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

The results of research to reach the conditions that prevents the emergence of primary or secondary voids and achieve worker benefit from molded by almost 100%, which was the situation that cast poured in a mold heated and insulated from all sides to achieve freezing directional full starting from the region remote from the casting and ending then. Has also been compared to the microscopic structure of the resulting castings of various molding conditions, as these conditions have achieved the best sound microscopic structures.

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

The analysis, behavior of two-phase flow incompressible fluid in T-juction is done by using "A Computational Fluid Dynamic (CFD) model" that application division of different in industries. The level set method was based in “Finite Element method”. In our search the behavior of two phase flow (oil and water) was studed. The two-phase flow is taken to simulate by using comsol software 4.3. The multivariable was studying such as velocity distribution, share rate, pressure and the fraction of volume at various times.  The velocity was employed at the inlet (0.2633, 0.1316, 0.0547 and 0.0283 m/s) for water and (0.1316 m/s) for oil, over and above the pressure set at outlet as a boundary condition. It was observed through the program

Rapid and continuous developments and changes in the modern business environment in all areas of economic, environmental, social, technology and communications push economic units to search for modern methods and methodologies to produce products at low cost as well as produce products that meet the wishes of customers in terms of quality and environment to maintain their market position, and accounting for the costs of the flow of materials is one of the most prominent environmental management accounting techniques capable of providing information to help produce

Mefenamic acid belongs to non-steroidal anti-inflammatory drugs that are used widely for the treatment of analgesia. Our aim from this study is to establish a new assay for the quantitative determination of mefenamic acid (MFA) in the pharmaceutical sample by two sensitive and rapid flow injection-fluorometric methods. A homemade fluorometer was used in fluorescence measurements, which using solid-state laser diode 405 and 532 nm as a source, combined with a continuous flow injection technique. The first method depends on the effect of MFA on calcein blue (CLB) fluorescence at 405 nm. Another method is a study of rhodamine-6G (Rh-6G) fluorescence after adding MFA, and recording at 532 nm. Optimum parameters as fluorescent dye concen

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class