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Acoustic emission experiments in paper, a disordered material, give evidence for power-law probability distributions of statistical quantities as event energies or intervals. Two setups, usual mode I tensile tests and a nip-in-peel one have been studied in our work. In both cases, even using the same material, we observe “criticality”. This has wide implications for theories of statistical fracture. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]

The impairment of the quality of water is a serious and rising issue globally. The extreme impairment cases often be the main reason to unbalanced human and ecosystem impacts. It causes a very limit of resources for quality consumption and the manufacturing of food, domestic use and also damaging ecosystems. It is expected that various factors combination makes conditions suitable for terrible water quality. The aim is to find the suitable water quality parameter that is relate to extreme cases of water quality. Extreme value theory will be introduce as statistical tools for analyzing extreme data and predict future extreme occurrences based on return level. [ABSTRACT FROM AUTHOR]

The authors of the paper present a computational method for constructing the time delay distribution function for a closed control loop of the dynamic parameters of the system. The method is based on an algorithmic estimation of the temporal characteristics of the structural elements of the control system that ensure the transmission of control information signals in real time. The web-results of the script are obtained, which algorithmizes the calculation procedures for the coordinate-wise construction of the time delay distribution function of the elements of a closed loop for controlling the dynamic parameters of the system. The listing code of the java script that algorithmizes the calculation procedures is presented in the paper. The proposed computational method is necessary for the correct evaluation of the synchronous control algorithm of the designed dynamic system, which includes closed control loops. [ABSTRACT FROM AUTHOR]

Two new applications of high performance computing based on the DSMC approach were presented in the Graeme Bird Plenary Lecture and are summarized in this paper. The paper first discusses the importance of bimodality in the velocity distribution function in characterizing unsteady shock oscillations as well as their role in understanding transitioning laminar shock-boundary layer flows. A second computational problem of the neutralization of a low-temperature ion beam plasma using the particle-in-cell approach is discussed and again the non-Maxwellian behavior of plasma electrons is shown to change the behavior of unsteady electron solitary waves. The paper looks both back and forwards in time and provides some assessment of the fundamental role of particle kinetic approaches in nonequilibrium gas dynamics. [ABSTRACT FROM AUTHOR]

There are limited studies being done that include risk assessment when calculating lead time in manufacturing process. This study proposes a model that integrates Variable VSM (V-VSM) with Risk Assessment- Failure Mode and Effect Analysis (RA-FMEA). Each process needs to define the best fit probability distribution. Value Stream Mapping (VSM) was used in determining total throughput time, cycle time (CT) and lead time (LT). Information on Value added activities (VAA) and Non-value-added activities (NVAA) within the process need to be identified and mentioned prior to VSM analysis. Monte Carlo simulation with @Risk software was then used for the model. The simulated result produces values for (minimum, most-likely(mean), maximum) time values of total CT/LT and risk value for management to deploy in planning raw material order, VAA/ NVAA, Work in Progress (WIP), process layout and shipment schedule. Validation of this proposed model was done using a real case study involving a small /medium scale manufacturer producing several mixes of powdered drink. This paper will focus on the modelling of V-VSM and RA-FMEA for Monte Carlo simulation using @ Risk software. [ABSTRACT FROM AUTHOR]

Since Abid and Abdullrazak (2017)[1,2] suggested unit truncated H-G family of distributions, a lot of published papers based on this family to derive new distributions for representing set(s) of real data more flexibly. In this paper, we present two new distributions, named unit truncated Inverted Gamma - rectangular Distribution (UTIG-RD) and unit truncated Inverted Gamma - doubly truncated Exponential Distribution (UTIG-DTED). The rth raw moments function form derives for new densities. Stress-strength reliability, Shannon and relative entropies have also been discussed. We conduct two simulation studies, one for each distribution of UTIG-RD and UTIG-DTED to detect the acts of the maximum likelihood estimations of the models. [ABSTRACT FROM AUTHOR]

In real data analysis, there is no value assigned as infinity, this fact is reflected on the traditional distributions which are deal with infinity theoretically. Truncated distributions are more matched with them in the analysis and inferences aspects. Therefore, in this paper, some important properties of doubly truncated generalized Gompertz distribution and doubly truncated Marshal-Olkin extended Uniform distribution are derived analytically. [ABSTRACT FROM AUTHOR]

The modeling of lifetime data has been an important study issue in the last years. Several papers have been published on this topic, with the goal of introducing new statistical approaches for dealing with lifespan phenomena. We use the family [0,1] Truncated Inverse Weibull-G to extend the Exponentaited Exponential distribution in this paper. The result is a [0,1] Truncated Invers Weibull Exponentaited Exponential distribution. TIWEE. We give precise formulations for properties such as the hazard function, quantile function, moments, MGF, reliability function, and order statistics. This is the section for you. The failure times of 50 components (per 1000 hours) are represented in the data set, demonstrating the flexibility in modeling real-life data. [ABSTRACT FROM AUTHOR]

