Placental dysfunction and or fetal central nervous system infestation caused by Human cytomegalovirus (HCMV) is the leading cause of congenital non-genetic neuro-developmental problems of the newborn, worldwide. Although the highest rates of congenital infection and CMV seroprevalence occurs in developing countries like Iraq, there remains a paucity of data from that part of the world. This descriptive case control study was undertaken in Babylon/ Iraq to determine the local seroprevalence of CMV in women of child bearing age, and to identify the socio-demographic factors associated with it.  This study found a seropositivity peak amongst the 26-35 yr olds which declined in the 36 – 45 yr olds. However, the

A new simple and sensitive spectrophotometric method is described for quantification of Nifedipine (NIF) and their pharmaceutical formulation. The selective method was performed by the reduction of NIF nitro group to yield primary amino group using zinc powder with hydrochloric acid. The produced aromatic amine was submitted to oxidative coupling reaction with pyrocatechol and ammonium ceric nitrate to form orange color product measured spectrophotometrically with maximum absorption at 467nm. The product was determined through flow injection analysis (FIA) system and all the chemical and physical parameters were optimized. The concentration range from 5.0 to 140.0 μg.mL-1 was obeyed Beer’s law with a limit of detection and quantitatio

Use of Surveillance cameras in houses and markets became common, that resulted to minimize theft and make it a difficult task because it let recording and viewing what is going around. The wide application of these cameras, pushed thieves to seek new ways for abolition of the surveillance system and digital recording of events, such as cutting the signal wire between the camera and Digital video recorder or changing the direction of the camera away from the focus spot or damaging the camera or steal the device which means the loss of the recorded media. This paper focuses on such abolitions and fixed it by suggesting a way to notify the administrator immediately and automatically by Email about any violation of the system using MATLAB, whic

The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr