Learning range estimation on the firing line. (OSRD, 1944; Publ. Bd., No. 4023.).

1946 ◽  
Author(s):  
M. S. Viteles
Keyword(s):  
1970 ◽  
Author(s):  
Robert L. Hilgendorf ◽  
John C. Simons
Keyword(s):  

2018 ◽  
Vol 2 (2) ◽  
pp. 257
Author(s):  
Zulparis Zulparis

This research is a classroom action research. The formulation of the problem in this research is whether theapplication of the firing line strategy can improve the learning outcomes of Islamic religious education materialnatural of jaiz for Allah SWT grade IV students SDN 005 Koto Perambahan Kecamatan Kampa KabupatenKampar? This research aims to increase learning outcomes Islamic religious education grade IV SDN 005 KotoPerambahan Kecamatan Kampa Kabupaten Kampar through the strategy of the firing line. The research wasconducted two cycles. The data outlined are prior to action, in cycle I and cycle II. Each cycle is done in twomeetings. As for the stages in each cycle, that is 1) action planning/ preparation, 2) action implementation, 3)observation, and 4) reflection. Based on the research result of the application of the firing line strategy on PAIsubjects, it is known that there is an increase in learning outcome test from before action, cycle I to cycle II.Before the students learning outcomes were medium by percentage with an average of 56.8%, there is anincrease in learning outcomes from cycle I to cycle II. In the cycle I, students learning outcomes were 72.2% inthe medium category. In the cycle II, students learning outcomes were 85,2% in the good category. From theabove data it is known that the results of student learning on the subjects of Islamic religious education on thematerial nature of jaiz for Allah SWT can be increased through the application of the strategy of the firing line.


Author(s):  
Anton Rozhkov ◽  
Anton Popov ◽  
Vitaliy Balahonskiy

The article is devoted to the study of subjective factors affecting shooting accuracy of law enforcement officers. The empirical study identified some subjective factors reducing gun shooting accuracy and effectiveness among law enforcers. These characteristics include sensorimotor coordination and subjective experience of stress during the shooting process. Scientific analysis made it possible to determine statistical significance of the influence of these factors on the accuracy of shooting. To increase the effectiveness of shooting among officers with a low index of sensorimotor coordination, the authors suggest using exercises aimed at cultivating sensorimotor coordination in fire training classes. While working with employees being under a high level of subjectively experienced stress, more attention should be paid to training techniques to overcome stress and form intelligent behavior in extreme situations. The authors also draw readers’ attention to factors increasing the effectiveness of shooting: officers’ ability to determine the subjective level of stress, their knowledge of emotional self-regulation techniques, knowledge of the sequence of their actions in the firing line.


2021 ◽  
Vol 13 (10) ◽  
pp. 1956
Author(s):  
Jingyu Cong ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Mengxing Huang ◽  
Liangtian Wan

The traditional frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar two-dimensional (2D) super-resolution (SR) estimation algorithm for target localization has high computational complexity, which runs counter to the increasing demand for real-time radar imaging. In this paper, a fast joint direction-of-arrival (DOA) and range estimation framework for target localization is proposed; it utilizes a very deep super-resolution (VDSR) neural network (NN) framework to accelerate the imaging process while ensuring estimation accuracy. Firstly, we propose a fast low-resolution imaging algorithm based on the Nystrom method. The approximate signal subspace matrix is obtained from partial data, and low-resolution imaging is performed on a low-density grid. Then, the bicubic interpolation algorithm is used to expand the low-resolution image to the desired dimensions. Next, the deep SR network is used to obtain the high-resolution image, and the final joint DOA and range estimation is achieved based on the reconstructed image. Simulations and experiments were carried out to validate the computational efficiency and effectiveness of the proposed framework.


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