Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of security to Triple Data Encryption Standard algorithm using Nth Degree Truncated Polynomial Ring Unit algorithm. This aim achieved by adding two new key functions, the first one is Enckey(), and the second one is Deckey() for encryption and decryption key of Triple Data Encryption Standard to make this algorithm more stronger. The obtained results of this paper also have good resistance against brute-force attack which makes the system more effective by applying Nth Degree Truncated Polynomial Ring Unit algorithm to encrypt and decrypt key of Triple Data Encryption Standard. Also, these modifications enhance the degree of complexity, increase key search space, and make the ciphered message difficult to be cracked by the attacker.
In this study, the circulating fluidized bed was used to remove the Tetracycline from wastewater utilizing a pistachio shell coated with ZnO nanoparticles. Several parameters including, Tetracycline solution flowrate, initial static bed height, Tetracycline initial concentration and airflow rate were systematically examined to show their effect on the breakthrough curve and the required time to reach the adsorption capacity and thus draw the fully saturated curve of the adsorbent. Results showed that using ZnO nanoparticles will increase the adsorbent surface area and pores and as a result the adsorption increased, also the required time for adsorbent saturation increased and thus the removal efficiency may be achieved at mi
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In this paper, the generation of a chaotic carrier by Lorenz model
is theoretically studied. The encoding techniques has been used is
chaos masking of sinusoidal signal (massage), an optical chaotic
communications system for different receiver configurations is
evaluated. It is proved that chaotic carriers allow the successful
encoding and decoding of messages. Focusing on the effect of
changing the initial conditions of the states of our dynamical system
e.i changing the values (x, y, z, x1, y1, and z1).
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The thermal method was used to produce silicoaluminophosphate (SAPO-11) with different amounts of carbon nanotubes (CNT). XRD, nitrogen adsorption-desorption, SEM, AFM, and FTIR were used to characterize the prepared catalyst. It was discovered that adding CNT increased the crystallinity of the synthesize SAPO-11 at all the temperatures which studied, wile the maximum surface area was 179.54 m2/g obtained at 190°C with 7.5 percent of CNT with a pore volume of 0.317 cm3/g ,and with nano-particles with average particle diameter of 24.8 nm, while the final molar composition of the prepared SAPO-11 was (Al2O3:0.93P2O5:0.414SiO2).
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Nanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above while the non-filtered sample purity was around The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous
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Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.
In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include
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Orthogonal polynomials and their moments have significant role in image processing and computer vision field. One of the polynomials is discrete Hahn polynomials (DHaPs), which are used for compression, and feature extraction. However, when the moment order becomes high, they suffer from numerical instability. This paper proposes a fast approach for computing the high orders DHaPs. This work takes advantage of the multithread for the calculation of Hahn polynomials coefficients. To take advantage of the available processing capabilities, independent calculations are divided among threads. The research provides a distribution method to achieve a more balanced processing burden among the threads. The proposed methods are tested for va
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