建模与解模:探寻培养小学生计算思维的密码——以小学Scratch编程课为例

信息技术学科要培养的计算思维是当今学生要具备的核心素养之一,受到了中小学教师的关注,就目前研究现状,计算思维的理论研究成果较为丰富,但应用研究仍处在初级阶段。笔者试从小学信息技术课培养计算思维的实施策略着手,以Scratch编程课为例,阐述培养计算思维的"建模——解模"过程。

逆象形:让数学从无形到有形——关于小学数学解模思想的实践性思考

数学思想是数学基础知识与数学应用之间的桥梁.模型思想本身的局限性及其在实践中的缺失、学生的认知发展特点等催生了解模思想.将已有抽象的数学概念还原成事物本身,使数学知识具有逆象形性,便于学生理解和接受,这是数学解模思想.

物理建模与物理解模教学探究——以“轻物”模型教学为例

物理模型思维是中学物理最重要的思维方法之一,亦是高中物理学科核心素养重要要素之一。物理模型教学在实际教学中却存在巨大障碍,根本原因在于课程资源缺乏建模思想,且教师自身建模意识淡薄、建模能力薄弱。通过整理物理模型理论知识,明确了物理建模和物理解模两种思维过程,从而提高师生建模意识、提高建模能力。

Modified multiple-component scattering power decomposition for PolSAR data based on eigenspace of coherency matrix

A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.

Local existence and uniqueness of solutions to the evolutionary model for magnetoviscoelasticity

In this paper,we prove the local existence and uniqueness of solutions to the evolutionary model for magnetoviscoelasticity in R^(2),R^(3).This model consists of an incompressible Navier-Stokes,a regularized system for the evolution of the deformation gradient and the Landau-Lifshitz-Gilbert system for the dynamics of the mag-netization.Our approach depends on approximating the system with a sequence of perturbed systems.

Slope displacement prediction based on multisource domain transfer learning for insufficient sample data

Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.

Temperature-Induced Unfolding Pathway of Staphylococcal Enterotoxin B:Insights from Circular Dichroism and Molecular Dynamics Simulation

In this study,circular dichroism(CD)and molecular dynamics(MD)simulation were used to investigate the thermal unfolding pathway of staphylococcal enterotoxin B(SEB)at temperatures of 298–371 and 298–500 K,and the relationship between the experimental and simulation results were explored.Our computational findings on the secondary structure of SEB showed that at room temperature,the CD spectroscopic results were highly consistent with the MD results.Moreover,under heating conditions,the changing trends of helix,sheet and random coil obtained by CD spectral fitting were highly consistent with those obtained by MD.In order to gain a deeper understanding of the thermal stability mechanism of SEB,the MD trajectories were analyzed in terms of root mean square deviation(RMSD),secondary structure assignment(SSA),radius of gyration(R_(g)),free energy surfaces(FES),solvent-accessible surface area(SASA),hydrogen bonds and salt bridges.The results showed that at low heating temperature,domain Ⅰ without loops(omitting the mobile loop region)mainly relied on hydrophobic interaction to maintain its thermal stability,whereas the thermal stability of domain Ⅱ was mainly controlled by salt bridges and hydrogen bonds.Under high heating temperature conditions,the hydrophobic interactions in domain Ⅰ without loops were destroyed and the secondary structure was almost completely lost,while domain Ⅱ could still rely on salt bridges as molecular staples to barely maintain the stability of the secondary structure.These results help us to understand the thermodynamic and kinetic mechanisms that maintain the thermal stability of SEB at the molecular level,and provide a direction for establishing safer and more effective food sterilization processes.

