Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysis of samples from selected sites proved that the most abundant component of aromatic hydrocarbons were phenanthrene naphthalene, and acenaphthylene, followed by fluorene, acenaphthene, fluoranthene, benzo (a) pyrene, anthracene. and pyrene were
present in low concentrations ranging in a descending order. Chrysene and benzo (a) anthracene were found in very low concentration.
A laboratory unit was designed to optimize the factors which may influence the feasibility of degradation processes of naphthalene and phenanthrene in aqueous matrices by oxidation with Fenton reagent. The study proved that 83% and 79% removal of naphthalene and phenanthrene were achieved applying optimum conditions of pH=3, temperature=40 ° C, H2O2=50 ppm and Fe2+ catalyst = 6 ppm
The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats. This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat
... Show MoreFinding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over
... Show MoreThe combined system of electrocoagulation (EC) and electro-oxidation (EO) is one of the most promising methods in dye removal. In this work, a solution of 200 mg/l of Congo red was used to examine the removal of anionic dye using an EC-EO system with three stainless steel electrodes as the auxiliary electrodes and an aluminum electrode as anode for the EC process, Cu-Mn-Ni Nanocomposite as anode for the EO process. This composite oxide was simultaneously synthesized by anodic and cathodic deposition of Cu (NO3)2, MnCl2, and Ni (NO3)2 salts with 0.075 M as concentrations of each salt with a fixed molar ratio (1:1:1) at a constant current density of 25 mA/cm2. The characteristics structure and surface morphology of the depo
... Show MoreThe purpose of the theme of redesign of jobs one of the topics the task that offers the possibility for individuals to perform several tasks in the organization of health at the same time gain experience and diverse skills and achieve compatibility between the requirements of the most appropriate function and organization of the hand ,hence, the idea of studying the redesign of jobs of the division of blood transfusion services in the department of health Baghdad Rusafa to change the conventional methods used in the performance of functions ,which are no longer able to meet the needs of patients where blood transfusion is a key ingredient in health care and equal access to safe blood is needed
... Show MoreThis study aims to create spatial balance between two Iraqi writers' novels (Maysaloon
Hadi, Alya Talib) technical and objective illustrates similarity points and difference in the
writers' style. We depended in our research on spatial classification considering the aggressive
and friendly, since the writers focused on them.
The research study concluded to many sides, some of which are similar and some are
different. Firstly, ingenuity description of the writers. Followed by the deep connection they
have. Because of the personal experience it emanated from alienation sensations and nostalgia
to deep roots to homeland.
On the other hand, difference aspects, we see Maysaloon takes symbols and illusions
unlike Aly
The objective of this research is employ the special cases of function trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of Baghdad and Basra, has been the adoption of different periods of the functions belonging to see the change happening in the matrix matches and the impact that the strategies and decision-making available to each player and the impact on societ
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreBackground: Depression in elderly aged (60 year and above )is a widespread mental health problem . The current primary healthcare systeminadequately recognize and treat elderly patients with depression..
Objectives:To determine the prevalence of depression among elderly patientsin Mosul city, its correlation with some sociodemographic variablesand to assess severity of depression in relation to past history of depression.
Type of the study: This is a cross-sectional study.
Methods: This study assess the prevalence of depression in a randomly selected sample 150 elderly patients aged 60 years and above (89 female &
... Show MoreThe exercise of activities and sports are of great importance to public health and to maintain the ideal health weight as well as the psychological and mental comfort of humans. The aim of this study is to determine the contribution and participation of educated females in physical activities at the University of Baghdad hall for the years 2011-2016, and to show the factors that influence women's contribution to physical activities at the university by selecting 100 students of males and 100 females' students randomly. During the questioning questions and statistical analysis of the questioning to find out the reasons for the discouraging contribution of the women to the various physical activities and try to find solutions and r
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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