scholarly journals A Comparison of GPS Performance in a Southern Hardwood Forest: Exploring Low-Cost Solutions for Forestry Applications

2009 ◽  
Vol 33 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Scott D. Danskin ◽  
Pete Bettinger ◽  
Thomas R. Jordan ◽  
Chris Cieszewski
Keyword(s):  
Mean Squared Error ◽  
Low Cost ◽  
Slope Position ◽  
Horizontal Position ◽  
Differential Correction ◽  
Position Accuracy ◽  
Squared Error ◽  
Wide Area Augmentation System ◽  
Receiver Performance ◽  
Improved Performance

Abstract The global positioning system (GPS) exhibits much potential for forestry applications, where traditional methods of position determination still dominate. Recent advances in GPS technology may offer improved performance of GPS in forested conditions, and at a considerable cost advantage compared with previous GPS alternatives. We examined the use of several mapping- to recreation-grade GPS receivers across a topographic gradient and the influence of using the Wide Area Augmentation System (WAAS) to their performance under leaf-on and leaf-off conditions. Generally, the mapping-grade receiver with postprocessed differential correction offered the highest position accuracies, which improved root mean squared error (RMSE95) from 3.64 to 5.32 m across leaf conditions, compared with recreation-grade receiver performance, which ranged in RMSE95 from 12.76 to 38.74 m under leaf-on conditions to 8.22 to 36.81 m under leaf-off conditions. Users of this information should keep in mind that RMSE95 equals actual RMSE × 1.7308. These results are consistent with the general thoughts that (a) mapping-grade receivers should provide higher horizontal position accuracy than consumer-grade receivers, (b) better horizontal position accuracy is obtained during leaf-off forest conditions (i.e., winter), (c) differential correction can improve horizontal position accuracy, and (d) WAAS, when available, can improve horizontal position accuracy. Results also indicate that slope position and the number of position fixes acquired may influence the performance of the GPS units.

scholarly journals Improvement of DC Motor Speed Control for Mobile Robot to Minimize Slip Phenomenon

Jurnal INFORM ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 28-34
Author(s):  
Bayu Sandi Marta ◽  
Dewi Mutiara Sari
Keyword(s):  
Mobile Robot ◽  
Mean Squared Error ◽  
Dc Motor ◽  
Motor Speed ◽  
Slip Control ◽  
Position Accuracy ◽  
Squared Error ◽  
Speed Performance ◽  
Robot Position ◽  
Slip Phenomenon

Slip on the mobile robot has a significant impact on the maneuver and the accuracy of the mobile robot movement. The slip phenomenon occurs because of the loss of traction between the surface and the wheels due to the spontaneous acceleration or declaration application. This paper presents a method to improve DC motor performance by using slip control as an observer such that the slip phenomenon effect can be minimized. The performance that will be analyzed is the accuracy of motor speed and robot position accuracy when the robot is moving. The result shows that the Root Mean Squared Error (RMSE) for the motor speed performance that does not use slip control is 2.680, the system using slip control produces RMSE 1.3393. Regarding the robot position accuracy, the RMSE of the system that does not use slip control is 0.0379, the system using slip control is 0.0065.

scholarly journals Accuracy of the TanDEM-X Digital Elevation Model for Coastal Geomorphological Studies in Patagonia (South Argentina)

2019 ◽  
Vol 11 (15) ◽  
pp. 1767 ◽  
Author(s):  
Francesca Pasquetti ◽  
Monica Bini ◽  
Andrea Ciampalini
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Mean Squared Error ◽  
Low Cost ◽  
High Agreement ◽  
Squared Error ◽  
Digital Elevation ◽  
Vertical Error ◽  
Global Coverage ◽  
Elevation Model

The aim of this paper is to evaluate the usefulness of TanDEM-X DEM (digital elevation model) for remote geomorphological analysis in Argentinian Patagonia. The use of a DEM with appropriate resolution and coverage might be very helpful and advantageous in vast and hardly accessible areas. TanDEM-X DEM could represent an unprecedented opportunity to identify geomorphological features because of its global coverage, ~12 m spatial resolution and low cost. In this regard, we assessed the vertical accuracy of TanDEM-X DEM through comparison with Differential Global Positioning System (DGPS) datasets collected in two areas of the Patagonia Region during a field survey; we then investigated different types of landforms by creating the elevation profiles. The comparison indicates a high agreement between TanDEM-X DEM and reference values, with a mean absolute vertical error (MAE) of 0.53 m, and a root mean squared error (RMSE) of 0.73 m. The results of landform analysis show an appropriate spatial resolution to detect different features such as beach ridges, which are impossible to delineate with other lower resolution DEMs. For these reasons, TanDEM-X DEM constitutes a useful tool for detailed geomorphological analyses in Argentinian Patagonia.

