Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

Elevated C-Reactive Protein (CRP) level in serum is a risk factor for type 2 diabetes ,this relationship is likely to be the cause it means elevated CRP leads to T2D in future . Our objective was to examine CRP in male Type 2 Diabetes(T2D) patients in different age ,we studied 120 male subjects divided to two groups according to their age. First group A age (31 - 40) year old ,60 person )30 control & 30 T2D patients(,3 person for each same age: second group B age (41 – 50) years old ,60 person )30 control & 30 T2D patients(,3 person for each same age. We examined blood sugar ,cholesterol and CRP in each group. and we toke the mean of samples in the same age in each data in all the 4 groups. Our data shows that CRP

Background: Oral Lichen Planus is a chronic inflammatory mucosal disease, presenting in various clinical forms .Both antigen-specific and non-specific mechanisms involved in the pathogenesis of OLP. Apoptosis or programmed-cell death is a physiological process essential for the normal development and maintenance of homeostasis in many organisms. Fas is a cell-surface glycoprotein, 40-kDa, that belongs to the nerve growth factor / tumor necrosis factor (TNF) receptor family. Fas is expressed in several tissues including blood, where its expression is upregulated on activated T and B lymphocytes and natural killer cells. Fas ligand is a type II transmembrane protein that belongs to the tumor necrosis factor family. The proto-oncogene c-Myc is

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Polycystic ovarian syndrome (PCOS) is increasingly recognized as a significant health concern among women of reproductive age, exerting its influence on the reproductive system and overall female physiology. Paraoxonase-1 (PON1) gene polymorphism, -108 C >T in the promoter region, have been identified as factors that influence both the stability of the enzyme and its active site. This, in turn, contributes to increase oxidative stress, a recognized risk factor associated with PCOS. This study aimed to investigate the connection between paraoxonase-1-108 C >T gen polymorphisms with PCOS in Iraqi women in a case-control study included 40 women with PCOS and 40 women with normal cycles and no symptoms of