scholarly journals Measurements and Statistical Analysis for Assessment of Availability of Mobile Network Services

2018 ◽  
Vol 2 ◽  
pp. 48-52 ◽  
Author(s):  
Grażyna Kadamus ◽  
Małgorzata Langer
Keyword(s):  
Monte Carlo ◽  
Essential Feature ◽  
Mobile Network ◽  
Simulation Method ◽  
Network Services ◽  
Telecommunication Services ◽  
Network Testing ◽  
The Monte Carlo Method ◽  
Numerical Tools

Availability is an essential feature of telecommunication services. It influences the quality of experience (QoE) associated with individual networks and with the services offered. Therefore, it needs to be allowed for at each level of network design, and has to be controlled at the operation stage. This is achieved by means of various mathematical and numerical tools. In this project listening quality and speech level, which are quality-related features of mobile network services, are measured and analyzed with the Monte Carlo simulation method. Measurements are taken with assistance of the Diversity Benchmarker, a reliable device designed for mobile network testing. Finally, results obtained are compared to assess the applicability of the Monte Carlo method.

scholarly journals Simulasi Monte Carlo dalam Memprediksi Tingkat Lonjakan Penumpang (Studi Kasus di PT. Tri Arga Travel)

2020 ◽  
pp. 92-97
Author(s):  
Dina Mardiati ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Simulation Method ◽  
Transportation Services ◽  
The Monte Carlo Method ◽  
Linear Congruential Generator ◽  
High Level ◽  
Linear Congruential ◽  
A Company

Tri Arga Travel is a company engaged in transportation services. The company really prioritizes the quality of service to consumers. So that on holidays there is usually a surge in passengers that cannot be predicted by the company. This greatly affects service to passengers. The purpose of this research is to predict the surge rate of PT. Tri Arga Travel, making it easier for the leadership of PT. Tri Arga Travel to take a policy when there is a surge in passengers in the future. The data used in this study is data on the number of passengers in 2017, 2018, and 2019 with the aim of padang-perawang. Then, the data is processed using the Monte Carlo method. The Monte Carlo method is a simulation method that uses random numbers obtained from the Linear Congruential Generator (LCG) to predict the rate of passenger spike in the following year by utilizing the previous year's passenger data. The results obtained from testing the Monte Carlo simulation can be seen that in July it is predicted that there will be a surge in passengers with an average level of accuracy of 86.74%. With a fairly high level of accuracy, the application of the Monte Carlo method can be used as a recommendation to predict the level of passenger spikes and also help in improving services to prospective passengers of PT. Tri Arga Travel.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

scholarly journals Technical-Economic Analysis of Grapple Saw

2020 ◽  
Vol 41 (2) ◽  
pp. 219-229 ◽  
Author(s):  
Ricardo Hideaki Miyajima ◽  
Paulo Torres Fenner ◽  
Gislaine Cristina Batistela ◽  
Danilo Simões
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distributions ◽  
Simulation Method ◽  
Forest Harvesting ◽  
Production Costs ◽  
Wood Harvesting ◽  
Food And Agriculture ◽  
The Monte Carlo Method

The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some associated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic technical-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost.

Spreading Characteristics of Molecularly Thin Lubricant on Surfaces With Groove-Shaped Textures: Effects of Molecular Weight and End-Group Functionality

2003 ◽  
Vol 125 (2) ◽  
pp. 350-357 ◽  
Author(s):  
Hedong Zhang ◽  
Yasunaga Mitsuya ◽  
Maiko Yamada
Keyword(s):  
Molecular Weight ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Ising Model ◽  
Monte Carlo Simulations ◽  
Simulation Method ◽  
Solid Surfaces ◽  
The Monte Carlo Method ◽  
End Groups ◽  
End Group

Effects of molecular weight and end-group functionality on spreading of molecularly thin perfluoropolyether (PFPE) film over solid surfaces with groove-shaped textures have been studied by experiments and Monte Carlo simulations. In the experiments, lubricant spreading on a surface with groove-shaped textures was measured by making use of the phenomenon in which diffracted light weakens in the lubricant-covered region. It is found that grooves serve to accelerate spreading and this effect increases for deeper grooves, and also the accelerating rate becomes larger for a lubricant having a larger molecular weight or functional end-groups. In the simulations, the Monte Carlo method based on the Ising model was extended to enable us to evaluate the effect of molecular weight on the spreading of non-functional lubricant inside a groove. The validity of the newly developed simulation method was well confirmed from the agreement between the simulation and experimental results.

