scholarly journals Optimization of training time for self-conducting classes by cadet managers using a computer program in everyday activities

2021 ◽  
Vol 10 (2) ◽  
pp. 260-265
Author(s):  
Mikhail Yuryevich Kasavtsev ◽  
Danil Viktorovich Rychkov ◽  
Ruslan Mikhailovich Dulishkin
Keyword(s):  
Computer Program ◽  
Military Personnel ◽  
Training Group ◽  
Training Process ◽  
Training Time ◽  
Everyday Activities ◽  
Time Control ◽  
Automatic Mode ◽  
The Hours ◽  
Monitoring Training

The paper describes the process of training sessions, where cadets-leaders are trained to independently teach military personnel general military regulations with an emphasis on the procedure for monitoring training time. Observations of military personnel conducted by the authors during the training showed that the issue of monitoring the methodological parts and the breaks between the hours of the class makes it necessary to distract the attention of military personnel from training with a certain frequency. Moreover, the switching of attention occurs among the cadet-head and the duty officer for the training group. The authors propose to solve this problem by automating the control of the chronology of the lesson through the use of computer technologies. As a result, a computer program was developed; it performs operations of monitoring training time in automatic mode and, if necessary, visualizes its timing. Testing of the developed program for military personnel training in the course of daily activities confirmed the hypothesis of the study and showed that after a period of cadets adaptation to the automation of training time control, its optimization is achieved due to a more complete concentration of students on the training process.

SVM-based global vision system of sports competition and action recognition

2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma
Keyword(s):  
Target Recognition ◽  
Vision System ◽  
Task Assignment ◽  
Recognition Algorithm ◽  
Control Factor ◽  
Training Time ◽  
Adaboost Algorithm ◽  
Advantages And Disadvantages ◽  
Time Control ◽  
Correlation Degree

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.

Early Morning Training Impacts Previous Night’s Sleep in NCAA Division I Cross Country Runners

2020 ◽  
Vol 28 (1) ◽  
pp. 27-33
Author(s):  
Courteney L. Benjamin ◽  
William M. Adams ◽  
Ryan M. Curtis ◽  
Yasuki Sekiguchi ◽  
Gabrielle E.W. Giersch ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Ncaa Division I ◽  
Early Morning ◽  
Sleep Diary ◽  
Training Time ◽  
Sleep Quantity ◽  
The Hours ◽  
Cross Country ◽  
Cross Country Runners ◽  
Study Participants

The effects of training time on sleep has been previously studied; however, the influence on sleep in female collegiate cross-country runners is unknown. The aim of this study was to investigate the influence of training time on self-reported sleep metrics. Eleven female collegiate cross-country runners (mean [M] age = 19 years, standard deviation [SD] age = 1 year; M [SD] body mass = 58.8 [9.6] kg; M [SD] height = 168.4 [7.7] cm; M [SD] VO2max = 53.6 [5.6] mL·kg−1·min−1) competing in the 2016 NCAA cross-country season were included in this study. Participants completed a sleep diary daily to assess perceived measures of sleep on days when training took place between the hours of 5:00–8:00 a.m. (AM), and when training did not take place during this time (NAM). Sleep quality questions utilized a 5-point Likert scale, in which a score of 1 is associated with the worst outcomes and a score of 5 is associated with the best outcomes. Sleep duration was significantly higher on NAM (M [SD] = 8.26 [1.43] h) compared to AM (M [SD] = 7.97 [1.09] h, p < .001). Sleep quality was significantly higher on NAM (M [SD] = 3.30 [1.01]) compared to AM (M [SD] = 3.02 [1.06], p < .001). The impairment of sleep quantity and quality the night prior to early morning training suggests that future considerations should be made to sleep schedules and/or training times to optimize perceived sleep quality.

scholarly journals Tactile angle discriminability improvement: roles of training time intervals and different types of training tasks

