Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Objective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

The process of discharging the quantities of dyes resulting from industrial processes with wastewater leads to the occurrence of a serious environmental problem that threatens the environmental health security of humans. Therefore, a number of studies have been addressed that include presenting many physical and chemical treatment methods to get rid or reduce the proportion of pigments such as biological decomposition, ion exchange, and sedimentation. Chemotherapy, reverse osmosis, coagulation, Toxic sludge generation, flocculation. In addition to the above, this review deals with a number of studies that present activated carbon of plant origin, methods of obtaining it, types and advantages of it being cheap and environmentally friendly. A

The pumping station became widely used in many fields. Free surface vortices at intakes of pumps are not favorable. It may cause noise, excessive vibration, damage to the pumping structure, reduction in efficiency and flow for hydro-turbines, etc. One of the important problems encountered during the pump intake design is the depth of submergence and other design parameters to avoid strong free-surface vortices formation. This study aims to compute the critical submergence depth with some geometrical and hydraulic limitations by using Computational Fluid Dynamic (CFD) package. The mathematical model was validated with a laboratory model that had been conducted. The model of three intake pipes was investigated under five d

The use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions  pb.2+   from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption  pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f

Treatment of a high strength acidic industrial wastewater was attempted by activated carbon
adsorption to evaluate the feasibility of yielding effluents of reusable qualities. The experimental
methods which were employed in this investigation included batch and column studies. The
former was used to evaluate the rate and equilibrium of carbon adsorption, while the latter was
used to determine treatment efficiencies and performance characteristics. Fixed bed and expanded
bed adsorbers were constructed in the column studies. In this study, the adsorption behavior of acetic acid onto activated carbon was examined as a function of the concentration of the adsorbate, contact time and adsorbent dosage. The adsorption data was mo

This paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60)   The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-or

The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w