Today, data security is a major problem concerning organizations and indi- viduals. The confidentiality of information is associated with using reliable and robust encryption algorithms in systems. Cyber-attacks on data and systems have become prevalent and sophisticated, and are increasing rapidly; hence, the need for developing robust encryption algorithms is crucial nowadays. This paper proposes a new encryption algorithm using dynamic symmetric key cryptography to encrypt text files. It utilizes a secret key for encryption and decryption processes, where the key’s length is varied depending on the text size. This presented approach gives a trade-off between speed and security, making it suitable for various applications, such as secure messages and files. It utilizes the Genetic Algorithm (GA) only for creating a robust key, which re- duces the complexity and computation overheads. The robustness and effectiveness of the proposed encryption algorithm were evaluated thoroughly by implementing several analysis tests, such as entropy, correlation, and the avalanche effect. The results of these tests demonstrate high randomness and uniformity in the created ciphertext and provide an important contribution to the enhancement of the cryptography field for protecting data.
The automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the leve
... Show MoreIntended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted
... Show MoreThe study using Nonparametric methods for roubust to estimate a location and scatter it is depending minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .
It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu
... Show MoreIn this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreGenetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem
... Show MoreIn architectural learning, it is difficult to stimulate cultural awareness through the traditional education approaches, which results in historic places being neglected as knowledge sources. This research explores the premise that sketch-based visual storytelling may act as a generative approach to connect cognition, emotion, and behavior in historical contexts. The study adopts a qualitative methodology to explore a learning experience comprising two phases: the first is a formal educational setting, and the second is a historical and cultural context, aiming to investigate the role of sketch-based storytelling in enhancing cultural awareness. MAXQDA was employed to code the students’ storyboards on three levels of cultural awareness, m
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