Coefficient Of Quadratic Term Research Articles

Research on the Synergistic Development and Operation Mechanism of Vocational Education and Innovative Development Concepts in the Context of Deep Learning

Abstract This paper proposes that the synergistic mechanism promotes the vocational education innovation system to transition from the primitive low-level, ordered and relatively balanced stage to the high-level, ordered and fully synergistic stage. By analyzing the dynamic evolution process of the order parameter, a complex system with self-evolution capability is built, and the vocational education collaborative innovation model is constructed at three levels: macro, meso and micro. Finally, in carrying out the benefit distribution and arithmetic example analysis, the spillover effect of the synergistic subject is explored, and the optimal value is taken using the optimization model of synergistic development of higher vocational colleges and universities. The results show that when the quadratic term coefficient of innovation output is 0.086, the stabilization strategy is (0,1) or (1,0), and the multi-body innovation resources realize interaction stabilization without spillover or feedback effects. This study proposes the optimal path of innovation integration mechanism from the aspects of mechanism, mode and content, which can provide new ideas for the collaborative development of vocational education and enterprises.

Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects

Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a theoretical basis for efficient utilization of GTI and ER. This study employs a Dynamic Spatial Durbin Model and utilizes panel data from 2003 to 2017 for 30 Chinese provinces to examine the impact of GTI on EEE in the presence of ER. The empirical results reveal: (1) GTI has a U-shaped impact on EEE, primarily driven by SubGI. (2) GTI’s influence on EEE is predominantly reflected in PTE, also stemming from SubGI. (3) The interaction term between ER and GTI is 0.0022, while the GTI coefficient is − 0.0741, and the GTI quadratic term coefficient is 0.0007, all statistically significant. This implies that ER mitigates the negative impact of GTI on EEE while strengthening its positive effect. These findings provide empirical evidence and policy insights for more effectively utilizing GTI and ER to enhance EEE and achieve energy conservation and emissions reduction goals.

Optimization of Discharge Plasma Reactor for Dry Reforming of Methane using Response Surface Methodology

This research provides a study of the dry reforming of methane (DRM), which converts two main greenhouses gases (CO2 and CH4) to synthesis gas (H2 and CO) by a Dielectric Barrier Discharge (DBD) plasma reactor at atmospheric pressure. The Box-Behnken Design (BBD) method based on the Response Surface Methodology (RSM) was applied to determine the optimum experimental conditions on the plasma stability and the synthesis gas production. The synergistic effects of input power (P), CO2/CH4 ratio (R), and flow rate (FR) on the CO2, CH4 conversions, H2, CO yields, and the syngas ratio of H2 to CO were studied. With the desirability value of 0.97, the optimum values of 10.05 W (P), 1.03 (R), and 1.58 L.min−1 FR were identified with CO2 conversion of 48.56% and CH4 conversion of 86.67%; H2 and CO yields of 45.87% and 39.43% respectively; and syngas ratio of H2 to CO of 0.88. The study shows that both P and FR have a major significant effect on the reactant conversions and syngas ratio, followed by R. Meanwhile, the value of R has a significant impact on the H2, CO yields followed P and FR. In contrast, the synergistic effects between P-R, P-FR, and R-FR had a weak significant on the CO2 and CH4 conversions, H2 and CO yields, and H2 to CO ratio respectively. The quadratic term coefficients of P, R, and FR had a remarkable effect on all responses. Thus, the synergistic effect of the most important parameters improves the process efficiency. Copyright © 2023 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Analysis and Suppression of Nonlinear Error of Pendulous Integrating Gyroscopic Accelerometer at Instrument Level.

The error coefficients of the pendulous integrating gyroscopic accelerometer (PIGA) mainly include the bias, scale factor, and nonlinear error. Previous works have fully studied and suppressed the bias and scale factor of PIGAs. At present, the nonlinear error is the most critical factor restricting the measurement accuracy of PIGAs. To address this barrier, a study on the analysis and suppression of the nonlinear error of PIGAs at the instrument level was carried out. Firstly, the error model of a PIGA is established by kinematics and dynamics analyses. Then, nonlinear error is analyzed based on the established model. Finally, a suppression method for the nonlinear error is proposed based on the analysis results. The nonlinear error analysis found that (1) the nonlinear error includes a quadratic term error caused by unequal inertia and the inertia product, cross-coupling error is caused by lateral accelerations, and error is caused by unequal stiffness; (2) unequal inertia and the inertia product were the most critical factors resulting in nonlinear error. Based on the results in the nonlinear error analysis, the suppression method for error focuses on unequal inertia and the inertia product. The proposed method of analysis and suppression was validated experimentally as the quadratic term coefficient was reduced by an order of magnitude from 1.9 × 10-6/g0 to 1.91 × 10-7/g0.

