Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to a subsystem consisting of an Reversible Logic Gate (RLG) group to obtain the secret keys that are passed to Rivest Shamir Adleman (RSA) to finish encrypting the image. The results indicate that the proposed method has the ability to generate a very large set of highly complex and secure secret keys that can be used later in the encryption stage. Moreover, the number and complexity of those keys will change each time the image is changed, and this represents the contribution of the proposed method. They experienced no time loss throughout the encryption and decryption processes when using RLG, which indicates that the proposed system did a good job in making different keys from the same image. And it differs in the strength of the key from one image to another, depending on the nature of the color imge.
In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among
This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient
Can not reach a comprehensive concept for interior design through the use of Harmonization term according transformations experienced by the terms of the variables associated with the backlog of cultures that characterize concepts according to the nature of the users of the spaces in the design output, which necessitates the meaning of the combination of knowledge, art, science, such as the type of perceptions design the Harmonization cognitive science with art to create products of the use of design configurations that help the designer to put such a product within the reality and like the fact that reliable, as well as the rational knowledge tend somehow to the objective specifically in facilitating the substance subject to perceptible
... Show MoreThe current research deals with studying the aesthetics of symbolic values in the design of internal spaces and their connotations through their existence as a material value, as well as the symbolic meanings and their connotations that touch the spiritual and emotional side of the human being as an intangible value, and the research included four chapters, so the research problem was embodied by the following question (What is the role of values Symbolism and aesthetics in the design of interior spaces)? Therefore, the aim was to clarify the role of symbolic values and their aesthetics in the design of internal spaces. The first chapter included the importance of research, the need for it, the limits of the research and its terminology.
... Show MoreMalware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel
... Show MoreThe current research aims to develop the skills of the kindergarten students in designing and implementing a theater for gauntlets made of cardboard materials. To study this, the researcher determined to build teaching plans for design and implementation skills according to (Kolb model).
The results of this research showed the effectiveness of teaching plans according to (Kolb's model) in developing skills of design and implementation (theater for gauntlets made of cardboard materials) for the students of the Kindergarten Department - the experimental group. Which had a positive effect to reach the desired results in the design and implementation of the gauntlet theater and dealing with cardboard materials
The research aimed to identify the effectiveness of instructional design according to whole brain theory of Herman in the achievement of chemistry at the fifth scientific students at a secondary school of the General Directorate for Educational in Diyala / Baladruz in Iraq. The research sample Consisted of (57 student, (29) students as experimental group studied according to instructional design strategies for whole brain theory of Herrmann and (28) a student as a control group studied by the usual way for two semesters, a prepared achievement test as article and objective type of multiple choice, the coefficient stability of alpha-Cronbach equation reached (0.86). The research Results showed the presence of a statistically significant d
... Show MoreRehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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