Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze medical images with favorable results. It can help save lives faster and rectify some medical errors. In this study, we look at the most up-to-date methodologies for medical image analytics that use convolutional neural networks on MRI images. There are several approaches to diagnosing and classifying brain cancers. Inside the brain, irregular cells grow so that a brain tumor appears. The size of the tumor and the part of the brain affected impact the symptoms.
Fibroepithelioma of Pinkus (FEP) is a slowly growing, low-grade malignant tumor with very low metastatic potential that is considered a distinct variant of basal cell carcinoma (BCC). It usually manifests as sessile or polypoidal lesions on the trunk of middle-aged patients. However, it may present in younger age groups, even in children. In this case, we present a rare case of FEP atypically presenting as a scaly plaque on the lower back for several years in an elderly female who was eventually diagnosed by excisional biopsy and histopathology.
The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive ex
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This paper presents mechanical and electrical design, and implementation process of industrial robot, 3-DoF type SCARA (selective compliment assembly robot arm),with two rotations and one translation used for welding applications.The design process also included the controller design which was based on PLC(programmable logic controller) as well as selection of mechanical and electrical components.The challenge was to use the available components in Iraq with reasonable costs. The robot mentioned is fully automated using programmable logic controller PLC(Zelio type SR3-B261BD),with 16inputs and 10 outputs. The PLC was implemented in FBD logic to obtain three different automatic motions with hi
... Show MoreIn this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
Skin drug administration is the method used to provide drugs for local or systemic therapy, which is recognized for clinical usage. It is the third-largest method of medication delivery, after only intravenous administration and oral administration. Using a transdermal delivery method makes the administration easy, and blood concentration and adverse effects can be reduced. A microneedle is a micron-sized needle with a short height of no more than 500 micrometers and a width of no more than 50 micrometers. The needle comes into contact with the epidermal layer of the skin before it gets to the dermal layer, where there is no discomfort. Several materials, such as metals, inorganic, and polymer materials, are used to create microneed
... Show MoreThe emergence of staphylococci, either coagulase negative (CNS) or coagulase positive (CPS), as important human pathogens has implied that reliable methods for their identification are of large significance in understanding the diseases caused by them. The identification and characterization of staphylococci from biopsies taken from human breast tumors is reported here. Out of 32 tissue biopsies, a total of 12 suspected staphylococci grew on mannitol salt agar (MSA) medium, including 7 fermenters and 5 non-fermenter staphylococci based on traditional laboratory methods. Polymerase chain reaction (PCR) successfully identified seven isolates at the genus level as methicillin resistant Staphylococcus spp. by targeting a common region of the me
... Show MoreCohesion is well known as the study of the relationships, whether grammatical and/or lexical, between the different elements of a particular text by the use of what are commonly called 'cohesive devices'. These devices bring connectivity and bind a text together. Besides, the nature and the amount of such cohesive devices usually affect the understanding of that text in the sense of making it easier to comprehend. The present study is intendedto examine the use of grammatical cohesive devicesin relation to narrative techniques. The story of Joseph from the Holy Quran has been selected to be examined by using Halliday and Hasan's Model of Cohesion (1976, 1989). The aim of the study is to comparatively examine to what extent the type
... Show MoreBackground: This study aimed to evaluate the outcome of long-term results of dacryocystorhinostomy (DCR) techniques in specialized eye care center in Iraq.
Subjects and Method: This is a prospective study of 650 patients from July 2014 to July 2019 with nasolacrimal duct obstruction in Ibn Al Haitham Eye Teaching Hospital. A preoperative questionnaire was done, then one month, three months, six months and one year postoperatively. The success of surgery defined as follow; Absence of epiphora completely, Resolve of dacryocele or mucocele or any new attack of daryocystitis, Appearance of fluorescein dye from nose in fluorescein disappearance test, Successful irriga
... Show MoreThe radio drama is considered to be one of the arts that is discovered after a long period of theater's discovery. Initially , it was the broad framework of the theater's work when radio was broadcasting the shows on the huge theaters. This beginning encouraged many of the radio specialists to correlate plays with radio and make a novice and distinctive type of art. Thus, radio drama made its first step including the following ( plays, short and long series drama as well as other types of radio arts). Because of the above mentioned , the researcher is stimulating to study directing techniques to process the radio drama script ( Khata'a play as a sample).
The first chapter deals with the
... Show MoreSelf-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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