<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 convolutional neural network that uses other activation functions (exponential linear unit (ELU), rectified linear unit (ReLU), Swish, Leaky ReLU, Sigmoid), and the result is that utilizing CWNN gave better results for all performance metrics (accuracy, sensitivity, specificity, precision, and F1-score). The results obtained show that the prediction accuracies of CWNN were 99.97%, 99.9%, 99.97%, and 99.04% when using wavelet filters (rational function with quadratic poles (RASP1), (RASP2), and polynomials windowed (POLYWOG1), superposed logistic function (SLOG1)) as activation function, respectively. Using this algorithm can reduce the time required for the radiologist to detect whether a patient has COVID or not with very high accuracy.</p>
Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an
... Show MoreThe interest of application of liquid membrane (pertraction) processes for recovery of medicinal compounds from dilute ammoniacal leach solutions is demonstrated. Selectivity of the liquid membrane ensures a preferential transport of the desired solute from the native extract into the strip solution, vinblastine was successfully extracted from basic media (pH 9.2) and stripped by acidic media of sulfuric acid (pH= 1.3) applying continuous pertraction in a rotating discs contactor and using n-decane as liquid membrane. Transport of vinblastine in three-liquid-phase system was studied and performed by means of a kinetic model involving two consecutive irreversible first-order reactions. The kinetic parameters (apparent rate constants of th
... Show MoreIn this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t
... 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
... Show MoreIntroduction: A Pap test can detect pre-cancerous and cancerous cells in the vagina and uterine cervix. Cervical cancer is the easiest gynecologic cancer to be prevented and diagnosed using regular screening tests and follow-up. This study aimed to estimate the cytological changes and the precancerous lesions using Pap smear test and visual inspection of the cervices of Iraqi women, and also to determine the possible relationship of this cancer with patients’ demographic characteristics. Methods: The study included 140 women aged (18-67) years old referred to the National Cancer Research Center (NCRC), Baghdad, Iraq, during the period 2011-2016. Both visual inspections of the uterine cervix and Papanicolaou smear screening were performed
... Show MoreThis work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show More