Stochastic Analysis Method Research Articles

The stochastic frontier analysis technique in measuring the technical and economic efficiency of hospital diagnostic laboratories: a case study in Iran

An inefficient health system wastes scarce resources even if it makes considerable gains in accountability and equity. Such a system is expected to perform better. Therefore, it is vital to examine the current performance of health systems and their constituents and assess how to reach their maximum potential. This study aimed to evaluate the technical and economic efficiency of medical diagnostic laboratories in hospitals affiliated with Urmia University of Medical Sciences (UUMS) in 2016. In this descriptive-analytical study, data from diagnostic laboratories of the hospitals of UUMS have been inputted into Frontier4.1 software after taking the log of variables. Then, the technical and economic efficiency of the laboratories were obtained by estimating the production and cost function using the stochastic frontier analysis method, assuming input minimization for 2016. The mean technical and economic efficiency score of the diagnostic laboratories were determined to be 93.1% and 51.9%, respectively. These laboratories need to reduce their inputs and costs in order to achieve full efficiency without changing the amount of their output. Although the average economic efficiency of the diagnostic laboratories of the studied hospitals was high, there is still an increase in the efficiency of these units, given the cost of inputs at the time of allocating resources. In addition, it is possible to improve the technical efficiency of the clinical laboratories of hospitals affiliated with UUMS by 48.1% by applying the same level of inputs and without increasing the costs.

Statistical Descriptions of Inhomogeneous Anisotropic Turbulence

Descriptions are given of the Langevin and diffusion equation of passively marked fluid particles in turbulent flow with spatially varying and anisotropic statistical properties. The descriptions consist of the first two terms of an expansion in powers of C0−1, where C0 is an autonomous Lagrangian-based Kolmogorov constant: C0≈7. Solutions involve the application of methods of stochastic analysis while complying with the basic laws of physics. The Lagrangian-based descriptions are converted into Eulerian-based fixed-point expressions through asymptotic matching. This leads to novel descriptions for the mean values of the fluctuating convective terms of the conservation laws of continua. They can be directly implemented in CFD codes for calculating fluid flows in engineering and environmental analysis. The solutions are verified in detail through comparison with direct numerical simulations of turbulent channel flows at large Reynolds numbers.

ANALISIS PERHITUNGAN POTENSI PAJAK DAERAH KABUPATEN/KOTA DENGAN METODA STOCHASTIC FRONTIER ANALYSIS (SFA)

To increase local tax revenues, the initial steps that need to be done by local governments is to estimate their local tax potential. By using the Stochastic Frontier Analysis (SFA) method, this study tries to: (1) estimates local tax potential from each region/city and answer the question (2) have each of the regions reached its maximum potential? The results of this study aim to provide an alternative model/method of calculating the local taxes potential for a local government. In addition, for the central government, the local tax potential figures will be used as the fiscal capacity component instead of revenues realization in General Allocation Fund (DAU) formulation. The results from the SFA method are: (1) from the 504 local governments, on average, the Actual Tax Ratio (TRA) is 0.37%, while the Potential Tax Ratio (TRP) is 0.48 %. So only about 73.31% of local tax potential can be collected by the local governments. (2) The majority of the top ten ranked local governments that have the largest TRP, are local governments with an urban character and tourist areas, with a TRA range between 1.48% to 6.72%, and a TRP between 1.78% to 7.66%. So that the local tax potential that has been collected is about 80%. (3) On the bottom rank regions that have the lowest TRP, 8 out of 10 local governments are located in Papua with TRA ranges between 0.01% to 0.06% and TRP between 0.02% to 0.11%. So that the local tax potential that has been collected is in the range of 32% to 83%.

Evaluation of water-user performance in smallholder irrigation schemes in KwaZulu-Natal Province, South Africa: A stochastic meta-frontier analysis

Smallholder Irrigation Schemes (SIS) are pivotal in sustaining livelihoods and creating employment in rural communities of South Africa. However, despite the revitalization and rehabilitation of SIS by the government, the performance of farmers is still below par. This study evaluates the performance of water-users across four SIS in KwaZulu-Natal Province (KZN). Technical Efficiency was used as a proxy for performance and the Stochastic Meta-Frontier Analysis method was employed to measure the overall efficiency across 306 households. The efficiency model results showed that governance index, psychological capital, land tenure security, credit access and gender affect water-users' technical efficiency. The study concludes that interventions should be geared toward strengthening institutions and the empowerment of farmers through relevant training and access to credit. Furthermore, adequacy of water and its availability in the schemes should be improved to ensure profitability and productivity of water.

