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.
The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
... Show MoreTerrorism is a global phenomenon that engulfs most regions of the world to varying degrees. Media outlets are aware of the many incidents of violence and terrorism that have increased in recent times. The differences between the size of the phenomenon in different societies are the causes and severity of the phenomenon. On the role of local satellite channels in shaping the knowledge and trends of the Iraqi public towards the events of terrorism, in light of the assumptions of reliance on the media. The importance of this study is that it assesses the role of local satellite channels in the formation of knowledge and trends The study seeks to know the extent of exposure of the Iraqi public to local satellite channels, and to reveal the e
... Show MoreGlutathione-S-transferases (GSTs) play a role in the detoxification of environmental chemicals and mutagens, such as those inhaled during tobacco smoking. There have been conflicting reports concerning GST polymorphisms as risk factors in the development of lung cancer. No studies focused on Arab populations exposed to Waterpipe (WP) tobacco smoke have been undertaken. Here Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) and gene sequenc- ing were applied to analyze allelic variations in GSTP1-rs1695 and -rs1138272 amongst 123 lung cancer patients and 129 controls. The data suggest that WP smoking raised the risk of lung cancer more than three-fold (OR 3.6; 95% CI 2.1–6.0; p < 0.0001). However, there was no s
... Show MoreThis paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign
... Show MoreObjective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign
... Show MoreThis article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t
... Show MoreThe inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end
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