Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.

基于分数阶傅里叶变换和图像加权熵的chirp scaling算法

针对传统的基于傅里叶变换和匹配滤波实现的chirp scaling(CS)成像算法中多普勒参数随斜距变化以及成像分辨率低的问题,提出利用分数阶傅里叶变换(FRFT)对CS成像算法进行优化。首先建立斜视合成孔径雷达(SAR)回波信号模型,理论推导利用FRFT代替匹配滤波进行信号压缩。针对方位向最优旋转角的搜索问题,对得到的图像基于加权最小熵建立代价函数,利用动量法的梯度下降优化算法进行迭代计算,最终得到分辨率更高的SAR图像。为验证算法的有效性,分别在点目标仿真数据和实测SAR数据集上进行实验。结果表明,与传统CS成像算法相比,该算法的成像结果成像主瓣宽度更窄、旁瓣更低、成像更加清晰。

Fault diagnosis method of link control system for gravitational wave detection

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed.Different from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling nonlinearity.By constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault parameters.The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

Validation of adherence prediction system for lifestyle interventions in nonalcoholic fatty liver disease

This editorial delves into the research article by Zeng et al published in the latest issue of World Journal of Gastroenterology.The manuscript contributes significantly to addressing the global health issue of nonalcoholic fatty liver disease(NAFLD)by introducing and validating the Exercise and Diet Adherence Scale(EDAS).The article effectively conveys the importance of the study,highlighting the prevalence of NAFLD,the lack of approved drugs for its treatment,and the crucial role of lifestyle correction.The use of the Delphi method for scale development and the subsequent evaluation of its reliability add scientific rigor to the methodology.The results demonstrate that the scale is correlated with key lifestyle indicators,which makes it a promising tool for assessing patient adherence to interventions.The identification of specific score thresholds for predicting adherence to daily calorie intake and exercise adds practical value to the scale.The differentiation among scores indicative of good,average,and poor adherence enhances its clinical applicability.In conclusion,the manuscript introduces EDAS,a valuable instrument that can contribute substantially to the field of NAFLD research and clinical practice.

Synergizing Wind,Solar,and Biomass Power:Ranking Analysis of Off-Grid System for Different Weather Conditions of Iran

Nowadays,the use of renewable energies,especially wind,solar,and biomass,is essential as an effective solution to address global environmental and economic challenges.Therefore,the current study examines the energy-economic-environmental analysis of off-grid electricity generation systems using solar panels,wind turbines,and biomass generators in various weather conditions in Iran.Simulations over 25 years were conducted using HOMER v2.81 software,aiming to determine the potential of each region and find the lowest cost of electricity production per kWh.In the end,to identify the most suitable location,the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method was employed to rank different stations based on simulation output parameters and some other influential factors.Considering the evaluation of various parameters,the stations in Yazd,Marand,and Dezful achieved the best results,while the stations in Ramsar,Shahrekord,and Gonbad presented the least favorable outcomes.In Yazd,the wind turbine is an economic priority,and a 100 kW wind turbine is utilized in the optimal system.In Yazd,where the simultaneous use of renewable energies is most prominent,the lowest pollutant production occurred with a quantity of 1174 kg/year.Annual energy losses are highest in Jask station and lowest in Yazd.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

The Impact of Model Based Offset Scaling Technique on the Amplitude Variation with Offset Responses from 3D Seismic Data Acquired from the Tano Basin, Offshore Ghana

Amplitudes have been found to be a function of incident angle and offset. Hence data required to test for amplitude variation with angle or offset needs to have its amplitudes for all offsets preserved and not stacked. Amplitude Variation with Offset (AVO)/Amplitude Variation with Angle (AVA) is necessary to account for information in the offset/angle parameter (mode converted S-wave and P-wave velocities). Since amplitudes are a function of the converted S- and P-waves, it is important to investigate the dependence of amplitudes on the elastic (P- and S-waves) parameters from the seismic data. By modelling these effects for different reservoir fluids via fluid substitution, various AVO geobody classes present along the well and in the entire seismic cube can be observed. AVO analysis was performed on one test well (Well_1) and 3D pre-stack angle gathers from the Tano Basin. The analysis involves creating a synthetic model to infer the effect of offset scaling techniques on amplitude responses in the Tano basin as compared to the effect of unscaled seismic data. The spectral balance process was performed to match the amplitude spectra of all angle stacks to that of the mid (26°) stack on the test lines. The process had an effect primarily on the far (34° - 40°) stacks. The frequency content of these stacks slightly increased to match that of the near and mid stacks. In offset scaling process, the root mean square (RMS) amplitude comparison between the synthetic and seismic suggests that the amplitude of the far traces should be reduced relative to the nears by up to 16%. However, the exact scaler values depend on the time window considered. This suggests that the amplitude scaling with offset delivered from seismic processing is only approximately correct and needs to be checked with well synthetics and adjusted accordingly prior to use for AVO studies. The AVO attribute volumes generated were better at resolving anomalies on spectrally balanced and offset scaled data than data delivered from conventional processing. A typical class II AVO anomaly is seen along the test well from the cross-plot analysis and AVO attribute cube which indicates an oil filled reservoir.

Assessment of Groundwater Stability Using Corrosion and Scaling Tendency Indices on Selected Springs in the Manga Region in Nyamira County, Kenya

We present the result of groundwater stability assessment on three major springs in the Manga region in Nyamira County found in Kenya in 2018. These springs are Kiangoso (SP1), Kerongo (SP2) and Tetema (SP3). The corrosion and scaling tendency indices were obtained using the Langelier saturation index (LSI), Ryznar stability index (RSI), and Puckorius scaling index (PSI). The LSI values obtained for SP1, SP2, and SP3 are −3.93, −4.71, and −4.17, respectively, while using RSI, the values obtained for SP1, SP2, and SP3 are 14.15, 14.53, and 13.74, respectively. Using PSI, the values of SP1, SP2, and SP3 are 5.58, 5.45, and 5.58, respectively. From the interpretation of the indices, the groundwater from the three springs in the Manga region using LSI and RSI showed intolerable corrosion;hence, it is unlikely to scale as obtained from PSI.

Promoting Ethical Sensitivity in Nursing Education:A Systematic Review of Case Study-Based Health Education

Introduction: Nursing ethical sensitivity refers to a nurse’s capacity for thoughtful consideration of ethical issues when faced with dilemmas. In the nursing domain, ethical dilemmas arise when nurses face challenges in making sound ethical decisions during clinical practice. These challenges may stem from conflicts between personal values and professional responsibilities. Methodology: Articles downloaded from Pub Med, CNKI, and Google Scholar were reviewed. Results: After rigorous screening, a meticulous analysis was conducted, encompassing 10 articles and involving a substantial cohort of 2863 participants. Existing literature revealed variations in the ethical dilemmas faced by nurses across different departments. The ethical sensitivity of nurses also varies, with higher ethical sensitivity correlating with stronger empathetic abilities. Zhen et al. classified the causes of ethical dilemmas into four main categories: (1) Ethical dilemmas arising from personal reasons of nursing students;(2) Ethical dilemmas stemming from the actions of teachers;(3) Ethical dilemmas triggered by patients;(4) Ethical dilemmas resulting from miscellaneous reasons. Conclusion: According to literature findings, nursing ethical sensitivity was positively linked to the nurse’s ethical decision-making ability. A case study-oriented teaching program has proven effective in enhancing ethical sensitivity among nursing students.

Inhibition of CaCO_3 Scaling in Reverse Osmosis System by Zinc Ion

Scaling of reverse osmosis (RO) membrane surface is one of the main problems in desalination proc- esses. To mitigate scales, organic anti-scalants are often used. If the dosages of anti-scalants are reduced, by using other much cheaper scale inhibitors, RO running cost will decrease greatly. The present paper investigated the inhi- bition of CaCO3 precipitation by zinc ions in RO system. The results show that the zinc ion concentration of 2mg?L-1 was able to exert a marked suppression effect on both bulk precipitation of CaCO3 and on membrane scaling on waters of moderate hardness.

Effects of PAA and PBTCA on CaCO_3 Scaling in Pool Boiling System

Formation of mineral scales on heat exchangers is a persistent and expensive problem. In the presentpaper, the calcium carbonate scale inhibition by two inhibitors, polyacrylic acid (PAA) and 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTCA) has been studied in a pool boiling system. It is found that PBTCA has abetter inhibition effect than PAA under the identical conditions. X-ray diffraction(XRD) and Fourier transform-infrared(FTIR) analyses demonstrate that the content of vaterite increases as inhibition effects increase. Themetastable crystal forms of vaterite and aragonite are stabilized kinetically in the presence of inhibitors. Therelationship between the inhibition effect and the fractal dimension has also been investigated. The result showsthat the fractal dimension is higher in the presence of inhibitors. The better the inhibition effect, the higher thefractal dimension. The step morphology was observed by atomic force microscopy (AFM) images. It is shown thatthe step space on the calcium carbonate surface increases in the presence of inhibitors. Moreover, with the increaseof inhibition effect, both the step space and the fractal dimension increase. The step bunching is found on thecalcium carbonate by AFM. The better the inhibition effect of the inhibitor, the slower the step velocity in theunbunched location. As a result, the step space becomes wider in the presence of PBTCA than that in the presenceof PAA.

Breakdown of Scaling in Aggregation-Fragmentation- Annihilation Process of n-Species Systems

The kinetic behaviors of aggregation-fragmentation-annihilation processes of three n-species systems arestudied in this paper. Aggregation reaction occurs only between the same species but irreversible annihilation reactionoccurs between two different species, and meanwhile the fragmentation reaction coexists. Based on the mean-field theory,we investigate the rate equations of the processes and obtain the asymptotic descriptions of the cluster-mass distributionsfor the symmetrical cases. We find that the fragmentation reaction may lead to the complete breakdown of the standardscaling description for the cluster-mass distribution of each species contrast to the scaling behavior of aggregation-annihilation processes without fragmentation.In our joint annihilation model, we also observe that the kinetic behaviorsof distinct species are quite complicated for the case with different initial concentrations. The cluster-mass distributionof heavy species with the largest initial concentration possesses peculiar scaling properties, while that of light species hasnot scaling behavior.

A STUDY ON THE SCALING RATE MODEL OF CALCIUM CARBONATE IN SATURATED WATER SYSTEM

1 INTRODUCTIONCalcium carbonate scaling is quite common in chemical processes,especially in heatexchangers.Only limited work has been done in mathematical modelling describingthe calcium carbonate scaling phenomenon.Hasson’s ionic diffusion model happenedto be one being rather broadly accepted.

Modified scaling function projective synchronization of chaotic systems

This paper investigates a kind of modified scaling function projective synchronization of uncertain chaotic systems using an adaptive controller. The given scaling function in the new method can be an equilibrium point; a periodic orbit, or even a chaotic attractor in the phase space. Based on LaSalle＇s invariance set principle, the adaptive control law is derived to make the states of two chaotic systems function projective synchronized. Some numerical examples are also given to show the effectiveness of the proposed method.

Evolvement of the System Complexity Degree under Different Time Scalings:an Illustration of the Traffic Flow System

It is investigable how the system scaling affects the system complexity degree. The traffic flow system is taken in this paper as an illustration to study this question. First, the Lempel-Ziv algorithm is introduced for accurate depiction of the complexity degree of the traffic flow system. We gain 3 actual sequences and 20s period traffic flow sequences on the basis of the measure of the traffic flow data; we gain 5 traffic flow sequences whose periods are between 1-5min by simulating the traffic flow system. By calculating the complicacy of the 11 sequences, we obtain two hypothesis: the complicacies of the same system are different under different time scalings; negative correlation exists between the complicacy and the time scaling of the system.

基于逆chirp scaling的合成孔径雷达卷积欺骗干扰方法

针对现有合成孔径雷达(synthetic aperture radar,SAR)欺骗干扰方法生成虚假场景时难以兼顾逼真度和低计算量的问题,提出了一种基于逆chirp scaling(CS)成像方法的SAR卷积欺骗干扰方法.该方法利用相位相乘补偿虚假场景内各虚假点的距离徙动,避免了插值运算,在降低求解干扰机频率响应函数计算量的同时,提高了虚假场景的生成精度.并且通过对欺骗模板进行线性调频Z变换(chirp-Z transform,CZT),直接从模板图像变换到实际SAR信号对应的空间频域,再次避免了插值运算,进一步降低了求解干扰机频率响应函数的计算量,提高了干扰机实时性.理论分析和仿真实验验证了相比逆omega-K(ωk)近似方法和经典的两步生成方法,本文方法能够兼顾虚假场景的生成精度和计算效率.

Scalings for the Alfvén-cyclotron instability in a bi-kappa plasma

The particle velocity distribution in space plasma usually exhibits a non-Maxwellian high-energy tail that can be well modeled by kappa distributions.In this study,we focus on the growth rates of the Alfvén-cyclotron instability driven by ion temperature anisotropy in a kappa plasma.By solving the kinetic linear dispersion equation,we explore the sensitivity of growth rates to the spectral indexκof a bi-kappa distribution under different plasma conditions,including a variety of plasma beta β_(hp) and temperature anisotropy A_(hp) values of hot protons.Furthermore,a concise,analytic scaling formula is derived that relates the dimensionless maximum growth rate to three independent variables:the spectral index and the plasma beta and temperature anisotropy of hot protons.Our results show that as theκ-value increases,the instability bandwidth narrows and the maximum growth rate increases significantly.For higherβ_(hp)and A_(hp)′the maximum instability undergoes a sharp increase as well.When our fits of dimensionless maximum growth rates are compared with solutions to kinetic linear dispersion theory,the results generally exhibit good agreement between them.Especially under the circumstances of largeκ-values and highβ_(hp)and A_(hp)′the scalings of maximum growth rates primarily accurately model the numerical solutions.Our analytic expressions can readily be used in large-scale models of the Earth’s magnetosphere to understand wave generation due to the Alfvén-cyclotron instability.