2019 ◽  
Vol 122 (5) ◽  
pp. 1918-1927
Author(s):  
Wu Wang ◽  
Jiajia Yang ◽  
Yinghua Yu ◽  
Qiong Wu ◽  
Jiabin Yu ◽  
...  
Keyword(s):  
Perceptual Learning ◽  
Task Performance ◽  
Early Stage ◽  
Interval Training ◽  
Training Group ◽  
Orientation Discrimination ◽  
Time Interval ◽  
Time Intervals ◽  
Training Time ◽  
Angle Discrimination

Perceptual learning, which is not limited to sensory modalities such as vision and touch, emerges within a training session and between training sessions and is accompanied by the remodeling of neural connections in the cortex. However, limited knowledge exists regarding perceptual learning between training sessions. Although tactile studies have paid attention to between-session learning effects, there have been few studies asking fundamental questions regarding whether the time interval between training sessions affects tactile perceptual learning and generalization across tactile tasks. We investigated the effects of different training time intervals on the consecutive performance of a tactile angle discrimination (AD) task and a tactile orientation discrimination (OD) task training on tactile angle discriminability. The results indicated that in the short-interval training group, AD task performance significantly improved in the early stage of learning and nearly plateaued in the later stage, whereas in the long-interval training group, significant improvement was delayed and then also nearly plateaued in the later stage; additionally, improved OD task performance resulted in improved AD task performance. These findings suggest that training time interval affects the early stage of learning but not the later stage and that generalization occurs between different types of tactile tasks. NEW & NOTEWORTHY Perceptual learning, which constitutes important foundations of complicated cognitive processes, is learning better perception skills. We demonstrate that training time interval can affect the early stage of learning but not the later stage. Moreover, a tactile orientation discrimination training task can also improve tactile angle discrimination performance. These findings may expand the characteristics of between-session learning and help understand the mechanism of the generalization across tactile tasks.

AUV 3D Path Planning Based on the Improved Hierarchical Deep Q Network

2020 ◽  
Vol 8 (2) ◽  
pp. 145 ◽  
Author(s):  
Yushan Sun ◽  
Xiangrui Ran ◽  
Guocheng Zhang ◽  
Hao Xu ◽  
Xiangbin Wang
Keyword(s):  
Path Planning ◽  
Simulation Training ◽  
Autonomous Underwater Vehicle ◽  
Field Tests ◽  
Underwater Vehicle ◽  
Artificial Potential Field ◽  
Training Process ◽  
Training Time ◽  
Experience Replay ◽  
Planning Task

This study proposed the 3D path planning of an autonomous underwater vehicle (AUV) by using the hierarchical deep Q network (HDQN) combined with the prioritized experience replay. The path planning task was divided into three layers, which realized the dimensionality reduction of state space and solved the problem of dimension disaster. An artificial potential field was used to design the positive rewards of the algorithm to shorten the training time. According to the different requirements of the task, this study modified the rewards in the training process to obtain different paths. The path planning simulation and field tests were carried out. The results of the tests corroborated that the training time of the proposed method was shorter than that of the traditional method. The path obtained by simulation training was proved to be safe and effective.

scholarly journals The effect of the EWTD on training in general surgery: an analysis of electronic logbook records

2007 ◽  
Vol 89 (3) ◽  
pp. 106-109 ◽  
Author(s):  
T Bates ◽  
E Cecil ◽  
I Greene
Keyword(s):  
Negative Impact ◽  
Junior Doctors ◽  
Training Time ◽  
Duty Hours ◽  
Hands On ◽  
Hours Of Work ◽  
The Hours ◽  
Electronic Logbook ◽  
The Uk ◽  
The New Deal

The introduction of time-limited surgical training in the UK in 1994 following the Calman report raised concerns over the hands-on experience of trainees, heightened by the hours reduction demanded by the New Deal. From 1994, junior doctors' on-duty hours of work for hard-pressed posts were targeted to a limit of 56 hours but SpRs were allowed a voluntary extension from 73 on-duty hours to a maximum of 83 hours per week. By 1995 concern was being expressed at the reduction in training time and continuity of patient care and although calls for more targeted training were made, evidence of a negative impact on training has continued to surface.

