scholarly journals Comparative Monte Carlo Analysis of Background Estimation Algorithms for Unmanned Aerial Vehicle Detection

2021 ◽  
Vol 13 (5) ◽  
pp. 870
Author(s):  
Grzegorz Matczak ◽  
Przemyslaw Mazurek
Keyword(s):  
Monte Carlo ◽  
Unmanned Aerial Vehicle ◽  
Nearest Neighbor ◽  
Monte Carlo Analysis ◽  
K Nearest Neighbor ◽  
Background Estimation ◽  
Estimation Algorithms ◽  
Monte Carlo Studies ◽  
Aerial Vehicle ◽  
Mixture Of Gaussian

Background estimation algorithms are important in UAV (Unmanned Aerial Vehicle) vision tracking systems. Incorrect selection of an algorithm and its parameters leads to false detections that must be filtered by the tracking algorithm of objects, even if there is only one UAV within the visibility range. This paper shows that, with the use of genetic optimization, it is possible to select an algorithm and its parameters automatically. Background estimation algorithms (CNT (CouNT), GMG (Godbehere-Matsukawa-Goldberg), GSOC (Google Summer of Code 2017), MOG (Mixture of Gaussian), KNN (K–Nearest Neighbor–based Background/Foreground Segmentation Algorithm), MOG2 (Mixture of Gaussian version 2), and MEDIAN) and the reference algorithm of thresholding were tested. Monte Carlo studies were carried out showing the advantages of the MOG2 algorithm for UAV detection. An empirical sensitivity analysis was presented that rejected the MEDIAN algorithm.

MONTE CARLO STUDIES OF A NEW MODEL DRIVEN DIFFUSIVE SYSTEM WITH REPULSIVE INTERACTIONS

1992 ◽  
Vol 06 (26) ◽  
pp. 1673-1679
Author(s):  
K.K. MON
Keyword(s):  
Monte Carlo ◽  
Lattice Gas ◽  
Nearest Neighbor ◽  
Two Dimensions ◽  
Model Driven ◽  
New Class ◽  
Driven Lattice Gas ◽  
Driven Diffusive System ◽  
Monte Carlo Studies ◽  
Repulsive Interactions

We propose a new class of driven lattice gas with repulsive nearest-neighbor interactions. Particles are allowed to jump to empty next-nearest-neighbor (nnn) sites in addition to the standard nearest-neighbor moves. In contrast to previous model with repulsive interactions, the external driving field (E) acts only along the nnn directions and does not destroy ground state sublattice ordering. Extensive Monte Carlo simulations in two dimensions for small E are consistent with a line of continuous transitions with Ising exponents. First-order transitions are also found for larger E.

207PB NMR and Monte Carlo Studies of Ionic Solid Solutions

1998 ◽  
Vol 547 ◽  
Author(s):  
Young-Sik Kye ◽  
Bruno Herreros ◽  
Gerard S. Harbison
Keyword(s):  
Monte Carlo ◽  
Solid Solutions ◽  
Nearest Neighbor ◽  
Positive Curvature ◽  
Lattice Parameter ◽  
Mixed Crystals ◽  
Strontium Nitrate ◽  
Ion Distributions ◽  
Monte Carlo Studies ◽  
Ionic Solid

AbstractLead, strontium and barium nitrates, like the titanates of the same cations, form a continuous set of solid solutions. 207Pb NMR spectra of mixed crystals of lead/strontium nitrate and lead/barium nitrate each show up to 13 lines, arising from lead ions with from zero to twelve Pb2+ nearest-neighbor cations replaced by Sr2+ or Ba2+. In the case of (Pb,Sr)(NO3)2 these shifted lines are further split by the multiplicity of inequivalent nearest-neighbor replacements. The average shift per Sr2+ ion is 21.8 ppm; that for Ba2+ is smaller. Using Monte Carlo/Metropolis calculations, the intensities of the resonances can be fit to statistical models of Pb2+ and Sr2+ ion distributions, and used to probe the microenergetics of solid solution formation. The data can be satisfactorily fit by distributions in which the cations are slightly clustered, with like pairs of nearest neighbors being favored by 120 J/mol over unlike pairs. Interestingly, this finding is inconsistent with the conventional interpretation of powder diffraction results for the mixed crystals, where the dependence of lattice parameter on composition shows a slight positive curvature, generally held to indicate a favorable interaction between unlike ions.

