Mustansiriyah journal of pure and applied sciences

In this study, a hybrid encryption scheme is proposed for secure encryption of various types of data such as images, text, documents, and videos. The scheme employs 6-D chaos to generate unpredictable and highly secure keys for the RC6 encryption algorithm. The proposed method also constructs eight new S-boxes and eight new P-layers to enhance the security of the encryption process. The S-boxes and P-layers are generated using chaotic initial state parameters and stored in arrays for use in the encryption process. The encryption process uses the RC6 algorithm, S-boxes, and P-layers, with eight rounds of encryption. The resulting cipher text is highly secure and suitable for protecting sensitive data. The proposed scheme is evaluated for security and efficiency using various metrics, and the results show that the proposed scheme outperforms existing methods in terms of security and efficiency. The proposed scheme is a promising approach for secure encryption of various types of data in real-world applications. The test results indicate to the highest value of peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel change rate (NPCR) are 7.748 dB, 33.4842 and 99.6082, respectively. While the encryption and decryption speed up 0.1735 and 0.1864 second respectively.

The thyroid gland in pregnant women undergoes significant structural and physiological changes. One example is the universal enlargement of the gland in pregnant women in countries with sufficient and deficient body iodine levels. In addition, an increase of 50% occurs in both the production of the thyroid hormones and the daily need for iodine. Such alterations also continuously occur in women in general, but the pathological reactions taking place during pregnancy may lead to various aspects of dysfunction of the glans, including hypothyroidism which is commonly observed in pregnant women who might be seriously affected, along with the developing fetus. The situation can become complicated with other physiological disorders, including gestational hypertension, premature delivery, and fetal growth restriction. About 3 to 5 % of pregnant women develop hypothyroidism, making it the main form of thyroid dysfunction in this group of women. As compared to the overt form, subclinical hypothyroidism occurs in a higher frequency. It is diagnosed when the level of the thyroid-stimulating hormone (TSH) in the serum is higher compared to the pregnancy-specific reference range. Hormone levels higher than 2•5 mIU/L in the 1st trimester and 3 mIU/L in the 2nd and 3rd trimesters are also indicative of this condition. However, a number of studies reported serum TSH values of 5-10 and >10 mIU/L to diagnose subclinical and overt hypothyroidism, respectively. Close monitoring is especially important during the first trimester because untreated hypothyroidism during this time might lead to irreversible disorders in the nervous system of the developing fetus.

In this paper, the parameters and reliability of the inverse Kumaraswamy distribution were estimated through estimation methods namely: Moments, Modified Moments, Percentiles, White, Modified White and Maximum Likelihood. The simulation was used for estimation through samples of different sizes and then the mean square error criterion was used to compare between them. The results obtained from parameter estimators are shown: As for the shape parameter, the Percentile method is the best in most of the experiments that were used, for the exponentiated parameter, the Maximum Likelihood method is the best in most of the experiments conducted. As for reliability, its preference varies between the Maximum Likelihood method and the Modified White method.

The newest energy source that is non-depleting, affordable, and easy to harness by various users is wind energy. One of the possible locations in Iraq for wind energy generation is Al-Shihabi area, since there is a big lack of information regarding the power of at this location, additional studies and researches of wind are crucial. A precise planning and execution of any wind energy project requires a shared understanding of the behavior of the wind. This paper‟s goal is to explore the potential for wind energy in Al-shihabi area, which is located south of Wassit, Iraq. Because of this, wind data were gathered for a year between December 2014 and December 2015 at heights of 10, 30, and 50 meters, in 10-minute intervals. After that, for the examination of datasets (the weibull-probability distribution function was conducted in order to evaluate of the wind energy power, and the Fast-Fourier-Transform was employed for spectral analyses. Giving spectral analysis for the data, the average yearly wind speed at 50 m was 6.84 m/sec, and the peak wind speed was 185921.078 -m/sec/12hour at a frequency of (2 Hz) at that height throughout night hours. And for the lowest values of wind speed was about 95161.3369- m/sec/12hour for the (2 Hz) frequency at that height throughout night hours. The wind was blowing faster in the morning than it was at night. While the predominant wind directions in the region were from the north-northwest and west-northwest.