Feasibility and Efficacy of Brief Computerized Training to Improve Emotion Recognition in Premanifest and Early-Symptomatic Huntington’s Disease

2017 ◽  
Vol 23 (4) ◽  
pp. 314-321 ◽  
Author(s):  
Clare L. Kempnich ◽  
Dana Wong ◽  
Nellie Georgiou-Karistianis ◽  
Julie C. Stout
Keyword(s):  
Huntington's Disease ◽  
Sample Size ◽  
Emotion Recognition ◽  
Huntington’S Disease ◽  
Training Group ◽  
Control Group ◽  
Significant Group ◽  
Training Time ◽  
Training Tool ◽  
Computerized Training

AbstractObjectives: Deficits in the recognition of negative emotions emerge before clinical diagnosis in Huntington’s disease (HD). To address emotion recognition deficits, which have been shown in schizophrenia to be improved by computerized training, we conducted a study of the feasibility and efficacy of computerized training of emotion recognition in HD. Methods: We randomly assigned 22 individuals with premanifest or early symptomatic HD to the training or control group. The training group used a self-guided online training program, MicroExpression Training Tool (METT), twice weekly for 4 weeks. All participants completed measures of emotion recognition at baseline and post-training time-points. Participants in the training group also completed training adherence measures. Results: Participants in the training group completed seven of the eight sessions on average. Results showed a significant group by time interaction, indicating that METT training was associated with improved accuracy in emotion recognition. Conclusions: Although sample size was small, our study demonstrates that emotion recognition remediation using the METT is feasible in terms of training adherence. The evidence also suggests METT may be effective in premanifest or early-symptomatic HD, opening up a potential new avenue for intervention. Further study with a larger sample size is needed to replicate these findings, and to characterize the durability and generalizability of these improvements, and their impact on functional outcomes in HD. (JINS, 2017, 23, 314–321)

scholarly journals DIGITAL INFORMATION TECHNOLOGIES IN THE SELECTION AND TRAINING OF YOUNG DRAUGHTS PLAYERS

2020 ◽  
Vol 30 (1) ◽  
pp. 69-75
Author(s):  
P.K. Petrov ◽  
S.P. Torokhova
Keyword(s):  
Computer Program ◽  
Information Technologies ◽  
Selection Process ◽  
Educational Resource ◽  
Digital Information ◽  
Training Process ◽  
Functional Features ◽  
Student’S T ◽  
And Training ◽  
Student’S T Test

The article discusses issues related to the study of the effectiveness of a digital educational resource in the form of a computer program for the selection and training of children 6-8 years old in the intellectual sport of "draughts (checkers)". The structure and functional features of the created computer program are revealed. The scale of the coefficient of combinational vision has been substantiated, which allows assessing the level of development of combinational vision in young draughts players both during selection in the draughts section and during correction of the training process. To assess the effectiveness of the developed methodology, a pedagogical experiment was used; the significance of differences between the results was calculated using Student's t-test for dependent results. The results obtained in the study showed the effectiveness of using the developed computer program in training and evaluating the development of the combinational vision of young draughtsmen as one of the main indicators of the draughtsman’s ability to make a final strike, leading to the win of the match. The results can be used in the selection process and in the training process in sports sections and draughts (checkers) clubs.

scholarly journals The Interim Evaluation of Training Processes: The Case of the Second Level Professional Master’s Program in Family and Community Mediation

2021 ◽  
Vol 13 (20) ◽  
pp. 11434
Author(s):  
Sara Molgora ◽  
Chiara Fusar Poli ◽  
Giancarlo Tamanza
Keyword(s):  
Evaluation System ◽  
Process Analysis ◽  
Training Evaluation ◽  
Training Group ◽  
Outcome Evaluation ◽  
Sustainable Growth ◽  
Master's Program ◽  
Training Process ◽  
Community Mediation ◽  
The Individual