scholarly journals Texton Based Segmentation for Road Defect Detection from Aerial Imagery

2021 ◽  
Vol 4 (2) ◽  
pp. 107
Author(s):  
Adhi Prahara ◽  
Son Ali Akbar ◽  
Ahmad Azhari
Keyword(s):  
Nearest Neighbor ◽  
Aerial Imagery ◽  
Support Vector ◽  
Morphological Operation ◽  
K Nearest Neighbor ◽  
The Road ◽  
Blob Analysis ◽  
Aerial Vehicle ◽  
The Government

Road defect such as potholes and road cracks, became a problem that arose every year in Indonesia. It could endanger drivers and damage the vehicles. It also obstructed the goods distribution via land transportation that had major impact to the economy. To handle this problem, the government released an online complaints system that utilized information system and GPS technology. To follow up the complaints especially road defect problem, a survey was conducted to assess the damage. Manual survey became less effective for large road area and might disturb the traffic. Therefore, we used road aerial imagery captured by Unmanned Aerial Vehicle (UAV). The proposed method used texton combined with K-Nearest Neighbor (K-NN) to segment the road area and Support Vector Machine (SVM) to detect the road defect. Morphological operation followed by blob analysis was performed to locate, measure, and determine the type of defect. The experiment showed that the proposed method able to segment the road area and detect road defect from aerial imagery with good Boundary F1 score.

scholarly journals Optimization of Missing Value Data Imputation Automatic Dependent Surveillance Broadcasting (ADS-B) Based on K-Nearest Neighbor and Genetic Algorithm

2020 ◽  
Vol 9 (12) ◽  
pp. 327-331
Author(s):  
Didik Hariyanto ◽  
Sholeh Hadi Pramono ◽  
Erni Yudaningtyas
Keyword(s):  
Genetic Algorithm ◽  
Monte Carlo ◽  
Technology Use ◽  
Missing Values ◽  
Nearest Neighbor ◽  
Data Imputation ◽  
Flow Data ◽  
K Nearest Neighbor ◽  
Missing Value ◽  
K Value

The flight navigation equipments technology use still conventional, namely using radar, now slowly starting to switch to Automatic Dependent Surveillance-Broadcast (ADS-B [6]. In this study, using RTL-SDR to detect aircraft and carry out tests through the Monte Carlo alltitude method, latitude, and longitude only [3]. However, in this system there is a problem regarding the missing value in the preprocessed data results / ADS-B flow data. In handling missing values, the KNN method is the most popular, but the weakness in the KNN method, can reduce the performance[9]. So a Genetic Algorithm (GA) is proposed to optimize the k value in the KNN method. The results of this study obtained a better MSE value in the imputation process. Altitude k = 3, with MSE 128668.96, Speed k = 6, with the MSE value = 457.5201, while the k value in the Heading variable k = 61 with MSE = 752.1429. For Lattitude and Longitude, the value of k = 3, MSE 9.16E-05 and k = 2 and MSE 1.68E-05.

scholarly journals Unmanned aerial vehicle-aided cooperative regenerative relaying network under various environments

2021 ◽  
Vol 11 (6) ◽  
pp. 5153
Author(s):  
Thanh-Luan Nguyen ◽  
Duy-Hung Ha ◽  
Phu Tran Tin ◽  
Hien Dinh Cong
Keyword(s):  
Monte Carlo ◽  
Unmanned Aerial Vehicle ◽  
Ergodic Capacity ◽  
Relay Network ◽  
Cooperative Relay ◽  
Power Splitting ◽  
Amplify And Forward ◽  
High Rise ◽  
Aerial Vehicle ◽  
Cooperative Relay Network

This paper studies a cooperative relay network that comprises an unmanned aerial vehicle (UAV) enabling amplify-and-forward (AF) and power splitting (PS) based energy harvesting. The considered system can be constructed in various environments such as suburban, urban, dense urban, and high-rise urban where the air-to-ground channels are model by a mixture of Rayleigh and Nakagami-m fading. Then, outage probability and ergodic capacity are provided under different environment-based parameters. Optimal PS ratios are also provided under normal and high transmit power regimes. Finally, the accuracy of the analytical results is validated through Monte Carlo methods.

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