This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.

With a descriptive and analytical approach, it discusses the concept of phenomenology as an approach to seeing the aesthetics of ugliness as one of the concepts associated with the aesthetic experience in contemporary art designs, as it is the result of communication between artistic production and the recipient, which leads to creating a state of aesthetic pleasure. A phenomenological method is used to uncover the aesthetics of ugly and to connect ugliness and beauty since ugliness in aesthetics incorporates beauty as a modern aesthetic vision from the phenomenological perspective. The study investigated aesthetics as a phenomenon of perception, sensory knowledge, and the aesthetic response to the production of designs in contemporary a

Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

Abstract

                  The study aimed to prepare a practical guide for procedures for auditing the strategies of municipal institutions in achieving sustainable development by adopting the idea of ​​the audit matrix through which a classified report is prepared according to the dimensions of sustainable development, by preparing a specialized audit program for the purpose of auditing strategies for achieving sustainable development and emptying the results of the application of each of the paragraphs The program in the audit matrix that was prepared for the purpose of determining the impact of each observation and linkin

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

Despite the simplicity that characterized the administration in the era of the Prophet
(peace be upon him), but it put the Muslim community nucleus Administrative Organization
who walked Garret Caliphs (RIP) and came after them, who added to this organization what
they found necessary and dictated by their conditions of life has begun regulation Managing
this appoint leaders and armies of workers on the state and various tribes to spread the Islamic
religion and to teach people the provisions of the Koran and Altfvh in religion and establish
prayer and collect Zakat money so you do not appoint leaders and workers and governors
followed random, but it is in an objective manner takes reasons to meet expectations.

Background: Semen contamination is a detrimental factor in decreasing fertility. Seasonal changes may affect the contamination, too. Objectives: This study was designed to detect semen contamination in ovine and caprine during different seasons. Methods: Six fully mature male sheep and goats were subjected to electro-ejaculator collection twice monthly from February 1, 2022, to January 31, 2023 (Spring, February 1, 2022-April 30, 2022; Summer, May 1, 2022, July 31, 2022; Autumn August 1, 2022, October 31, 2022; Winter November 1, 2022, January 31, 2023), for studying the seasonal effect. A total of 288 semen samples were collected from both species (36 samples from each per season). All samples were subjected to bacterial isolatio

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise