“目标定向—分类指导”教学再探

“目标定向—分类指导”教学是班级授课制适应学生个别差异、发展优势潜能、提高教学效率的有效模式。“目标定向—分类指导”的核心 ,是根据不同教学环境和要求 ,对学生进行非歧视性分类教学、指导和评价 ,以有利于各类学生的全面发展。

谈“目标定向,分类指导”教学应注重的四个环节

“目标定向,分类指导”教学的基本模式可概括为:教师:“激趣导向→点拨导思→拓展导创;过程:读→思→练;学生:自主参与→自主探究→自主发展”.其中“过程”中的“读”,教师将“目标”定向激发动机,学生异步自学感知质疑.“过程”中的“思”,教师将问题导引分类研讨,学生领悟反思总结规律.“过程”中的“练”,教师将分类达标反馈回授,学生拓展迁移实践创新.

Oriented Bounding Box Object Detection Model Based on Improved YOLOv8

In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different orientations.Existing OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed detection.In this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing images.Firstly,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation information.Secondly,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information appropriately.Finally,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion layer.This innovative structure helped the model to better focus on the target area.The precision and robustness of oriented target detection were also improved.Experimental results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original model.This improvement is effective in detecting small targets and complex scenes.

Application of Kalman filter on mobile robot self-localization

Self-localization is a fundamental requirement for the mobile robot. Robot usually contains a large number of dif- ferent sensors, which provide the information of robot localization, and all the sensor information should be considered for the optimal location. Kalman filter is efficient to realize the information fusion. Used as an efficient sensor fusion algorithm, Kalman filter is an advanced filtering technique which can reduce errors of the position and orientation of the sensors. Kalman filter has been paied much attention to robot automation and solutions to solve uncertainties such as robot localization, navigation, following, tracking, motion control, estimation and prediction. The paper briefly describes Kalman filter theory, and establishes a simple mathematical model based on muti-sensor mobile robot. Meanwhile, Kalman filter is used in robot self-localization by simulations, and it is demonstrated by simulations that Kalman filter is effective.

SCENARIO AND TARGET SIMULATION FOR A GROUND BASED MULTIFUNCTION PHASED ARRAY RADAR

This paper describes a scenario and target simulation which operates in non real-time to provide full closed-loop operation of the ground based multifunction phased array radar simulation system in support of ballistic missile defence experiments against countermeasure. By simulating the target scattering signature and dynamical signature, this scenario and target simulation provide re-alistic scenario source to evaluate the system performance of multifunction phased array radar, and the key algorithms verification and validation such as target tracking, multi-target imaging and target recognition.

Methods, current status, and prospect of targeted observation

Targeted observation is an observation strategy by which the concerned phenomenon is observed. In geoscienee, targeted ob- servation is mainly related to the forecasts of weather events or predictions of climate events. This paper will first review the history of targeted observation, and then introduce the main methods used in targeted observation. The discussion on the theo- retical basis of targeted observation includes its advantages and limitations. After presenting the current situation of domestic and international targeted observations in atmospheric and oceanic sciences, the methods used for targeted observation, and their effect evaluation and testing are mainly discussed here. Finally, the author presents his suggestion about the prospect of further development in the field, and how to extend the method of targeted observation to deal with numerical model errors.

Optimization of equimolar reverse constant-temperature mass-diffusion process for minimum entransy dissipation

The mass entransy describes the mass-diffusion ability of the solution system, and the mass-diffusion process with the finite concentration difference always leads to the mass-entransy dissipation. This paper studies the equimolar reverse constant-temperature mass-diffusion process with Fick's law( g∝Δ(c)). The optimal concentration paths for the MED(Minimum Entransy Dissipation) are derived and compared with those for the MEG(Minimum Entropy Generation) and CCR(Constant Concentration Ratio) operations. It is indicated that the strategy of the MED is equivalent to that of the CCD(Constant Concentration Difference) of the same component; whether the MED or the MEG is selected as the optimization objective, the strategy of the CCD is much better than that of the CCR.

ON CONE D.C. OPTIMIZATION AND CONJUGATE DUALITY

This paper derives first order necessary and sufficient conditions for unconstrained coned.c. Programming problems where the underlined space is partially ordered with respect to acone. These conditions are given in terms of directional derivatives and subdifferentials of thecomponent functions. Moreover, conjugate duality for cone d.c. Optimization is discussed andweak duality theorem is proved in a more general partially ordered linear topological vectorspace (generalizing the results in [11]).