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.
Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m
... Show MoreColon cancer is an abnormal growth of cells that occurs in the large intestine. Sometimes growth remains restricted for a relatively long time before it becomes a malignant tumor and then spreads through the intestinal wall to the lymph nodes and other parts of the body. The study aims to estimate the effectiveness and partial purification of lipoxygenase (LOX) enzyme and measure gamma-glutamyle transferase (GGT) activity in serum patients of colon cancer in Baghdad. The study included (80) case male patients with colon cancer with (50) samples of apparently healthy males (control) as comparison group. The result displayed a noteworthy increase in lipoxygenase effectivene
... Show MoreBackground: Previous studies about the correlation of genetic polymorphisms in the multigene family of cyto- chrome P450 (CYPs), the effect of tobacco smoking, and the risk of developing cancer have been well in- vestigated in different populations, but not in Iraq. Furthermore, the studies of malignance occurrence re- lationship with cigarette tobacco smoking revealed the presence of strong association, however, little is known about the risk of Waterpipe (WP) tobacco smoking. Thus, determination two important genetic polymorphisms in CYP1A1, a main member of CYPs, among Iraqi men was our first aim. This is the first study that highlights the correlation of CYP1A1 polymorphisms with the risk of lung cancer in Iraq. The second aim was to ev
... Show MoreThe aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est
... Show MoreEncouraging micro-enterprises for comprehensive economic development are crucial to achieve the ambitious vision 2030 of the Kingdom of Saudi Arabia.
Small and Medium enterprises are inputting around 15.5 per cent to GDP while 33 per cent contribution as a private sector to Saudi Arabia's gross domestic product (GDP). This study aims to identify the most important factors that affect the efficiency of small enterprises in Saudi Arabia. To accomplish this objective, the study was conducted for small projects via the comprehensive inventory method under the supervision of the Institute of Entrepreneurship. A total of 282 questionnaires were collected from entrepreneurs and the differentiation analysis
... Show MoreCorruption, in all its categories and forms, is regarded as the nowadays virus which has greatly spread in most institutes and society, a matter that cause a great waste of resources.
According to the reports of international transparency Institute, Iraq is regarded as one of the greatest countries in corruption.
Regardless of the reasons and forms of corruption, the retreat in work – values and ethics are the main reasons behind that.
Being the main source of providing qualified staff "educators" for the working market, the high education institutes face great challenges in standing against corruption inside and outside
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