In this paper, we study single server Markovian queue with finite capacity with catastrophe and restoration and the server is permitted for single working vacation. The arrival process follows Poisson distribution. The service time follows exponential distribution with slow service rate during vacation and with normal service rate during busy period. The server goes on vacation when there is no one in the queue. The vacation duration is exponentially distributed. Customers arrived during vacation receive service with slow service rate. When Catastrophe occurs, it removes all from the system. Then the system needs some sort of time to accept a new customer which is referred to as restoration time. This model is analysed by using probability generation method. Some queueing performances are performed. [ABSTRACT FROM AUTHOR]

This study discusses the strategy of determining logistics hubs' location to carry out an efficient distribution function in terms of logistics costs. This study examines the logistics hub for rice commodities. In 2018 Indonesia experienced a rice surplus and rice imports simultaneously. The surplus of rice production in question is 2.85 million tons. However, in the same year, Indonesia imported 2.2 million tons of rice. The problem arises when it comes to the different costs of distribution from one point to another. Efforts need to be made to improve the performance of logistics hubs in terms of strategic, tactical, and operational capabilities. Operational costs are assumed to be minimal to achieve distribution effectiveness and efficiency by determining the logistics hub based on the cheapest shipping costs. This study contributes to the determination of the location of the logistics hub by using two stages of the clustering analysis, namely Ward's and K-Means clustering methods. At the first stage, this paper utilizes Ward's method and results in the significant increasing coefficient at the 20th stage indicating that 2 clusters were formed. The value of these 2 (two) clusters will be the input (k value) on the second stage, K-Means. The K-Means method produces 14 and 8 members in clusters 1 and 2, respectively. In cluster 1, points 4, 9, 12, and 19 were selected to be logistics hubs. Another logistics hub in cluster 2 will be located in points 8 and 11. [ABSTRACT FROM AUTHOR]

Distribution function seems be the most full analytical description of any stochastic process. Distribution function for multiple Coulomb scattering for infinite and uniform medium had been obtained at the first half of the last century. We have used it successfully for the dynamics exploration of the beam crossing thin foil normally to its surface. The function mentioned cannot be used directly for the case of the foil installed at some angle to the beam direction of propagation. In mathematical sense, this case is already new problem and new analytical solution is required. To find out the analytical solution for this case, partial differential equation with appropriate boundary conditions must be solved. As it takes place for the majorities of the mathematical physics problems, the exact analytical solution in this specific case is unavailable. We tried to find a different approach searching for approximate solution of boundary problem based on exact solution for infinite scattering. The paper describes the flow lines model for multiple Coulomb scattering that results in analytical explanations of different phenomena taking place in the case of beam incline incidence on the border separating vacuum and scattering medium [ABSTRACT FROM AUTHOR]

In this paper, we have investigate the effect of kappa distribution function in the presence of parallel electric field by using the method of kinetic approaches are discussed. The kinetic method has been adopted to obtain the dispersion relation, growth rate and growth length of the electromagnetic ion-cyclotron waves in minimum low βcondition (β is the part of plasma pressure to magnetic pressure), homogeneous plasma has been obtained. In this paper, the effect of kappa distribution in presence of parallel electric field EII on EMIC waves in magnetosphere plasma is to enhance the damping/growth rate with increases the growth length of EMIC waves in low β condition. The results are interpreted for the space plasma parameters appropriate to the auroral acceleration region. The results of the work is consistent for EMIC emissions observations by Polar, FAST and S3-3 satellite of the auroral acceleration region as reported by [1,2] as well as the astrophysical and astronomical applications of these processes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of testing exponentiality. Among the multiple statistics tests available to test this hypothesis, we consider the Jackson and the Lilliefors exponentiality tests. In particular, we test the null hypothesis of exponential- ity against the alternative hypothesis of the generalized exponential distribution. Using Monte Carlo computations we obtain and compare the empirical power of both statistic tests. [ABSTRACT FROM AUTHOR]

