Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

Background: Tubal ligation, recognized as a surgical intervention that ensures permanent contraception, has established itself as an option for women seeking a definitive solution for family planning. Objective: To assess the psychosexual implications of tubal ligation in a sample of women in Baghdad, Iraq. Methods: A prospective cohort study was conducted in a teaching hospital for 2 years, from the first of January 2022 to the end of December 2023, in which 203 women who underwent tubal ligation were included. Results: In the present study, we found that 158 (77.8%) had no depression, mild depression presented in 27 (13.3%), and moderate depression in only 15 (7.4%). While 163 (80.3%) of women did not suffer from anxiety, 32 (15.8

Democracy in any country is measured by the cultural, social and economic level reached by women in it in general and women with disabilities in particular, and the extent of their participation in political life and political decision-making. As a result of the patriarchal power that societies have known, including Iraq, history has witnessed multiple types and forms of discrimination against women, which differed from one country to another, this matter has pushed women and since the beginning of the last century the issue of women's rights has been raised at the global, regional and national levels, through holding international conferences and agreements In order to empower women in all social, economic and political fields.

Gender has considered and become a new trend in women's studies, as it reflects the behaviors, roles and attitudes imposed by society on its members in accordance with their biological nature,with focusing on gender rather than on concentration on women, which is closely linked to the vision that concentrates on women's problems which are not primarily according to their biological differences But rather to a greater extent to social, cultural, historical and religious barriers and Obstacles.
Therefore, the qualitative division due to the concept of "gender" is not a rigid biological division, but is relied on the broad general context through which the social division of work is done. Thus, content in the pages of Facebook with high-

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a