Objective: The present study aims to investigate molecular confirmation for <i>Cryptosporidium</i> species in fish handlers in Baghdad City, central Iraq. Materials and Methods: Sixty stool samples were collected between early November 2023 and late April 2024. All samples were examined phenotypically using a modified Ziehl-Neelsen stain and genotypically (nested polymerase chain reaction technique) based on a partial sequence of 18S rRNA genes with sequencing and phylogenetic tree analysis. Results: The total molecular results identified <i>Cryptosporidium parvum</i> with an infection rate of 45% (27/60). A higher infection rate of 51.9% (14/27) was found in the age group between 15 and 35 years, and male

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

Crime is one of the most severe challenges facing States, and strives to find preventive measures, reduce its seriousness, and prevent them; due to developments, crimes have increased, and emerging new patterns of crimes, there is an urgent need to prevent crimes and reduce their effects. Modernizing its punitive system and diverting it to correctional rehabilitative justice to redress the prejudice caused by the crime and rehabilitate the convicted person by using alternative measures to short-term imprisonment. This research emphasizes alternative sanctions' value to minimizing short-term imprisonment penalties and their impact on societal security through several goals like, the negative consequences, justifications, and alternatives

The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of t

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on