In 2002–2004, the first CIPM Key Comparison of triple-point-of-water (TPW) cells, CCT-K7, was carried out. One of the major observations in CCT-K7 was the bimodal distribution of the results because 3 out of 21 participating labs had their TPW realization based on Vienna Standard Mean Ocean Water (V-SMOW) and thus followed the definition of the TPW given in the Supplementary Information to the International Temperature Scale of 1990 (ITS-90), which resulted in "warmer" national realizations compared to the rest of the participants. Based on the CCT-K7 results, the "Clarification of the definition of the kelvin" was issued in 2005, where the importance of the isotopic corrections to V-SMOW water was emphasized. The successor of CCT-K7, CCT-K7.2021, was carried out in 2021–2022. In this paper, we compare the results of the two comparisons side-by-side to illustrate: a) the improved measurement capabilities of the participants over the past 20 years and b) the improved quality of the TPW cells. As expected, in CCT-K7.2021 most participants renewed their national reference ensembles with newer, higher quality and vitreous-silica cells and applied the isotopic corrections to their respective national references. This, in turn, led to: 1) a smaller spread of the national realizations by almost a factor of two — 28 µK instead of 50 µK in CCT-K7, 2) an only slightly asymmetric distribution of the results, and 3) an increase in KCRV value by approximately 66 µK compared to CCT-K7. [ABSTRACT FROM AUTHOR]

Extreme rainfall prediction is a critical aspect in hydrological and climate research fields to estimate the probability of extreme events, such as heavy rainfall or floods. These extreme events occur all over the world and have a tremendous impact on human health, injury and illness, and the imbalance of the ecosystem. This paper aims to compare the prediction of extreme rainfall between generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) for 10 years return period. The daily rainfall data of northern region in Peninsular Malaysia were obtained from Department of Irrigation and Drainage Malaysia (DID) for 29 stations for the period 1999 to 2019 is used. The findings will be beneficial for hydrologists to improve understanding of the difference between the analysis of the standard data modeling with extreme data modeling as well as to understand the difference between two main approaches in extreme data analysis. Both models show Klinik Bkt. Bendera station will encounter the highest 10 years return level compared to the other stations. The maximum corresponding 10-years return value for GPD is 147.26mm while for GEV is 142.39mm. These values are reaching the very heavy category of rainfall intensity index in Malaysia. [ABSTRACT FROM AUTHOR]

This document discusses the N-policy for M/G/1 priority retrial queue with working vacations. The authors use the probability generating function (PGF) technique and the supplemental variable method to obtain the number of customers in the system and its orbit. They also derive the mean queue length of the system and orbit. The results of this study have applications in telephone consultation and telecommunications systems for medical service systems. The authors acknowledge the editor and referees for their suggestions in improving the paper. [Extracted from the article]

In this paper, we will consider a problem of strong consistency with rates of estimates density function from stationary random sequence of linearly positive quadrant dependent random variables. We first established uniform strong rates of convergence over compact sets in R are for the estimates of distribution function and then for the estimates of density function and all its partial derivatives up to a given order r from stationary random sequence of linearly positive quadrant dependent random variables. [ABSTRACT FROM AUTHOR]

In the paper, we investigate two semiparametrical estimators of distribution function in informative model of random censorship from both sides. Under investigating of estimators, the characterization properties of the considered informative model are used. The properties of the semiparametric estimators by using methods of numerical modeling are discussed. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study of water-to-air optical camera communication (OCC) in the presence of wavy surface conditions. It evaluates the system performance in terms of the signal-to-noise ratio (SNR), considering various camera exposure times and regions of interest (ROI) in captured images. The results reveal a noticeable reduction in the SNR due to the presence of surface waves. However, the system performance is improved by considering the average value of several illuminated pixels produced by the point spread function as the ROI. Furthermore, the statistical characteristics of the received optical signals in the presence of surface waves are assessed. [ABSTRACT FROM AUTHOR]

The present form of quantum mechanics is based on the Copenhagen school of interpretation. Einstein did not belong to the Copenhagen school, because he did not believe in probabilistic interpretation of fundamental physical laws. This is the reason why we are still debating whether there is a more deterministic theory. One cause of this separation between Einstein and the Copenhagen school could have been that the Copenhagen physicists thoroughly ignored Einstein’s main concern: the principle of relativity. Paul A. M. Dirac was the first one to realize this problem. Indeed, from 1927 to 1963, Paul A. M. Dirac published at least four papers to study the problem of making the uncertainty relation consistent with Einstein’s Lorentz covariance. It is interesting to combine those papers by Dirac to make the uncertainty relation consistent with relativity. It is shown that the mathematics of two coupled oscillators enables us to carry out this job. We are then led to the question of whether the concept of localized probability distribution is consistent with Lorentz covariance. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

This paper presents a new entropy-parametric test for identifying symmetric probability models. In paper it was obtained a test parameter with a known probability due to research the two features space, that are given by both entropy coefficient and anti-kurtosis. A test for comparative analysis of modeling realizations using various types of distributions is obtained. The test is given as the circle radius in the reduced centered coordinate system. This ensures the universality of the significance level of the entropy-parametric test regarding the shape of the symmetric distribution. It is depending on the values of the test the probability of committing of the type I error was estimated when the null hypothesis is rejected. [ABSTRACT FROM AUTHOR]

