The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Abstract

Objectives: To find out the association between enhancing learning needs and demographic characteristic of (gender, education level and age).

Methods: This study was conducted on purposive sample was selected to obtain representative and accurate data consisting of (90) patients who are in a peroid of recovering from myocardial infarction at Missan Center for Cardiac Diseases and Surgery, (10) patients were excluded for the pilot study, Data were analyzed using descriptive statistical data analysis approach of frequency, percentage,  and analysis of variance (ANOVA).

Results: The study finding shows, there was sign

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Background: Lymphomas are a group of diseases caused by malignant lymphocytes that accumulate in lymph nodes and cause the characteristic clinical features of lymphadenopathy. Intercellular adhesion molecule-1 (ICAM-1) (CD54) is a transmembrane glycoprotein belonging to the immunoglobulin superfamily of adhesion molecules. Cortactin was first identified as one of the major substrates for src kinase. because it localized to Cortical actin structures, The aims of this study was to evaluate and compare the immunohistochemical of ICAM-1 expression as cell adhesion molecule marker and Cortactin expression as invasive marker. Material and Methods: This study was performed on (68) formalin-fixed, paraffin-embedded blocks, histopathologically diagn

Ionic liquids (ILs) and deep eutectic solvents (DESs) have been found to be highly effective as electrolytes in TiO2 NTAs-graphite cells when combined with additives that enhance conductivity by reducing the viscosity of these liquids. The presence of CaCl2.6H2O: Acetamide DES with DI water as an additive resulted in a cell voltage of 1.31V and an internal resistance of 19 ohm. This can be attributed to the concentration and quality of the ionic species. The cells exhibited an interesting response to the AlCl3-chloroacetamide IL with dichloromethane DCM as an additive, with a cell voltage of 1.81V and an internal resistance of 5.0 ohm. Once again, this is influenced by the quality and concentration of the ionic species. Furthermore,

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati