Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba

Background: With the increasing trends of global culinary boom and food revolution, and since adolescents are one of the most important age groups that intereact actively with new emerging waves, the health impacts of overweight adolescent pregnancy could be an evolving issue. Additionally, prematurity has different risks of disease and fatality in different areas and nations. Objectives: We aimed to measure the prevalence of complications of prematurity in 1000 neonates in Baghdad city born to overweight adolescent mothers and general maternal characteristics. Methods: Data of 1000 premature (case) and full-term (control) neonates were collected from hospital records in Baghdad over 12 years. The mothers of our samples were overwei

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

Submerged arc welding (SAW) process is an essential metal joining processes in industry. The quality of weld is a very important working aspect for the manufacturing and construction industries, the challenges are made optimal process environment. Design of experimental using Taguchi method (L9 orthogonal array (OA)) considering three SAW parameter are (welding current, arc voltage and welding speed) and three levels (300-350-400 Amp. , 32-36-40 V and 26-28-30 cm/min). The study was done on SAW process parameters on the mechanical properties of steel type comply with (ASTM A516 grade 70). Signal to Noise ratio (S/N) was computed to calculate the optimal process parameters. Percentage contributions of each parameter are validated by using an

Not necessarily to be malnutrition is a result of poverty and lack of food, it may be the outcome of the wrong food practices; and the lack of knowledge in nutrition basis and chronic diseases. Some studies have confirmed that the more the knowledge in nutrition basis increased, the more the child has well-balanced food.

Unhealthy eating habits spread among children at an early age, which is one of the negative factors affecting the nutritional status they have causing various disorders as a result of lack or increase of food or lack of balance. The signs and symptoms of these disorders can be simple or can lead to deadly diseases.

Training children on proper eating habits in different fields of life is considered the mos

Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.