试论《大学语文》教学的理想目标及达成方法

本文从《大学语文》教学存在的若干问题入手 ,从教材编写和师资队伍建设两个方面 ,对《大学语文》

初中英语听说课精准教学目标的达成方法解读

在开展初中英语教学时,我们需要在课堂教学中实现“简约”、“生本”,而实现这一目标的基础是我们要做到“精准”。如要和学生的真实想法进行对话,要了解学生的现实学情,要把握学生的未来需求,进而让我们设计的课堂教学活动与其能够实现“精准对接”。如我们要挖掘英语的文化内涵,在课上四十几分钟的时间里不仅仅引导初中学生学习英语的语法技巧,还要让学生“精准”的应用英语,了解其所承载的人文情怀与思想认知。如我们要展现出英语的学科特色,进而让英语成为辅助学生生成能力、素养的载体。在这一过程中,我们要“精准”的设计每一个学习活动。由此可见,能够实现“精准”,是因为我们拥有了教育自信,能够实施优化教学,而学生成为了主动性的学习者,二者之间可以生成合力,进而让课堂教学流程变得“简约有效”,而学生可以获得更多的展示机会。本文中笔者就对如何在听说课中实现“精准”目标进行了分析。

基于工程教育专业认证的毕业要求与课程目标达成评价方法研究

以大连东软信息学院某计算机相关专业为例,提出一种评价毕业要求及课程目标达成的方法,并以单片机原理与接口技术课程为例,介绍课程目标及其支撑的毕业要求达成度评价与持续改进的做法,以期为工程教育专业认证背景下教学活动的建设提供一种思路。

浅谈中职学生个体职业生涯规划达成的方法

随着社会经济的快速发展,各行各业对从业者的整体素质的要求越来越高,职业竞争也越来越激烈,如何引导中职学生树立正确的职业教育观念,指导学生达成职业生涯规划顺利就业越来越受到人们的关注。本人将从以下几个方面。

基于工程教育认证的毕业设计达成度分析方法研究

工程教育认证背景下的毕业设计达成度定量化评价与分析是对专业建设内涵、建设成效、建设目标达成度等指标完成情况的重要评价依据。以信息技术学院计算机科学技术专业为例,分析建立毕业设计达成度评价指标体系,并对2020年、2021年、2022年3年198名毕业生毕业设计达成度情况从整体与单项指标上进行定量化分析,通过对各指标结果的相关性分析及时间序列分析,探讨专业毕业设计各影响要素之间的相互作用关系,分析产生结果的过程,提出评价指标需要持续改进的重点内容,为专业在毕业设计改革和学生质量提升上提供依据和方法。

New extrusion process of Mg alloy automobile wheels

The recent research and development of forged magnesium road wheel were reviewed.Methods of flow-forming,spin forging of manufacturing a forged magnesium alloy wheel were introduced.A new extrusion method was investigated especially. Extrusion from hollow billet was proposed in order to enhance the strength of spoke portion and reduce the maximum forming load. By means of the developed technique,the one-piece Mg wheels were produced successfully by extrusion from AZ80+alloy.At the same time,the existing problems on the research and development of forged magnesium road wheel were analyzed.The impact testing,radial fatigue testing and bending fatigue testing results show that AZ80+wheel can meet application requirement in automobile industry.

IMAGE-BASED SCALING FOR SHIP TOP VIEW ISAR IMAGES

A high quality top view or side view ship ISAR image with proper cross-range scale is very useful for target recognition. A technique aiming at solving the ship top view image scaling is developed, in which the cross-range scale information is obtained by measuring the slopes of the two feature lines of the ship, the centerline and the stern line. Neither the prior knowledge about the ship nor the tracking data is required. The proposed technique is fully based on the image. It is used with ease and high efficiency. Examples are provided to demonstrate its effectiveness with both simulated and real data. The scaled results are in accordance with the real shape of the ship.

Inverse synthetic aperture radar imaging based on sparse signal processing

Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector,an imaging method was presented with the application of sparse signal processing.This method can form higher resolution inverse synthetic aperture radar images from compensating incomplete measured data,and improves the clarity of the images and makes the feature structure much more clear,which is helpful for target recognition.The simulation results indicate that this method can provide clear ISAR images with high contrast under complex motion case.

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.

Research on weak signal extraction and noise removal for GPR data based on principal component analysis

The ground penetrating radar （GPR） detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of underground medium seriously. A method based on principal component analysis （PCA） was proposed to ex- tract the target signal and remove the uncorrelated noise. According to the correlation of signal, the authors get the eigenvalues and corresponding eigenvectors by decomposing the covariance matrix of GPR data and make linear transformation for the GPR data to get the principal components （PCs）. The lower-order PCs stand h^r the strong correlated target signals of the raw data, and the higher-order ones present the uneorrelated noise. Thus the authors can extract the target signal and filter uncorrelated noise effectively by the PCA. This method was demonstrated on real ultra-wideband through-wall radar data and simulated GPR data. Both of the results show that the PCA method can effectively extract the GPR target signal and remove the uncorrelated noise.

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

InSAR Kalman Filter Phase Unwrapping Algorithm Based on SRTM DEM

PU （phase unwrapping） is the key step and important problem in DEM （digital elevation model） extraction and the measurement of surface deformation of InSAR （Interferometric synthetic aperture radar）. The CKFPUA （conventional Kalman filter phase unwrapping algorithm） can obtain reliable results in the flat terrain areas, but it caused error transmission not making the accurate inversion of surface deformation information in the steep terrain. Considering this situation, so it needs to introduce topographic information for guiding phase unwrapping. Here the 90 m resolution DEM data have been used and it is obtained by SRTM （shuttle radar topography mission） measured jointly by NASA （National Aeronautics and Space Administration） and NIMA （National Imaging Mapping Agency） of U.S. Department of Defense. This paper presents a SD-KFPUA （Kalman filter phase unwrapping algorithm） based on SRTM DEM. With SRTM DEM directing InSAR image to implement phase unwrapping, the speed and accuracy are improved. By analyzing with the conventional Kalman filter phase unwrapping algorithms, it is shown that the proposed method can achieve good results in particular to improve unwrapping accuracy in the low coherence region.

