In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the procedure in this queueing model, which involved using trapezoidal and hexagonal fuzzy numbers. It can be concluded that graded mean integration approach is efficient with fuzzy queueing models to convert fuzzy queues into crisp queues. This finding has contributed to the body of knowledge by suggesting a new procedure of defuzzification as another efficient alternative.
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
Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti
... Show MoreMultiple sclerosis (MS) is a neuro-inflammatory disorder in which the Epstein-Barr virus (EBV) is proposed to have a pathogenic role. Therefore, a case-control study was performed (93 patients with relapsing-remitting MS and 113 healthy controls (HC) to analyze the prevalence and viral load of EBV infection using real time-polymerase chain reaction. Prevalence of EBV infection was lower in patients compared to HC but the difference was not significant (12.9 vs. 21.2%; probability [p] = 0.187). EBV-positive MS cases were more common in females than in males (83.3 vs. 16.7%), while an opposite distribution was observed in HC (37.5 vs. 62.5%), and the difference was significant (p = 0.041). Blood group O frequency was higher in EBV-p
... Show MoreBackground: Multiple Sclerosis disease is a demyelination process which interferes with the neuronal signal transmission, thus leading to different cognitive and physical dysfunctions like optic neuritis, motor, sensory and coordination problems. Recently many researches have been directed toward studying the relation between some genes and multiple sclerosis. Among the important genes to be studied in multiple sclerosis is the forkhead box P3 gene expression.
Objectives: The aims of the present work were to study the expression of forkhead box P3 gene by real time polymerase chain reaction, and to perform chromosomal analysis on the multiple sclerosis patients peripheral blood lymphocytes.
Patients and methods: A case-control stud
This research include the designation of newly instrument (Turbidmeter) depending on using photo voltaic detector (8.5mm.*8.5mm.).These dimensions have large area which increases the scattering rays with a variable intensity. The properties of this design are local mode and the used tools are a available in the local markets as well as its less cost light weight system. It is worth mentioning that the possibility of its application in many fields such as: Clinical, Laboratory, Industrial and Fuel fields. This designation, applied to estimate Barium Sulphate in turbidity method. The analytical results show high accuracy and repetition, also the linearity ranges from (4-180) ppm. At the detection limit (0.05) ppm. With correlation coefficient
... Show MoreThis review explores the Knowledge Discovery Database (KDD) approach, which supports the bioinformatics domain to progress efficiently, and illustrate their relationship with data mining. Thus, it is important to extract advantages of Data Mining (DM) strategy management such as effectively stressing its role in cost control, which is the principle of competitive intelligence, and the role of it in information management. As well as, its ability to discover hidden knowledge. However, there are many challenges such as inaccurate, hand-written data, and analyzing a large amount of variant information for extracting useful knowledge by using DM strategies. These strategies are successfully applied in several applications as data wa
... Show MoreThis paper is interested in certain subclasses of univalent and bi-univalent functions concerning to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the second Hankel determinant have been investigated for the functions in our classes.
Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
The efficient behavior of a low-concentrating photovoltaic-thermal system with a micro-jet channel (LCPV/T-JET) and booster mirror reflector is experimentally evaluated here. Micro-jets promote the thermal management of PV solar cells by implementing jet water as active cooling, which is still in the early stages of development. The booster mirror reflector concentrates solar irradiance into solar cells and improves the thermal, electrical, and combined efficiencies of the LCPV/T-JET system. The LCPV/T-JET system was tested under ambient weather conditions in the city of Bangi, Selangor, Malaysia, and all data was recorded between 10:00 a.m. and 4:00 p.m. Parametric studies were conducted to compare the performance of the LCPV/T-JET system
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