Evaluation of Low Cost Digital Cameras for Producing Photogrammetric Output from UAV

2018 ◽  
Vol 7 (2.29) ◽  
pp. 792 ◽  
Author(s):  
Syafiq Sukor ◽  
Anuar Ahmad
Keyword(s):  
Global Positioning System ◽  
Mean Squared Error ◽  
Low Cost ◽  
Control Point ◽  
Ground Control ◽  
Digital Cameras ◽  
Squared Error ◽  
Digital Elevation ◽  
Global Positioning ◽  
Elevation Model

Recently there a lot of improvement in digital photogrammetry and this allow photogrammetry to become faster and cheaper . This study discuss about two type of low cost camera which is the compact camera (Canon Power Shot SX230 ) and action camera (Xiaomi yi) where both of them have different lens distortion. This study is conducted within UTM (Universiti Teknologi Malaysia) Skudai campus at Kolej  Tun Razak. Both of the Canon Power Shot SX230 and Xiaomi yi camera would be attach to the UAV  to take aerial photo with three different altitude which is 60 meter, 80 meter and 100 meter with a similar flight path. Check point (CPs) and Ground control point (GCPs) were also established using rapid static technique of Global Positioning System (GPS) and Total Station. The Canon Power Shot SX230 and Xiaomi yi camera is then calibrated using checkboard calibration this is done by using Agisoft  Lens software. Then all of the pictures that been taken by the Canon Power Shot SX230 and the Xiaomi yi would be processed by using Agisoft Photoscan software to generate Digital Elevation Model (DEM), orthophoto and contour line. The accuracy of DEM was determined based on Root Mean Squared Error (RMSE) value. Both of the result is then analyze visually and statically. Overall both of the camera gives a slight different in accuracy. 

scholarly journals Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

2021 ◽  
Vol 49 (1) ◽  
pp. 21-28
Author(s):  
Dušan Ranđelović ◽  
Goran Vorotović ◽  
Aleksandar Bengin ◽  
Pavle Petrović
Keyword(s):  
Atmospheric Pressure ◽  
Mean Squared Error ◽  
Low Cost ◽  
Flight Altitude ◽  
Data Filtering ◽  
Squared Error ◽  
The Mean ◽  
Low Altitude ◽  
Accuracy Data ◽  
Altitude Estimation

The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor.

scholarly journals Iterative Intercell Interference Cancellation in MIMO Multicell Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhengzhen Zhang ◽  
Chao Dong ◽  
Qian Wan
Keyword(s):  
Interference Cancellation ◽  
Mean Squared Error ◽  
Base Station ◽  
Intercell Interference ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Pilot Allocation ◽  
Receiver Performance ◽  
Multicell Networks

An iterative intercell interference cancellation algorithm is introduced to improve the receiver performance of uplink transmission in multicell networks. At first, the uplink signal detection is performed independently in each cell according to minimum mean squared error (MMSE) criterion. Subsequently, the detection results are applied to reconstruct the transmit signals of different users and cancel their interference to neighboring cells. With the help of reconstruction results, the MMSE detection matrix of each cell is updated. The channel responses of both efficient and interference links are estimated with the help of pilots. The pilot allocation parameter is introduced to indicate the quality of channel estimation. The simulation results indicate that intercell interference can be greatly mitigated by the proposed algorithm with a moderate number of receiver antennas at the base station.

scholarly journals Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning

Fermentation ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 34
Author(s):  
Alexander Bowler ◽  
Josep Escrig ◽  
Michael Pound ◽  
Nicholas Watson
Keyword(s):  
Machine Learning ◽  
Mean Squared Error ◽  
Low Cost ◽  
Absolute Error ◽  
Alcohol Concentration ◽  
Measured Temperature ◽  
Beer Fermentation ◽  
Non Invasive ◽  
Squared Error ◽  
Ultrasonic Sensing

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultrasonic sensor combined with machine learning to predict the alcohol concentration during beer fermentation. The highest accuracy model (R2 = 0.952, mean absolute error (MAE) = 0.265, mean squared error (MSE) = 0.136) used a transmission-based ultrasonic sensing technique along with the measured temperature. However, the second most accurate model (R2 = 0.948, MAE = 0.283, MSE = 0.146) used a reflection-based technique without the temperature. Both the reflection-based technique and the omission of the temperature data are novel to this research and demonstrate the potential for a non-invasive sensor to monitor beer fermentation.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function

2018 ◽  
pp. 397
Author(s):  
Nadia Hashim Al-Noor ◽  
Shurooq A.K. Al-Sultany
Keyword(s):  
Maximum Likelihood ◽  
Expectation Maximization ◽  
Mean Squared Error ◽  
Maximum Likelihood Estimators ◽  
Reliability Function ◽  
Fuzzy Data ◽  
Monte Carlo Simulation Study ◽  
Weibull Parameters ◽  
Squared Error ◽  
Newton Raphson

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function in terms of their mean squared error values and integrated mean squared error values respectively.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

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