In recent years, image encryption algorithms have been developed to protect against unauthorized persons and maintain the privacy of recipients. Therefore, it is very important to choose the right algorithm and build it in a way that meets security and performance requirements. The DES algorithm is slow in encryption and decryption operations and vulnerable to attacks. There is a lightweight block cipher for devices with limited resources. May be more vulnerable than differential cryptanalysis. The study suggests that to encrypt and decrypt images as quickly as possible, to achieve security, the key of the two algorithms (DES-Present) was generated using a two-dimensional chaos equation system. Where the Twice DES algorithm executes four rounds within each round, the present algorithm executes only four rounds. The performance evaluation of the proposed algorithm was measured through several metrics, where a PSNR low value of (8.614653) indicates that the good encryption quality, Reverse it high value MSE (8945.715332) and MAE (77.625417) this indicates that the original image is completely different from the encrypted image. The NPCR high value of (99.4965%) indicates a high degree of accuracy in changing pixel values. In addition, the uniform average change intensity (UACI) less than30 % shows that the algorithm is good at making large changes in pixel intensity. Correlation coefficient test: horizontal 0.002574; diagonal -0.003017; vertical -0.035860 this indicates that all three correlation values are close to zero. Key space equal for the ) is It is quite enough space to resist brute force penetration. The results showed that the proposed algorithm is good for encrypting color images, which makes it suitable for use in various applications that need security and speed.

The advancement of computerized automated diagnostic technologies ensures that health plants are more effective by detecting diseases early. The damage caused by them can be minimized. Recently, many scientists have been trying to use methods and algorithms in image processing and extracting features based on color, texture, and shape and employing them in building smart systems capable of detecting plant diseases in their early stages. In this paper, proposed a smart farming aims to automated remove shadow and segmentation the pepper fruit diseases region, then extracted strong features from diseases region, and finally detected and diagnosis pepper fruit disease using PNN algorithm. In addition, in this work we used, (Diyala Pepper), which relies on a dataset of pepper plants named Diyala Pepper. The suggested system's implementation was done on a real dataset of pepper fruits. Experimental results of the proposed method showed 100% accuracy in the training phase and 81.82% in the phase of testing.

In this paper we show that, every Jordan generalized higher symmetric reverse bi-derivations is a generalized higher symmetric reverse bi-derivations on a ring M. Additionally, a generalized higher symmetric reverse is Jordan generalized higher symmetric triple reverse bi-derivation on a 2-torsion free ring M.

The study aims to use a quantum gate to create eight entangled states in a quantum circuit consisting of four qubits. Where using gates | ⟩ entanglement states can be shown, by using quantum gates that give the same arrangement as the circuit gates and for the same inputs, taking into account the outputs of a quantum circuit containing entangled functions. The study explains how to use control gates to isolate specific qubits. And measuring their condition, which allows for studying the interconnection between them. Study methodology: Using The results indicated that the change in the output states occurred effectively in all eight state (The quantum circuit was simulated using the MATLAB R2023b quantum computing language) and that similar results could be obtained using gates operating on three qubits, but the entangled state created by the CNOT gates must be preserved. The results also indicated that it is not possible to create 8 states for one state. The output of a two-qubit quantum circuit | ⟩ , but this can be generated for a 3-qubit quantum circuit, and we also need three Hadamard gates and this applies to (( , where It represents the number of qubits in the circuit.

In order to provide a new method for partial optimal control of systems, this work uses Bernoulli wavelets and uses Caputo's formula to solve partial optimal control problems (FOCPs) with inequality constraints. For the new optimization technique, the work uses partial order Bernoulli wave functions (F-BWFs) as basic functions. The answer using this method is expressed in terms of F-BWF where the coefficients have not yet been found. To simplify FOCPs in a system of nonlinear algebraic equations the procedure entails transforming inequality constraints into equality requirements by using operational matrices of fractional integration and F-BWFs and using the multipliers technique Lagrange. Numerical examples confirm the validity of the proposed strategy and demonstrate its correctness and efficiency when compared to the analytical or approximate answers provided by other methods.

The method of electrospinning with a rotating cylinder collector was used to prepare PMM/TiO2 nanofibers. The effect of the collector rotation speed on the diameters, morphology, and structural properties of the prepared PMM/TiO2 nanofibers was studied, with the remaining parameters of the electrospinning system held constant. relied on the FE-SEM to study the diameters and regularity of the prepared nanofibers, which showed that the obtained nanofibers with diameters of 366 nm decreased to 127 nm and their regularity increased as the collector speed increased. The X-ray diffraction spectra showed that the prepared PMM/TiO2 nanofibers have an amorphous structure and begin to transform into a polycrystalline structure with increasing collector speed. Functional groups identified through FTIR tests have been shown to not be affected by the increase in rotation speed, regularity, or decrease in the diameter of the prepared PMM/TiO2 nanofibers.

The study focuses on the optimization of black silicon (B-Si) fabrication via etching using a solution composed of KOH, NaOH, and Na2SiO3 at constant concentrations and varying durations. Surface morphology was analyzed using Field Emission Scanning Electron Microscopy (FE-SEM). The results showed that pyramidal structures were formed on the silicon surface with heights between 1.2 and 4.1 μm. The uniform distribution was confirmed by AFM images. The surface roughness decreased as the etching time increased; it was measured at 14.03 nm for 15 minutes and 5.59 nm for 30 minutes. The properties of photoluminescence (PL) were evaluated using a spectrometer and it was found that peak emission shifts to lower energies (red shift) when etching time is increased. Optical reflectivity decreases sharply when etching time is increased. Additionally, the longer the etching duration, the greater the energy gap of the material which increased from 1.25 eV to approximately 1.4 eV.

Diopside (CaMgSi₂O₆), a calcium magnesium silicate mineral, is of significant interest for its potential applications in ceramics, bioceramics, and glass-ceramics due to its excellent thermal and mechanical properties. This study explores the synthesis of diopside powders using the sol-gel method, a versatile chemical process that offers precise control over composition and homogeneity at the molecular level. The sol-gel process involves hydrolysis and polycondensation of metal alkoxides in an aqueous or alcoholic solution, followed by drying and calcination to achieve the desired crystalline phase. In this work, calcium nitrate (Ca(NO₃)₂·4H₂O), magnesium nitrate (Mg(NO₃)₂·6H₂O), and tetraethyl orthosilicate (TEOS, Si(OC₂H₅)₄) were used as precursors for Ca, Mg, and Si, respectively. The preparation began with dissolving the metal nitrates in deionized water, followed by the addition of TEOS under continuous stirring to form a clear sol. The sol was then aged, dried, and calcined at various temperatures to determine the optimal conditions for diopside formation.
Characterization techniques such as - Thermal gravimetric analysis (TGA) Differential thermal analysis(DTA),X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR) were employed to analyze the phase composition, microstructure, and chemical bonding of the synthesized powders scanning electron microscopy (SEM),. The results indicated that a pure diopside phase was successfully obtained at a calcination temperature of around 900°C, with the powders exhibiting a fine and uniform microstructure

Heart disease is a leading cause of death worldwide and a major global health concern. For effective treatment and prevention, early and accurate diagnosis is essential. To increase the efficiency and objectivity of heart disease diagnosis, this study investigates the application of machine learning techniques. Large datasets can be analyzed by machine learning algorithms, which can also identify complex patterns that human specialists might overlook. However, since different models have different hypothesis spaces, some patients whose features do not match may be missed. To improve diagnostic accuracy, we propose a novel strategy that combines multiple machine learning methods and professional judgment. To assign appropriate relevance to patient data and expert opinions, we seek to use advanced weighting methods based on artificial neural networks. Our prototype was evaluated on the University of California, Irvine, heart disease dataset and outperformed other techniques including XGBoost, SVC, and decision trees, with a maximum accuracy of 96.65%. The model achieved the highest accuracy, significantly outperforming other methods. Other techniques used include XGBOOST: 79.61, SVC: 73.41, DT: 54.02, RF: 74.92, KNN: 54.21. This strategy has the potential to enhance clinical decision-making frameworks and enhance the recognition of heart disease.

Due to the importance of integral equations in engineering and scientific applications, there are many papers that have solved integral equations of both linear and nonlinear types.In this paper, Karry-Kalim Adnan transform (KKAT) is utilized to find the solution of convolution kind linear Volterra equations of the first and second kind. Examples are offered to illustrate the Karry-Kalim Adnan technique for solving convolution kind Volterra operator equations. It was noted that this technique is much easier in terms of mathematical operations and simplicity in arriving at the exact solution and this is explained through the applications in the paper.

This research presented reliability formula for multicomponent stress-strength of coherent system, based on Chen Distribution with unknown parameters and known common parameter . Three methods discussed for estimating the parameters of Chen distribution that used to estimate the reliability function using Maximum Likelihood, Pitman and Least Square Methods. These estimates are compared via a simulation study using mean square error criteria to large, medium and small samples. The comparison’s most important results are that the estimator performs of the maximum likelihood is better in most of the experiments that have been studied.

In this study, Al:CdS-PVA nanocomposites thin films were prepared on glass substrates by the chemical bath deposition (CBD) method. The impact of aluminum (Al) concentrations of (0, 0.04, 0.08, and 0.12) M on the crystal structure and morphology characteristics of the prepared nanocomposites film was investigated. XRD tests show that all of the samples have a polycrystalline crystal structure with a cubic phase for CdS. The (111) plane is the preferred orientation. The Al:CdS-PVA film crystallinity improved, and the crystallite size increased with the increase in Al concentrations. The surface morphology from FESEM images showed that the Al:CdS-PVA nanocomposites film surface is porous. The AFM results showed that surface roughness and RMS values increased with an increasing of impurity