小学数学“度量性”概念优化教学探究

根据国家教育局的规定,小学生需要掌握的数学概念大致有500多个,之所以受到重视,是因为数学概念是学生们建立自己数学理论体系的基础。在小学阶段,学生们学习数学的主要原因是提高自己的思维模式,增强自己的逻辑思维,只要让学生理解并学会了概念,在之后的学习中才会提高学习质量,为后续知识的学习做好了基础准备。基于此,本文章对小学数学“度量性”概念优化教学进行探讨,以供相关从业人员参考。

议小学数学“度量性”概念优化教学

对于处于小学阶段的小学生而言,数学是培养独立思考能力及发散思维能力为主的重要学科,而从数学学科所涉及的诸多方面教学内容来看,度量性概念相关教学内容由于在一定程度上属于虚拟与现实的有机融合。对于学生的逻辑思维及理性思考的影响非常广泛深刻,为了切实有效实现数学学科教学初始预期理想目标,需要在积极秉持开放发展及与时俱进核心指导思想的基础上,采取诸多得力措施持续优化调整完善数学学科特别是所涉及度量性概念相关教学内容的基本模式及方法,唯有如此才能在最大限度上保证数学学科教学的整体效率及效果。基于此,本文章对小学数学“度量性”概念优化教学进行探讨,以供相关从业人员参考。

Characterization of a Powertrain Test Bed in the Context of Virtual Validation of Drivability

Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting with hardware-in-the-loop testing of control units and reproducing real-world maneuvers and physical interaction chains.Here,the road-to-rig approach offers a vast potential to reduce validation time and costs significantly.The present research study investigates the maneuver reproduction of drivability phenomena at a powertrain test bed.Although drivability phenomena occur in the frequency range of most up to 30∙Hz,the design and characteristics substantially impact the test setup’s validity.By utilization of modal analysis,the influence of the test bed on the mechanical characteristic is shown.Furthermore,the sensitivity of the natural modes of each component,from either specimen or test bed site,is determined.In contrast,the uncertainty of the deployed measurement equipment also affects the validity.Instead of an accuracy class indication,we apply the ISO/IEC Guide 98 to the measurement equipment and the test bed setup to increase the fidelity of the validation task.In conclusion,the present paper contributes to a traceable validity determination of the road-to-rig approach by providing objective metrics and methods.

Effects of Planting Density on Yield and Sourcesink Characteristics of Sweet Potato[Ipomoea batatas(L.) Lam]

[Objective] The aim was to resolve the issue of sparsely planting （37 500-40 500 plants/hm2） of sweet potato in hilly areas. [Method] The starch-oriented Jishu No.21 and raw-eating oriented Jishu No.22 were studied to explore effects of planting density on yield and sink and source characteristics of sweet potato. [IRe- suit] Leaf area index of Jishu No.21 and Jishu No.22 were increasing upon planting density. Leaf area index of the same planting density showed a single-peak curve. Specifically, leaf area index grew fast during the 40th-80th d after planting, and reached the peak on the 80th d after planting, followed by decreasing. What＇s more, ventilation and sunshine transmission both declined upon planting density, as well as the number of leaf, the number of branch, the length of vine, dry and fresh weights of stem and leaf. When planting density exceeded 75 000 plants/hm2, the yield of sweet potato dropped dramatically. Besides, the optimal planting density tended to be volatile upon cultivars. For example, the range of 45 000-60 000 plants/hm2 is the optimal planting density of Jishu No.21 and the range of 60 000-75 000 plants/hm2 is the optimal planting density of Jishu No.22. [Conclusion] It can be concluded that rational planting densities would well coordinate sweet potato growth of ground parts and underground parts to get a high yield by providing a rational group structure. Considering the optimal planting density differs upon cultivars, it is necessary to take genotype, environment, soil fertility and planting density into consideration in determining planting density.

