scholarly journals Automatic Wheels and Camera Calibration for Monocular and Differential Mobile Robots

2021 ◽  
Vol 11 (13) ◽  
pp. 5806
Author(s):  
Konstantin Chaika ◽  
Anton Filatov ◽  
Artyom Filatov ◽  
Kirill Krinkin
Keyword(s):  
Camera Calibration ◽  
Normal Operation ◽  
Automatic Calibration ◽  
Test Results ◽  
Suggested Approach ◽  
Relevant Today ◽  
Fully Automatic ◽  
Using Data ◽  
Two Stages ◽  
Marked Area

Mobile robotic systems are highly relevant today in various fields, both in an industrial environment and in terms of their applications in medicine. After assembling the robot, components such as the camera and wheels need to be calibrated. This requires human participation and depends on human factors. The article describes the approach to fully automatic calibration of a robot’s camera and wheels with a subsequent calibration refinement during the operation. It consists of placing the robot in an inaccurate position, but in a pre-marked area, and using data from the camera, information about the environment configuration, as well as the ability to move, in order to perform calibration without external observers or human participation. There are two stages in this process: the camera and the wheel calibrations. The camera calibration collects the necessary set of images by automatically moving the robot in front of the fiducial markers template, and then moving it on the marked floor, assessing its trajectory curvature. Upon calibration completion, the robot automatically moves to the area of its normal operation and it is proposed to refine the calibration during its operation without blocking its work. The suggested approach was experimentally tested on the Duckietown project base. Based on test results, the approach proved to be comparable to manual calibrations and is capable of replacing a human for this task.

Perancangan Aplikasi Prediksi Kelulusan Tepat Waktu Bagi Mahasiswa Baru Dengan Teknik Data Mining (Studi Kasus: Data Akademik Mahasiswa STMIK Dipanegara Makassar)

2015 ◽  
Vol 1 (4) ◽  
pp. 270
Author(s):  
Muhammad Syukri Mustafa ◽  
I. Wayan Simpen
Keyword(s):  
Data Mining ◽  
Nearest Neighbor ◽  
Test Results ◽  
K Nearest Neighbor ◽  
Accuracy Rate ◽  
Sample Data ◽  
New Students ◽  
K Nearest Neighbor Algorithm ◽  
Using Data ◽  
Existing Data

Penelitian ini dimaksudkan untuk melakukan prediksi terhadap kemungkian mahasiswa baru dapat menyelesaikan studi tepat waktu dengan menggunakan analisis data mining untuk menggali tumpukan histori data dengan menggunakan algoritma K-Nearest Neighbor (KNN). Aplikasi yang dihasilkan pada penelitian ini akan menggunakan berbagai atribut yang klasifikasikan dalam suatu data mining antara lain nilai ujian nasional (UN), asal sekolah/ daerah, jenis kelamin, pekerjaan dan penghasilan orang tua, jumlah bersaudara, dan lain-lain sehingga dengan menerapkan analysis KNN dapat dilakukan suatu prediksi berdasarkan kedekatan histori data yang ada dengan data yang baru, apakah mahasiswa tersebut berpeluang untuk menyelesaikan studi tepat waktu atau tidak. Dari hasil pengujian dengan menerapkan algoritma KNN dan menggunakan data sampel alumni tahun wisuda 2004 s.d. 2010 untuk kasus lama dan data alumni tahun wisuda 2011 untuk kasus baru diperoleh tingkat akurasi sebesar 83,36%.This research is intended to predict the possibility of new students time to complete studies using data mining analysis to explore the history stack data using K-Nearest Neighbor algorithm (KNN). Applications generated in this study will use a variety of attributes in a data mining classified among other Ujian Nasional scores (UN), the origin of the school / area, gender, occupation and income of parents, number of siblings, and others that by applying the analysis KNN can do a prediction based on historical proximity of existing data with new data, whether the student is likely to complete the study on time or not. From the test results by applying the KNN algorithm and uses sample data alumnus graduation year 2004 s.d 2010 for the case of a long and alumni data graduation year 2011 for new cases obtained accuracy rate of 83.36%.

scholarly journals A Fully Automatic Calibration System for Hydrometers in NIM

MAPAN ◽  
2021 ◽  
Author(s):  
Jintao Wang ◽  
Xiang Liu ◽  
Wencai Shi ◽  
Changhong Xu
Keyword(s):  
Full Range ◽  
Density Measurement ◽  
Fused Silica ◽  
Automatic Calibration ◽  
Liquid Density ◽  
Calibration Data ◽  
Calibration System ◽  
Solid Density ◽  
Fully Automatic ◽  
Better Than

AbstractHydrometers are widely used in industry for liquid density measurement. It is important to achieve rapid and high accuracy calibration for hydrometers. Based on the Archimedes principle, a fully automatic hydrometer calibration system in NIM was designed using Cuckow’s method. The liquid density of n-tridecane (C13H28)is calibrated with 441 g high-purity fused silica ring as the solid density standard. The buoyancy of hydrometer is measured by static weighing system with resolution 0.01 mg. The alignment between liquid surface and hydrometer scale was achieved by the lifting platform with the positioning accuracy of 10 μm. According to the weighing value of hydrometer in air and liquid, the density correction value at different scales is calculated. Hydrometer covering a full range (650–1500) kg/m3can be calibrated without changing the liquid. Taking the calibration data of PTB as reference, the experimental data show that the measurement uncertainty of this system is better than 0.3 division (k = 2).

scholarly journals Multiscale variation model and activity level estimation algorithm of the Earth's magnetic field based on wavelet packets

2018 ◽  
Vol 36 (5) ◽  
pp. 1207-1225 ◽  
Author(s):  
Oksana V. Mandrikova ◽  
Igor S. Solovyev ◽  
Sergey Y. Khomutov ◽  
Vladimir V. Geppener ◽  
Dmitry M. Klionskiy ◽  
...  
Keyword(s):  
Geomagnetic Field ◽  
Numerical Algorithms ◽  
Estimation Algorithm ◽  
Solar Wind Plasma ◽  
Activity Level ◽  
High Temporal Resolution ◽  
Suggested Approach ◽  
Characteristic Variation ◽  
Using Data ◽  
Multiscale Mathematical Model

Abstract. We suggest a wavelet-based multiscale mathematical model of geomagnetic field variations. The model is particularly capable of reflecting the characteristic variation and local perturbations in the geomagnetic field during the periods of increased geomagnetic activity. Based on the model, we have designed numerical algorithms to identify the characteristic variation component as well as other components that represent different geomagnetic field activity. The substantial advantage of the designed algorithms is their fully automatic performance without any manual control. The algorithms are also suited for estimating and monitoring the activity level of the geomagnetic field at different magnetic observatories without any specific adjustment to their particular locations. The suggested approach has high temporal resolution reaching 1 min. This allows us to study the dynamics and spatiotemporal distribution of geomagnetic perturbations using data from ground-based observatories. Moreover, the suggested approach is particularly capable of discovering weak perturbations in the geomagnetic field, likely linked to the nonstationary impact of the solar wind plasma on the magnetosphere. The algorithms have been validated using the experimental data collected at the IKIR FEB RAS observatory network. Keywords. Magnetospheric physics (storms and substorms)

scholarly journals Derivation and Performance of Standardized Enhanced Liver Fibrosis (ELF) Test Thresholds for the Detection and Prognosis of Liver Fibrosis

2019 ◽  
Vol 3 (5) ◽  
pp. 815-826 ◽  
Author(s):  
James Day ◽  
Preya Patel ◽  
Julie Parkes ◽  
William Rosenberg
Keyword(s):  
Liver Fibrosis ◽  
Delphi Panel ◽  
Test Results ◽  
Hazard Ratios ◽  
Test Thresholds ◽  
And Performance ◽  
Using Data ◽  
Relationship Of ◽  
The Relationship ◽  
Selection Of

Abstract Introduction Noninvasive tests are increasingly used to assess liver fibrosis and determine prognosis but suggested test thresholds vary. We describe the selection of standardized thresholds for the Enhanced Liver Fibrosis (ELF) test for the detection of liver fibrosis and for prognostication in chronic liver disease. Methods A Delphi method was used to identify thresholds for the ELF test to predict histological liver fibrosis stages, including cirrhosis, using data derived from 921 patients in the EUROGOLF cohort. These thresholds were then used to determine the prognostic performance of ELF in a subset of 457 patients followed for a mean of 5 years. Results The Delphi panel selected sensitivity of 85% for the detection of fibrosis and >95% specificity for cirrhosis. The corresponding thresholds were 7.7, 9.8, and 11.3. Eighty-five percent of patients with mild or worse fibrosis had an ELF score ≥7.7. The sensitivity for cirrhosis of ELF ≥9.8 was 76%. ELF ≥11.3 was 97% specific for cirrhosis. ELF scores show a near-linear relationship with Ishak fibrosis stages. Relative to the <7.7 group, the hazard ratios for a liver-related outcome at 5 years were 21.00 (95% CI, 2.68–164.65) and 71.04 (95% CI, 9.4–536.7) in the 9.8 to <11.3 and ≥11.3 subgroups, respectively. Conclusion The selection of standard thresholds for detection and prognosis of liver fibrosis is described and their performance reported. These thresholds should prove useful in both interpreting and explaining test results and when considering the relationship of ELF score to Ishak stage in the context of monitoring.

