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

Rheumatoid arthritis is a chronic, progressive, inflammatory autoimmune disease of unidentified etiology, associated with articular, extra-articular and systemic manifestation that require long-standing treatment. Taking patient’s beliefs about the prescribed medication in consideration had been shown to be an essential factor that affects adherence of the patient in whom having positive beliefs is an essential for better adherence. The purpose of the current study was to measure beliefs about medicines among a sample of Iraqi patients with Rheumatoid arthritis and to determine possible association between this belief and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid

      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift

In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.

The complexation between folic acid and a typical polyaromatic hydrocarbon, fluorene, was investigated using FTIR and UV spectra. Appearance of a new IR band at 2401cm−1 demonstrates that NH2–C=N moiety on pterin ring in folic acid is protonated when fluorene is introduced. The emergence of two charge transfer bands at 217 nm and 278 nm in UV difference spectra shows the presence of π-π complexation between folic acid and fluorene. These experiments confirm that fluorene could combine with the pterin ring of folic acid through π-π donor–acceptor interaction and induce the protonation process in folic acid upon strengthening electron accepting ability of pterin ring. The results suggest that complexatio

In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.

The new Schiff base, namely (2-Amino-phenylimino)-acetic acid (L) was prepared
from condensation of glyoxylic acid with o-phenylene diamine. The structure (L) was
characterized by, IR,
1
H,
13
C-NMR and CHN analysis. Metal complexes of the ligand (L)
were synthesized and their structures were characterized by Atomic absorption, IR and UV-Visible spectra, molar conductivity, magnetic moment and molar ratio determination (Co
+2
,
Cd
+2
) complexes. All complexes showed octahedral geometries.