Model Scaling in Smartphone GNSS-Aided Photogrammetry for Fragmentation Size Distribution Estimation

Fragmentation size distribution estimation is a critical process in mining operations that employ blasting. In this study, we aim to create a low-cost, efficient system for producing a scaled 3D model without the use of ground truth data, such as GCPs (Ground Control Points), for the purpose of improving fragmentation size distribution measurement using GNSS (Global Navigation Satellite System)-aided photogrammetry. However, the inherent error of GNSS data inhibits a straight-forward application in Structure-from-Motion (SfM). To overcome this, the study proposes that, by increasing the number of photos used in the SfM process, the scale error brought about by the GNSS error will proportionally decrease. Experiments indicated that constraining camera positions to locations, relative or otherwise, improved the accuracy of the generated 3D model. In further experiments, the results showed that the scale error decreased when more images from the same dataset were used. The proposed method is practical and easy to transport as it only requires a smartphone and, optionally, a separate camera. In conclusion, with some modifications to the workflow, technique, and equipment, a muckpile can be accurately recreated in scale in the digital world with the use of positional data.

The Relationship Between Preschool Teachers’ Proactive Personality and Innovative Behavior: The Chain-Mediated Role of Error Management Climate and Self-Efficacy

Objective: This study, aims to explore the relationship of error management climate and self-efficacy between preschool teachers’ proactive personality and innovative behavior.Methods: Four hundred thirty-nine preschool teachers were tested by proactive personality scale, error management climate scale, general self-efficacy scale, and employee innovation behavior scale.Results: Preschool teachers’ proactive personality can directly predict their innovative behaviors, has a significant indirect effect on innovative behaviors through error management climate, and has a significant indirect effect on innovative behaviors through self-efficacy. Error management climate and self-efficacy play a chain-mediated role in the relationship between preschool teachers’ proactive personality and innovative behavior.Conclusion: Error management climate and self-efficacy play a chain-mediated role in the relationship between preschool teachers’ proactive personality and innovative behavior.

Aplikasi solidwork untuk rancangan CAD 3D pada mesin 3D printer 2x2x2 meter

ABSTRAK Mesin 3D printing dapat membuat proses produksi menjadi singkat dan sederhana, keunggulan ini menjadikan banyak peneliti mulai menggembangkan mesin printing. Pengembangan mesin printing yang sudah dilakukan salah satunya adalah mesin 3D printer 2 x 2 x 2 meter. Keberhasilan mesin printing dapat dilihat dari hasil printing yang sesuai dengan desain yang diharapkan. Oleh karena itu, diperlukan aplikasi yang dapat membantu merancang desain objek 3D pada mesin printer 2x2x2 meter, salah satunya menggunakan aplikasi CAD (Computer Aided Design) “SolidWork”. Aplikasi “SolidWork” bersifat opensource yang dapat membantu mengetahui pengaruh desain 3 dimensi menggunakan software CAD terhadap jarak, sudut dan skala objek pada mesin printer 2x2x2 meter. Desain objek 3D “SolidWork” disimpan dalam dalam format file STL, kemudian diproses di dalam Simplify 3D, objek akan diiris secara software. Hasil irisan gambar 3D akan menghasilkan sebuah file G-Code. Output koordinat dari G-Code digunakan untuk menggerakan motor stepper. Hasil cetak objek 2D memiliki error ukuran bentuk segitiga 4,62%, bentuk straight slog 7,49%, bentuk oval 5,54%, error sudut sebesar 0% dan error skala objek 0%. Sedangkan untuk objek 3D memiliki error rata – rata sebesar 0,29%. Berdasarkan hasil pengujian aplikasi “SolidWork” dapat menujukkan kinerja mesin dan membantu dalam pembuatan desain 2D dan 3D pada mesin 3D printer 2x2x2 meter di Lab Elektro Prodi Elektronika Politeknik Negeri Malang. ABSTRACT 3D printing machines can make the production process short and simple, this advantage has made many researchers start to develop printing machines. One of the developments in printing machines that have been carried out is the 2 x 2 x 2 meter 3D Printer machine. The success of the printing machine can be seen from the printing results by the expected design. Therefore, an application is needed that can help design 3D object designs on a 2x2x2 meter printer machine, one of which is using the CAD (Computer-Aided Design) application "SolidWork". The application "SolidWork" is open source which can help determine the effect of 3-dimensional design using CAD software on the distance, angle, and scale of objects on a 2x2x2 meter printer machine. "SolidWorks" 3D object design is saved in STL file format, then processed in Simplify 3D, the object will be sliced ​​automatically. The sliced ​​3D image will produce a G-Code file. The coordinate output from the G-Code is used to drive the stepper motor. The printout of 2D objects has a triangular size error of 4.62%, a straight slog shape of 7.49%, an oval shape of 5.54%, an angle error of 0%, and a scale error of 0%. Meanwhile, 3D objects have an average error of 0.29%. Based on the results of testing the "SolidWork" application can show machine performance and assist in making 2D and 3D designs on a 2x2x2 meter 3D printer machine at the Electrical Lab of Electronics Study Program, State Polytechnic of Malang.

Linearisation of flow sensors using evolutionary optimised function-based methods

Purpose This study aims to propose optimised function-based evolutionary algorithms in this research to effectively replace the traditional electronic circuitry used in linearising constant temperature anemometer (CTA) and Microbridge mass flow sensor AWM 5000. Design/methodology/approach The proposed linearisation technique effectively uses the ratiometric function for the linearisation of CTA and Microbridge mass flow sensor AWM 5000. In addition, the well-known transfer relation, namely, the King’s Law is used for the linearisation of CTA and successfully implemented using LabVIEW 7.1. Findings Investigational results unveil that the proposed evolutionary optimised linearisation technique performs better in linearisation of both CTA and Mass flow sensors, and hence finds applications for computer-based flow measurement/control systems. Originality/value The evolutionary optimisation algorithms such as the real-coded genetic algorithm, particle swarm optimisation algorithm, differential evolution algorithm and covariance matrix adopted evolutionary strategy algorithm are used to determine the optimal values of the parameters present in the proposed ratiometric function. The performance measures, namely, the full-scale error and mean square error are used to analyse the overall performance of the proposed approach is compared to a state of art techniques available in the literature.

Synthesis of a linear static function for grain moisture meter with capacitive sensors

Moisture content is a grain quality factor, a parameter which changes during the processes of storage and processing and determines consumer properties of different food products. OIML organization in its international recommendation OIML R59 “Moisture Meters for Cereal Grain and Oilseeds” restricts maximal permissible value of moisture meters uncertainty to not more than 3% of relative full scale error. Main task of the research is in receiving linear static function for the grain moisture meter with four capacitive sensors. Method of Least Squares and general linear regression instruments had been used for that purpose. Analyzing the graphs of modified static function for different moist substances it was possible to say that it happened to be far more effective than initial static function and the static function received from a first-order polynomial after the LS method implementation. Root mean estimator was calculated for initial static function, the static function received with the LS method and static function, received after general linear regression implementation as an integral difference between nominal and calculated values of moisture content. Corresponding root mean estimator values were 1.3062%, 1.1616% and 0.4158%, that proves the effectiveness of a static function modified with the general linear regression instruments. Keywords: moisture content measurement; capacitive moisture meter; reference channel; capacitive sensor; linear static function

False cue influence on motion cue quality for 10 motion cueing algorithms

Motion simulators are becoming increasingly popular for many applications in which human sensation is important to replicate and optimize target motions. For the emulation of the perceived human acceleration, motion cueing algorithms (MCAs) have been proposed in the literature that mimics the motion sensation by a combination of actual acceleration and tilted gravity effects, termed g-force or specific force. However, their relative performance has not yet been analyzed. This paper reviews existing families of MCAs and compares their performance for a simple offline S-shaped planar test trajectory featuring only lateral acceleration. The comparison is carried out both numerically using two previously published objective measures, the “performance indicator” of Pouliot, Gosselin, and Nahon, and the “good criterion” of Schmidt, as well as subjectively by a preliminary passenger rating on a real motion platform—Robocoaster testbed. The results show that (a) the novel optimizing MCA group exploits more effectively the workspace of the motion platform than the traditional MCA group for reducing false cue with small scale error and shape errors, (b) path-dependent tuning of MCA parameters may improve motion sensation, (c) average subjective ratings can be made to correlate well with the “good criterion” when expanded with a penalty for false angular velocity cues, and (d) the scale error of specific force seems to play the most important role to the evaluation of test subject on the motion cue quality. However, still a strong variance in subjective ratings was observed, making further research necessary.

Research on the Performance of Impressionist Painting Color Visual Communication Based on Wireless Communication and Machine Vision

In order to solve the problem of poor visual communication effect of impressionist painting colors and low accuracy of painting color enhancement by existing methods, this thesis proposes a research on the performance of impressionist painting color visual communication based on machine vision under the background of wireless network. This method can improve the vision, speed, and efficiency of communication, through the analysis of the characteristics of impressionist paintings, and determine the visual communication objects of impressionist painting colors. The process of visual communication is analyzed, and the color matching of impressionist painting is completed with the help of BP neural network algorithm. On this basis, the histogram method is used to process the image brightness of impressionist paintings, the image interpolation method is used to process the image brightness of impressionist paintings, and the image is corrected by gamma correction to complete the image performance research. The color vision communication of impressionist painting needs to correct the gray scale error of impressionist painting and enhance the color of impressionist painting. The experimental results show that the accuracy of this method for the color matching of impressionist painting images is about 98%, which has a certain degree of credibility.

Spectral nudging in an hourly 4DVar framework: Status and Plans

<p>The Met Office hourly 4D-Var was introduced operationally to its convective-scale limited area model (UKV) in summer 2017, improving forecast skill for nowcasting and short-range purposes. However, in recent tests a downscaler run from a global analysis tends to be better than hourly 4D-Var, especially for some variables (e.g. screen temperature). This is probably due to a poor representation of large-scale dynamics in the LAM DA system, which is now integrated on an extended domain, whilst the global model has improved to a 10km resolution and with better DA (hybrid 4D-Var). Therefore, the MO recognises the necessity of coupling large scale dynamics with convective systems using the better estimation of these motions from the global model.<br>We opted for a solution similar to spectral nudging, which uses large scale increments derived from a model with a better representation of these scales. At the same time, the short scales from UKV are maintained. We call this method ‘Background Increments’ (BGInc), as it updates the UKV background fields using a spectrally filtered increment derived from a different (global) model. This update is calculated just prior to computing the analysis increments from the hourly DA cycle. We investigated different set-ups for the implementation, changing the cut-off wavelength, the vertical weights, the frequency of updates of BGInc and other set-up features.<br>This novel system is now in a testing phase for operational purposes. From preliminary results, the forecast is improved for about the first 12 hours for different variables. We also notice a reduction in the gravity wave activity generated when new lateral boundary conditions are introduced to the LAM from the latest global forecast. This research shows the benefits of a better representation of large-scale motions for LAM forecasts. <br>In the short term, future development involves the computation of new static covariances using a better representation of the large-scale error. In the longer term, this technique could be useful in a hybrid 4D-Var scheme while enabling the use of large-scale ensemble perturbations in the analysis without causing large adjustments at the lateral boundaries.</p>