This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions, (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear multiplicity between most explanatory variables. These new combinations of linear compounds resulting from the two methods will reduce the number of explanatory variables to reach a new dimension one or more which called the effective dimension. The mean root of the error squares will be used to compare the two methods to show the preference of methods and a simulation study was conducted to compare the methods used. Simulation results showed that the proposed weight standard Sir method is the best.
The research included preparation of new iron(II) complexes with mixed ligands including benzilazine(BA) and semicarbazone ligands {benzilsemicarbazone- BSCH or benzilbis(semicarba-zone)- BBSCH2 or salicylaldehydesemicarbazone- SSCH2 or benzoinsemicarbazone- B'SCH2}.by classical and microwave methods. The resulted complexes have been characterized using chemical and physical methods. The study suggested that the above ligands form ionic complexes having formulae [Fe(SCHi)(BA)(Cl)m](Cl)2-m {where SCH, BSCH, BBSCH2, SSCH¬2 or B'SCH2 ligands; m=1 or 2}. Hexacoordinated mononuclear complexes have been investigated by this study and having octahedral geometries. The effect of laser ray type visible region have been studied on solid ligands and
... Show MoreThe aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas
... Show MoreThe two-neutron halo-nuclei (17B, 11Li, 8He) was investigated using a two-body nucleon density distribution (2BNDD) with two frequency shell model (TFSM). The structure of valence two-neutron of 17B nucleus in a pure (1d5/2) state and in a pure (1p1/2) state for 11L and 8He nuclei. For our tested nucleus, an efficient (2BNDD's) operator for point nucleon system folded with two-body correlation operator's functions was used to investigate nuclear matter density distributions, root-mean square (rms) radii, and elastic electron scattering form factors. In the nucleon-nucleon forces the correlation took account of
... Show MoreBackground: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreThis work investigates the use of hydrogenated amorphous silicon (a-Si:H) as a high-refractive-index material for quarter-wave distributed Bragg reflectors (DBRs) in photonic applications. In comparison to Si3N4, a-Si:H enables enhanced optical confinement, broader omnidirectional reflectance, and improved figures of merit, including higher Purcell and quality factors, while minimizing mirror complexity. To evaluate the practical impact of these advantages, a theoretical comparison is conducted between Fabry–Pérot cavities based on a-Si:H/SiO2 and Si3N4/SiO2 DBRs, examining resonance shifts as functions of cavity refractive index (1.0–3.0) and temperature (0–250 °C). The numerical results indicate that Si3N4/SiO2 planar Bragg caviti
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