借助直观表征优化计算算理教学

计算教学是小学数学教学的重要组成部分。理解算理和建构算法是计算教学的核心。教学中,教师可以引导学生借助＂操作表征＂＂图像表征＂和＂符号表征＂,优化算理教学,促进学生理解算理、掌握算法,让学生抵达理法融通的计算之境。

计算算理下小学数学教学模式的探究

数学作为一门在生产生活中有着广泛应用的学科,具有较强的抽象性和严密的逻辑性,对于学生数学计算能力有较高的要求.因此,在小学数学教学中,数学计算是重要的教学内容,也是学生必备的重要技能,需要教师重视培养学生对计算算理的理解,以不断提升学生对数学题目的思考力和培养创新思维,使其深入理解相关概念、定理及数学性质,并形成灵活的解题思维,不断提高学生的数学品质及素养.本文就计算算理下小学数学教学模式进行探究,以期对提高小学数学教学水平有所增益.

小学低年级学生数学运算意义理解力的培育

算理即“运算意义理解力”,是计算过程中的思维方式。算理为计算提供了正确的思维方式,能有效提升学生的计算能力。计算是数学学习的基础,教师应在教学中关注算理与算法的关系,以课堂教学评价前置为导向,通过教与评相融合等策略的运用,引导学生理解、掌握算理,促进数学运算能力的发展,并培育学生的数学核心素养。

讲究算理教学策略 提升学生计算能力

计算能力是学生应具备的基本素养之一,提高学生的计算能力应加强算理教学。算理是算法的基础,教师不仅要教会学生计算,更应该让学生明白算理、巩固算法,在教学中要关注学生的生活经验,讲究算理教学策略,注重以做悟理、以经验探理、以比显理、以联识理、以用思理,实现真正意义上升华算理、算法,进而提高学生数学思考力和计算力,促进学生计算能力与素养的提升。

基于数学素养下的小学数学计算教学的指导策略研究

国内的教育改革对于基础教育有了更高的要求,加强小学阶段计算算理的教育对于学生后期数学的学习有很大的帮助。计算教学是数学教育中的基础,在小学数学教育中计算算理的教学可以帮助学生建立数感,培养小学生的逻辑思维能力。本文对小学数学教育中计算算理的教育进行探讨,对计算教学中发现的问题,提出一些建议。

浅谈“数形结合”在计算教学中的运用

计算教学抽象、枯燥。教师在计算教学中可运用"数形结合",通过以形感知,理解算式意义;以形促思,探究计算算理;以形建模,掌握计算法则的方式,促使学生对运算意义的正确理解,领会运算算理,使形象思维与抽象运算完美结合。

提升数学关键能力——计算技能

计算技能是提升数学的关键能力，在教学中，要重视算理教学，丰润计算课型，梳理易错类型，培养计算习惯，提升学生的计算能力。

Two-Dimensional Entropy Method Based on Genetic Algorithm

Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.

让学生在数形结合中放飞思维

数形结合思想就是将现实世界的数量关系和空间形式联系在一起并以形助数或以数解形的方法去解决问题的一种数学思想方法。本文从应用数形结合思想帮助学生建立数学概念、理解计算算理、解决实际问题和探索数学规律四个方面进行了论述。

DFT calculation on relaxation and electronic structure of sulfide minerals surfaces in presence of H_2O molecule

First-principles calculations are performed to investigate the relaxation and electronic properties of sulfide minerals surfaces(MoS2, Sb2S3, Cu2 S, ZnS, PbS and FeS2) in presence of H2 O molecule. The calculated results show that the structure and electronic properties of sulfide minerals surfaces have been influenced in presence of H2 O molecule. The adsorption of the flotation reagent at the interface of mineral-water would be different from that of mineral surface due to the changes of surface structures and electronic properties caused by H2 O molecule. Hence, the influence of H2 O molecule on the reaction of flotation reagent with sulfide mineral surface will attract more attention.

Image Series Segmentation and Improved MC Algorithm

A semiautomatic segmentation method based on active contour is proposed for computed tomography (CT) image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial contour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes (MC) algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by experimental results.