Discovering hidden information of gene ontology based on complex networks analysis

To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empirical studies of the gene ontology with various perspectives, this paper shows that the whole gene ontology displays the same topological features as complex networks including ＂small world＂ and ＂scale-free＂,while some sub-ontologies have the ＂scale-free＂ property but no ＂small world＂ effect.The potential important terms in an ontology are discovered by some famous complex network centralization methods.An evaluation method based on information retrieval in MEDLINE is designed to measure the effectiveness of the discovered important terms.According to the relevant literature of the gene ontology terms,the suitability of these centralization methods for ontology important concepts discovering is quantitatively evaluated.The experimental results indicate that the betweenness centrality is the most appropriate method among all the evaluated centralization measures.

Clustering analysis algorithm for security supervising data based on semantic description in coal mines

In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.

The Effect of Sowing Date and Density on the Characters and Yield of Maize in Chongqing

In order to investigate the most suitable sowing period and the optimum planting density of new com variety ‘Yudan 30＇ In Chongqing region, using split plot experiment design, the effect of sowing date and planting density on main a- gronomic characters and yield of maize in the field was studied. The results showed that in Chongqing, the delay of sowing date could shorten the fertility peri- od, and reduce 100-grain Weight and yield, but could increase plant height and ear height, panicle traits did not change significantly. With the density increasing, plant height and ear height also increased, while ear length, ear diameter, stem diameter, row number and kernel number also decreased. 100-grain weight and yield also in- creased with the increase of density, but to a certain threshold, yield and 100-grain weight decreased with the increase of density. The yield of 3 sowing periods pre- sented as AI〉A2〉A3, the yield of 4 kinds of density presented as B3〉EH〉B2〉B1, and the yield under sowing time and density interaction presented as AIB3〉A1B4〉 A2.B3〉A2.B4〉A3B3〉 A3B4〉A2.B2〉A1BI〉A2BI〉A3BI. So proper eady sowing and increase of planting density could raise the yield of maize per unit area, and AIB3 was the optimum planting configuration in Chongqing area.

Effects of Planting Density and Nitrogen Amount on Stalk Lodging-Resistance and Yield of Summer Maize in Sichuan Basin

[Objective] The experiment was conducted to explore the suitable planting density and nitrogen amount for summer maize in Sichuan Basin with the objective to provide technical reservation and scientific basis for high-yielding cultivation technique.[Method] A widely planted maize cultivar ＇Chengdan 30＇ was used as experimental material to study the effects of planting density and nitrogen amount on the stalk agronomic traits,stalk lodging-resistance mechanical characters,stalk breaking percentage and yield of maize.Experiment was arranged in a two-factor split plot design with three replicates.The planting density was the main factor with three density gradients（4.5×10^4,6.0×10^4 and 7.5×10^4 plants/hm^2） and the nitrogen amount was the second factor with two different levels of nitrogen content（300 and 375 kg/hm^2）.[Result] The stalk lodging-resistance and yield were affected by planting density significantly.The increase of planting density would result in an increase of internode length and decrease of internode diameter,dry matter weight of per unit stalk length,rind penetration strength and breaking resistance of 3rd and 4th basal internodes.When planting density increased from 6.0×10^4 plants/hm2 to 7.5×10^4 plants/hm^2,the stalk breaking percentage in the whole growing season increased by 17.17%,and the yield reduced by 17.58%.The interaction between planting density and nitrogen amount affected the stalk breaking percentage in the whole growing season and yield significantly.The treatment with planting density of 6.0×104 plants/hm^2 and nitrogen amount of 375 kg/hm^2 of pure N was an optimal combination,which may not only control the stalk breaking percentage of whole growing stage effectively,but also could obtain an optimum grain yield.[Conclusion] In Sichuan Basin,the appropriate planting density and nitrogen amount for summer maize were 6.0×10^4 plants/hm^2 and 375 kg/hm^2.

