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Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
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Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using six S-Boxes, as in the traditional method. Moreover, the CAST encryption algorithm was modified to be used on the private keys and substitution stage (S-Boxes), with the keys and S-Boxes of the encryption algorithm being generated according to the 2D and 3D chaotic map functions. The proposed system passed all evaluation criteria, including (MSE, PSNR, EQ, MD, SC, NC, AD, SNR, SIM, MAE, Time, CC, Entropy, and histograms). Results: Moreover, the results also illustrate that the created S-Boxes passed all evaluation criteria; compared with the results of the traditional method that was used in creating S-Box, the proposed method achieved better results than other methods used in the other works. The proposed solution improves the entropy which is between (7.991–7.999), reduces the processing time which is between (0.5–11 s/Images), and improves NCPR, which is between (0.991–1). Conclusions: The proposed solution focuses on reducing the total processing time for encryption and decryption and improving transmission security. Finally, this solution provides a fast security system for surgical telepresence with secure real-time communication. The complexity of this work needs to know the S-Box creation method used, the chaotic method, the values of the chaotic parameters, and which of these methods was used in the encryption process.

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Evaluation of Low Level Laser Therapy using 785 nm Diode Laser on the Enhancement of Chronic Wound Healing
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Low-intensity laser irradiation has been explored as an alternative, non-invasive method to encourage chronic wounds to heal. This study aimed to evaluate the effects of low level laser therapy (biostimulation) using semiconductor diode laser with wavelength (785 nm) on the enhancement of chronic wound healing. Fifty patients with chronic wounds were selected to be treated with Low Level Laser Therapy. Their ages ranged between 1 to 76 years. The wound sites were distributed in the lower limb, upper limb, trunk , perineum and head (70%,14%,12%,2%,2%, respectively). Application of laser therapy by noncontact method few millimeters from the skin for 15 minutes per one session twice weekly for two months ; ie,16 sessions for each patient. R

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult.
FORECASTING THE EXCHANGE RATES OF THE US DOLLAR AGAINST THE IRAQI DINAR USING THE BOX-JENKINS METHODOLOGY IN TIME SERIES WITH PRACTICAL APPLICATION
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The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

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Scopus
Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Horizontal Fragmentation for Most Frequency Frequent Pattern Growth Algorithm
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Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Modified Bees Swarm Optimization Algorithm for Association Rules Mining
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Mining association rules is a popular and well-studied method of data mining tasks whose primary aim is the discovers of the correlation among sets of items in the transactional databases. However, generating high- quality association rules in a reasonable time from a given database has been considered as an important and challenging problem, especially with the fast increasing in database's size. Many algorithms for association rules mining have been already proposed with promosing results. In this paper, a new association rules mining algorithm based on Bees Swarm Optimization metaheuristic named Modified Bees Swarm Optimization for Association Rules Mining (MBSO-ARM) algorithm is proposed. Results show that the proposed algorithm can

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Determination Optimum Inventory Level for Material Using Genetic Algorithm
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The integration of decision-making will lead to the robust of its decisions, and then determination optimum inventory level to the required materials to produce and reduce the total cost by the cooperation of purchasing department with inventory department and also with other company,s departments. Two models are suggested to determine Optimum Inventory Level (OIL), the first model (OIL-model 1) assumed that the inventory level for materials quantities equal to the required materials, while the second model (OIL-model 2) assumed that the inventory level for materials quantities more than the required materials for the next period.             &nb

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
An Improved Adaptive Spiral Dynamic Algorithm for Global Optimization
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This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
An Optimal Algorithm for Resource Allocation in D2D Communication
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