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2022 ◽  
Author(s):  
Koushik Saha ◽  
SUBHAJIT SINHA

Abstract It is crucial for policy makers and environmental managers to determine the future dynamics of coastal wetlands, especially the existence of their response, disruption, and recovery regimes. Reconstruction of meso-scale evolution in coastal ecosystems can help to adapt coastal resource management techniques to the natural scales of system activity, thereby encouraging true biodiversity. This research provides an overview of decadal (mesoscale) geomorphic transition by high-resolution grain size analysis of a sediment deposit from a barrier estuary regime on the Chandipur coast, India. Coastal marshland’s grain size distribution (GSD) has generally been analyzed using End Member Mixing Models (EMMA) and Probability Density Function (PDF) methods (e.g. log-normal, log skew-Laplace). Although these techniques do not consider the compositional nature of the records, which can undermine the outcomes of the interpretation of sedimentary deposits. The approach to reliable granulometric analysis of lithostratigraphic sequences aims at establishing direct links between fluid dynamics and subsequent shifts in the texture of sediments. In this study, GSD analysis of marsh sediment is represented by compositional data analysis (CoDa) and a multivariate statistical framework. Barrier estuary evolution, presented by time lapses of satellite maps coupled with grain size and carbon content of marsh sediment, primarily reflects the evolving hydrodynamics of the back barrier area. These findings will provide a statistically robust analysis of the depositional system in coastal marshland. Multiannual environmental variations in the back barrier configuration illustrate the importance of this applied approach with respect to bridging the basis of estuarine evolution and process information.


2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
R. Alshenawy ◽  
Navid Feroze ◽  
Ali Al-Alwan ◽  
Mahreen Saleem ◽  
Sahidul Islam

This study discusses the posterior estimation for the parameters of the Burr type II distribution (BIID). The informative and noninformative priors along with different loss functions have also been assumed for the posterior estimation. The applicability of the proposed distribution has also been discussed. The modeling capability of the proposed model has been compared with seven classes of the lifetime distributions using real data. The generalizations of Weibull, exponential, Rayleigh, gamma, log normal, Pareto, Maxwell, Levy, Laplace, inverse gamma, Gompertz, chi-square, inverse chi-square, half normal, and log-logistic distributions have been considered for the comparison. The comparison has been made based on different goodness-of-fit criteria, such as Akaike information criteria (AIC), Bayesian information criteria (BIC), and Kolmogorov-Smirnov (KS) test. Based on the results from the study, it can be suggested that the BIID can efficiently replace commonly used lifetime distributions and their modifications. The results under this model were comparable with different conventional/modified distributions having up to six parameters.


Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 560
Author(s):  
Wenbin Cai ◽  
Wen Li ◽  
Jinze Xu

During the oil production process, sucker rods are subjected to cyclic alternating load. After a certain number of cycles, a sucker rod can experience fatigue failure. The number of cycles is called fatigue life (N), and the accurate relationship between maximum stress (S) and fatigue life (N) under a certain reliability (P), namely the P-S-N curve, is an important basis for the reliability analysis and fatigue life prediction of sucker rods. The Basquin model, based on log-normal distribution, is widely used for fitting the P-S-N curves of sucker rods. Due to the limitation of this model, it is difficult to extrapolate the conclusion obtained from a finite fatigue region to the high-cycle or ultra-high-cycle fatigue region, which makes it impossible to estimate the fatigue limit of the sucker rod. Compared to the log-normal distribution, Weibull distribution causes the sucker rod to have a minimum safety life, namely the safety life at 100% survival rate, which complies with the fatigue characteristics of the sucker rod and is more in line with the actual situation. In this study, the fatigue data for ultra-high-strength HL and HY grade sucker rods were obtained through experimental fatigue tests. A new fatigue life model was established and the P-S-N curves of two types of ultra-high strength sucker rods were obtained. For HL- and HY-type ultra-high strength sucker rods, the average error between the fitting result and fatigue test value is 1.25% and 4.39%, respectively. Compared to the S-N curve fitting result obtained from the Basquin model commonly used for sucker rods, the new model based on three-parameter Weibull distribution provides better fitting precision and can estimate fatigue limit more accurately, so this model is more suitable for estimating fatigue life and can better guide the design of ultra-high strength sucker rod strings.


2022 ◽  
Vol 16 (1) ◽  
pp. 87-101
Author(s):  
Julien Meloche ◽  
Alexandre Langlois ◽  
Nick Rutter ◽  
Alain Royer ◽  
Josh King ◽  
...  

Abstract. Topography and vegetation play a major role in sub-pixel variability of Arctic snowpack properties but are not considered in current passive microwave (PMW) satellite SWE retrievals. Simulation of sub-pixel variability of snow properties is also problematic when downscaling snow and climate models. In this study, we simplified observed variability of snowpack properties (depth, density, microstructure) in a two-layer model with mean values and distributions of two multi-year tundra dataset so they could be incorporated in SWE retrieval schemes. Spatial variation of snow depth was parameterized by a log-normal distribution with mean (μsd) values and coefficients of variation (CVsd). Snow depth variability (CVsd) was found to increase as a function of the area measured by a remotely piloted aircraft system (RPAS). Distributions of snow specific surface area (SSA) and density were found for the wind slab (WS) and depth hoar (DH) layers. The mean depth hoar fraction (DHF) was found to be higher in Trail Valley Creek (TVC) than in Cambridge Bay (CB), where TVC is at a lower latitude with a subarctic shrub tundra compared to CB, which is a graminoid tundra. DHFs were fitted with a Gaussian process and predicted from snow depth. Simulations of brightness temperatures using the Snow Microwave Radiative Transfer (SMRT) model incorporating snow depth and DHF variation were evaluated with measurements from the Special Sensor Microwave/Imager and Sounder (SSMIS) sensor. Variation in snow depth (CVsd) is proposed as an effective parameter to account for sub-pixel variability in PMW emission, improving simulation by 8 K. SMRT simulations using a CVsd of 0.9 best matched CVsd observations from spatial datasets for areas > 3 km2, which is comparable to the 3.125 km pixel size of the Equal-Area Scalable Earth (EASE)-Grid 2.0 enhanced resolution at 37 GHz.


2022 ◽  
Vol 15 (1) ◽  
pp. 149-164
Author(s):  
Alberto Sorrentino ◽  
Alessia Sannino ◽  
Nicola Spinelli ◽  
Michele Piana ◽  
Antonella Boselli ◽  
...  

Abstract. We consider the problem of reconstructing the number size distribution (or particle size distribution) in the atmosphere from lidar measurements of the extinction and backscattering coefficients. We assume that the number size distribution can be modeled as a superposition of log-normal distributions, each one defined by three parameters: mode, width and height. We use a Bayesian model and a Monte Carlo algorithm to estimate these parameters. We test the developed method on synthetic data generated by distributions containing one or two modes and perturbed by Gaussian noise as well as on three datasets obtained from AERONET. We show that the proposed algorithm provides good results when the right number of modes is selected. In general, an overestimate of the number of modes provides better results than an underestimate. In all cases, the PM1, PM2.5 and PM10 concentrations are reconstructed with tolerable deviations.


2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiang Li ◽  
Yang Ming ◽  
Hongguang Ma ◽  
Kaitao (Stella) Yu

PurposeTravel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the development of digital technology and big data analytics ability in the bus industry, practitioners prefer to generate deterministic travel time based on the on-board GPS data under maximum probability rule and mean value rule, which simplifies the optimization procedure, but performs poorly in the timetabling practice due to the loss of uncertain nature on travel time. The purpose of this study is to propose a GPS-data-driven bus timetabling approach with consideration of the spatial-temporal characteristic of travel time.Design/methodology/approachThe authors illustrate that the real-life on-board GPS data does not support the hypothesis of normal (log-normal) distribution on travel time at inter-stops, thereby formulating the travel time as a scenario-based spatial-temporal matrix, where K-means clustering approach is utilized to identify the scenarios of spatial-temporal travel time from daily observation data. A scenario-based robust timetabling model is finally proposed to maximize the expected profit of the bus carrier. The authors introduce a set of binary variables to transform the robust model into an integer linear programming model, and speed up the solving process by solution space compression, such that the optimal timetable can be well solved by CPLEX.FindingsCase studies based on the Beijing bus line 628 are given to demonstrate the efficiency of the proposed methodology. The results illustrate that: (1) the scenario-based robust model could increase the expected profits by 15.8% compared with the maximum probability model; (2) the scenario-based robust model could increase the expected profit by 30.74% compared with the mean value model; (3) the solution space compression approach could effectively shorten the computing time by 97%.Originality/valueThis study proposes a scenario-based robust bus timetabling approach driven by GPS data, which significantly improves the practicality and optimality of timetable, and proves the importance of big data analytics in improving public transport operations management.


