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.
Providing Iraqi students with proficiency in English is the ultimate goal of the educational system which is a way of getting knowledge in the fields of arts, sciences, transferring knowledge and sciences to other communities. Therefore, conducting such a type of study is very important because the contents of English textbooks have a huge influence on learning of the students. Once the content of English textbooks contain errors as the correct one, this will effect on his/her learning. The present study is an attempt to evaluate the new course entitled “English for Iraq” for fifth grade students for secondary schools, by Olivia Johnston and Mark Farell. It aims to answer eleven questions relating to the following domains: strength, obj
... Show MoreNew chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: 1HNMR, 13CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N3O2, N2O2, and the geometry of the new complexes are identified as octahedral for (Rh & Pt) complexes a
... Show MoreThis study was aimed to determine the mutations and single nucleotide polymorphisms (SNPs) in exon 3 and 7 of estrogen receptor beta (ESR2) gene in women with breast cancer from Iraq. Different samples (blood, fresh tissue with blood from same patient, and formalin fixed paraffin embedded, FFPE) were collected from women with breast cancer. Molecular analysis exon 3 and 7 in ESR2 has been studied by using PCR. It was found exon 3 and 7 in ESR2 were revealed as a single band with size 151 and 157 bp, respectively. There was no SNP in exon 3 has been identified. While three novel polymorphisms (ACT, AGG and GCA) were detected in exon 7, the type of those polymorphisms deletion for ACT and AGG while substitution polymorphism for GCA. From this
... Show MoreNew chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: 1HNMR, 13CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N3O2, N2O2, and the geometry of the new complex
... Show MoreCitrus fruits are one of the consumer agricultural products of the Iraqi citizen. It is rich in vitamins and usedin many food industries as well as medicines. Classifying the amount of production of citrus treesaccording to the producing governorates has been done to find a map that shows the production of citrustrees according to Iraqi governorates. A cluster analysis method was used according to the hierarchicalmethod. The results showed that Najaf and Qadisiyah are the most similar in citrus production, whileSaladin and Najaf were the two governorates with the furthest distance in proximity matrix. Diyalagovernorate was clustered in the first cluster within two, three, four or five of the clusters for classifyingIraqi governorates covere
... Show MoreIn this research we present An idea of setting up same split plots experiments in many locations and many periods by Latin Square Design. This cases represents a modest contribution in area of design and analysis of experiments. we had written (theoretically) the general plans, the mathematical models for these experiments, and finding the derivations of EMS for each component (source) of sources of variation of the analysis of variance tables which uses for the statistical analysis for these expirements
In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg
... Show MoreThe continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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