Psychological aspects are a major influence and motivation factor in many cinematic and television works such as television series. There are many films that dealt with psychological issues through the personality affected by psychological projections and complexes that lead towards abnormal behavior and actions in most cases, so the researchers chose the title and the research problem was raised through the following question: What is the mechanism that fulfills a psychological role in the narrative film? The objectives of the research were to reveal the mechanism used to instill psychological contents in the feature film? As for the limits of the research, it was an intentional sample, and the researchers adopted the descriptive anal

These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A

Abstract As the United Nations approaches its 70th anniversary, the world is going through the most severe accumulation of serious international security failures in recent memory, challenging the UN Security Council’s ability to address them effectively. Over the past four years, crises in Libya, Syria and Ukraine have precipitated a worrisome erosion of great power relations that has complicated Security Council decision making on a number of trouble spots. Its inability to devise consensus responses to the escalating civil war in Syria has been particularly troubling, resulting in the regional spill over into Iraq and the emergence of Islamic State as a new threat to peace in the region and beyond. Meanwhile, the UN’s often under

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

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