A survey has been conducted of the resonance data available in the major evaluated libraries for a range of mid-mass isotopes. Although many isotopes have data derived from experimental measurements and rigorous analyses, the data for some others, particularly for isotopes that are unstable, are purely theoretically generated, e.g. via the use of the TARES code. A subsequent project has developed a suite of automated tools to rapidly inspect the resonance data available for a specified isotope. These tools calculate a range of values and distributions for the available data (e.g. cumulative number of resonances versus neutron energy) and use a comparison against expected theoretical values (e.g. a Porter-Thomas distribution) to suggest their physical validity or otherwise. The motivation for this study, the tools developed, and results for a number of isotopes, are presented in this paper. [ABSTRACT FROM AUTHOR]

Financial optimization is one of the most intriguing aspects of the problem of decision making in the face of uncertainty. For example, 1) asset allocation for insurance company retirement plans; 2) securities selection for portfolio managers, stocks and bonds; 3) currency hedging for multinational corporations; and 4) risk management for large corporations. Time and uncertainty are important factors in this situation. The optimization of decision making in the presence of uncertainty over time is referred to as stochastic programming. This paper proposes a stochastic programming model to solve the financial optimization problem. This model is essentially proposed to replace the deterministic model, in which unknown coefficients or parameters are assumed to be random with the assumption that the probability distribution is free of decision variables. [ABSTRACT FROM AUTHOR]

The aim of research was obtained range number of the statistical texture feature of finger nail image that can be feature in classification. This paper consist of three steps such as preprocessing, feature extraction, and group frequency distribution. Preprocessing consist of resize, cropping and grayscaling. Feature extraction is used was statistical texture feature that consist of mean, variance, skewness, kurtosis and entropy. For obtained range number of texture feature, this research used group frequency distribution. The result showed that the range number of mean for normal data is 119 – 126, for prediabetes data is 137-145 and for diabetes data is 127 – 135. In variance, its range number for normal data was about 3802 – 4486, for prediabetes data was about 3734 – 4614 and for diabetes data was about 3175 – 3892. In skewness, its range number for normal data was about 0,8 – 1,02, for prediabetes data was about 1,21 – 1,44 and for diabetes data was about 1,22 – 1,42. And for kurtosis, the range number in normal data around (-0,56) (-0,08), in prediabetes data around (0,44) – (-0,07) and in diabetes data around (-0,24) – 0,31. Whereas in entropy, range number for normal data is 5,46 -5,69, for prediabetes data around 5,39 – 6,07 and for diabetes data around 5,27 – 5,49. In the future works, combination of two features or more in finger nail image could be used as feature for classification. [ABSTRACT FROM AUTHOR]

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries. [ABSTRACT FROM AUTHOR]

On data that are not normally distributed, classical linear regression is developed into the Generalized Linear Model (GLM). One of them is logistic regression which is used for binary discrete data. A different strategy is to consider all variables (response and predictors) to be random observations from the joint probability distribution. A model with dependencies should be used because some factors are dependent. The copula model, one of which is the Gaussian copula, is a popular technique for creating multivariate models with dependencies. The Gaussian copula regression model (GCMR) is a general structure that can be used to model any form of dependent response. The Gaussian copula blends the ease of interpretation of marginal modeling with the flexibility of the dependency structure specification. In this case, the estimated parameter is the regression coefficient and the error is expressed in the dependency structure. The model estimation uses the maximum likelihood method. This paper aims to apply the GCMR model to time series data where the dependent variable is discrete with a binomial distribution. A case study was conducted to see the effect of weather factors on Covid cases in DKI Jakarta. The regression model used is binomial data logistic regression with the dependency structure expressed in the correlation matrix with the assumption that the error is obtained from the ARMA(p,q) process. The dependent variable is the number of Covid-19 cases and the independent variable is the maximum temperature, average temperature and humidity. The data are a daily time series with a range of March 1, 2020 to April 30, 2022. Based on the GCMR model, Maximum temperature, average temperature and Humidity have a significant influence on the number of Covid-19 cases in Jakarta. For this case study, the results show that the GCMR model is better than logistic regression analysis. [ABSTRACT FROM AUTHOR]

In this paper, we study a single server queue with the customer's population is finite. The services are given singly as a well batches of fixed size. The inter arrival times and service times follows different exponential distributions. For this model the system state probabilities are obtained. Also we have obtained the expressions for some system performance measures and some special cases. We have provided some numerical illustrations. [ABSTRACT FROM AUTHOR]