Design of new biomedical titanium alloy based on d-electron alloy design theory and JMatPro software

A new kind offl biomedical titanium alloy, Ti-35Nb-4Sn-6Mo-9Zr, composed of non-toxic elements Nb, Mo, Zr and Sn with lower elastic modulus and higher strength was designed based on d-electron alloy design theory and JMatPro software using orthogonal experiment. The microstructure and basic mechanical properties of designed alloy were investigated. The results show that the alloy is composed of single fl equiaxed grains after solution treatment at 800 ~C. Compared with Ti-6A1-4V, the mechanical properties of the designed alloy are more excellent： E=65 GPa, σb=834 MPa, σ0.2=802 MPa, and σ=11%, which is expected to become a promising new type implanted material. The research approach adopted can reduce the experimental time and cost effectively, and get the ideal experimental results.

Multiple attribute decision making method based on trapezoid fuzzy linguistic variables

The problem of multiple attribute decision making under fuzzy linguistic environments, in which decision makers can only provide their preferences （attribute values）in the form of trapezoid fuzzy linguistic variables（TFLV）, is studied. The formula of the degree of possibility between two TFLVs is defined, and some of its characteristics are studied. Based on the degree of possibility of fuzzy linguistic variables, an approach to ranking the decision alternatives in multiple attribute decision making with TFLV is developed. The trapezoid fuzzy linguistic weighted averaging （TFLWA） operator method is utilized to aggregate the decision information, and then all the alternatives are ranked by comparing the degree of possibility of TFLV. The method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision results reasonable and effective. Finally, the implementation process of the proposed method is illustrated and analyzed by a practical example.

ANALYSIS FOR AIRCRAFT TAXIING AT VARIABLE VELOCITY ON UNEVENNESS RUNWAY BY THE POWER SPECTRAL DENSITY METHOD

In this paper a novel approach for the analysis of non stationary response of aircraft landing gear taxiing over an unevenness runway at variable velocity is explored, which is based on the power spectral density method. A concerned analytical landing gear model for simulating actual aircraft taxiing is formulated. The equivalent linearization results obtained by probabilistic method are inducted to treat landing gear non linear parameters such as shock absorber air spring force, hydraulic damping and Coulomb friction, tire stiffness and damping. The power spectral density for non stationary analysis is obtained via variable substitution and then Fourier transform. A representative response quantity, the overload of the aircraft gravity center, is analyzed. The frequency response function of the gravity overload is derived. The case study demonstrates that under the same reached velocity the root mean square of the gravity acceleration response from constant acceleration taxiing is smaller than that from constant velocity taxiing and the root mean square of the gravity acceleration response from lower acceleration taxiing is greater than that from higher acceleration.

Use of the pilodyn for assessing wood properties in standing trees of Eucalyptus clones

The effectiveness of pilodyn was tested in evaluating wood basic density, outer wood density, heartwood density, and modulus of elasticity （MoE） at 22 four-year-old eucalyptus clones in Guangxi, China. Results indicated that the mean value ranged from 9.44 to 15.41 mm for Pilodyn penetration, 0.3514 to 0.4913 g.cm^-3 for wood basic density, and 3.94 to 7.53 Giga Pascal （GPa） for MoE, respectively. There were significant differences （1% level） in pilodyn penetration between different treatments, different directions and among the clones. Generally strongly negative correlations were found between pilodyn penetration and wood properties, and the coefficients ranged from -0,433 to -0,755. Our results, together with other studies, suggest that the use of pilodyn for assessing wood density and MoE was confirmed as a possibility.

Effect of slice scope on data slice-based class cohesion metrics

This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.

