Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficacy of several classification algorithms on four reputable datasets, using both the full features set and the reduced features subset selected through the proposed method. The results show that the feature selection technique achieves outstanding classification accuracy, precision, and recall, with an impressive 97% accuracy when used with the Extra Tree classifier algorithm. The research reveals the promising potential of the feature selection method for improving classifier accuracy by focusing on the most informative features and simultaneously decreasing computational burden.
Facing the Iraqi economy, a number of economic challenges that threaten the future of Iraq and the security of economic, political and social, such as poverty, unemployment, inflation and the dilapidated infrastructure and rising production costs and administrative and financial corruption, environmental pollution, water problems and the deterioration of agricultural and industrial production, etc., and over the seriousness of these challenges, they are intertwined and overlapping and growing worse, without the corresponding adoption of state strategies that will develop appropriate solutions and appropriate to resolve those challenges because of concern the subject of security and terrorism, which requires the development of an
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Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared
... Show MoreThe physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t
... Show MoreWellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It
... Show MoreABSTRACT. 4-Sulfosalicylic acid (SSA) was used as a ligand to prepare new triphenyltin and dimethyl-tin complexes by condensation with the corresponding organotin chloride salts. The complexes were identified by different techniques, such as infrared spectra (tin and proton), magnetic resonance, and elemental analyses. The 119Sn-NMR was studied to determine the prepared complexes' geometrical shape. Two methods examined the antioxidant activity of (SSA) and prepared complexes; Free radical scavenging activity (DPPH) and CUPRRAC methods. Tri and di-tin complexes gave high percentage inhibition than ligands with both methods due to tin moiety; the triphenyltin carboxylate complex was the best compared with the others. Also, antibacter
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