This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

It was aimed to understand the interleukin-4 (IL-4) role in etio-pathogenesis of rheumatoid arthritis (RA). Two approaches were adopted. In the first one, a quantitative expression of IL4 gene was assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and such findings were correlated with some demographic, clinical and laboratory parameters, which included gender, duration of disease, disease activity score (DAS-28), rheumatoid factors (RFs), C-reactive protein (CRP) and anti-cyclic citrullinated peptide (ACCP) antibodies. In the second approach, a single nucleotide polymorphism (SNP) of IL4 gene (rs2243250) was inspected by DNA sequencing using specific primers. Fifty-one Iraqi RA patients (22 males and 29 fem

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

60 patients diagnosed as having urticaria were included in the study ; 30 patients were effected with acute urticaria and 30 patients were affected with chronic urticaria. In addition, 30 healthy adult volunteers were selected as control group .The patients and control groups sera were examined with enzyme linked immunosorbent assay ( ELISA) to detect total level IgE and radial immunodiffusion (RID) to detect levels of IgG , IgA and IgM . The total level of IgE in acute urticaria ( 1.45±0.13) IU/mL and chronic urticaria (2.12 ± 0.10) IU/mL patients were significantly higher than the control groups ( 0.85 ± 0.10)IU/mL (p<0.05). The level of IgG in acute urticaria ( 12.5± 0.42) g/L and chronic (13.16±0.40) g/L patients , IgA in acute (2.

This study aims at suggesting flow as a strategy for training female EFL student-teachers in the teaching training course and finding out the effect of this strategy on their performance and their flow state. The training course syllabuses will be constructed according to the flow nine factors and the teaching skills. The measurement tools are the student-teacher performance checklist that has already been used by the department of English language and SHORT Flow State Scale (S FSS-2). The study population is represented with the (60) female student-teachers/ fourth stage/ evening studies at theEnglish department /college of education for women/the University of Baghdad. The study is used the experimental design in that (30) of the student-

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Education quality evaluation is one of the objectives of education quality. The evaluation includes assessing the education standards and academic program outcomes to develop intellectual, scientific and practical concepts for the educational structure. It considers the determination of the rates of the number of accepted students and graduates. The research focuses on "what are the levels of education quality according to the evaluation mechanisms in the design department" to enhance the quality system and the objectives of theoretical and applied education.
It is identifying the levels of education quality and evaluating it according to the numbers and rates of graduate students of the design department branches for morning and ev