Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

The present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in

The sample's physical characteristics and laser parameters impact the generation and characterization of Laser-Induced Plasma (LIP), which is a relevant phenomenon in many applications. We investigated the effect of laser energy on laser-induced Zn plasma characterization in this study. A Zn plasma with a repeating frequency of 6 Hz, a first wavelength of 1064 nm, a pulse duration of 10 ns, and a laser energy range of 300 mJ to 500 mJ was created using a Q-switched ND: YAG laser. The basic plasma properties, such as electron temperature and density, were estimated using optical emission spectroscopy (OES). The electrons' temperature was measured by the Boltzmann plot method, and the value of the electrons' temperature ranged from 1.6 eV

Congenital anomalies commonly occur in humans, possibly visible. If these anomalies appear in visible parts in human body such as face, hands and feet. They may only appear after utilizing a number of special tests in order to show by means of the anomalies that occur in the internal organs of the body such as heart, stomach and kidneys.

    Research data have comprised accessible information in the anomalies birth statistics form situated of Health and Life Statistics section at the Ministry of Health and environment, where the number of anomalies births involved in the study (2603 anomalies birth) in Iraq, except Kurdistan region, at 2015. A two way-response logistic regression analysis h

   The current investigation concluded an  anatomical study of the cultivated species Pelargonium graveolens  L. 'Hér belong to the  Geraniaceae family and which  cultivated as an  ornamental plant, fresh specimen were collected from different region  in  Baghdad ,the study vegetative parts (leaf, stem and petiole) in details ,the upper and lower epidermis of leaf and epidermis of  stem  also studied, ordinary epidermal cells and stomatal complexes studied in term of shapes and  dimensions  ,the result showed that stomatal in leaf and stem is anomocytic type, the cross sections of the vegetative parts  prepared by microtome and free hand sectioning. The tissues of these parts include the number an