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 research aims to reveal the role of financial analysis in rationalizing the investor decision on the Iraqi stock Exchange market, by studying the relationship and impact techniques and methods of financial analysis on the decisions of investors in the market. The most important techniques and methods discussed in this study were: analysis (financial ratios analysis, comparison of financial statements analysis, cash flow statement analysis) for companies listed in the Iraqi stock Exchange market. The researcher adopted the analytical descriptive method which depends on the collection of data on the phenomenon and its interpretation. The questionnaire wa
... Show MoreSocial networking sites represent one of the modern communication technologies that have contributed to the expression of public opinion trends towards various events and crises of which security crisis is most important being characterized by its ability to influence the community life of the public. In order to recognize its role in shaping opinions of the educated class of the public that is characterized by a high level of knowledge, culture and having experience in dealing with the media. Its advantage is that they have an active audience by expressing their views on the situations, events, and news published on them as well as expressing their attitudes and sympathy with the events. So a number of questions are included in the ques
... Show MoreThe objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le
... Show MoreIn Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.
... Show MoreThe aim of the research is to identify the economic and cultural role of contemporary interactive artworks from the public's point of view, with knowledge of the most important obstacles and proposals to improve the level of design and spread of interactive artworks. The descriptive approach was used, and the researcher used a questionnaire tool that was distributed to the audience for the events of Noor Al Riyadh (2021) and the size of the participating sample was (194) individuals from all spectrums of society. It was found through the results of the existence of public approval of the economic role of contemporary interactive artworks, as they contribute to supporting the national economy. It attracts the public to attend various paid
... Show MoreObjective:To Evaluate of Estradiol and Prolactin hormones levels for Breast Cancer women in
Baghdad City.
Methodology: The current study was conducted on 60 breast cancer women and 40 apparently
healthy subjects to evaluate the levels of estradiol and prolactin "hormones in the serum" of
({premenopausal & postmenopausal}) breast cancer and healthy controle women. Estradiol and
prolactin hormones estimated for all cases by using the IMMULITE 2000 instrument that performs
chemiluminescent immunoassays results are calculated for each sample.Data were analysed using
SPSS-18.data of two groups was comparison by the student's t-test.
Results: The results showed a non significant""(P>0.05) elevation in the –mean
Genetic polymorphisms of genes whose products are responsible for activities, such as xenobiotic metabolism, mutagen detoxification and DNA-repair, have been predicted to be associated with the risk of developing lung cancer (LC). The association of LC with tobacco smoking has been extensively investigated, but no studies have focused on the Arab ethnic- ity. Previously, we examined the association between genetic polymorphisms among Phase I and Phase II metabolism genes and the risk of LC. Here, we extend the data by examining the correlation of OGG1 Ser326Cys combined with CYP1A1 (Ile462Val and MspI) and GSTP1 (Ile105Val and Ala103Val) polymorphisms with the risk of LC. Polymerase chain reaction- restriction fragment length polymorphism (
... Show MoreInformation from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect
... Show MorePermeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.
This paper will try to develop the permeability predictive model for one of Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).
Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua
... Show MoreThis paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue
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