Background :The cotton factories have difference steps, spinning and weaving are van important parts of the factories. Cotton industry workers are exposed to various hazards in the different departments of textile factories. The major health problems associated with cotton dust are respiratory problems. Cotton workers display an excess of lung function abnormalities when compared to a community control population.
Aim of Study: This study assessed the effect of exposure to cotton dust in spinning and weaving workers on the lung function in Iraq, by measuring Forced Vital Capacity (FVC),Forced Expiratory Volume in the first second(FEV1), FEV1 ∕ FVC Ratio, and Forced Expiratory Flow 50%(FEF50%),with varying degree of reduction in lung function.
Methods:151 workers exposed to cotton dust were enrolled in the study, and 100 non exposed workers were selected as control. The age of the workers ranged between 20 to 60 years. Both groups were smokers and non smokers, has no chronic pulmonary disease or symptoms during the time of the study. Sprometric study was used for measuring the lung function.
Results: Statistically significant reduction in FEV1and FEF50%were found in exposed workers when compared to control. Lung function indices were not affected with increasing duration of exposure to cotton dust nor to smoking.
Conclusion: Exposure to cotton dust in spinning and weaving workers may result in reduction in the pulmonary function and may lead to respiratory diseases. So improvement in protective measures is recommended.
In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application
The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (Mbias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial
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Health service institutions suffer from challenges resulting from the great changes that our world is witnessing today. This has affected the value that these institutions add to the patient.
This research aims to identify the effect of integrating each of the techniques of QFD and value engineering for the health services provided to the patient to improve the value for him and thus obtain his satisfaction, which is reflected in the reputation of the surveyed hospitals. To achieve this, the descriptive analytical method was used, and a questionnaire was designed to collect the necessary data, which represents a measure of this research. The questionnaire was distri
... Show MoreIn this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes
This paper discusses reliability R of the (2+1) Cascade model of inverse Weibull distribution. Reliability is to be found when strength-stress distributed is inverse Weibull random variables with unknown scale parameter and known shape parameter. Six estimation methods (Maximum likelihood, Moment, Least Square, Weighted Least Square, Regression and Percentile) are used to estimate reliability. There is a comparison between six different estimation methods by the simulation study by MATLAB 2016, using two statistical criteria Mean square error and Mean Absolute Percentage Error, where it is found that best estimator between the six estimators is Maximum likelihood estimation method.
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Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
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Critical buckling temperature of laminated plate under thermal load varied linearly along the thickness, is developed using a higher-order shape function which depends on a parameter ‘‘m’’, which is improved to obtain results for thin and thick plates. Laminated plates’ equations of motion are obtained using virtual work principle and solved for simply supported boundary conditions. Angle and cross laminates thermal buckled mode shapes with different E1/E2 proportion, number of plies, (α2/α1) proportion, aspect ratios, are investigated. It is observed that this shape function gives thermal buckling for thin and thick plates but with m = 0.05 that agree well with other theories and linear distribution of temperature giv
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Survival analysis is the analysis of data that are in the form of times from the origin of time until the occurrence of the end event, and in medical research, the origin of time is the date of registration of the individual or the patient in a study such as clinical trials to compare two types of medicine or more if the endpoint It is the death of the patient or the disappearance of the individual. The data resulting from this process is called survival times. But if the end is not death, the resulting data is called time data until the event. That is, survival analysis is one of the statistical steps and procedures for analyzing data when the adopted variable is time to event and time. It could be d
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This paper presents a hybrid software copy protection scheme, the scheme is applied to
prevent illegal copying of software by produce a license key which is unique and easy to
generate. This work employs the uniqueness of identification of hard disk in personal
computer which can get by software to create a license key after treated with SHA-1 one way
hash function. Two mean measures are used to evaluate the proposed method, complexity
and processing time, SHA-1 can insure the high complexity to deny the hackers for produce
unauthorized copies, many experiments have been executed using different sizes of software
to calculate the consuming time. The measures show high complexity and short execution
time for propos