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A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      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.

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Publication Date
Tue Oct 29 2019
Journal Name
Journal Of Engineering
Demand Priority in a Power System With Wind Power Contribution Load Shedding Scheme Based
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The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

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Publication Date
Thu Jun 15 2023
Journal Name
Romanian Neurosurgery
A giant A4-A5 distal anterior cerebral artery aneurysm treated with microsurgical clip reconstruction
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Background. Aneurysms of the distal anterior cerebral artery (DACA) are uncommon; they often form near the pericallosal-callosomarginal junction and are typically small. To our knowledge, giant DACA aneurysms developing from the more distant parts of the anterior cerebral artery (ACA), A4-5, have been described only once in the literature. Case description. A 66-year-old gentleman reported with a brief loss of consciousness followed by weakness in his right lower leg. The patient was admitted with a Glasgow Coma Score (GCS) of 15. A computed tomography (CT) scan of the head revealed a left hyperdense mass in the frontal parasagittal supracallosal region. Contrast MRI revealed a heterogeneously enhancing mass measuring 35x30x25 mm. C

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Relationship Between Orexin-A and Insulin Resistance in Patients with Type 2 Diabetes Mellitus
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Background: Orexin-A is an orexigenic hormone that plays an important role in the metabolism of blood glucose, insulin, and insulin resistance (IR). The pathogenesis of type 2 diabetes mellitus (T2DM) is related to the abnormality in insulin and IR. However, no sufficient studies to date have clearly shown the association of orexin-A with biochemical parameters related to T2DM.

Objectives: The aim of this study was to determine the relation of orexin-A with IR and how they associate with physiological changes in T2DM patients. Understanding this relation will offer some pharmacological tools to reduce some complications in diabetes.

Materials and Methods: A total of 41 T2

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
A Comparative Study on the Double Prior for Reliability Kumaraswamy Distribution with Numerical Solution
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This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Sun Apr 28 2024
Journal Name
Bmc Medical Education
Pharmacy faculty experiences with student academic entitlement: a multinational study from the Arab world
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Abstract<p>Academic Entitlement (AE) is the expectation by students to receive high grades or preferential treatment without significant effort. Exploring AE from faculty perspective has not been investigated in Arab colleges of pharmacy. The aim of this study was to explore experiences and perceptions towards student AE among pharmacy faculty in the Arab World. A cross-sectional, self-administered, anonymous, electronic survey was sent to pharmacy faculty across pharmacy colleges in Arab countries. The survey collected demographic data, an AE measure including 17 items reflecting seven AE components, and faculty perceptions and perceived reasons for AE. A total of 345 responses were collected. The AE level wa</p> ... Show More
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Modified Model to Calculate Low Earth Orbit (LEO) for A satellite with Atmospheric Drag
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In this paper, the satellite in low Earth orbit (LEO) with atmospheric drag perturbation have been studied, where Newton Raphson method to solve Kepler equation for elliptical orbit (i=63 , e = 0.1and 0.5, Ω =30 , ω =100 ) using a new modified model. Equation of motion solved using 4th order Rang Kutta method to determine the position and velocity component which were used to calculate new orbital elements after time step ) for heights (100, 200, 500 km) with (A/m) =0.00566 m2/kg. The results showed that all orbital elements are varies with time, where (a, e, ω, Ω) are increased while (i and M) are decreased its values during 100 rotations.The satellite will fall to earth faster at the lower height and width using big values for ecce

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique
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Abstract<p>Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essent</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Transportation Model Technique to Determine the Minimum Total Cost Using a Novel Ranking Function
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The transportation problem (TP) is employed in many different situations, such as scheduling, performance, spending, plant placement, inventory control, and employee scheduling. When all variables, including supply, demand, and unit transportation costs (TC), are precisely known, effective solutions to the transportation problem can be provided. However, understanding how to investigate the transportation problem in an uncertain environment is essential. Additionally, businesses and organizations should seek the most economical and environmentally friendly forms of transportation, considering the significance of environmental issues and strict environmental legislation. This research employs a novel ranking function to solve the transpor

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