数学建模中线性规划与目标规划的比较

对数学建模中的线性规划与目标规划模型的概念、特点、模型的结构以及解模的方法进行了比较,展示了较前沿的建模与解模方向。

基于EMC2的并联运动机床的控制系统设计与仿真

针对六自由度并联运动机床,首先在UG三维造型器中虚拟构建了其模型,通过Matlab软件计算其运动学逆解模型,继而通过Adams软件验证了该逆解模型的正确性。最后通过重新编译EMC2运动学逆解模块,并通过数控加工代码实例加以仿真验证,为后续的样机制造及电机输出控制奠定了重要基础。

关于L－Fuzzy集上广义Fuzzy积分的可积性

文献［２］通过引进广义三角模定义了一类广义ｆｕｚｚｙ积分。本文讨论了当这类广义ｆｕｚｚｙ积分建立于Ｌ－ｆｕｚｚｙ集上时有关可积性的问题，给出了非负可测函数在有限测度集上及任意可测集上可积的充要条件，并证明了积分转化定理。

The filtering characteristics of HHT and its application in acoustic log waveform signal processing

Array acoustic logging plays an important role in formation evaluation. Its data is a non-linear and non-stationary signal and array acoustic logging signals have time-varying spectrum characteristics. Traditional filtering methods are inadequate. We introduce a Hilbert- Huang transform （HHT） which makes full preservation of the non-linear and non-stationary characteristics and has great advantages in the acoustic signal filtering. Using the empirical mode decomposition （EMD） method, the acoustic log waveforms can be decomposed into a finite and often small number of intrinsic mode functions （IMF）. The results of applying HHT to real array acoustic logging signal filtering and de-noising are presented to illustrate the efficiency and power of this new method.

ALGORITHM FOR AMBIGUITY RESOLUTION IN RANGE AND VELOCITY

For enhancing performances and increasing functions of PD radar, High PRF, medium PRF and low PRF are commonly applied into system ambiguity appeared in range and velocity in some PRF. Based on clustering, a sliding window correlator algorithm for resolving the radar object ambiguity in range and velocity is described. Slide window algorithm is a searching algorithm. The probability of ambiguity resolution for targets and the computational efficiency are discussed. The relations between the probability of ambiguity resolution of this algorithm and PRF, the range of interest, and the width of sliding window are analyzed. Simulational results are also given.

建立“数学模型” 让学生轻松学数学

建立"数学模型"就是要利用学生已有的数学知识,在解决问题中对数学进行探究,把数学知识与现实世界联系起来,诱发学生的学习兴趣,使学生轻轻松松地学习数学,提高学习效率。一、理解掌握建模概念及"数学模型"的含义;二、进行操作活动,培养学生"建模"的兴趣;三、掌握数学学科的本质,构建"数学模型";四、建立数学模型,利用模型求解。

Salt-assisted Synthesis of Hollow Bi_2WO_6 Microspheres with Superior Photocatalytic Activity for NO Removal

Hollow Bi2WO6 microspheres are successfully synthesized by a facile ultrasonic spray pyrolysis（USP） method using NaCl as a salt template.The as-prepared hollow microspheres assembled as nanoplates with dimensions of approximately 41-148 nm and are dispersed with non-uniform pores on the template surface.By swapping the salt template with KC1 or Na2SO4,different morphologies of Bi2WO6 are obtained.The experimental results demonstrate that NaCl plays a key role on the formation of Bi2WO6 with hollow structures.The specific growth mechanism of hollow microspheres was studied in detail.The Bi2WO6 hollow microspheres exhibit an excellent photocatalytic efficiency for NO removal under solar light irradiation,which is 1.73 times higher than for the Bi2WO6 obtained in the absence of any salt template.This enhancement can be ascribed to the simultaneous improvement on the surface area and visible light-harvesting ability from the hollow structures.Electron spin resonance（ESR） results suggest that both radicals of ·OH and ·O2^- are involved in the photocatalytic process over the BWO-NaCl sample.The production of ·O2^- radicals offers better durability for NO removal.

