This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional bulk queues. This new model focus on mixed-integer non-linear programming (MINLP) tenders a mathematical computational approach is known as (0 -1) variables. To measure the efficiency of the method, the efficient solution strategy plays a crucial role in the adequate application of these techniques. Furthermore, different stages of the α-cut intervals were analyzed and the final part of the article gives a numerical solution of the proposed model to achieve practical issues.
The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
In the present work theoretical relations are derived for the efficiency evaluation for the generation of the third and the fourth harmonics u$ing crystal cascading configuration. These relations can be applied to a wide class of nonlinear optical materials. Calculations are made for beta barium borate (BBO) crystal with ruby laser /.=694.3 nm . The case study involves producing the third harmonics at X. =231.4 nm of the fundamental beam. The formula of efficiency involves many parameters, which can be changed to enhance the efficiency. The results showed that the behavior of the efficiency is not linear with the crystal length. It is found that the efficiency increases when the input power increases. 'I'he walk-off length is calculated for
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In this study, the adsorption of Zn (NO3)2 is carried out by using surfaces of malvaparviflora. The validity of the adsorption is evaluated by using atomic absorption Spectrophotometry through determination the amount of adsorbed Zn (NO3)2. Various parameters such as PH, adsorbent weight and contact time are studied in terms of their effect on the reaction progress. Furthermore, Lagergren’s equation is used to determine adsorption kinetics. It is observed that high removal of Zn (NO3)2 is obtained at PH=2. High removal of Zn (NO3)2 is at the time equivalent of 60 min and reaches equilibrium,where 0.25gm is the best weight of adsorbant . For kinetics the reaction onto malvaparviflora follows pseudo first order Lagergren’s equation.
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In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.
The thermal method was used to produce silicoaluminophosphate (SAPO-11) with different amounts of carbon nanotubes (CNT). XRD, nitrogen adsorption-desorption, SEM, AFM, and FTIR were used to characterize the prepared catalyst. It was discovered that adding CNT increased the crystallinity of the synthesize SAPO-11 at all the temperatures which studied, wile the maximum surface area was 179.54 m2/g obtained at 190°C with 7.5 percent of CNT with a pore volume of 0.317 cm3/g ,and with nano-particles with average particle diameter of 24.8 nm, while the final molar composition of the prepared SAPO-11 was (Al2O3:0.93P2O5:0.414SiO2).
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The removal of Ibuprofen antibiotics (IBU) by photo-degradation UV/H2O2/Fe+2 system was investigated in a batch reactor under different initial concentrations of H2O2 (100-500) mg/L, Fe+2 (10-40) mg/L, pH (3-9) and initial concentrations of IBU (10-80) mg/L, and their relationship with the degradation efficiency were studied. The result demonstrated that the maximum elimination of IBU was 85.54% achieved at 300 mg/L of H2O2, 30 mg/L of Fe+2, pH=3, and irradiation time of 150 min, for 10 mg/L of IBU. The results have shown that the oxidation reagent H2O2 plays a very important role in IBU degradation.
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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