In this paper, an experimental investigation is conducted to examine the electrical conductivity of glass epoxy composites containing graphene and carbon nanofillers. The hand lay-up technique was used to fabricate the GN–glass, MWCN–glass, and GN–MWCN–glass hybrid epoxy composites. The nanofiller weight fraction at 1.5 and 3 wt. % was analysed. The electrical conductivity test was carried out using two-probe methods to evaluate the GN and MWCN nanofiller's contribution to forming conductive networks within the epoxy matrix and glass fibre. The result indicates a higher electrical conductivity value of GN–MWCN–glass hybrid epoxy composites due to hybrid nanofillers incorporation. Field emission scanning electron microscope analyses the nanofiller's dispersion and random distribution in the composites. The good conductivity was related to the better bond formation of the nanofillers with the epoxy matrix. The electrical conductivity results obtained from this study will serve as a basis for investigating the correlation between electrical resistance and strain characteristics in the self-sensing monitoring composite for future research. [ABSTRACT FROM AUTHOR]

This paper deals with obtaining the best estimator for the reliability function of a two-parameter exponential distribution using the Bayesian estimation method under four different loss functions: squared error loss function, precautionary loss function, and entropy loss function. The exponential distribution prior and Gamma distribution have been assumed as the priors for the scale γ and location δ parameters, respectively. In Bayesian estimation, maximum likelihood estimators have been used as the initial estimators for the two unknown parameters, and the Tierney-Kadane approximation has been effectively employed. The estimators were compared using the Monte-Carlo simulation method based on the integral mean squared error (IMSE). [ABSTRACT FROM AUTHOR]

In this paper, we introduce Right Truncated Inverse Gompertz Distribution with two parameters δ and ϑ and we proposes three methods by hybrid Algorithms (Cuckoo Search Algorithm with Moment Method (CSA_MOM), Firefly Algorithm with Moment Method (FA_MOM) and Bee Colony Algorithm with Moment Method (BCA_MOM)) to estimate Survival functions based on the parameters (δ, ϑ) of Right Truncated Inverse Gompertz distribution. The proposed methods are compared to the traditional methods (Moment Method and Maximum Likelihood Estimation) via simulation. The results indicate that (CSA_MOM) algorithm is superior to other algorithms, and then comes (BCA_MOM) algorithm. Both algorithms are superior to the classical methods in all cases discussed. [ABSTRACT FROM AUTHOR]

A Shewhart control chart that used to monitor product quality by modern manufacturing and service organizations based on assumption of normal distribution, and is not appropriate for skewed distribution. In this paper, we propose an X ¯ –chart for monitoring the process variability based on Johnson family to design robust control charts for skewed distribution. The applied study shows that the performance of the proposed control charts when compared before using Johnson transformation have good properties, and efficient control limits and flexible. [ABSTRACT FROM AUTHOR]

Indonesia is the third-largest paddy producer in the world. From 2019 to 2021 total paddy harvested was more than 100 million tonnes. This huge quantity has an inherent by-product, i.e., rice straw, even in a more significant amount. Unfortunately, poor rice straw management causes farmers to treat the waste by open field burning. Monte Carlo simulations were performed to investigate the side effect of the open-burning treatment. This paper also discussed the worth of considering applications of using rice straw that could make rice straw more valuable. The uniform probability distribution was used to deal with the uncertainty of gas emissions generated from the open field burning of rice straw. In this scheme, at the highest estimate, more than 300 million tonnes of CO2 are released into the atmosphere each year when Indonesia does not apply well management of rice straws. Another 8 million tonnes of other emissions CO, (fine) particulate matter, N2O, NOx, CH4, NMHC, and SO2. Those pollutants more harmful to human health and well-being are also released. Transforming rice straw to particle board has great potential due to this application's high demand and value. It is also an environmentally friendly approach since it can potentially reduce deforestation. In conclusion, appropriate treatment of rice straw management will significantly contribute to the sustainable development of Indonesia. [ABSTRACT FROM AUTHOR]

In many fields of science, modelling and analyzing survival rates has shown to be a valuable element of statistical study. This paper aims at proposing the partly-interval censored data into the fixed and time-varying covariates and measure the performances of Exponential survival distribution using mean square error (MSE), mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and standard error. As a result, when dealing the data without censored observations, the exponential distribution significantly fit the simulation data since low values of error measurements appeared when the data included the exact and complete types of simulation. Thus, this study proposed that the uncensored data could be applicable towards the Exponential survival distribution compared to other distributions of survival analysis. [ABSTRACT FROM AUTHOR]

