Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

The goal of current research is marked "student services for the university student at the Faculty of Education for Girls at Baghdad University in light of the overall quality indicators)" to identify the relative importance of the availability of student services offered by the College of Education at the University of Baghdad, from the viewpoint of the students. The research was Aaguetdy followers researcher Find descriptive approach to suitability research topic and in order to achieve the purposes of research, the researcher designed questionnaire examined consisted of (18) items and has been questionnaire on arbitrators and experts to verify the validity and reliability that's been applied to the questionnaire on a group of students

Breast mass is by far the most important clinical problem that concerns the breast today. This study was carried out to evaluate diode laser as a cutting tool in breast mass excision and as a hemostatic tool for coagulation during surgery. Using 810 nm diode laser with optical fiber 600μm in diameter of conical tip, udder (cow's breast) tissue, and three female patients (mean age of 35.5 y with clinically palpable breast mass) had been used in this study. The patients were followed up regularly postoperatively. In preliminary work on udder tissue, the power needed for cutting and excision was 15W (power density= 5.3 kW/cm2). The time consumed for excision of a piece of udder tissue, 40×10×3 mm in dimensions was 5 min. The depth range

Letrozole (LZL) is a non-steroidal competitive aromatase enzyme system inhibitor. The aim of this study is to improve the permeation of LZL through the skin by preparing as nanoemulsion using various numbers of oils, surfactants and co-surfactant with deionized water. Based on solubility studies, mixtures of oleic acid oil and tween 80/ transcutol p as surfactant/co-surfactant (Smix) in different percentages were used to prepare nanoemulsions (NS). Therefore, 9 formulae of (o/w) LZL NS were formulated, then pseudo-ternary phase diagram was used as a useful tool to evaluate the NS domain at Smix ratios: 1:1, 2:1 and 3:1.

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

The advent of UNHCR reports has given rise to the uniqueness of its distinctive way of image representation and using semiotic features. So, there are a lot of researches that have investigated UNHCR reports, but no research has examined images in UNHCR reports of displaced Iraqis from a multimodal discourse perspective. The present study suggests that the images are, like language, rich in many potential meanings and are governed by clearly visual grammar structures that can be employed to decode these multiple meanings. Seven images are examined in terms of their representational, interactional and compositional aspects. Depending on the results, this study concludes that the findings support the visual grammar theory and highlight the va

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol