88 research outputs found
Accuracy Assessment of UAS Photogrammetry with GCP and PPK-Assisted Georeferencing
No full textAbstract
Establishing a dense, well-distributed ground control point (GCP) network for unmanned aerial system (UAS) surveys can be time-consuming and impractical. Recent availability of UASs capable of GNSS-assisted aerial triangulation (AAT) has provided an alternative method, wherein the refinement of the positional accuracy of camera stations via, for example, post-processing kinematic (PPK) correction reduces the need for GCPs. Studies have highlighted how AAT can provide nearly equal accuracy to GCP-based georeferencing, especially if at least one GCP is utilized for bias correction. However, results on the utility of more than one GCP together with AAT are scarce or mixed. This study explores how the number of GCPs affects model accuracy when mapping a ~1 km2 site with a UAS capable of PPK correction. Also, a comparison between two different local base stations and a virtual reference station (VRS) is provided. Based on analysis with 3D checkpoints, increasing the number of GCPs provided only negligible improvements in horizontal accuracy. However, significant improvement is seen in vertical accuracy when increasing the number of GCPs, with the VRS providing the most accurate results. The results indicate that UAS surveys with AAT may benefit from utilization of multiple GCPs.Abstract
Establishing a dense, well-distributed ground control point (GCP) network for unmanned aerial system (UAS) surveys can be time-consuming and impractical. Recent availability of UASs capable of GNSS-assisted aerial triangulation (AAT) has provided an alternative method, wherein the refinement of the positional accuracy of camera stations via, for example, post-processing kinematic (PPK) correction reduces the need for GCPs. Studies have highlighted how AAT can provide nearly equal accuracy to GCP-based georeferencing, especially if at least one GCP is utilized for bias correction. However, results on the utility of more than one GCP together with AAT are scarce or mixed. This study explores how the number of GCPs affects model accuracy when mapping a ~1 km2 site with a UAS capable of PPK correction. Also, a comparison between two different local base stations and a virtual reference station (VRS) is provided. Based on analysis with 3D checkpoints, increasing the number of GCPs provided only negligible improvements in horizontal accuracy. However, significant improvement is seen in vertical accuracy when increasing the number of GCPs, with the VRS providing the most accurate results. The results indicate that UAS surveys with AAT may benefit from utilization of multiple GCPs
On the value of corner reflectors and surface models in InSAR precise point positioning
No full textTo correctly interpret the estimated displacements in InSAR point clouds, especially in the built environment, these need to be linked to real-world structures. This requires the accurate and precise 3D positioning of each point. Artificial ground control points (GCPs), such as corner reflectors, serve this purpose, but since they require efforts and resources, there is a need for criteria to assess their usefulness. Here we evaluate the value and necessity of using GCPs for different scenarios, concerning the required efforts, and compare this to alternatives such as digital surface models (DSM) and advanced (geo) physical corrections. We consider single-epoch as well as multi-epoch GCP deployment, reflect on the number of GCPs required in relation to the number of SAR data acquisitions, and compare this with digital surface models of different quality levels. Analyzing the geolocation performance using TerraSAR-X and Sentinel-1 data, we evaluate the pros and cons of various deployment options and show that the multi-epoch deployment of a GCP yields optimal geolocalization results in terms of precision, accuracy, and reliability.Accepted Author ManuscriptMathematical Geodesy and Positionin
Cloud AI ecosystems of Amazon, Microsoft, and Google
No full textThis dataset provides information about the entire cloud offerings of Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) that comprise the ‘cloud AI ecosystem’, collected between January–June 2023. This information includes: (a) the entire cloud products and service offerings (N = 852) collected from AWS (aws.amazon.com), Azure (azure.microsoft.com), and GCP (cloud.google.com); (b) additional information about each product and service, including descriptions, service categories and subcategories, and links; (c) comparisons of Google Cloud services mapped to similar offerings in AWS and Microsoft Azure; (d) citation networks of all cloud products and services across AWS, Azure, and GCP product documentation pages (N = 4,124 citations); (e) citation networks of all cloud products and services across industry-specific documentation pages (N = 318 citations); (f) mentions of AI and machine-learning terminology across both corpora (N = 1,811); and (g) counts of AWS, Azure, and GCP marketplace solutions per marketplace category and subcategory (N = 13,793 apps in total). All products and services were collected in January 2023, analyses were conducted on 15–19 May 2023. Marketplace solutions were collected on 30 June 2023.
The dataset is deposited for the (open access) journal article: van der Vlist, F. N., Helmond, A., & Ferrari, F. L. (2024) Big AI: Cloud infrastructure dependence and the industrialisation of artificial intelligence. Big Data & Society, 1(1): 1–16. SAGE Publications. https://doi.org/10.1177/20539517241232630
Contemporary Methods for Graph Coloring as an Example of Discrete Optimization
No full textThis paper provides an insight into graph coloring application of the contemporary heuristic methods. It discusses a variety of algorithmic solutions for The Graph Coloring Problem (GCP) and makes recommendations for implementation. The GCP is the NP-hard problem, which aims at finding the minimum number of colors for vertices in such a way, that none of two adjacent vertices are marked with the same color.With the advent of multicore processing technology, the metaheuristic approach to solving GCP reemerged as means of discrete optimization. To explain the phenomenon of these methods, the author makes a thorough survey of AI-based algorithms for GCP, while pointing out the main differences between all these techniques
Contemporary Methods for Graph Coloring as an Example of Discrete Optimization
No full textThis paper provides an insight into graph coloringapplication of the contemporary heuristic methods. It discusses avariety of algorithmic solutions for The Graph Coloring Problem(GCP) and makes recommendations for implementation. TheGCP is the NP-hard problem, which aims at finding the minimumnumber of colors for vertices in such a way, that none of twoadjacent vertices are marked with the same color.With the adventof multicore processing technology, the metaheuristic approachto solving GCP reemerged as means of discrete optimization. Toexplain the phenomenon of these methods, the author makes athorough survey of AI-based algorithms for GCP, while pointingout the main differences between all these techniques
Simultaneous Process Optimisation and Molecular Design: Development of a group contribution method for a physically based equation of state
No full textIn this report the range of compounds that can be considered for simultaneous optimisation of process parameters and molecular structure through the CoMT-CAMD method is largely increased. The approach is extended by expanding a database of component PCP-SAFT parameters and development and implementation of a group contribution method GCP-SAFT. Before implementation of these approaches, the amount of structures for consideration was about one hundred, but it was shown here that this amount can be increased to over 1,000 and 100,000 respectively through implementation of an expanded PCP-SAFT parameter database and development of a group-contribution method (GCP-SAFT) respectively. An expanded PCP-SAFT parameter database was created by fitting measurements from the DIPPR database When this expanded database, containing PCP-SAFT parameters for 1371 components, is used for structure mapping, the value of the minimisation goal function (Second order Taylor Expansion approximation) can be decreased by an order of magnitude, compared to results obtained by Steur (2009). This indicates that the potential process performance, utilising real molecules, can be further increased by increasing the amount of molecules taken into consideration. The thermodynamic behaviour of components, for which no measurements have been performed, can be predicted through the development of a group contribution method for a physically based equation of state: Group Contribution Polar Statistical Associating Fluid Theory (GCP-SAFT). Three related group contribution approaches, derived from homogeneous fluid theory, showed very similar accuracy for the prediction of adapted non-associative PC-SAFT parameters. Therefore the approach developed by Vijande et al (2004) was adopted here as well, where the molecular parameters m , ms 3 and me k are linearly dependant on contributions for thecontained functional groups. This approach was expanded to associative and polar components constituting a maximum of a single dipolar or associative group. Molecular quadrupolar moments and binary interaction parameters were left out of consideration. Both dipolar and associative group contribution parameters were obtained by simple averaging. The prediction of dipole moments was relatively accurate, with AARE values for this parameter generally below 10% (36 out of 45 polar functional groups). Furthermore it is shown that the assumption of constant relative associative volume is rather strong for the homologous series of alcohols, whereas it is not well, statistically, supported for acids and amines. This is mainly due to the rejection of associative behaviour (negligible converged e AB k and k AB values) for a large portion of these series of compounds by the algorithm that fits PCP-SAFT parameters. AARE values for molecular adapted PCP-SAFT parameters m ,ms 3 and m2s 3e k are 9.28; 2.87 and 5.58% respectively for the GCP-SAFT method that takes dipolar and associative behaviour into account. This is less accurately than literature values obtained for the same model but can be largely explained through the incorporation of associative components. It is expected that Simultaneous Process Optimisation and Molecular Design overall prediction accuracy for mixtures will increase through the added prediction of dipolar and associative parameters. Model constants were fitted to 593 component PCP-SAFT parameter sets, which contained data for 75 associative components. This produced a set of 66 first order functional groups for which GCP-SAFT contributions are known. The confidence of this method is limited to components with a maximum of three branches, as the linear equations for m ,ms 3 and m2s 3e k are biased for cyclic and highly branched structures. These 66 functional groups were utilised in a sample structure generation algorithm to conveniently generate over a 100,000 different non-linear, non-aromatic structures and corresponding GCP-SAFT parameter sets that can be taken into account in simultaneous process optimisation and molecular design.Engineering ThermodynamicsProcess and EnergyMechanical, Maritime and Materials Engineerin
Surfzone monitoring using rotary wing unmanned aerial vehicles
No full textThis study investigates the potential of rotary wing unmanned aerial vehicles (UAVs) to monitor the surfzone. This paper shows that these UAVs are extremely flexible surveying platforms that can gather nearcontinuous moderate spatial resolution and high temporal resolution imagery from a fixed position high above a study site. The rotary wing UAVs used in this study can fly for ;12 min with a mean loiter radius of 1–3.5m and a mean loiter error of 0.75–4.5 m. These numbers depend on the environmental conditions, flying style, battery type, and vehicle type. The images obtained from the UAVs, and in combination with surveyed ground control points (GCPs), can be georectified to a pixel resolution between 0.01 and 1m, and a reprojection error—that is, the difference between the surveyed GPS location of a GCP and the location of the GCP obtained from the georectified image—of O(1 m). The flexibility of rotary wing UAVs provides moderate spatial resolution and high temporal resolution imagery, which are highly suitable to quickly obtain surfzone and beach characteristics in response to storms or for day-to-day beach safety information, as well as scientific pursuits of surfzone kinematics on different spatial and temporal scales, and dispersion and advection estimates of pollutants.Hydraulic EngineeringCivil Engineering and Geoscience
Temperature changes and thermo-light polymerization efficacy of two LED curing lights and 445-nm diode laser on glass carbomer material
No full textPurpose: To evaluate thermo-light polymerization efficacy on the Vickers microhardness (VH) of a glass carbomer material (GCP) and on temperature changes (?T) using a diode laser (445 nm, DL) and two light-emitting diode (LED) units. Methods: Fifty-four GCP samples (2 × 8 mm) were prepared and exposed to three polymerization units: GCP CarboLED (G1), 3 M Elipar™ DeepCure-S (G2), and 445-nm SIRO Laser Blue (G3). A K-type thermo-couple was used to measure ?T. After 24 h, VH values were measured, and surface changes were evaluated. The data were analysed by t test, one-way analysis of variance (ANOVA) and Welch ANOVA, and Tamhane post hoc tests (p 0.05). There were no alterations in surface morphology or chemical composition of GCP after laser treatment. Conclusion: 3 M Elipar and 445-nm DL applications yielded higher VH compared to GCP CarboLED, but with higher temperature increases. Application of 445 nm DL has the advantage of causing no difference between top and bottom VH values. Clinical significance. Our data reveal that heat application with any one of these three devices was safe for all treatment groups without causing pulp damage. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.The authors are grateful to the Dentsply Sirona company for providing the SIRO Laser blue diode laser. The authors would like to thank Prof. Aslıhan Usumez for scientific contribution. The authors deny any conflicts of interest related to this study