Effect of Speed of Adjustments on Capital Structure Decision: A Conceptual Analysis

This study conceptually examines the effect of speed of adjustments on capital structure decisions. The study provides a conceptual and theoretical underpinning focused on the review of several studies on the effect of speed of adjustments on capital structure decisions. The study discovered firm size, assets, growth, profitability, and other factors that influence the speed of adjustments. The findings from a prior study showed that estimators of the speed of adjustments include the regression analysis, generalized methods of moments (GMM) and stochastic frontier analysis (SFA) models without a predictive model. The study recommends for a generalized predictive model that determines the speed of adjustments to the optimum capital structure of firms.

Group decision making with hesitant fuzzy linguistic preference relations based on multiplicative DEA cross-efficiency and stochastic acceptability analysis

The aim of this paper is to investigate a novel approach to group decision making (GDM) based on multiplicative DEA cross-efficiency and stochastic acceptability analysis with hesitant fuzzy linguistic preference relations (HFLPRs), which can avoid information distortion and obtain more credible decision-making results. First, a transform function is defined, which can extract effective information of the hesitant fuzzy linguistic term set (HFLTS) sufficiently. Then, an optimization model is proposed to derive the occurring probabilities of the elements in the HFLTS. It can avoid the normalization process of HFLPRs and simulate the element-selection process of decision makers (DMs). Moreover, a Maximum Log DEA Cross Efficiency model is proposed to evaluate the relative efficiency of each alternative from HFLPR. We further develop the stochastic weight space acceptability analysis method to solve the GDM problem and a step-by-step procedure is presented. Finally, numerical examples are given to illustrate the validity and applicability of the proposed method. This is the first attempt of employing the multiplicative DEA cross-efficiency to the GDM with HFLPRs.

Uncertainty Propagation of Fission Product Yields from Uranium and Plutonium in Pebble-Bed HTGR Burnup Calculation

Quantifying fission product yield uncertainty contribution to reactor burnup calculation is an important aspect of pebble-bed High Temperature Gas-cooled Reactor (pebble-bed HTGR) uncertainty analysis. In this work, uncertainty propagation of fission product yield to pebble-bed HTGR burnup calculation is conducted. Uncertainty of fission product yields from four fissile isotopes, namely 233U, 235U, 239Pu and 241Pu, are considered. The stochastic sampling-based uncertainty analysis method is adopted and fission product yield covariance matrices are estimated from ENDF/B-VII.1. The covariance matrix for each fissile actinide is estimated based on the Bayesian method and fission product yields are assigned with log-normal distribution in the sampling process with the Latin Hypercube Sampling (LHS) method. Since the fission fraction from 239Pu plays an important role in fissions of fuels with high burnup value in pebble-bed HTGR, the fission product yield uncertainty contribution from 239Pu is highlighted in this work. The result shows that, in the burnup equilibrium state of pebble-bed HTGR, fission product yield uncertainty contributions from 235U and 239Pu to relative uncertainty of keff are 0.027% and 0.026%, respectively. The overall uncertainty contribution from four fissile isotopes (233U, 235U, 239Pu and 241Pu) to relative uncertainty of equilibrium core keff is 0.038%. Furthermore, fission product yield uncertainty has an important contribution to the nuclide density uncertainty of fission products. The most relative uncertainty, 10.82%, is observed in 109Ag contributed from the fission product yield uncertainty of 239Pu at the burnup equilibrium state. This indicates the uncertainty contribution from the fission product yield of 239Pu cannot be neglected in pebble-bed HTGR burnup uncertainty analysis.

Investigating influencing factors of regional healthcare efficiency: a case study of China

ABSTRACT Healthcare as a kind of service is closely related to human health, but its uneven distribution among regions could affect the equity of residents’ access to the service and lead to the unbalanced development of healthcare levels. Therefore, this article establishes an integrated model by means of the stochastic frontier analysis method to evaluate regional healthcare efficiency and analyse its influencing factors. Specifically, the distribution and change trend of healthcare technical output (TO) efficiency and health output (HO) efficiency are investigated from the temporal and spatial perspectives, and then the influencing factors of the two types of healthcare efficiency are explored, respectively. Taking China as a case study, the results show that there are obvious regional differences in TO efficiency as a whole, where the values of the eastern and central regions are significantly higher, while the western and northeast regions have lower TO efficiency. Economic, social, and regional factors have a significant influence on both TO efficiency and HO efficiency, among which the impacts of population density on the two types of efficiency are opposite. Accordingly, some policy recommendations have been put forward for improving regional healthcare efficiency.