Prediction Model of Dissolved Oxygen Fuzzy System in Aquaculture Pond Based on Neural Network

A dissolved oxygen fuzzy system predicting model based on neural network was put forward in this study. 106 groups of data were used to confirm the fitness of the predicting model. The first 80 groups of data were acted as training input and the other 26 groups of data were acted as the confirmed data in the system. The result showed that the testing data was approximately the same as the predicted data. So it gave a new way to solve the problem that the status of the water quality couldn＇t be predicted in time and it＇s hard to watching and measuring the factors dynamic.

Random noise attenuation by f–x spatial projection-based complex empirical mode decomposition predictive filtering

The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in signal damage and limited denoising. Second, decomposing the real and imaginary parts of complex data may lead to inconsistent decomposition numbers. Thus, we propose a new method named f–x spatial projection-based complex empirical mode decomposition（CEMD） prediction filtering. The proposed approach directly decomposes complex seismic data into a series of complex IMFs（CIMFs） using the spatial projection-based CEMD algorithm and then applies f–x predictive filtering to the stationary CIMFs to improve the signal-to-noise ratio. Synthetic and real data examples were used to demonstrate the performance of the new method in random noise attenuation and seismic signal preservation.

Study on the tradeoff between interpretability and precision in fuzzy modeling

An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select input variables by increasing the number of input variables, and the Gustafson-Kessel fuzzy clustering algorithm, combined with the least square method, was used to identify the fuzzy model. Subsequently, an interpretability measure was described by the product of the number of input variables and the number of rules, while precision was weighted by root mean square error, and the selection objective function concerning interpretability and precision was defined. Given the maximum and minimum number of input variables and rules, a set of fuzzy models was constructed. Finally, the optimal fuzzy model was selected by the objective function, and was optimized by a genetic algorithm to achieve a good tradeoff between interpretability and precision. The performance of the proposed method was illustrated by the well-known Box-Jenkins gas furnace benchmark; the results demonstrate its validity.

Reservoir detection based on EMD and correlation dimension

In hydrocarbon reservoirs, seismic waveforms become complex and the correlation dimension becomes smaller. Seismic waves are signals with a definite frequency bandwidth and the waveform is affected by all the frequency components in the band. The results will not define the reservoir well if we calculate correlation dimension directly. In this paper, we present a method that integrates empirical mode decomposition （EMD） and correlation dimension. EMD is used to decompose the seismic waves and calculate the correlation dimension of every intrinsic mode function （IMF） component of the decomposed wave. Comparing the results with reservoirs identified by known wells, the most effective IMF is chosen and used to predict the reservoir. The method is applied in the Triassic Zhongyou group in the XX area of the Tahe oil field with quite good results.

A Novel Analytical Model for Surface Electrical Field Distribution and Optimization of TFSOI RESURF Devices

A novel analytical model for the thin film silicon on insulator (TFSOI) reduced surface field (RESURF) devices has been proposed.Based on the 2-D Poisson equation solution,the analytical expressions for the surface potential and field distributions are derived.From this analysis,the optimum design condition for the maximum breakdown voltage is obtained.The dependence of the maximum breakdown voltage on the drift region length is examined and the relationship between the critical doping concentration and the front- and back- interface oxide layer thickness is discussed.The numerical simulation performed by the advanced semiconductor simulation tool,DESSIS-ISE,has been shown to support the analytical results.

Extension of analytical model of solid-state phase transformation

Departing from an analytical phase transformation model, a new analytical approach to deduce transformed fraction for non-isothermal phase transformation was developed. In the new approach, the effect of the initial transformation temperature and the accurate ＂temperature integral＂ approximations are incorporated to obtain an extended analytical model. Numerical approach demonstrated that the extended analytical model prediction for transformed fraction and transformation rate is in good agreement with the exact numerical calculation. The new model can describe more precisely the kinetic behavior than the original analytical model, especially for transformation with relatively high initial transformation temperature. The kinetic parameters obtained from the new model are more accurate and reasonable than those from the original analytical model.