This contribution illustrates the training evaluation system developed within the Master’s Program in Family and Community Mediation at Università Cattolica del Sacro Cuore in Milan. This is an interim evaluation which focuses on the training process and which considers the collaboration with the subjects of the training to be fundamental. The peculiarity of this work concerns the possibility of inserting research within the training process, following a logic of mutual enrichment both in terms of content and learning. The contribution illustrates in detail the outcome and the process evaluation system, defining the perspective, the objectives, and the methodology of implementation. In particular, the outcome evaluation focuses on the distal and proximal outcomes of the training, while the process analysis focuses on the dynamics within the group of participants. Preliminary findings from 33 participants highlighted that the majority of participants (19) have a “regular” profile, that is, they appreciate both the theoretical contents, as well as the practical activities proposed during the training program. As for the process, the findings showed the importance of reflexivity as a major factor of change. Although these findings are referred to the specific experience of a particular group, and so further evaluations involving different training groups and other training processes are needed, this training evaluation system sheds light on both the topic and the context in which training is delivered. The integration between different points of view and several levels of analysis allows the researchers to deepen the individual path of each participant as well as to obtain feedbacks on the progress of the training group as a whole and allows participants to better understand their contexts of work thanks to the use of reflexivity. This can guarantee a sustainable growth both at individual and interpersonal level.

scholarly journals Training-Time-Friendly Network for Real-Time Object Detection

2020 ◽  
Vol 34 (07) ◽  
pp. 11685-11692
Author(s):  
Zili Liu ◽  
Tu Zheng ◽  
Guodong Xu ◽  
Zheng Yang ◽  
Haifeng Liu ◽  
...  
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Batch Size ◽  
Training Process ◽  
Training Time ◽  
Sample Weights ◽  
Gaussian Kernels ◽  
Novel Approach ◽  
Training Samples ◽  
Speed And Accuracy

Modern object detectors can rarely achieve short training time, fast inference speed, and high accuracy at the same time. To strike a balance among them, we propose the Training-Time-Friendly Network (TTFNet). In this work, we start with light-head, single-stage, and anchor-free designs, which enable fast inference speed. Then, we focus on shortening training time. We notice that encoding more training samples from annotated boxes plays a similar role as increasing batch size, which helps enlarge the learning rate and accelerate the training process. To this end, we introduce a novel approach using Gaussian kernels to encode training samples. Besides, we design the initiative sample weights for better information utilization. Experiments on MS COCO show that our TTFNet has great advantages in balancing training time, inference speed, and accuracy. It has reduced training time by more than seven times compared to previous real-time detectors while maintaining state-of-the-art performances. In addition, our super-fast version of TTFNet-18 and TTFNet-53 can outperform SSD300 and YOLOv3 by less than one-tenth of their training time, respectively. The code has been made available at https://github.com/ZJULearning/ttfnet.

scholarly journals Design of Artificial Neural Networks to Recognize Fingerprint Patterns

2019 ◽  
Vol 3 (1) ◽  
pp. 58
Author(s):  
Frinto Tambunan ◽  
Yudi Y ◽  
Muhammad Fauzi
Keyword(s):  
Pattern Recognition ◽  
Recognition System ◽  
Research Data ◽  
Training Process ◽  
Fingerprint Image ◽  
Training Time ◽  
Digital Fingerprint ◽  
Fingerprint Pattern ◽  
Level Of Understanding ◽  
Threshold Process

Image or pattern recognition system is one of the branches in computer science, this system can help the processing of fingerprint patterns, especially in the banking, police and users of other institutions who really feel the importance of using fingerprints. Several stages in fingerprint pattern image recognition are through the process of scanning, then the resulting digital fingerprint image is converted to a certain value, among others, the threshold process, the division of images, and representation of input values. The training process is carried out using two treatments: the first with a different level of understanding and the second training with different unit numbers, the best training is obtained with a level of understanding of 0.3 and the number of hidden units 10 by producing a short training time and relatively small errors. Fingerprint pattern recognition is done by two trials, based on 1 number of training patterns and 5 number of training patterns. From the research data, the ability of the system to recognize output patterns is greater if the number of training patterns increases, with a number of 1 training patterns, the system is able to recognize 50% external patterns while the 5 system training patterns are able to recognize 70% output patterns.

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