The paper substantiates the need to create an information system for decision support in the development of systems for protecting objects of informatization, analyzes existing such systems in various fields of activity, defines the requirements for the functionality of the system in relation to the field of information security, considers methods for developing models of functioning of protected information systems in conditions of destructive impact on the basis of Bayesian networks, a description of the functioning of a typical module of this model is given, the structures of probabilistic models of the relationship of vulnerabilities, threats to information security, methods and scenarios for their implementation, the formation of measures to protect objects of informatization, the formation and assessment of the risks of incidents and damage from them are considered, clusters are identified the formation of typical information security events, a methodological apparatus is provided for calculating the joint probability distribution of protective and destructive events iy, typical chains of interrelationships of such events have been identified, a mathematical apparatus has been developed for calculating their probabilities, a verbal description of the patterns of their mutual influence is given, and a method is presented for converting quantitative probabilistic values of security indicators of an informatization object into qualitative ones, and the results of the study are summarized. [ABSTRACT FROM AUTHOR]

Value Stream Mapping (VSM) is one of the most used lean manufacturing methods for determining cycle time (CT) and lead time (LT) in the process flow from customer order to shipment. Value-added (VAA) and non-value added (NVAA) events in the flow must be defined and noted in the VSM. However, there are only a few studies that take risk management into account when calculating lead times. Variable VSM (V-VSM) will be used in this report, with (minimum, most-likely(mean), maximum) values for each CT/LT and Risk Assessment-Failure Mode and Effect Analysis (RA-FMEA) for all risks reported. For a more accurate result, the model will be simulated using Monte Carlo simulation with @Risk software. Prior to the simulation, each process must be described by the best-fit probability distribution. The (minimum, most-likely(mean), maximum) time values of total CT/LT and Risk that the management should consider when preparing the raw material order, VAA/NVAA activities in the production line, Work in Progress (WIP), process layout and shipment schedule are the results of this analysis. For management, the current and future VSMs could be finalized, displaying all relevant variables. This model will be tested in a small and medium food manufacturing facility that produces mixed powder drinks. However, the emphasis of this paper will be on the Monte Carlo simulation using @ Risk software based on V-VSM and RA-FMEA model created. [ABSTRACT FROM AUTHOR]

The paper proposes a method for testing of numerical schemes used to solve the Vlasov equation, a collisionless kinetic equation. The method is based on comparing numerical data with exact analytical solutions and control of the behavior of the second-order moments of the distribution function. An efficient software implementation on Tensor Processor Units (TPUs) for calculating the moments is described. The results of test computations of the dynamics of a rotating and pulsating infinitely thin disk in an external field are presented; the computations have been performed using a multidimensional semi-Lagrangian method with both the conservative WENO and linear upwind schemes of the 5th order. [ABSTRACT FROM AUTHOR]

This paper examines the performance of shrimp supply chain coordination under buy-back policies while the market demand is stochastic and price-dependent. Three shrimp supply chain models comprising of centralized supply chain, conventional decentralized supply chain, and decentralized chain using buy-back contract are compared the expected profit each other by specific theories about parameters and variables. The mathematical theorems with probability distribution and supply chain theories are applied to determine the optimal expected profit, order quantity, and acquisition pricing. A numerical study in Ca Mau Province, Vietnam is studied for demonstrating the efficiency of model. The outcome revealed that the coordination of shrimp supply chain integrated with buy-back contract is more optimal than the conventional decentralized supply chain. [ABSTRACT FROM AUTHOR]

One of the few goals of statistical modeling is to see and analyze the probability of an event which can be represented with data. A probability distribution that is used for modeling data should have some abilities such as flexibility for modeling different kinds of data. Therefore, modeling data is of great importance. Furthermore, insurance companies also need to model data, which in this case is called modeling claim data. Modeling the claims distribution has its own challenge (e.g. skewed and heavy tailed) since most of the claim distributions are different from any classical distributions, therefore researchers are trying to find new models that can fit insurance data better. In this paper, a composite Exponential-Pareto distribution was proposed and introduced. This distribution is equal, but not equivalent to, an exponential density up to a certain threshold value, and a Pareto type-I density for the rest of the model. When being compared with the exponential distribution, the emerging density has a similar shape and a larger tail, and while being compared with the Pareto distribution, the emerging density has a smaller tail. A method to develop a composite distribution is called as composite parametric modeling, which introduced by Cooray and Ananda (2005). In this model, both the exponential distribution and the Pareto type-I distribution have the same weight. Based on the result, composite Exponential-Pareto distribution has some limitations, which are likely to severely diminish its potential for practical applications to real world insurance data. In order to address these issues, there are two different composite Exponential-Pareto distributions based on exponential and Pareto type-I distributions in order to address these concerns. These two different composite Exponential-Pareto distributions are based on the two-component mixture model introduced by Scollnik (2007). The first distribution, which is a reinterpreted composite Exponential-Pareto distribution from the first composite Exponential-Pareto distribution based on the two-component mixture model, has a fixed mixing weight. Meanwhile, the second distribution is a composite Exponential-Pareto distribution with a mixing weight that is not fixed so the distribution can be more flexible and can model different kinds of data. These three composite Exponential-Pareto distributions has k-th raw-moment that only defined for some k > 0. Therefore, this distribution can be categorized as a heavy-tail distribution. The result of this research is a composite distribution that could model a lot of data with characteristics such as unimodal, right-skewed, and heavy-tail because the composite distribution has similar characteristics. A data illustration was presented as a demonstration for how to implement the composite Exponential-Pareto distribution. [ABSTRACT FROM AUTHOR]

