The Skyrme–Hartree–Fock (SHF) method with the Skyrme
parameters; SKxtb, SGII, SKO, SKxs15, SKxs20 and SKxs25 have
been used to investigate the ground state properties of some 2s-1d
shell nuclei with Z=N (namely; 20Ne, 24Mg, 28Si and 32S) such as, the
charge, proton and matter densities, the corresponding root mean
square (rms) radii, neutron skin thickness, elastic electron scattering
form factors and the binding energy per nucleon. The calculated
results have been discussed and compared with the available
experimental data.
Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.
Background/objectives: To study the motion equation under all perturbations effect for Low Earth Orbit (LEO) satellite. Predicting a satellite’s orbit is an important part of mission exploration. Methodology: Using 4th order Runge–Kutta’s method this equation was integrated numerically. In this study, the accurate perturbed value of orbital elements was calculated by using sub-steps number m during one revolution, also different step numbers nnn during 400 revolutions. The predication algorithm was applied and orbital elements changing were analyzed. The satellite in LEO influences by drag more than other perturbations regardless nnn through semi-major axis and eccentricity reducing. Findings and novelty/improvement: The results demo
... Show MoreNon-steroidal anti-inflammatory drugs (NSAIDs) contain free –COOH which thought to be responsible for the GI irritation associated with all traditional NSAIDs. The esterification of this group is one of an approach to ultimate aim for reduce the gastric irritation; so in this study we synthesized and preliminarily evaluated new ester compounds as new analogues with expected selectivity toward COX-2 enzyme. Synthetic procedures have been successfully developed for the generation of the target compounds (III a and b). The synthetic approach involved multi-steps procedures which include: Synthesis of 4-hydroxy benzene sulphonamide ( I b ), synthesis of Naproxen and Ibuprofen acyl chloride and then reacting them with 4-hydroxy benzene sulphon
... Show MoreSome nonlinear differential equations with fractional order are evaluated using a novel approach, the Sumudu and Adomian Decomposition Technique (STADM). To get the results of the given model, the Sumudu transformation and iterative technique are employed. The suggested method has an advantage over alternative strategies in that it does not require additional resources or calculations. This approach works well, is easy to use, and yields good results. Besides, the solution graphs are plotted using MATLAB software. Also, the true solution of the fractional Newell-Whitehead equation is shown together with the approximate solutions of STADM. The results showed our approach is a great, reliable, and easy method to deal with specific problems in
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreToday in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,
... Show MoreIn this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.
This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the cov
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