MULTIVARIATE ABSOLUTE DEGREE OF GREY INCIDENCE BASED ON DISTRIBUTION CHARACTERISTICS OF POINTS

The analysis result of absolute degree of grey incidence for multivariate time series is often inconsistent with the qualitative analysis. To overcome this shortage, a multivariate absolute degree of grey incidence based on distribution characteristics of points is proposed. Based on the geometric description of multivariate time se- ries, the neighborhood extrema are extracted in the different regions, and a characteristic point set is constructed. Then according to the distribution of the characteristic point set, a characteristic point sequence reflecting the ge- ometric features of multivariate time series is obtained. The incidence analysis between multivariate time series is transformed into the relational analysis between characteristic point sequences, and a grey incidence model is established. The model possesses the properties of translational invariance, transpose and rank transform invari- ance, and satisfies the grey incidence analysis axioms. Finally, two cases are studied and the results prove the ef- fectiveness of the model.

Rock critical porosity inversion and S-wave velocity prediction

A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.

Part-level 3-D object classification with improved interpretation tree

For classifying unknown 3-D objects into a set of predetermined object classes, a part-level object classification method based on the improved interpretation tree is presented. The part-level representation is implemented, which enables a more compact shape description of 3-D objects. The proposed classification method consists of two key processing stages： the improved constrained search on an interpretation tree and the following shape similarity measure computation. By the classification method, both whole match and partial match with shape similarity ranks are achieved; especially, focus match can be accomplished, where different key parts may be labeled and all the matched models containing corresponding key parts may be obtained. A series of experiments show the effectiveness of the presented 3-D object classification method.

Modeling and performance evaluation of QoS-aware job scheduling of computational grids

To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.

Preparation of phenol formaldehyde resin from phenolated wood

The technique for preparing phenol formaldehyde resin from phenolated wood (PWF) and its characters were studied and analyzed. Poplar (Populus spp.) wood meal was liquefied by phenol in the presence of sulfuric acid as a catalyst. After the liquefied products were cooled, alkaline catalyst and formaldehyde were added. The mixture was kept at (60?) C for 1h and then was heated to (85?) C for 1h. The influence of molar ratio of formaldehyde to phenol (F/P) was investigated. The results showed when the molar ratio of formaldehyde to phenol was over 1.8, the PWF adhesives had high bond quality, bond durability and extremely low aldehydes emissions.

Study on Matter Production and Population Photosynthetic Characteristics of High-yielding Spring Maize under Different Modes

In order to construct a good population structure, improve the light energy utilization ratio, and give a full play to the high-yielding potential of spring maize, the effects of maize variety, planting density and fertilizer management on matter production and population photosynthetic physiological indices of spring maize were investigated under three different modes （traditional mode, optimized mode and high- yielding mode）. The results showed that compared with those under the traditional mode, the yield of spring maize under the optimized mode and high-yielding mode was increased by 10.79% and 27.62%, respectively, and the barren tip length was reduced significantly. Among the three modes, the leaf area index （LA/）, leaf area duration （LAD）, dry matter accumulation （DMA） and crop growth rate （CGR） all ranked as high-yielding rnode＇s〉optimized mode＇s〉traditional mode＇s. In conclusion, optimized variety, appropriately increased planting density and strengthened fertilizer management are the key measures to obtain high yield of spring maize.

Noise filtering of full-gravity gradient tensor data

In oil and mineral exploration, gravity gradient tensor data include higher- frequency signals than gravity data, which can be used to delineate small-scale anomalies. However, full-tensor gradiometry （FTG） data are contaminated by high-frequency random noise. The separation of noise from high-frequency signals is one of the most challenging tasks in processing of gravity gradient tensor data. We first derive the Cartesian equations of gravity gradient tensors under the constraint of the Laplace equation and the expression for the gravitational potential, and then we use the Cartesian equations to fit the measured gradient tensor data by using optimal linear inversion and remove the noise from the measured data. Based on model tests, we confirm that not only this method removes the high- frequency random noise but also enhances the weak anomaly signals masked by the noise. Compared with traditional low-pass filtering methods, this method avoids removing noise by sacrificing resolution. Finally, we apply our method to real gravity gradient tensor data acquired by Bell Geospace for the Vinton Dome at the Texas-Louisiana border.