Differential Fiber Grating Vector Flow Velocity Sensor Based on Strain Amplifying Cantilever Beam Structure

A vector flow velocity sensor with a stainless steel equal-strength cantilever beam as the elastic element and dual fiber-optic gratings as the sensitive element has been proposed and experimentally demonstrated. And it uses differential measurement to eliminate the effect of temperature. To improve the sensitivity and stress transfer efficiency, we focus on the structural design of the cantilever beam through theoretical derivation and simulation. The cantilever beam structure combines two lug bosses on both sides, a rectangular beam, and an enlarged thrust surface. Three sensors A–C with cantilever beams that are 0.3, 0.4, and 0.4 mm thick with double size, are selected for experiments. The displacement sensitivities of the three sensors at static stress tests are 1.4405, 1.6455, and 0.6662 pm/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> , respectively. For practical measurements of underwater velocity, the quadratic term coefficients of the flow velocity sensitivity fitting curves as 210.2, 48.9, and 354.6, the linear term coefficients as −6.67, +5.05, and −19.76, and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math></inline-formula> as 0.9963, 0.9887, and 0.9981, have been calculated respectively. The error between the forward and reverse displacement sensitivities of sensor C is 0.404%, and its average error between the forward and reverse flow velocity measurements is 4.98%. Temperature-controlled experiments are further conducted and verify that the sensors can resist the effect of temperature. Experiments show that the sensor with large size and small thickness of cantilever beam has better velocity sensitivity. And experiment results prove that the sensors have application prospects in 3-D ocean current measurements.

INFLUENCE OF CLIMATE CHANGE ON THE GROWTH RATES AND DIRECTION OF GROWTH OF OUTPUTS OF SELECTED FOOD GRAINS IN NIGERIA (1981-2020)

The study assessed the influence on the growth rates and direction of growth of prices of outputs of selected food grans (rice, maize and wheat) in Nigeria from 1981 to 2020. Time series data were collected from secondary sources. The data was analyzed using regression analysis. The analysis showed that, the instantaneous growth rates were 4.8%, 4.3% and 1.5% for outputs of maize, rice and wheat, respectively, per annum increase in Nigeria (1981-2020); Whereas the value of the coefficient of quadratic term (t2) for rice (5.22), maize (0.649) and wheat (-0.62) were positive for rice and maize but negative for wheat which implies stagnated growth rates in rice and maize production and accelerated growth process in wheat production. In the same, the result revealed that the instantaneous growth rates were 15.5%, 13.2% and 13.1% for prices of maize, rice and wheat, respectively, per annum increase in Nigeria (1981-2020). Also, the value of the coefficient of t2 for rice (13.2%), maize (15.5%) and wheat (13.1%) were all positive and significant – which implies accelerated growth process in Nigeria (1981-2020). The study concluded that, climate change, environmental degradation and stagnating yields could have catastrophic effects and reduce yields and increase prices of food grains like rice, maize and wheat in Nigeria. It was therefore, recommends that, effort should be made by government and other relevant stakeholders in agriculture towards providing irrigation facilities in order to adjust any unfavourable influence of increase or decrease in rainfall on food grains’ growth and yield in Nigeria.

Segmented disc dynamo with symmetric multidirectional patterns of multiscroll chaotic attractors

Rather than adopting the common approach that the multiscroll attractors are obtained through reconstruction of nonlinear functions, this work presents a systematic mechanism for designing multidirectional symmetric multiscroll patterns of chaotic attractors. The present scheme is based on the multilevel signal that work with the nonlinearities and state variables of chaotic system to generate symmetric multidirectional patterns of multiscroll chaotic attractors (MPMCA). To illustrate the mechanism of this systematic approach, the coefficients of quadratic terms of segmented disc dynamo are modified and designed a chaotic system that generates a chaotic attractor consisting of two pairs of symmetrical attractors. The state variables under the multilevel signal are transformed and then combined the symmetric attractors to generate a complete family of symmetric MPMCA in multi directions (including one directional (1D), two directional (2D) and three directional (3D) symmetric patterns of multiscroll chaotic attractors). Chaotic dynamical characteristics of symmetric MPMCA are analysed​ by means of equilibrium points distribution and phase portraits. Matlab simulations results obtained in this work are consistent well with our theoretical analysis verifying the effectiveness of the presented scheme.

