In this paper, Min-Max composition fuzzy relation equation are studied. This study is a generalization of the works of Ohsato and Sekigushi. The conditions for the existence of solutions are studied, then the resolution of equations is discussed.

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment.  This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020.  The results revealed that positive and negative shocks for both exchange rates have unequal effects on

Perimenopausal bleeding, is a very common problem, which is an alarming symptom for both; women and their doctors because of the rising fears of cellular changes or tumor of endometrium. In our study we tried to prove that collecting endometrial samples using the outpatient method of Pipelle is as effective as collecting the endometrial samples in the traditional method of Dilation and Curettage (DandC) in operation theatre which necessitates general anesthesia. Ninety four patients more than 40 years old were included in the study, all of them were complaining of abnormal uterine bleeding (pregnant ladies and ladies using hormonal contraception were excluded from the study) and endometrial samples were collected first in outpatient

The present work was done in an attempt to build systematic procedures for treating warts by 810 nm diode laser regarding dose parameters, application parameters and laser safety. The study was done in Al- Kindy Teaching Hospital in Baghdad, Iraq during the period from 1st October 2003 till 1st April 2004. Fifteen patients completed the treatment and they were followed for the period of 3 months. Recalcitrant and extensive warts were selected for the study. Patients were randomly divided into 3 groups to be treated by different laser powers 9, 12 and 15 W, power density of 286 W/cm2, 381W/cm2, 477 W/cm2 pulse duration of 0.2 s, interval of 0.2 s and repeated pulses were used. The mode of application was either circular or radial. Pain oc

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization