The purpose of this paper is to introduce and study the concepts of fuzzy generalized open sets, fuzzy generalized closed sets, generalized continuous fuzzy proper functions and prove results about these concepts.

Abstract

 The issue of inequality in distribution of income and / or consumption expenditure is related to economic welfare because there is an inverse relationship between the economic welfare on the one hand, and the degree of inequality, on the other hand. Despite the fact that inequality is considered as normal phenomenon in every society, but if it exceeded certain limits it will lead to undesirable economic, social and political consequences. Therefore, the availability of indicators about inequality is a necessary tool for planning and evaluation of economic development programs. So, current study is aiming at measuring and analyzing the degree of inequality in distribution of consumpti

In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

This study aimed to isolate and identify Cryptococcus species from three distinct sources: sputum samples of pigeon fanciers, dried pigeon droppings, and eucalyptus tree leaves. A total of 150 specimens were collected over a two-month period, comprising 50 samples each from human sputum, pigeon droppings collected across various areas of Baghdad, and eucalyptus leaves obtained from the Baghdad College of Veterinary Medicine. All samples were cultured on Sabouraud dextrose agar supplemented with chloramphenicol and incubated at 25°C for 2–3 days. From the initial cultures, 20 isolates presumptively identified as Cryptococcus spp. were obtained: 6 isolates (12%) from human sputum, 9 isolates (18%) from pigeon droppings, and 5 isol

This study aimed to isolate and identify Cryptococcus species from three distinct sources: sputum samples of pigeon fanciers, dried pigeon droppings, and eucalyptus tree leaves. A total of 150 specimens were collected over a two-month period, comprising 50 samples each from human sputum, pigeon droppings collected across various areas of Baghdad, and eucalyptus leaves obtained from the Baghdad College of Veterinary Medicine. All samples were cultured on Sabouraud dextrose agar supplemented with chloramphenicol and incubated at 25°C for 2–3 days. From the initial cultures, 20 isolates presumptively identified as Cryptococcus spp. were obtained: 6 isolates (12%) from human sputum, 9 isolates (18%) from pigeon droppings, and 5 isol