The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.

Non-alcoholic fatty liver disease (NAFLD) has become one of the most common chronic liver diseases worldwide, which characterized by steatosis, inflammation, and fibrosis. The aim of this designed study is to evaluate the ability of guggulsterone to prevent high fat diet induced steatohepatitis in mice. Five groups of male mice were selected and treated as the following: group I, mice had free access to standard commercial diet and considered as control group, group II, mice were fed a specially formulated high-fat diet for 12 weeks to induce non-alcoholic liver disease, while groups III, IV and V the mice were administered high fat diet containing guggulsterone at 500, 1000 and 2000 ppm concentration respectively for 12 weeks. Maintaini

ABSTRACT Possible interference of vamin nutritional solution with the activity of several B-lactam antibiotics against E.coli was evaluated in vitro.In Minimal basal salts-glucose medium rapid growth inhibition of sensitive E. coli was induced by 4 µg/ml of ampicillin / cloxaillin, 8 µg/ml of ampicillin, 6 µg/ml of carbencillin, hostacillin, and cephalotin, and by 32 µg/ml of penicillin G and cloxacillin. Significant inactivation of up to 32 µg/ml of carbencillin, cephalotin, penicillin G, and hostacillin was induced by addition of 1:20 v/v vamin. This inactivation was due to the presence of specific amino acids in the mixture. Deletions of amino acids revealed that valine, leucine, isoleucine, tyrosine, tryptophan, phenylalanine, cys

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c