An Enhanced Hadoop Heartbeat Mechanism for MapReduce Task Scheduler Using Dynamic Calibration

MapReduce is a popular program- ming model for processing large-scale datasets in a distributed environment and is a funda- mental component of current cloud comput- ing and big data applications. In this paper, a heartbeat mechanism for MapReduce Task Scheduler using Dynamic Calibration （HMTS- DC） is proposed to address the unbalanced node computation capacity problem in a het- erogeneous MapReduce environment. HMTS- DC uses two mechanisms to dynamically adapt and balance tasks assigned to each com- pute node： 1） using heartbeat to dynamically estimate the capacity of the compute nodes, and 2） using data locality of replicated data blocks to reduce data transfer between nodes. With the first mechanism, based on the heart- beats received during the early state of the job, the task scheduler can dynamically estimate the computational capacity of each node. Us- ing the second mechanism, unprocessed Tasks local to each compute node are reassigned and reserved to allow nodes with greater capacities to reserve more local tasks than their weaker counterparts. Experimental results show that HMTS-DC performs better than Hadoop and Dynamic Data Placement Strategy （DDP） in a dynamic environment. Furthermore, an en- hanced HMTS-DC （EHMTS-DC） is proposed bv incorporatin historical data. In contrastto the ＂slow start＂ property of HMTS-DC, EHMTS-DC relies on the historical computation capacity of the slave machines. The experimental results show that EHMTS-DC outperforms HMTS-DC in a dynamic environment.

Fuzzy Ontology Construction Based on Incomplete Knowledge

There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomplete knowledge is proposed. First, the calculation principle of the attribute weight of the ontology concept is presented, and the calculation function of the attribute weight is derived through experiments. Then, the membership degree of the incomplete individual to the concept is computed. Finally, the incomplete individual is classified according to the principle of the variable precision rough set model. The experimental results show that the average precision of the classification of the incomplete individuals is 81.7% when the common attributes are omitted and that it is difficult to classify the incomplete individuals correctly when the private attributes are omitted. This method is significant for handling incomplete knowledge in the process of ontology construction.

Optimization of project payment schedules with Nash equilibrium model and genetic algorithm

To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner’s payment schedule with an activity schedule so as to maximize the client’s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.

Computer Processing of the Intersection of Two Cones with Their Axes Intersecting and a Method to Get the Special Points

The analytic expression of the special points on the intersection of two cones with their axes intersecting(ITCTAI) is given. It also presents a method to construct the special points graphically according to the analytic expression of them. Finally, with computer programming language, it gives a program to generate the intersection in several different cases.

Calculation of Turbulent Flow with Pseudo-spectral Method

This paper deals with the numerical simulation of incompressible turbulent boundary flow of a flat plate with the pseudo-spectral matrix method. In order to appear more than 10 nodes in the turbulent base-stratum and transition of 43×43 computational grids,a coordinate transformation is put up from physical panel to computational panel. Several zero turbulent models are computed comparatively. The results are credible when comparing with the previous methods.

The rough representation and measurement of quotient structure in algebraic quotient space model

Granular computing is a very hot research field in recent years. In our previous work an algebraic quotient space model was proposed,where the quotient structure could not be deduced if the granulation was based on an equivalence relation. In this paper,definitions were given and formulas of the lower quotient congruence and upper quotient congruence were calculated to roughly represent the quotient structure. Then the accuracy and roughness were defined to measure the quotient structure in quantification. Finally,a numerical example was given to demonstrate that the rough representation and measuring methods are efficient and applicable. The work has greatly enriched the algebraic quotient space model and granular computing theory.

调动学生的多种器官学习数学——两位数加减一位数和整十数(不进位)教学反思

课程标准《数与数》要求:应重视口算,加强估算,提倡算法多样化;应减少单纯的技能性训练,避免繁杂汁算和程式化的叙述“算理”。结合自己的教学实践,我对《两位数加减一位数和整十数》(不进位)教学进行了反思。

Spectrum sensing sequence prediction in cognitive radio networks

Spectrum sensing is one of the key issues in cognitive radio networks. Most of previous work concenates on sensing the spectrum in a single spectrum band. In this paper, we propose a spectrum sensing sequence prediction scheme for cognitive radio networks with multiple spectrum bands to decrease the spectrum sensing time and increase the throughput of secondary users. The scheme is based on recent advances in computational learning theory, which has shown that prediction is synonymous with data compression. A Ziv-Lempel data compression algorithm is used to design our spectrum sensing sequence prediction scheme. The spectrum band usage history is used for the prediction in our proposed scheme. Simulation results show that the proposed scheme can reduce the average sensing time and improve the system throughput significantly.

Design and parametric optimization of thermal management of lithium-ion battery module with reciprocating air-flow

Single cell temperature difference of lithium-ion battery(LIB) module will significantly affect the safety and cycle life of the battery. The reciprocating air-flow module created by a periodic reversal of the air flow was investigated in an effort to mitigate the inherent temperature gradient problem of the conventional battery system with a unidirectional coolant flow with computational fluid dynamics(CFD). Orthogonal experiment and optimization design method based on computational fluid dynamics virtual experiments were developed. A set of optimized design factors for the cooling of reciprocating air flow of LIB thermal management was determined. The simulation experiments show that the reciprocating flow can achieve good heat dissipation, reduce the temperature difference, improve the temperature homogeneity and effectively lower the maximal temperature of the modular battery. The reciprocating flow improves the safety, long-term performance and life span of LIB.