Nonfragile Dissipative Fuzzy PID Control With Mixed Fading Measurements

This article is concerned with the extended dissipative fuzzy proportional–integral–derivative (PID) control problem for nonlinear systems subject to controller parameter perturbations over a class of mixed fading channels. The sensors of plant are divided into two groups according to engineering practice, where the individual sensor group transmits the measurements to the controller via a respective communication channel undergoing specific fading effects. Considering the complicated nature of the signal fading with the transmission channels, two stochastic models (i.e., the independent and identically distributed fading model and the Markov fading model) are simultaneously employed to describe the mixed fading effects of the two communication channels corresponding to the two sensor groups. The objective of this article is to design a nonfragile PID controller such that the closed-loop system is exponentially stable in mean square and extended stochastically dissipative. With the assistance of the Lyapunov stability theory and stochastic analysis method, sufficient conditions are obtained to analyze the system performance. Then, within the established theoretical framework, an iterative optimization algorithm is proposed to design the desired controller parameters by using the convex optimization technique. Finally, two simulation examples are given to verify the effectiveness of the proposed control schemes.

Whether tough environmental regulatory measures can play a dominant role? Evidence from private enterprises in China

Based on the two-tier stochastic frontier analysis method, this paper constructs a basic model to analyze the environmental treatment investment of enterprises, and discusses the influence of the gambling power between enterprises and governments on the input of environmental pollution control. The data in this paper are from the Chinese Private Enterprise Survey (CPES). And empirical results show that the gambling power between enterprises and government affects the investment of pollution control to a great extent. The influence proportion of the gambling power of the enterprise on the investment of environmental pollution control is 84.44%, which is much higher than that of the government (15.56%). The enterprise is the executor with more real information, and can even reduce the investment of pollution control by concealing its actual situation and so on, hence the enterprise occupies the initiative in the game process. Although enterprises are still in the dominant position in the game, their advantages are continually shrinking. With the expansion of the scale of the enterprise and the high level of entrepreneur education, the game advantage of the enterprise is continuously decreasing.

Entrepreneurship and innovation efficiency: the moderating role of absorptive capacity

PurposeThis study aims to investigate the relationship between entrepreneurship and innovation efficiency (IE), as well as the moderating role of absorptive capacity.Design/methodology/approachThis study uses a sample of industrial enterprises from Chinese provinces from 2005 to 2016, and it tests the research questions using the method of stochastic frontier analysis.FindingsThe results of this study indicate that entrepreneurship promotes IE, and that absorptive capacity plays a positive moderating role. In addition, the effect of entrepreneurship on IE differs between the central and eastern regions and the western region.Originality/valueThis research provides direct policy implications by demonstrating the role of entrepreneurship and absorptive capacity in IE, thereby guiding corporate management practices and the formulation of government innovation and entrepreneurship policies.

Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty

Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty

Measuring Financial Efficiency of Insurance Companies in Indonesia Using Stochastic Frontier Analysis Approach

This paper aims to analyze the efficiency value and compare the efficiency ratio between sharia insurance and conventional insurance companies, both life insurance and general insurance in Indonesia, for 2018-2020. The research applies the Stochastic Frontier Analysis (SFA) method, which uses total capital and expenses as input variables, and total income as output variables. The efficiency values of Islamic and conventional insurance companies' results were compared using an independent sample t-test statistical test. The population of this research is all Islamic and conventional insurance companies listed on the website of the Financial Services Authority (OJK). The sample used is 19 sharia insurance companies (15 life insurance companies and four general insurance companies). The sample of conventional insurance is 23 companies (22 life insurance companies and one general insurance company). The results showed that the efficiency value of Islamic insurance companies (0.6549) was 0.0697 lower than conventional insurance (0.7246). It can be concluded that the efficiency of conventional insurance is better than Islamic insurance. Islamic insurance management capabilities are lower than conventional insurance companies’ management capabilities.

A new method for stochastic analysis of structures under limited observations

Reasonable modeling of non-Gaussian system inputs from limited observations and efficient propagation of system response are of great significance in uncertain analysis of real engineering problems. In this paper, we develop a new method for the construction of non-Gaussian random model and associated propagation of response under limited observations. Our method firstly develops a new kernel density estimation-based (KDE-based) random model based on Karhunen-Loeve (KL) expansion of observations of uncertain parameters. By further implementing the arbitrary polynomial chaos (aPC) formulation on KL vector with dependent measure, the associated aPC-based response propagation is then developed. In our method, the developed KDE-based model can accurately represent the input parameters from limited observations as the new KDE of KL vector can incorporate the inherent relation between marginals of input parameters and distribution of univariate KL variables. In addition, the aPC formulation can be effectively determined for uncertain analysis by virtue of the mixture representation of the developed KDE of KL vector. Furthermore, the system response can be propagated in a stable and accurate way with the developed D-optimal weighted regression method by the equivalence between the distribution of underlying aPC variables and that of KL vector. In this way, the current work provides an effective framework for the reasonable stochastic modeling and efficient response propagation of real-life engineering systems with limited observations. Two numerical examples, including the analysis of structures subjected to random seismic ground motion, are presented to highlight the effectiveness of the proposed method.

