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 algorithm is used for segmenting the affected areas of skin cancer images. Finally, these segmented images are given to a deep learning classifier called Deep forest for prediction of skin cancer. The experiments are carried out on two publicly available datasets called ISIC-2019 and HAM10000 datasets for the analysis of segmentation and classification. From the outcomes, it is clearly verified that the projected model achieved better performance than the existing deep learning techniques.
Many of the proposed methods introduce the perforated fin with the straight direction to improve the thermal performance of the heat sink. The innovative form of the perforated fin (with inclination angles) was considered. Present rectangular pin fins consist of elliptical perforations with two models and two cases. The signum function is used for modeling the opposite and the mutable approach of the heat transfer area. To find the general solution, the degenerate hypergeometric equation was used as a new derivative method and then solved by Kummer's series. Two validation methods (previous work and Ansys 16.0‐Steady State Thermal) are considered. The strong agreement of the validation results (0.3
In this study, an efficient photocatalyst for water splitting was developed. The Cr2O3 and TiO2 nanoparticles (Cr2O3-TNPs) nanocomposite with (Chitosan extract) was created using ecologically friendly methods, such as the impregnation technique as TiO2 exhibits nano spherical (TNPs) shape structure. According to the researchers, this nanocomposite material enhanced its ability to absorb ultraviolet light while also speeding up the recombination of photogenerated electrons and holes. The TNPs and prepared Cr2O3-TNPs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive x-ray sp
... Show MorePolycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day) .The second group received
... Show MoreFace recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o
In this paper,we estimate the parameters and related probability functions, survival function, cumulative distribution function , hazard function(failure rate) and failure (death) probability function(pdf) for two parameters Birnbaum-Saunders distribution which is fitting the complete data for the patients of lymph glands cancer. Estimating the parameters (shape and scale) using (maximum likelihood , regression quantile and shrinkage) methods and then compute the value of mentioned related probability functions depending on sample from real data which describe the duration of survivor for patients who suffer from the lymph glands cancer based on diagnosis of disease or the inter of patients in a hospital for perio
... Show MoreBecause the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat
... Show MoreEndometriosis is a painful disease that affects around 5% of women of reproductive age. In endometriosis, ectopic endometrial cells or seeded endometrial debris grow in abnormal locations including the peritoneal cavity. Common manifestations of endometriosis include dyspareunia, dysmenorrhea, chronic pelvic pain and often infertility and symptomatic relief or surgical removal are mainstays of treatment. Endometriosis both promotes and responds to estrogen imbalance, leading to intestinal bacterial estrobolome dysregulation and a subsequent induction of inflammation.
In the current study, we investigated the linkage be