Temperature changes and thermo-light polymerization efficacy of two LED curing lights and 445-nm diode laser on glass carbomer material
No full textPurpose: To evaluate thermo-light polymerization efficacy on the Vickers microhardness (VH) of a glass carbomer material (GCP) and on temperature changes (ΔT) using a diode laser (445 nm, DL) and two light-emitting diode (LED) units. Methods: Fifty-four GCP samples (2 × 8 mm) were prepared and exposed to three polymerization units: GCP CarboLED (G1), 3 M Elipar™ DeepCure-S (G2), and 445-nm SIRO Laser Blue (G3). A K-type thermo-couple was used to measure ΔT. After 24 h, VH values were measured, and surface changes were evaluated. The data were analysed by t test, one-way analysis of variance (ANOVA) and Welch ANOVA, and Tamhane post hoc tests (p 0.05). There were no alterations in surface morphology or chemical composition of GCP after laser treatment. Conclusion: 3 M Elipar and 445-nm DL applications yielded higher VH compared to GCP CarboLED, but with higher temperature increases. Application of 445 nm DL has the advantage of causing no difference between top and bottom VH values. Clinical significance. Our data reveal that heat application with any one of these three devices was safe for all treatment groups without causing pulp damage. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG
Good Statistical Practice—development of tailored Good Clinical Practice training for statisticians
No full text\ua9 The Author(s) 2024.Background: Statisticians are fundamental in ensuring clinical research, including clinical trials, are conducted with quality, transparency, reproducibility and integrity. Good Clinical Practice (GCP) is an international quality standard for the conduct of clinical trials research. Statisticians are required to undertake training on GCP but existing training is generic and, crucially, does not cover statistical activities. This results in statisticians undertaking training mostly unrelated to their role and variation in awareness and implementation of relevant regulatory requirements with regards to statistical conduct. The need for role-relevant training is recognised by the UK NHS Health Research Authority and the Medicines and Healthcare products Regulatory Agency (MHRA). Methods: The Good Statistical Practice (GCP for Statisticians) project was instigated by the UK Clinical Research Collaboration (UKCRC) Registered Clinical Trials Unit (CTU) Statisticians Operational Group and funded by the National Institute for Health and Care Research (NIHR), to develop materials to enable role-specific GCP training tailored to statisticians. Review of current GCP training was undertaken by survey. Development of training materials were based on MHRA GCP. Critical review and piloting was conducted with UKCRC CTU and NIHR researchers with comment from MHRA. Final review was conducted through the UKCRC CTU Statistics group. Results: The survey confirmed the need and desire for the development of dedicated GCP training for statisticians. An accessible, comprehensive, piloted training package was developed tailored to statisticians working in clinical research, particularly the clinical trials arena. The training materials cover legislation and guidance for best practice across all clinical trial processes with statistical involvement, including exercises and real-life scenarios to bridge the gap between theory and practice. Comprehensive feedback was incorporated. The training materials are freely available for national and international adoption. Conclusion: All research staff should have training in GCP yet the training undertaken by most academic statisticians does not cover activities related to their role. The Good Statistical Practice (GCP for Statisticians) project has developed and extensively piloted new, role-specific, comprehensive, accessible GCP training tailored to statisticians working in clinical research, particularly the clinical trials arena. This role-specific training will encourage best practice, leading to transparent and reproducible statistical activity, as required by regulatory authorities and funders
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