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

A liquid membrane process of Alkaloids extraction from Datura Innoxia solution was studied applying pertraction process in rotating discs contactor (RDC). Decane as a liquid membrane and dilute sulphuric acid as stripping solution were used. The effect of the fundamental parameters influencing the transport process, eg type of solvent used, effect of disks speed, amount of liquid membrane and effect of pH for feed and strip solution. The transport of alkaloids was analysed on the basis of kinetic laws of two consecutive irreversible first order reactions. Thus, the kinetic parameters (k1, k1,, tmax, and) for the transport of alkaloids were determined. The effect of organic membrane type on percentage of Alkaloids transport was found to be i

Leaching process applied for the extraction of bio active compounds from dried roots of (Elecampane) Inula helenium. Ethanol, hexane and distillated water were used as solvents. Roots were soaked with ethanol (5% w/v) with various concentration of ethanol (30 to 98%) at one day to know effect concentration of the solvent with concentration of bio active compound in Inula helenium. The same procedure was done using hexane as solvent. Also distilled water was used as solvent for extraction 5%(w/v) where plant material was soaked in water at different temperatures (25, 40, 65, 80, and 90) C. In all solvents undertaken, the effect of time duration on active ingredient (Thymol, Isoalatolactone, Alatolactone, 10-isobutyryl-oxy 8-9-epoxy thymol is

Retained soft tissue foreign bodies following injuries are frequently seen in the Emergency and Plastic Surgery practice. The patients with such presentations require a watchful and detailed clinical as- sessment to overcome the anticipant possibility of missing them. However, the diagnosis based on the clinical evaluation is usually challenging and needs to be supported by imaging modalities that are suboptimal and may fail in identifying some types of foreign bodies. Owing to that, serious complications such as chronic pain, infection, and delayed wound healing can be faced that necessitate a prompt intervention to halt those detrimental consequences. The classical method of removal is a surgical exploration which is not free of risks.

The development of economic and environmentally friendly extractants to recover cobalt metal is required due to the increasing demand for this metal. In this study, solvent extraction of Co(II) from aqueous solution using a mixture of N,N0-carbonyl difatty amides (CDFAs) synthesised from palm oil as the extractant was carried out. The effects of various parameters such as acid, contact time, extractant concentration, metal ion concentration and stripping agent and the separation of Co(II) from other metal ions such as Fe(II), Ni(II), Zn(III) and Cd(II) were investigated. It was found that the extraction of Co(II) into the organic phase involved the formation of 1:1 complexes. Co(II) was successfully separated from commonly associated metal

Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.