Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors.
Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o
... Show MoreIntrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system
... Show MoreHeart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,
... Show MoreIn this paper, a new class of nonconvex sets and functions called strongly -convex sets and strongly -convex functions are introduced. This class is considered as a natural extension of strongly -convex sets and functions introduced in the literature. Some basic and differentiability properties related to strongly -convex functions are discussed. As an application to optimization problems, some optimality properties of constrained optimization problems are proved. In these optimization problems, either the objective function or the inequality constraints functions are strongly -convex.
The main aim of conducting this research is to identify the applications of Smart libraries in the Arab world. The Researcher relied on the documentary and Survey approach to collect information and data through the Internet, and to get to know these libraries. Then the Research came in three sections dealing with the first topic: The general framework of the study. The second topic deals with: introducing Smart libraries and indicating their types and characteristics. The Third topic dealt with the requirements of Smart libraries'application by identifying the basic components of it (Smart building, Smart Librarian , Smart devices, systems and software, Smart information sources,and Smart beneficiaries), and dealt with Smart libraries appl
... Show MoreIn the last period there have been rapid developments and increased interest in the integration of the environment into urban planning. It has occupied a large part of the world’s most economically and economically important concerns, emphasizing the need to adopt the concepts of green urban construction as a basis for future cities. Both human and nature to continue and stay. Hence, the importance of research in building a base on the planning and design principles of the eco-friendly city for the purpose of local adoption”, thus facing the problem of” lack of application of knowledge on the basis of planning and design eco-friendly city. The hypothesis that “the development
The overlap between science and knowledge is a feature of the 21st century. This integration, which crosses the traditional boundaries between academic disciplines, has occurred because of the emergence of new needs and new professions. This overlap has overshadowed the arts in general and design in particular. The Design achievements have not been far away from the attempts of integration of more than one type or design application to produce new outputs unique in its functional and aesthetic character, including the terms of internal graphic design.
The researcher raises the question of the functional dimension of graphic design in the internal space, in order to answer it through the methodological framework, which includes th
... Show MoreSome new heterocyclic compounds containing, cyclohexenone, indazole, isoxazoline, pyrmidine and pyrazoline ring system were prepared from chalcones (1a,b). The starting chalcones (1a,b) were obtained by a base catalyzed condensation of appropriately substituted benzaldehydes and 2-acetylbenzofuran. The reaction of the prepared chalcones with ethylacetoacetate/hydrazine hydrate, hydroxylamine hydrochloride, urea, thiourea, hydrazine hydrate, phenyl hydrazine or hydrazide derivatives gave the mentioned heterocycles. All synthesized compounds have been characterized by physical and spectral methods.
Kriging, a geostatistical technique, has been used for many years to evaluate groundwater quality. The best estimation data for unsampled points were determined by using this method depending on measured variables for an area. The groundwater contaminants assessment worldwide was found through many kriging methods. The present paper shows a review of the most known methods of kriging that were used in estimating and mapping the groundwater quality. Indicator kriging, simple kriging, cokriging, ordinary kriging, disjunctive kriging and lognormal kriging are the most used techniques. In addition, the concept of the disjunctive kriging method was explained in this work to be easily understood.
A new family of distribution named Double-Exponential-X family is proposed. The proposed family is generated from the double exponential distribution. The forms of the probability densities and hazard functions of two distinct subfamilies of the proposed family are examined and reported. Generalproperties such as moment, survival, order statistics, probability weighted moments and quartile functions of the models are investigated. A sub family of the developed family of double –Exponential-X family of the distribution known as double-Exponential-Pareto distribution was used to fit a real life data on the use of antiretroviral drugs. Molecular simulation of efficacy of antiretroviral drugs is conducted to evaluate the performance of the
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