小学语文情感领域目标教学刍议

小学语文情感领域目标教学刍议西安市雁塔区教育局教研室李志远一、小学语文情感领域教学目标的制定心理学告诉我们，情感是人对客观事物是否符合自己需要而产生的态度体验．一个学生愿不愿意学习某一学科，并不是说他没有学习这一学科的能力，而是由于某种原因使他形成了...

Consensus-reaching methods for hesitant fuzzy multiple criteria group decision making with hesitant fuzzy decision making matrices

Group decision making plays an important role in various fields of management decision and economics. In this paper, we develop two methods for hesitant fuzzy multiple criteria group decision making with group consensus in which all the experts use hesitant fuzzy decision matrices （HFDMs） to express their preferences. The aim of this paper is to present two novel consensus models applied in different group decision making situations, which are composed of consensus checking processes, consensus-reaching processes, and selection processes. All the experts make their own judgments on each alternative over multiple criteria by hesitant fuzzy sets, and then the aggregation of each hesitant fuzzy set under each criterion is calculated by the aggregation operators. Furthermore, we can calculate the distance between any two aggregations of hesitant fuzzy sets, based on which the deviation between any two experts is yielded. After introducing the consensus measure, we develop two kinds of consensus-reaching procedures and then propose two step-by-step algorithms for hesitant fuzzy multiple criteria group decision making. A numerical example concerning the selection of selling ways about ＇Trade-Ins＇ for Apple Inc. is provided to illustrate and verify the developed approaches. In this example, the methods which aim to reach a high consensus of all the experts before the selection process can avoid some experts＇ preference values being too high or too low. After modifying the previous preference information by using our consensus measures, the result of the selection process is much more reasonable.

Current progress in sparse signal processing applied to radar imaging

Sparse signal processing is a signal processing technique that takes advantage of signal’s sparsity,allowing signal to be recovered with a reduced number of samples.Compressive sensing,a new branch of the sparse signal processing,has become a rapidly growing research field.Sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theories,new systems and new methodologies of microwave imaging.This paper first summarizes the latest application of sparse microwave imaging,including Synthetic Aperture Radar(SAR),tomographic SAR and inverse SAR.As sparse signal processing keeps evolving,an avalanche of results have been obtained.We also highlight its recent theoretical advances,including structured sparsity,off-grid,Bayesian approaches,and point out new research directions in sparse microwave imaging.

Bistatic weak target detection method using non-cooperative air surveillance radar

At present, most of the passive radar system researches utilize FM radios, TV broadcasts, navigation satellites,etc. as illuminators. The transmitted signals are not specifically designed radar waveforms. In this work, the frequency agile, phased array air surveillance radar(ASR) is used as the illuminator of opportunity to detect the weak target. The phased array technology can help realize beam agility to track targets from different aspects simultaneously. The frequency agility technology is widely employed in radar system design to increase the ability of anti-jamming and increase the detection probability. While the frequency bandwidth of radar signals is usually wide and the range resolution is high, the range cell migration effect is obvious during the long time integration of non-cooperative bistatic radar. In this context, coherent integration methods are not applicable. In this work, a parametric non-coherent integration algorithm based on task de-interweaving is proposed. Numerical experiments verify that this is effective in weak target detection.

A feature extraction method for synthetic aperture radar(SAR) automatic target recognition based on maximum interclass distance

Synthetic aperture radar(SAR) automatic target recognition is an important application in SAR.How to extract features has restricted the application of SAR technology seriously.In this paper,a new feature extraction method for SAR automatic target recognition based on maximum interclass distance is proposed,which integrates class and neighborhood information.This method can reinforce discriminative power using maximum interclass distance,so it can improve recognition rate effectively.

SAR motion compensation based on the correction of residual attitude errors

As residual attitude errors are likely to affect the synthetic aperture radar (SAR) imaging, this paper presents a SAR motioncompensation algorithm based on the correction of residual attitude errors. The existing methods all use the antenna stableplatform to correct the attitude errors, and then compensate the trajectory deviations in the following imaging process. Besidescompensating the trajectory deviations, the modified method of this paper also considers the influence of residual attitude er-rors on the SAR imaging, and can compensate both the trajectory deviations and the residual attitude errors. Compared withthe existing methods, the modified method in this paper can more precisely compensate the imperfect motion on the SAR im-aging, especially good for the SAR system with a small platform, near operating distance and a narrow antenna beam. Such asystem causes severe residual attitude errors and needs to consider the influence of antenna beam pointing errors on the imag-ing. The validity of the modified method presented by this paper is demonstrated by the result of the experiment.

Squint-mode InISAR imaging based on nonlinear least square and coordinates transform

Aiming at the interferometric inverse synthetic aperture radar （InlSAR） imaging in the presence of squint, we investigate the influence of squint on the InlSAR imaging. First, coupling of the squint additive phase and the target azimuth/altitude coordinates to be solved may make the solution more difficult. Second, the squint angle may lead to estimation error of the vertical coordinates and distortion of the ultimate image. Traditional InlSAR imaging algorithms can not solve the above two problems effectively, so we propose a new method which combines the nonlinear least square （NLS） and coordinates transform （CT） to estimate the target coordinates, and a three-dimensional （3-D） image consistent with the real target is obtained accordingly. Simulations show that the proposed method is effective for the squint-mode InlSAR imaging.