A new stochastic residual error based homotopy approach for stability analysis of structures with large fluctuation of random parameters

AbstractThe large fluctuation of uncertain parameters introduces a great challenge in the stability analysis of structures. To address this problem, a novel stochastic residual error based homotopy method is proposed in this article. This new method used the concept of homotopy to reconstruct a new governing equation for stochastic elastic buckling analysis, and the closed‐form solutions of the isolated buckling eigenvalues and eigenvectors are obtained by the stochastic homotopy analysis method. On this basis, apth order origin moment of the stochastic residual error with respect to the elastic buckling equation is defined. Then, the optimal form of the homotopy series can be determined automatically by minimizing thepth order origin moment, which overcomes the disadvantage of highly relying on sample values of the existing homotopy stochastic finite element method. Moreover, the proposed method is developed to deal with the stochastic closely spaced buckling eigenvalue problem. Three mathematical examples and three buckling eigenvalue examples, including a variable cross‐section column, a 7‐story frame, and a Kiewitt single‐layer latticed spherical shell, are performed to illustrate the accuracy and effectiveness of the proposed method by comparing with the existing methods when dealing with large fluctuation of random parameters.

How local outbreak of COVID-19 affect the risk of internet public opinion: A Chinese social media case study

Motivated by the realistic demand of controlling the Internet public opinion risk caused by the local outbreak of COVID-19, this paper creatively proposes a COVID-19 local outbreak Internet public opinion risk grading research framework. The SMAA-FAHPSort II method combining Analytic Hierarchy Process Sort II (AHPSort II) method with Stochastic Multicriteria Acceptability Analysis (SMAA-2) method is introduced into this framework, to evaluate the Internet public opinion risk level of social media during the local outbreak of COVID-19. In addition, this framework is applied to a case of Internet public opinion risk evaluation on Microblog platform of China. According to the number of new cases per day in mainland China, this paper divides the period from May 7, 2020 to September 3, 2021 into seven stages. A total of more than 10,000 Microblog hot topics were collected, after screening and preprocessing, 5422 related topics are remained to help complete the Internet public opinion risk evaluation. The case study analysis results show that the number of days classified as moderate risk and above has reached more than 280. This proves that the local outbreak of COVID-19 will indeed increase the risk of Internet public opinion, and correlation analysis confirms that the level of public opinion risk is positively correlated with the severity of the epidemic in the real world. Furthermore, the effectiveness and advantages of the proposed method are verified by comparative analysis and sensitivity analysis. Finally, some effective public opinion management suggestions have been put forward. This paper can provide reference for the government to formulate or improve relevant strategies, and also has great significance for reducing the risk of Internet public opinion in social media.

Effect of antitrust on innovative development with a different degree of intellectual property protection

Intellectual property is often referred to as a “legal monopoly”, which should stimulate the innovative activity of authors and inventors. In this formulation, increased antitrust regulation should always have a negative effect on the innovation industry, since it is aimed at reducing the companies’ profits, and therefore, other things being equal, reducing the innovation incentives. The paper reveals the conditions under which this statement can be true, and under which, on the contrary, the strengthening of antimonopoly regulation leads to an increase in innovative output. Using cross-country data, an empirical assessment of the mutual influence of the effectiveness of antimonopoly regulation and the degree of protection of intellectual property rights on the efficiency of the innovation sector and the economy are obtained. As an indicator of relative efficiency the paper considers the proximity to the production possibilities frontier, determined by the stochastic frontier analysis (SFA) method. As a result, the hypothesis for the complementary nature of the influence of both policies is confirmed: the strengthening of one gives a positive result only when the other is strong. The complementary nature of policies can be related to the following aspects. In the context of weak IP right protection, right holders are extensively using alternative mechanisms for the specification of property rights, which includes business practices that are controversial from the antitrust point of view. In such a case, strengthening the severity of antimonopoly regulation increases the costs of such practices and ultimately reduces the effectiveness of the intellectual property protection reducing output in the innovation industry. This result justifies the existence of exceptions for the IP owners, which could be present in the antimonopoly legislation in countries with a low level of IP rights protection. But as the effectiveness of the IP rights protection becomes stronger, such exceptions can be canceled. This result also shows that the notion of IP as a “legal monopoly” is overly simplistic and can lead to risks of Type I enforcement errors (punishing the innocent).

Intelligent meta-model construction and global stochastic sensitivity analysis based on PSO-CNN

A large-scale simulation model is needed for the stochastic sensitivity analysis of structural uncertainty. The finite element method often exceeds the computing power and cannot meet the analysis requirements and computational efficiency of stochastic sensitivity analysis. With the development of artificial intelligence, the calculation efficiency problem can be solved by a combination of the finite element model and a mathematical model, but the accuracy of the analysis results depends on the accuracy of the mathematical model. However, using artificial neural networks to construct mathematical models also has numerous problems, such as falling into local extrema. Thus, to address the computational efficiency and calculation accuracy problems, the particle swarm optimization (PSO)-convolutional neural network (CNN) meta-model is presented in this paper. This model was used to improve the training and prediction accuracy of a small-sample CNN, where the initial learning rate of the CNN was optimized by PSO. Additionally, the PSO was combined with the Adam optimizer to automatically screen the optimal network structure. The global stochastic sensitivity analysis method based on the Sobol sensitivity method and the Monte Carlo method was used to quantify the degree of influence of the input parameters on the model output parameters and to analyze the influence trend of the parameter changes on the structural response combined with the positive and negative Spearman’s rank correlation coefficients. The accuracy, good adaptability, and extension ability of the PSO-CNN meta-model was verified using the high-dimensional function examples and the structural models. Global stochastic sensitivity analysis was carried out on the joint of an extended end plate. The influence degree of the parameters on the initial rotational stiffness of the joint was determined, and corresponding design suggestions were obtained. These suggestions were consistent with the design specifications and the research results of other scholars, which verified the reliability of this method and could be applied to other types of structural sensitivity analyses.

Security-Based Resilient Robust Model Predictive Control for Polytopic Uncertain Systems Subject to Deception Attacks and RR Protocol

This article is concerned with the security-based resilient robust model predictive control (RMPC) problem for a class of discrete-time polytopic uncertain systems with deception attacks and the round-robin (RR) protocol. The well-known RR protocol is adopted with the hope to reduce the communication burden, where the control signal is transmitted only at the given transmission instant. By means of the concept of bounded energy and the independent Bernoulli-distributed (BD) white sequences, a representative attack model is given. A definition of mean-square (MS) security in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -sense is employed to reasonably explain the dynamics process of the controlled systems. We aim at designing a set of resilient RMPC controllers so as to make the closed-loop system state under consideration of deception attacks and the RR protocol enter and stay in a certain bounded region. Furthermore, with the aid of stochastic analysis methods and inequality analysis techniques, sufficient conditions are obtained to satisfy the desirable security requirements. To tackle the nonconvex obstacles resulting from attacks and the RR protocol, the cone complementary linearization (CCL) method is exploited to cast them into a convex optimization problem (OP) for its solvability. Then, an online OP regarding a certain upper bound of the concerned objective is provided for the solvability and resilient RMPC-based controller gains are obtained. Finally, two examples, including a high-purity distillation one and a numerical one, are used to demonstrate the effectiveness and the validity of the proposed techniques.

Machine Learning Based Developing Flow Control Technique Over Circular Cylinders

Abstract This paper demonstrates the feasibility of blowing and suction for flow control based on the computational fluid dynamics (CFD) simulations at a low Reynolds number flows. The effects of blowing and suction position, and the blowing and suction mass flowrate, and on the flow control are presented in this paper. The optimal conditions for suppressing the wake of the cylinder are investigated by examining the flow separation and the near wake region; analyzing the aerodynamic force (lift and drag) fluctuations using the fast Fourier transform (FFT) to separate the effects of small-scale turbulent structures in the wake region. A method for stochastic analysis using machine learning techniques is proposed. Three different novel machine learning methods were applied to CFD results to predict the variation in drag coefficient due to the vortex shedding. Although, the prediction power of all the methods utilized is in the acceptable accuracy range, the Gaussian process regression (GPR) method is more accurate with an R2(coefficient of determination) &amp;gt; 0.95. The results indicate that by optimizing the blowing and suction parameters like mass flowrate, slot location, and the slot configuration, up to 20% reduction can be achieved in the drag coefficient.