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bsj-9029
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-cancerous cells to find the best combination of parameters in CNN to predict lung cancer accurately.  The proposed system recorded the highest accuracy of 92.79%. In addition to that, the paper addresses 192 observations made using the CNN model. 

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Optical Diagnosis of Prostate Cancer
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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Stress Analysis of the Hip Bone
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The bony pelvis has a major role in weight transmission to the lower limbs. The complexities of its geometric form, material properties, and loading conditions render it an open subject to biomechanical analysis.

 The present study deals with area measurement, and three-dimensional finite element analysis of the hip bone to investigate magnitudes, load direction, and stress distribution under physiological loading conditions.

 The surface areas of the auricular surface, lunate surface, and symphysis pubis were measured in (35) adult hip bones. A solid model was translated into ANSYS parametric design language to be analyzed by finite element analysis method under different loading conditions.

The surface

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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Global Pharma Technology
Evalution of the effect of Gigaspora margarita and Glomus desriticola fungi in stimulating the resistance of the capsicum annuum L. plant towards chromium and lead
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The present study was conducted to evaluate the effect of fungi Gigaspora margarita and Glomus desriticola in stimulating the resistance of the capsicum annuum L. towards the chromium and lead after 60 days, planting and using the pots in the glass house. The highest concentration of chromium and lead in the root was found in the presence of the mycorrhizal mixture (194.93, 150.40) μg / g, respectively, compared to the lowest concentration (90.69, 79.37) μg / g respectively, while the highest concentration of chromium and lead in the shoot was found in the presence of the mycorrhizal mixture (94.63, 79.33) μg / g respectively, compared with the lowest concentration in the control treatment (72.58, 60.70) μg / g respectively. The results

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Publication Date
Fri Nov 27 2020
Journal Name
Journal Of Physics: Conference Series
Investigation of the State Vectors and Prediction of the Orbital Elements for Spot-6 Satellite during 1300 periods with Perturbations
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Abstract<p>Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4<sup>th</sup> order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 an</p> ... Show More
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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
China's Soft Power and Diplomacy towards Middle East Region after 2011
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The study deals with China's soft power and diplomacy in the Middle East, and it focuses specifically on the tools and foundations of China's soft diplomacy and how it achieves its goals in the region in addition to its challenges in the region. In this regard, the study also focuses on the Chinese Belt and Road Initiative and its soft foundations and how they serve China’s diplomacy and soft power in the region. The study ends with a set of conclusions, perhaps the most prominent of which is that diplomacy and soft power have become a fundamental pillar of China's foreign policy to achieve its foreign goals and to establish an international system compatible with China's principles. As for the Middle East, China has established a poli

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Development prediction algorithm of vehicle travel time based traffic data
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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Wellbore Breakouts Prediction from Different Rock Failure Criteria
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One of the wellbore instability problems in vertical wells are breakouts in Zubair oilfield. Breakouts, if exceeds its critical limits will produce problems such as loss circulation which will add to the non-productive time (NPT) thus increasing loss in costs and in total revenues. In this paper, three of the available rock failure criteria (Mohr-Coulomb, Mogi-Coulomb and Modified-Lade) are used to study and predict the occurrence of the breakouts. It is found that there is an increase over the allowable breakout limit in breakout width in Tanuma shaly formation and it was predicted using Mohr-Coulomb criterion. An increase in the pore pressure was predicted in Tanuma shaly formation, thus; a new mud weight and casing pr

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