FEATURE DETECTION AND CORRESPONDENCE FOR CAMERA CALIBRATION

2008 ◽  
Vol 05 (01) ◽  
pp. 41-50 ◽  
Author(s):  
ZHIGANG ZHENG ◽  
ZHENGJUN ZHA ◽  
LONG HAN ◽  
ZENGFU WANG
Keyword(s):  
Camera Calibration ◽  
Feature Detection ◽  
Checkerboard Pattern ◽  
Geometrical Constraint ◽  
Precise Position ◽  
3D Space ◽  
Corner Points ◽  
Calibration Pattern ◽  
Fully Automatic ◽  
Automatic Camera Calibration

This paper addresses the problem of highly accurate, highly speedy, more reliable and fully automatic camera calibration. Our objective is to construct a reliable and fully automatic system to supply a more robust and highly accurate calibration scheme. A checkerboard pattern is used as calibration pattern. After the corner points on image are detected, an improved Delaunay triangulation based algorithm is used to make correspondences between corner points on image and corner points on checkerboard in 3D space. In order to determine precise position of the actual corner points, a geometrical constraint based global curve fitting algorithm has been developed. The experimental results show that the geometrical constraint based method can improve remarkably the performance of the feature detection and camera calibration.

scholarly journals Proses Pembuatan Hidrolisat Protein Ikan Rucah

2012 ◽  
Vol 13 (3) ◽  
pp. 256
Author(s):  
Dyah Koesoemawardani ◽  
Fibra Nurainy ◽  
Sri Hidayati
Keyword(s):  
Soluble Protein ◽  
Emulsion Stability ◽  
Enzyme Concentration ◽  
Test Results ◽  
Fish Protein ◽  
Protein Hydrolyzate ◽  
Second Stage ◽  
Trash Fish ◽  
Two Stages ◽  
Fish Protein Hydrolysates

This study aimed to find optimum manufacturing trash fish protein hydrolyzate using the commercial papainenzyme. It is known that fish protein hydrolysates have good functional properties, so it is more widely utilized,especially for food. The study was conducted in two stages, the first stage was to make trash fish protein hydrolyzatetreated with enzyme concentration of 3%, 5%, 7% (w/w), and pH 5; 5.5; 6; 6.5; 7, whereas second stage was to maketrash fish protein hydrolyzate with same from the first stage and so the best treatment followed by treatment ofhalf-hour long incubation and one hour. Parameters observed were soluble protein, foamability, fat binding capacityand emulsion stability. The treatment was repeated three times and the first phase of data analysis using advancedtesting LSD and the second stage using the T test. Results show that the best soluble protein to produce a trashfish protein hydrolyzate enzyme was at a concentration of 5% and pH = 6.5 that was equal to 19.71%. In half an hourincubation produce higher soluble protein values and foamability that were equal to 24.97% and 9.63%, while thebinding capacity of fat in one hour incubation produces a higher value that was equal to 5.03%. Meanwhile, emulsionstability did not differ significantly at both incubation time.

scholarly journals Is there a growing social acceptance of earnings inequalities in Poland?

2018 ◽  
Vol 21 (8) ◽  
pp. 79-88
Author(s):  
Paweł Kumor
Keyword(s):  
Economic Growth ◽  
Social Acceptance ◽  
Gdp Growth ◽  
Gini Coefficients ◽  
Second Stage ◽  
Economic Level ◽  
Per Capita ◽  
Using Data ◽  
Two Stages

In our studies, we deal with the estimating of the optimal ranges of earnings – the optimal Gini indexes which are favourable to the maximisation of GDP growth in Poland. We suspect that the optimal Gini coefficients expressing the whole of society’s acceptance of earnings inequalities can increase. In the article, we formulated a hypothesis on society’s habituation to increasing earnings disparities. We verified the hypothesis on the basis of the model of economic growth using data from 1970 to 2007. We carried out econometric studies in two stages. In the first stage, we estimated the optimal Gini coefficients for short subsequent sub-periods. In the second stage, we studied the character of changes in the optimal Gini coefficients. In the studies, we proved the hypothesis on society’s habituation to increasing earnings disparities. The optimal Gini coefficients increase along with the increase of differences in earnings and the increase of the economic level per capita. The growth of the optimal Gini coefficients may be slowed down.

scholarly journals Goods Stock Management using the K-Means Algorithm Method

2020 ◽  
Vol 10 (1) ◽  
pp. 22-45
Author(s):  
Dhio Saputra
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
Test Results ◽  
Stock Management ◽  
Clustering Method ◽  
Sales Data ◽  
Using Data ◽  
Cluster 2

The grouping of Mazaya products at PT. Bougenville Anugrah can still do manuals in calculating purchases, sales and product inventories. Requires time and data. For this reason, a research is needed to optimize the inventory of Mazaya goods by computerization. The method used in this research is K-Means Clustering on sales data of Mazaya products. The data processed is the purchase, sales and remaining inventory of Mazaya products in March to July 2019 totaling 40 pieces. Data is grouped into 3 clusters, namely cluster 0 for non-selling criteria, cluster 1 for best-selling criteria and cluster 2 for very best-selling criteria. The test results obtained are cluster 0 with 13 data, cluster 1 with 25 data and cluster 2 with 2 data. So to optimize inventory is to multiply goods in cluster 2, so as to save costs for management of Mazayaproducts that are not available. K-Means clustering method can be used for data processing using data mining in grouping data according to criteria.

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