The aim of current study is estimate the ability of low cost adsorbents, which consist of extracted silica from rice husk ash in treatment of Industrial waste water that contains heavy metals (Cd, Co and Pb) with other pollutants by fixed filters technique with determine the best method for that, and study the effect of a number of variables and parameters. This study involved one waste water samples were collected from. State battery manufacturing company (SBMC) (before treatment unit) at 5th and 22th, of the January 2015. Adsorption tests showed that all tested adsorbent materials had a significant heavy metal removal efficiency. pH values showed a significant impact on adsorption process, but best removal efficiency occurred at pH 4.5

The relationship between F2- layer critical frequencies (foF2), total sunspot number (Ri), northern hemisphere sunspot number (Rn) and southern hemisphere sunspot number (Rs) at station located in mid- latitudes on latitude near to latitude of Iraq (Rome station, lat.: 42o N and lon.: 13o E) and for 2003(the descending phase of solar cycle 23) were studied.
This research work aims to know the correlation range between them, through correlation coefficients which correlate between them, and hence, the dependence on that index for predicting F2- layer critical frequencies. When the correlation coefficients between foF2, Ri, Rn and Rs were compared for different seasons of 2003, It is found that, correlation coefficient between foF2 and

The research seeks to clarify the problems related to the aspects of the financial and accounting process resulting from entering into contractual arrangements with a period of more than 20 years, among which is the research problem represented by the lack of clarity of the foundations and procedures for the recognition of oil costs and additional costs borne by foreign invested companies, which led to a weakening of their credibility and reflection. Negatively "on the measurement and accounting disclosure of financial reports prepared by oil companies, and the research aims to lay down sound procedures for measuring and classifying oil costs and additional costs paid to foreign companies, and recognizing and recording them in th

Background: Lenalidomide is an immunomodulatory drug having notable anti-inflammatory, and anti-antineoplastic properties. Lenalidomide suppresses the production of pro-inflammatory cytokines that have been linked to a variety of hematologic malignancies. Lenalidomide enhances the immune system of the host by regulating T cell proliferation, which results in changes in inflammation that are related to the etiology of psoriasis.

Objectives: The objectives of this study were to determine the efficacy of lenalidomide as an ointment in treating mouse models of psoriasis as well as how it may affect TNF-α levels in skin tissue in different experimental groups.

Methods: The stud

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Phishing is an internet crime achieved by imitating a legitimate website of a host in order to steal confidential information. Many researchers have developed phishing classification models that are limited in real-time and computational efficiency.  This paper presents an ensemble learning model composed of DTree and NBayes, by STACKING method, with DTree as base learner. The aim is to combine the advantages of simplicity and effectiveness of DTree with the lower complexity time of NBayes. The models were integrated and appraised independently for data training and the probabilities of each class were averaged by their accuracy on the trained data through testing process. The present results of the empirical study on phishing websi

    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Psoriasis is a long-lasting autoimmune disease that is characterized by swollen skin patches. Normally, these skin patches are dark, swollen, itchy and scaly. The single application of the innate TLR7/8 ligand Imiquimod (IMQ) in mice easily induces a dermatitis that closely resembles human psoriasis, critically dependent on the axis of IL-23/IL-17. Artemisia dracunculus prepared as an ointment and has been used topically to mice before imiquimod application. The results of the current study showed that A. dracunculus ointment can significantly reduce psoriasis area and severity index in (A. dracunculus ointment + imiquimod group as compared with both control group and (vehicle ointment + imiquimod) group.