Furfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentration of furfural decreased, but different H2O2concentrations indicated no significant effects on the reaction rate. UV/H2O2 process is effective for furfural degradation in wastewater at neutral pH where the disposal of such effluents will be within the environmental limitations.
In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.
The method of estimating the distribution parameters for each device was the OLS method.
The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
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Lowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.
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Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas
A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr
... Show MoreNurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-
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