We consider the problem of modeling the process of determining the distribution function of temperature and time varying structure of homogeneous bar of a given law changes in the average temperature. So there is an inverse problem for the heat equation in which together with finding the solution of the equation it is required to find unknown coefficient depending only on the time variable. The specific features of the considered problems is that the system of eigenfunctions of the multiple differentiation operator subject to boundary conditions of the initial problem does not have the basis property. In this paper, it is proved that this inverse problem has a unique generalized solution. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019, also known as Covid-19, is an infectious disease that has infected more than nineteen million people all around the world. This virus is a member of coronavirus family but it is the most mortal one. It has named as 2019-nCoV by World Health Organization(WHO) after Chinese Center for Disease Control and Prevention(CDC) discovered a new coronavirus from a swab sample of a patient. As we know this pandemic started December 2019 in China, and it is still spreading and causing deaths all around the world. In this paper, we aimed to estimate the right size of epidemic. For that purpose, we chose 10 countries, which are affected by, and still fighting with this disease, to forecast the upcoming death rates by using the previous week deaths. These 10 countries are Argentina, Austria, Brazil, France, Iran, Italy, Sweden, Turkey, United Kingdom, and United States of America. We used the death data of WHO with assumption that data is accurate. For this estimation, firstly, we used the assumption that the reported death delay distributed according to a gamma distribution. Then, we used a binomial distribution for assumption of deaths. This binomial formula led us to find a posterior distribution which is an extension of Bayes' theorem for death ratio. Lastly, we compared our estimations with real data. [ABSTRACT FROM AUTHOR]

We compare the results of two models for the breakup of ejecta particles for a simple test problem. We conclude that while they operate in significantly different manners, their overall results are quite comparable. We note that the χ2 distribution function widely used in particle breakup modelling is not in fact consistent with the distribution proposed by Hiroyasu & Kadota based on their original experiments, which may resolve the disagreement in particle radius distributions observed in subsequent work. This paper is UK Ministry of Defence © Crown Owned Copyright 2020/AWE. [ABSTRACT FROM AUTHOR]

Kinetic Alfven wave has been studied in superthermal plasma in both cases (warm and cold electron limit) in plasma sheet boundary layer. The effect of velocity distribution function (VDF) that exhibit a power law dependence on the high- energy tail and known as superthermal or kappa distribution, have been found to provide a better fitting to the VDF measured by several spacecraft in the plasma environment and is the key subject of this paper. Kinetic effects of electrons and ions are included to study kinetic Alfven wave because both are important in the transition region. In this work we introduce a mathematical formalism that provide expressions for dispersion relations for oblique propagating kinetic Alfven waves resulting from a kappa VDF. The effect of kappa index and thermal corrections on the dispersion relations of KAW is discussed. The method may be suitable to deal with the PSBL, where particle acceleration is also important along with wave emissions. [ABSTRACT FROM AUTHOR]

Classifying applicants with good credit risk is essential for developing the banking industry in the future. On the other hand, applicants with bad risk can certainly make banks, as financial institutions provide credit, experience difficulties. The opportunity for bad credit risk can be great if the credit application acceptance system misclassifies applicants with a bad risk. This paper aims to investigate two statistical learning models to classify applicants who have good credit risk reliably; multinomial naïve Bayes and decision tree ID3. These nonparametric models require that all predictor variables are of categorical type. The proposed strategy discretizes the numeric type variables using the Sturges frequency distribution table. The results, validated using k-fold cross-validation resampling methods, showed that the strategy is very appropriate, especially in the ID3 decision tree model, because it produces a classification with performance measures greater than 90% for accuracy and sensitivity, precision, and F1-score. Only the specificity is 83.23%. However, sensitivity as a performance measure that prioritizes credit risk has a value of almost 100%, namely 99.87%. The multinomial naive Bayes method also has good performance. All performance measures have a greater than 85% value, and only specificity is below 85%. These performance measures indicate that the ID3 decision tree method is better than the multinomial naive Bayes method for classifying credit risk. [ABSTRACT FROM AUTHOR]

The paper is devoted to the construction of the efficient numerical methods to solve model kinetic equations as applied to the pulsed laser ablation (evaporation) into vacuum. We briefly describe the general ALE-type discrete velocity method and outline the modifications required for the present study. Then, we compute a particular moderate-intensity flow using Nesvetay code and compare the results for time-of-flight distributions and average axial energies with those of the DSMC code LasInEx. An accurate calculation of these quantities involves integration of the velocity distribution function in very narrow conical parts of the molecular velocity space and therefore requires the usage of a specially constructed mixed-element unstructured velocity mesh. Good agreement confirms the robustness and accuracy of the proposed discrete velocity approach. [ABSTRACT FROM AUTHOR]

In the current paper we compare numerical results obtained with the model kinetic equations and the Boltzmann transport equation. The classical problem of shock wave internal structure is solved with a deterministic solver implemented on a multi-GPU cluster. The Boltzmann collision integral is calculated using a conservative interpolation scheme along with special quadrature formulas, a correction procedure for distribution functions close to the Maxwellian distribution and an adaptive algorithm of node selection. Numerical simulations are performed for a single-species gas at the shock wave Mach numbers M = 1.5 and 8 and for a binary mixture at M = 1.5. [ABSTRACT FROM AUTHOR]

The knowledge of the absolute positioning accuracy of a robotic arm is crucial to assess the feasibility of certain tasks. In evaluating the feasibility, a robot manipulator as well as a possibly external sensing system must be chosen. In choosing a robot arm, lightweight robots are often preferred because they require less safety precautions, but they can also be less accurate compared to a stiff industrial robot. A stiff industrial robot resists external loads better, resulting in a higher accuracy with payload or process forces, and oscillates less in motions. Additionally, typical robot inaccuracies must be considered: (i) absolute positioning errors due to kinematic model errors, (ii) error due to resonance or external forces, (iii) path-following errors from limitations in the dynamic model and control. For tasks where the goal object has an unknown or varying pose, its pose can be measured with a vision system and used to compensate the robot motion. When the measurement and compensation is done continuously, it realizes closed-loop visual servoing. This can reduce the absolute error, but only the components of the error which are of a low frequency relative to the motion control bandwidth of the robot. To evaluate whether a specific robot can meet a certain accuracy requirements with a visual servoing system, better understanding about the characteristics of the robot error is needed. For example, the frequency distribution of the robot error can indicate what proportion can be compensated with closed loop control – only that less than the position bandwidth of the robot (typically 3-7 Hz). Datasheets typically provide the accuracy value only for repeatability while the accuracy during motion and the influence of dynamic effects are ignored. If the endeffector oscillates during motion causing a positional error and at which frequency is typically not reported – leaving unanswered, if it can be compensated by control. The contribution of this paper is the experimental evaluation of an absolute accuracy during the robot motion, towards evaluating the accuracy with a visual servoing system. A tracker system is used to collect the motion data of a CNC milling machine, a Universal Robots UR5, and an industrial robot (Comau Racer7-1.4) under various motion speeds. The frequency distribution and histograms of the error are analysed with regard to possible sources and the suitability to reduction with visual servoing. [ABSTRACT FROM AUTHOR]

The paper considers the method of drawing up a model of the distribution of the duration of standing of the parameters of the external climate during the probably possible year. The method is based on the formation of an array of data based on possible hourly values of the parameters of the external climate and the presentation of discrete distributions of the duration of the combination of temperatures and relative humidity of the outside air in certain intervals of their values in the form of integral characteristics. The latter are represented by a system of mathematical functions, which in turn are generalized into one equation representing a mathematical model of the distribution of the duration of standing of a combination of given values of climate parameters. The proposed method can be implemented for any geographical point, in the presence of statistical distributions of climate parameters of the standard type. The model of distribution of parameters of the external air can be useful for the analysis of operation of systems of creation of microclimate of buildings in order to choose the rational technological scheme and modes of operation. [ABSTRACT FROM AUTHOR]

This paper presents an analytical solution for the growth of an ensemble of ellipsoidal particles and shows the difference in growth rate, supersaturation, and nucleation time for ellipsoidal and spherical crystals. The growth rate for an individual crystal evolving in a supersaturated solution is derived in the ellipsoidal reference frame. The kinetic and balance equations for the particle-volume distribution function and system supersaturation are solved analytically using the saddle-point method for a Laplace-type integral. [ABSTRACT FROM AUTHOR]

The focus is on random errors that occur when measuring height with an atomic force microscope. By repeating the height measurement, the probability distribution of random errors was obtained. From the width of the distribution function, the uncertainty of the height measurement was determined. The paper also describes the details of the measurement. [ABSTRACT FROM AUTHOR]

This paper deals with survey of the Dagum Distribution. Recently, this distribution has been used to model to the lifetime datas taken from various datasets. In this paper, we give some observation on the model for the life time. We also analyze our survey results using data year 2015 from TurkStat which is so-called "Turkish Statistical Institute". [ABSTRACT FROM AUTHOR]