Double-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared with the conventional double- and even triple-layer MPPs. The bandwidth can be increased to higher frequency by decreasing the cavity depth behind a sub-MPP with small hole diameter and a high perforation ratio, and to lower frequency by increasing the cavity depth behind a sub-MPP with large hole diameter and a small perforation ratio. The experimental data, measured by impedance tube, are in good agreement with the predicted results.
This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.
In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreThe research aims to know the effectiveness of a training program based on multiple intelligence theory in developing literary thinking among students of the Arabic Language Department at Ibn Rushd School of Humanities and to achieve the goal of research, the Safaris Research Institute, and the research community of Arabic language students in the Faculty of Education the third section of Arabic Language: The research sample consists of (71) students. Divided into (35) students in the experimental group and (36) students in the control group, the researcher balanced between the two groups with variables (intelligence, testing of tribal literary thinking, and time age in months), and after using the T-test for two independent samples, the
... Show MoreQ-switched lasers widely used in management skin diseases and
sometimes its effect may be inadequate or associated with
cytotoxicity. The current study aimed to investigate the effect of
Q-switched Nd:YAG laser upon cellular elements using in vitro
experimental model. Aqueous solutions of human albumin and pure
calf thymus double strand deoxyribonucleic acid (ctdsDNA)
irradiated with Q-switched Nd:YAG laser at different rates (1, 3 Hz)
and time exposure (up to 60 seconds) using 532 nm (400 mJ) and
1064 (1200 mJ) nm wavelength with fixed spot size of 4 mm. The
effect of laser irradiation on the albumin solution also studied in the
presence of elemental salts of copper, zinc and iron.
Q-switched laser irrad
Olive leaves extract is famous for its antioxidant and protective effects. In this study, the aqueous extract of Iraqi Olea europaea L. Leaves was investigated for its anti-diabetic effects against low double doses of alloxan induced Diabetes Mellitus in rats. Low double doses (75 mg\Kg body weight) of alloxan were injected intraperitoneally at day 1&29 of the experimental period in rats, whereas an aqueous extract of Iraqi Olea europaea L. Leaves was added continuously to their drinking water. Serum malondialdehyde concentration, total oxidative stress and oxidative stress index as oxidoreductive stress biomarker, activities of certain antioxidoreductive stress enzymes (glutathione peroxidase, super oxide dismutase and catalase) and concen
... Show MoreOlive leaves extract is famous for its antioxidant and protective effects. In this study, the aqueous extract of Iraqi Olea europaea L. Leaves was investigated for its anti-diabetic effects against low double doses of alloxan induced Diabetes Mellitus in rats. Low double doses (75 mgKg body weight) of alloxan were injected intraperitoneally at day 1&29 of the experimental period in rats, whereas an aqueous extract of Iraqi Olea europaea L. Leaves was added continuously to their drinking water. Serum malondialdehyde concentration, total oxidative stress and oxidative stress index as oxidoreductive stress biomarker, activities of certain anti-oxidoreductive stress enzymes (glutathione peroxidase, super oxide dismutase and catalase) and concen
... Show MoreThis paper investigates the recovery for time-dependent coefficient and free boundary for heat equation. They are considered under mass/energy specification and Stefan conditions. The main issue with this problem is that the solution is unstable and sensitive to small contamination of noise in the input data. The Crank-Nicolson finite difference method (FDM) is utilized to solve the direct problem, whilst the inverse problem is viewed as a nonlinear optimization problem. The latter problem is solved numerically using the routine optimization toolbox lsqnonlin from MATLAB. Consequently, the Tikhonov regularization method is used in order to gain stable solutions. The results were compared with their exact solution and tested via
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