of root-mean-square deviation to the sample mean) could exceed 100 %. Tests revealed the power-law relation of the coefficient of variation from the average for studied characteristics. That relation could be seen in filtration and growth rate charts; it was also true for estimates of production energy and metabolic costs. The exponent varied from -0.36 to -0.77. Individual growth rate variation of mussels was concluded to be an important criterion of the favorability of environmental conditions.
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Sen, Anupam. "Data Mining and Principal Component Analysis on Coimbra Breast Cancer Dataset." In Intelligent Computing and Technologies Conference. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.115.5.
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Machine Learning (ML) techniques play an important role in the medical field. Early diagnosis is required to improve the treatment of carcinoma. During this analysis Breast Cancer Coimbra dataset (BCCD) with ten predictors are analyzed to classify carcinoma. In this paper method for feature selection and Machine learning algorithms are applied to the dataset from the UCI repository. WEKA (“Waikato Environment for Knowledge Analysis”) tool is used for machine learning techniques. In this paper Principal Component Analysis (PCA) is used for feature extraction. Different Machine Learning classification algorithms are applied through WEKA such as Glmnet, Gbm, ada Boosting, Adabag Boosting, C50, Cforest, DcSVM, fnn, Ksvm, Node Harvest compares the accuracy and also compare values such as Kappa statistic, Mean Absolute Error (MAE), Root Mean Square Error (RMSE). Here the 10-fold cross validation method is used for training, testing and validation purposes.
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Nguyen, Vu Huy, and Won-jong Kim. "Design and Control of a Compact Light-Weight Planar Positioner Moving Over a Concentrated-Field Magnet Matrix." In ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control. ASMEDC, 2011. http://dx.doi.org/10.1115/dscc2011-5962.
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In this paper, a single-moving-part planar positioner with 6 coils is designed and implemented. A concentrated-field permanent-magnet matrix is employed as the stationary part. The moving platen has a compact size (185.4 mm × 157.9 mm), light mass (0.64 kg) and low center of mass. The moving platen carries three planar-motor armatures with two phases per motor. Force calculation is based on the Lorentz force law and conducted by volume integration. In order to deal with the nonlinearity due to trigonometric terms in the force-current relation, modified PID (proportional-integral-derivative) and lead-and-PI controllers are designed with computed currents to close the control loop and obtain the desired performances. Experimental results verify the commutation law and the force calculation. The new design with only 6 coils allows for simplification of the control algorithm and reduced power consumption of the positioner. The maximum travel ranges in x, y, and the rotation about the vertical axis are 15.24 cm, 20.32 cm, and 12.03°, respectively. The positioning resolution in x and y is 8 μm with the root-mean-square (rms) position noise of 6 μm. The positioning resolution in rotations about the vertical axis is 100 μrad.
Reports on the topic "Global field root mean square"
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Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41440.
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A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and 0.34/–0.05 m, respectively. Bathymetric data from another flight at Virginia Beach, VA, USA, demonstrates successful comparison (RMSE/bias of 0.17/0.06 m) in a secondary environment. UAS-derived engineering data products, total volume profiles and shoreline position, were congruent with those calculated from traditional topo-bathymetric surveys at Duck. Capturing both topography and bathymetry within a single flight, the presented multicamera system is more efficient than data acquisition with a single camera UAS; this advantage grows for longer stretches of coastline (10 km). Efficiency increases further with an on-board Global Navigation Satellite System–Inertial Navigation System (GNSS-INS) to eliminate ground control point (GCP) placement. The Appendix reprocesses the Virginia Beach flight with the GNSS–INS input and no GCPs.
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Al-Qadi, Imad, Qingqing Cao, Lama Abufares, Siqi Wang, Uthman Mohamed Ali, and Greg Renshaw. Moisture Content and In-place Density of Cold-Recycling Treatments. Illinois Center for Transportation, May 2022. http://dx.doi.org/10.36501/0197-9191/22-007.
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Cold-recycling treatments are gaining popularity in the United States because of their economic and environmental benefits. Curing is the most critical phase for these treatments. Curing is the process where emulsion breaks and water evaporates, leaving residual binder in the treated material. In this process, the cold-recycled mix gains strength. Sufficient strength is required before opening the cold-treated layer to traffic or placing an overlay. Otherwise, premature failure, related to insufficient strength and trapped moisture, would be expected. However, some challenges arise from the lack of relevant information and specifications to monitor treatment curing. This report presents the outcomes of a research project funded by the Illinois Department for Transportation to investigate the feasibility of using the nondestructive ground-penetrating radar (GPR) for density and moisture content estimation of cold-recycled treatments. Monitoring moisture content is an indicator of curing level; treated layers must meet a threshold of maximum allowable moisture content (2% in Illinois) to be considered sufficiently cured. The methodology followed in this report included GPR numerical simulations and GPR indoor and field tests for data sources. The data were used to correlate moisture content to dielectric properties calculated from GPR measurements. Two models were developed for moisture content estimation: the first is based on numerical simulations and the second is based on electromagnetic mixing theory and called the Al-Qadi-Cao-Abufares (ACA) model. The simulation model had an average error of 0.33% for moisture prediction for five different field projects. The ACA model had an average error of 2% for density prediction and an average root-mean-square error of less than 0.5% for moisture content prediction for both indoor and field tests. The ACA model is presented as part of a developed user-friendly tool that could be used in the future to continuously monitor curing of cold-recycled treatments.