인공신경망을 이용한 드레이프성 예측

This study aims to propose a prediction model for the drape coefficient using artificial neural networks and to analyze the nonlinear relationship between the drape properties and physical properties of fabrics. The study validates the significance of each factor affecting the fabric drape through multiple linear regression analysis with a sample size of 573. The analysis constructs a model with an adjusted R² of 77.6%. Seven main factors affect the drape coefficient: Grammage, extruded length values for warp and weft (m_warp, m_weft), coefficients of quadratic terms in the tensile-force quadratic graph in the warp, weft, and bias directions (c_warp, c_weft, c_bias), and force required for 1% tension in the warp direction (f_warp). Finally, an artificial neural network was created using seven selected factors. The performance was examined by increasing the number of hidden neurons, and the most suitable number of hidden neurons was found to be 8. The mean squared error was .052, and the correlation coefficient was .863, confirming a satisfactory model. The developed artificial neural network model can be used for engineering and high-quality clothing design. It is expected to provide essential data for clothing appearance, such as the fabric drape.

Generalized Hopf bifurcation analysis of a towed caster wheel system

This work concerns the generalized Hopf bifurcation analysis of a piecewise-smooth wheel system with higher order discontinuities. Center manifold reduction is used to reduce the towed caster wheel system to a planar dynamical system, in which the non-smoothness factor is considered. The analysis can be divided into two cases by the coefficient of quadratic term. If the coefficient of quadratic term is equal to zero, the type of generalized Hopf bifurcation can be determined by the stability of first-order fine focus. Otherwise, we have to construct a Poincaré map for illustrating the type of generalized Hopf bifurcation, which is the heart of our discussion. Besides, we put forward another convenient way to judge the bifurcation types due to the symmetrical characteristic of this wheel system. Numerical simulations show the feasibility of theoretical analysis.

Assessing different approaches to ab initio calculations of spin wave stiffness

Ab initio calculations of the spin wave stiffness constant $D$ for elemental Fe and Ni performed by different groups in the past have led to values with a considerable spread of 50-100 %. We present results for the stiffness constant $D$ of Fe, Ni, and permalloy Fe$_{0.19}$Ni$_{0.81}$ obtained by three different approaches: (i) by finding the quadratic term coefficient of the power expansion of the spin wave energy dispersion, (ii) by a damped real-space summation of weighted exchange coupling constants, and (iii) by integrating the appropriate expression in reciprocal space. All approaches are implemented by means of the same Korringa-Kohn-Rostoker (KKR) Green function formalism. We demonstrate that if properly converged, all procedures yield comparable values, with uncertainties of 5-10 % remaining. By a careful analysis of the influence of various technical parameters we estimate the margin of errors for the stiffness constants evaluated by different approaches and suggest procedures to minimize the risk of getting incorrect results.

On affine classification of permutations on the space GF(2)3

Abstract We give an elementary proof that by multiplication on left and right by affine permutations A, B ∈ AGL(3, 2) each permutation π : GF(2)3 → GF(2)3 may be reduced to one of the 4 permutations for which the 3 × 3-matrices consisting of the coefficients of quadratic terms of coordinate functions have as an invariant the rank, which is either 3, or 2, or 1, or 0, respectively. For comparison, we evaluate the number of classes of affine equivalence by the Pólya enumerative theory.

