Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect on how the network perform when predicting cases of brain tumor, contrast accounted for 64.3 %, correlation accounted for 56.7 %, and entropy accounted for 54.8 %. All remaining characteristics accounted for 21.3-46.8 % of normalized importance. The output of the neural networks showed that sensitivity and specificity were scored remarkably high level of probability as it approached % 96.
Heat shock protein 70 (HSP70) is a crucial protein with vital biological tasks in cell continuation of life. The variation of HSP70 activation occurs as a consequence of stress that includes temperature states, toxicity, poisoning with heavy metals, and tumor-related conditions. One of the master jobs of the HSP family is the suppression of caspase-mediated apoptosis signals. A high level of the expression of HSP70 is accountable for tumorigenesis and resistance against chemotherapeutic drugs. For this reason, the detection of HSP70 may help to diagnose cancerous diseases. From the other side, targeting this chaperone might help in treatment by maintaining late caspase-dependent events. This study was conducted to detect the presenc
... Show MoreClean water supply is one of the major factors contributing significantly to society’s socio-economic transformation by improving living standards, health, and increasing productivity. It is imperative to plan and construct appropriate water supply systems in modern society, which supply various segments of society with safe drinking water according to their requirements to ensure adequate and quality water supply. In the current study, here was an attempt to develop a model for geographic information systems to manage the assets of the water distribution networks in the Karrada region and to evaluate the network geometrically, and from the results of the engineering analysis of the
The synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.
Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co
... Show MoreDue to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra
... Show MoreRecently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua
... Show MoreIn this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint
... Show MoreThis study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
... Show MoreThe utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.
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