THE MONTE CARLO METHOD AS A RISK ASSESSMENT TOOL IN THE FORMATION OF A STOCK PORTFOLIO IN A CRISIS SITUATION

2020 ◽  
Author(s):  
Екатерина Андреевна Винниченко ◽  
Светлана Валентиновна Пупенцова
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Assessment Tool ◽  
Corporate Bonds ◽  
Simulation Method ◽  
Crisis Situation ◽  
The Monte Carlo Method ◽  
Financial Investments ◽  
Stock Portfolio

В работе разработан алгоритм применения метода имитационного моделирования при оценке эффективности финансовых инвестиций на примере оценки корпоративных облигаций в кризисной ситуации. Авторы рассчитали доходность к погашению корпоративных облигаций в период кризиса 2020 года и подготовили рекомендации по выбору наиболее привлекательных ценных бумаг для инвестора. In this paper, we have developed an algorithm for applying the simulation method to evaluate the effectiveness of financial investments on the example of evaluating corporate bonds in a crisis situation. The authors calculated the yield to maturity of corporate bonds during the crisis in 2020 and prepared recommendations for choosing the most attractive securities for investors.

Applications of the uranium’s set of isotopes for nuclear dating: the Monte-Carlo method

2019 ◽  
Vol 107 (3) ◽  
pp. 207-213
Author(s):  
Oksana Pop ◽  
Volodymyr Maslyuk
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Statistical Testing ◽  
Carpathian Mountains ◽  
Low Background ◽  
Statistical Errors ◽  
The Monte Carlo Method ◽  
Geochemical Studies ◽  
Standard Sets

Abstract The new abilities of the method of standard sets of nuclides (SSN) supplemented by the procedure of statistical testing for geochemical studies and nuclear dating are presented. The method allows one move from point-like to probabilistic dating procedures when both the age of the sample and the statistical errors of its determination can be estimated. Low background γ-spectrometric experiments were carried out for samples of rocks of the Carpathian Mountains and calculations for their dating by using the SSN of the series 238U were made. The dependence of the reliability of nuclear dating on the quality of the low background experiment is discussed too.

scholarly journals Simulating spatial aspects of a flash flood using the Monte Carlo method and GRASS GIS: a case study of the Malá Svinka Basin (Slovakia)

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Jaroslav Hofierka ◽  
Monika Knutová
Keyword(s):  
Monte Carlo ◽  
Preferential Flow ◽  
Flash Flood ◽  
Simulation Method ◽  
Distributed Hydrological Model ◽  
Protection Measures ◽  
Grass Gis ◽  
The Monte Carlo Method ◽  
Spatially Distributed ◽  
Gis Environment

AbstractThis paper focuses on the flash flood assessment using a spatially-distributed hydrological model based on the Monte Carlo simulation method. The model is implemented as r.sim.water module in GRASS GIS and was applied to the Malá Svinka Basin in Eastern Slovakia where a heavy rainfall (100 mm/hr.) caused a flash flood event with deadly consequences in July 1998. The event was simulated using standard datasets representing elevation, soils and land cover. The results were captured in time series of water depth maps showing gradual changes in water depths across the basin. The hydrological effects of roads in the study area were simulated using the preferential flow feature of the model. This simulation helped to identify source areas contributing to flooding in built-up areas. The implementation in a GIS environment simplifies the data preparation and eventual modification for various scenarios and flood protection measures. The simulation confirmed excellent robustness and flexibility of the method.

Atomistic Simulation of SiC Growth at the SiC(0001)/Si1-XCx Interface by the Monte Carlo Method

2011 ◽  
Vol 679-680 ◽  
pp. 87-90
Author(s):  
Makoto Itoh ◽  
Tsuyoshi Uda ◽  
Jun Nara ◽  
Takahisa Ohno
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Atomistic Simulation ◽  
Lattice Spacing ◽  
Potential Surface ◽  
Exchange Process ◽  
Simulation Method ◽  
Local Minima ◽  
The Monte Carlo Method ◽  
Local Relaxation

We developed the computer simulation method to study growth of SiC at the SiC(0001)/Si1-xCx interface based on the Monte Carlo method. Energy is calculated by using the Tersoff potential and the lattice spacing is sub-divided to enable the structural relaxation in a dicrete manner. Before making an attempt for the atomic difusion via the species exchange process in the Metropolis alogrithm, local relaxation is carried out to locate atoms at the local minima of the potential surface. Then, parallel computation is carried out to thermally equilibrate a system.

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