A New Motion Parameter Estimation and Relocation Scheme for Airborne Three-Channel CSSAR-GMTI Systems

This paper proposes a new scheme of motion parameter estimation and relocation for airborne three-channel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. Compared with the conventional straight-path SAR, the parameter estimation of a target is more challenging because the target’s range history and signal model are more complicated due to the complexity of the relative motion between CSSAR and ground moving target. In this paper, the signal model of a ground moving target and the expression for its along-track interferometric (ATI) phase from the environment of airborne three-channel CSSAR are derived. The coupling effect among the target’s motion and position parameters is also figured out. Then, a scheme of motion parameter estimation and relocation is proposed. The proposed scheme utilizes the ATI phase and the quadratic-term coefficient in the range equation to estimate the target’s motion and position parameters and utilizes an iterative strategy to address the coupling effect among these parameters. Numerical simulations are conducted to validate the satisfactory performance achieved by the proposed algorithm.

Response surface optimization and modelling for supercritical carbon dioxide extraction of Echium vulgare seed oil

Supercritical carbon dioxide extraction was used to extract oil from Echium vulgare seeds. Response surface methodology was applied to analyze the effect of temperature (30, 50 and 70 °C) and pressure (200, 300 and 400 bar) on the oil extraction yield. All extractions were performed at a constant CO2 flow rate of 3 kg/h and at a constant time of 120 min. The analysis of variance indicated that linear coefficients of temperature and pressure, the quadratic term coefficients of temperature and the interactions between pressure and temperature had significant effects on the oil yield under tested conditions. The optimal conditions were found to be 62 °C and 400 bar. Under these conditions, echium oil yield was predicted to be 14.4%. Composition analysis revealed that echium oil contains approximately 16.2% oleic acid and 72.3% polyunsaturated fatty acids. Furthermore, the physicochemical properties of the oil were determined in this study.

Non‐linear model‐order reduction based on tensor decomposition and matrix product

In this study, based on tensor decomposition and matrix product, the authors investigate two model-order reduction (MOR) methods for the quadratic-bilinear (QB) systems which are equivalently transformed from the non-linear input–output systems. Since the quadratic term coefficient of the QB system can be considered as the matricisation of a tensor, they propose two computationally efficient ways to obtain the reduced system by using tensor calculus. First, the Tucker decomposition of tensors is used to deal with the quadratic term coefficient of the QB system. The transformational matrix is constructed by applying the analysis of matrix product. Then, they get the reduced QB system which can match the first several expansion coefficients of the original output. Besides, they propose another MOR method based on the CANDECOMP/PARAFAC decomposition. These two methods can avoid large computational complexity in the process of computing the reduced system. Moreover, the error estimation and stability of the authors' MOR methods are discussed. The efficiency of their MOR methods is illustrated by two numerical examples and they show their competitiveness when compared to the proper orthogonal decomposition method.

Random attractor for stochastic Boissonade system with time-dependent deterministic forces and white noises

In this paper, we study the long-term dynamical behavior of stochastic Boisso nade systems with time-dependent deterministic forces, additive white noise and multiplicative white noise. We first prove the existence of random attrac tor for the considered systems. And then we establish the upper semi-continui ty of random attractors for the systems as the coefficient of quadratic term tends to zero and intensities of the noises approach zero, respectively. At last, we obtain an upper bound of fractal dimension of the random attractors for both systems without quadratic term.

Multimarket contact, market power and financial stability in the Turkish banking industry

This paper investigates the impact of multimarket contacts among the banks on market power and stability in the Turkish banking industry over the period 2002–2012. The Lerner index and Z-score are used as proxies for market power and bank stability, respectively. The results show that measures of multimarket contacts have increased during the sample period. The main results of the paper suggest that increases in the multimarket contacts among banks are positively related to individual bank stability, but negatively related to bank market power. The results further indicate that greater capitalization has positive impact on the bank stability. However, market concentration has positive and negative impact on bank stability and bank power, respectively. The cost inefficiency is negatively related to the Lerner index, suggesting that inefficient banks generate lower market power compared with efficient ones. The results also show that there is a nonlinear relationship between market power and multimarket contacts. The coefficient of quadratic term is always positive, suggesting that the relationship between market power and contact is a U-shaped form.

Global Attractors and Robustness of the Boissonade System

In this work, the existence and properties of a global attractor for the weak solution semiflow of the Boissonade system are proved. A parameter adjusting and grouping estimation method is developed to show the absorbing property and asymptotic compactness of the solution trajectories of this reaction-diffusion system with quadratic and cubic nonlinearity. The upper-semicontinuity of the global attractors in the \(H^1\) product space for the solution semiflow with respect to the quadratic term coefficient converging to zero is proved. The barrier of the perturbed singularity between zero quadratic term coefficient and non-zero one is overcome by the uniform adjusting parameter.