2022 ◽  
Vol 924 (1) ◽  
pp. 31
Author(s):  
Gibor Basri ◽  
Tristan Streichenberger ◽  
Connor McWard ◽  
Lawrence Edmond IV ◽  
Joanne Tan ◽  
...  

Abstract We present a method that utilizes autocorrelation functions from long-term precision broadband differential light curves to estimate the average lifetimes of starspot groups for two large samples of Kepler stars: stars with and without previously known rotation periods. Our method is calibrated by comparing the strengths of the first few normalized autocorrelation peaks using ensembles of models that have various starspot lifetimes. We find that we must mix models of short and long lifetimes together (in heuristically determined ratios) to align the models with the Kepler data. Our fundamental result is that short starspot-group lifetimes (one to four rotations) are implied when the first normalized peak is weaker than about 0.4, long lifetimes (15 or greater) are implied when it is greater than about 0.7, and in between are the intermediate cases. Rotational lifetimes can be converted to physical lifetimes if the rotation period is known. Stars with shorter rotation periods tend to have longer rotational (but not physical) spot lifetimes, and cooler stars tend to have longer physical spot lifetimes than warmer stars with the same rotation period. The distributions of the physical lifetimes are log-normal for both samples and generally longer in the first sample. The shorter lifetimes in the stars without known periods probably explain why their periods are difficult to measure. Some stars exhibit longer than average physical starspot lifetimes; their percentage drops with increasing temperature from nearly half at 3000 K to nearly zero for hotter than 6000 K.


2021 ◽  
Vol 14 (1) ◽  
pp. 442
Author(s):  
Victor Fernandes ◽  
Thiago F. A. Nogueira ◽  
H. Vincent Poor ◽  
Moisés V. Ribeiro

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.


2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Dang Thi Dieu Thuy ◽  
Christopher Gan ◽  
Baiding Hu

As an important area in terms of biodiversity and fish stocks in Vietnam, Cu Lao Cham or Cham Islands (CLC) marine protected area (MPA) is under increasing threat from human activities. Conservation efforts have recently been implemented but economic analysis of the CLC MPA’s natural values did not investigate what may affect policy decisions on CLC MPA’s sustainable development. Using a structured questionnaire and a payment card technique (based on the contingent valuation method), we estimate visitors’ willingness to pay (WTP) for conservation of marine resources in the CLC MPA. The log-normal regression results indicate that the visitors’ WTP for conservation is affected by their characteristics, perceptions of environmental protection and conservation, and their assessment of the current CLC MPA entrance fee. Visitors are WTP an additional amount of US$2.26 per person for conservation while visiting the CLC MPA. This indicates that with the introduction of the proposed entrance fee (the mean WTP added to the current entrance fee), the CLC MPA management would not only have sufficient funds for their management and conservation programmes, but also that the number of visitors may decline slightly, which would reduce some of the pressure on the environment, natural resources, and coral reefs.


2021 ◽  
Vol 15 (3) ◽  
pp. 1
Author(s):  
Nayara Costa ◽  
Michael Silveira Thebaldi ◽  
Karina Vilela Rodrigues

A evapotranspiração (ET) é um parâmetro fundamental na estimativa da exigência hídrica de uma determinada região, principalmente quando se trata de planejamento ou desenvolvimento de sistemas que envolvam o manejo da água, sendo a ET provável a lâmina de ET que pode ser igualada ou superada a determinado nível de probabilidade. Assim, objetivou-se neste estudo analisar a ET potencial provável mensal do município de Divinópolis – MG e, a partir da definição de distribuições estatísticas, identificar a que melhor representa as séries históricas de evapotranspiração mensal. Para isso, os dados diários coletados da estação meteorológica convencional do Instituto Nacional de Meteorologia foram analisados utilizando frequência de excedência de 90, 75, 50, 25 e 10%. Foram ajustadas, às séries observadas as distribuições de frequência Gumbel para Máximos, Fréchet, Gama, Log-Normal 2P e Beta, sendo as aderências destes modelos testadas pelos métodos de Kolmogorov-Smirnov e Qui-Quadrado, ambos a 5% de probabilidade. A distribuição Beta foi a que melhor aderiu à maioria das séries de evapotranspiração mensal, e a distribuição Log-Normal a 2 Parâmetros obteve a pior aderência. A ET potencial média mensal pode ser utilizada de forma satisfatória para estimar a ET potencial provável com diferentes níveis de probabilidade de ocorrência.


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