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.
With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show Moreتعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه
... Show MoreThis paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.
The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and this load w
... Show MoreThe objective of this study is to demonstrate the corrosion behavior of dental alloys Co-Cr-Mo, Ni-Cr-Mo and Ti-Al-V in artificial saliva at pH=4 and 37oC enriched with ethyl alcohol at 8% percentage. The linear and cyclic polarizations were investigated by electrochemical measurements. Laser surface modification was achieved for the three dental alloys to improve corrosion resistance. The results show that corrosion resistance of Co-Cr-Mo and Ni-Cr-Mo alloys only were increased after laser treatment due to the fact that laser radiation has caused a smoother surface, in addition to the decrement in corrosion current densities (icorr) for Co-Cr-Mo and Ni-Cr-Mo alloys and the reverse scan in cyclic polarization became in the wider range of
... Show MoreThe Internet of Things (IoT) technology is every object around us and it is used to connect these objects to the Internet to verify Machine to Machine (M2M) communication. The smart house system is the most important application of IoT technology; it is increase the quality of life and decrease the efforts. There were many problems that faced the existing smart house networking systems, including the high cost of implementation and upgrading, high power consumption, and supported limited features. Therefore, this paper presents the design and implementation of smart house network system (SHNS) using Raspberry Pi and Arduino platforms as network infrastructure with ZigBee technology as wireless communication. SHNS consists of two mai
... Show MoreWater is an essential aspect of life and important in evolution. Recently the potable water quality topic has received much attention. The study aims to determine drinking water quality in Al-Najaf City by collecting samples throughout Al-Najaf city and comparing the results with the Iraqi guidelines (IQS 417) and World Health Organization (WHO) guidelines, as well as to calculate the WQI. Samples were tested in the laboratory between December 2021 and June 2022. The results showed that multiple parameters exceeded the allowable limits during both testing periods; during winter months, the results of TDS and turbidity exceeded the upper limits in multiple locations. Total hardness values also
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