Optimized LSB Matching Steganography Based on Fisher Information

This paper proposes an optimized LSB matching steganography based on Fisher Information. The embedding algorithm is designed to solve the optimization problem, in which Fisher information is the objective function and embedding transferring probabilities are variables to be optimized. Fisher information is the quadratic function of the embedding transferring probabilities, and the coefficients of quadratic term are determined by the joint probability distribution of cover elements. By modeling the groups of elements in a cover image as Gaussian mixture model, the joint probability distribution of cover elements for each cover image is obtained by estimating the parameters of Gaussian mixture distribution. For each sub-Gaussian distribution in Gaussian mixture distribution, the quadratic term coefficients of Fisher information are calculated, and the optimized embedding transferring probabilities are solved by quadratic programming. By maximum posteriori probability principle, cover pixels are classified as the categories corresponding to sub-Gaussian distributions. At last, in order to embed message bits, pixels chose to add or subtract one according to the optimized transferring probabilities of the category. The experiments show that the security performance of this new algorithm is better than the existing LSB matching.

Response Surface Optimization of Nigella glandulifera Freyn Seed Oil Yield by Supercritical Carbon Dioxide Extraction

Supercritical carbon dioxide (SC-CO2) extraction was employed to extract oil from Nigella glandulifera Freyn seed in this study. Response surface methodology (RSM) was applied to evaluate the effects of the process parameters (pressure, temperature, and CO2 flow rate) on oil yield of N. glandulifera seed. A Box-Behnken design was used to optimize the extraction parameters. The analysis of variance indicated that the linear coefficients of pressure and CO2 flow rate, the quadratic term coefficients of pressure and temperature and the interactions between pressure and temperature, as well as temperature and CO2 flow rate, had significant effects on the oil yield (P<0.05). The optimal conditions to obtain the maximum oil yield from N. glandulifera seed were pressure 30.84 MPa, temperature 40.57°C, and CO2 flow rate 22.00 L h−1. Under these optimal conditions, the yield of oil was predicted to be 38.19%. The validation experiment results agreed with the predicted values. The fatty acid composition of N. glandulifera seed oil extracted using SC-CO2 was compared with that of oil obtained by Soxhlet method. The results showed that the fatty acid compositions of oil extracted by the two methods were similar. Identification of oil compounds with gas chromatography-mass spectrometry (GC-MS) showed that the contents of unsaturated fatty acids linoleic acid (48.30%), oleic acid (22.28%) and saturated fatty acids palmitic acid (16.65%), stearic acid (4.17%) were the most abundant fatty acids in seed oil from N. glandulifera

Photometric observations and orbital period variations of HS 0705 + 6700 and NY Vir

We present photometric observations of two post-common-envelope stars, NY Vir (=PG 1336-018) and HS 0705 + 6700. The V band CCD observation of NY Vir was performed by a 40 cm telescope at Ege University Observatory and the R band observations of HS 0705 + 6700 were performed by 100 cm telescope at TÜBİTAK National Observatory. The new light curves were analyzed by the WD code and the physical parameters of stars were determined. We obtained new mid-eclipse timings for HS 0705 + 6700 and combined them with those previously published data. The analysis of the O–C residuals yields a period of about 8.06 ± 0.28 yr and an amplitude of 98.5 s for the system HS 0705 + 6700, which is attributed to the third star physically bounded to the evolved eclipsing pair. A mass function of 1.2 × 10 −4 M ⊙ for the third star is obtained. The existence of a third star is also confirmed by the light curve analysis, indicating light contribution of about 0.043 at phase 0.25 in R-bandpass of the eclipsing pair. Using mass-luminosity relationship of the low mass stars we estimate a mass of 0.12 M ⊙ with an orbital inclination of about 20°. The O–C residuals obtained for the system NY Vir were represented by a downward parabola which indicates orbital period decrease in the system. Using the coefficient of quadratic term we calculate a rate of orbital period decrease of about dP/ dt = −4.09 × 10 −8days yr −1. The period decrease we have measured in NY Vir may be explained by angular momentum loss from the binary system.