Training Tasks Research Articles

Virtual reality as a method of cognitive training of processing speed, working memory, and sustained attention in persons with acquired brain injury: a protocol for a randomized controlled trial.

Acquired brain injury (ABI) often leads to persisting somatic, cognitive, and social impairments. Cognitive impairments of processing speed, sustained attention, and working memory are frequently reported and may negatively affect activities of daily living and quality of life. Rehabilitation efforts aiming to retrain these cognitive functions have often consisted of computerized training programs. However, few studies have demonstrated effects that transfer beyond the trained tasks. There is a growing optimism regarding the potential usefulness of virtual reality (VR) in cognitive rehabilitation. The research literature is sparse, and existing studies are characterized by considerable methodological weaknesses. There is also a lack of knowledge about the acceptance and tolerability of VR as an intervention method for people with ABI. The present study aims to investigate whether playing a commercially available VR game is effective in training cognitive functions after ABI and to explore if the possible effects transfer into everyday functioning. One hundred participants (18-65years), with a verified ABI, impairments of processing speed/attention, and/or working memory, and a minimum of 12months post injury will be recruited. Participants with severe aphasia, apraxia, visual neglect, epilepsy, and severe mental illness will be excluded. Participants will be randomized into two parallel groups: (1) an intervention group playing a commercial VR game taxing processing speed, working memory, and sustained attention; (2) an active control group receiving psychoeducation regarding compensatory strategies, and general cognitive training tasks such as crossword puzzles or sudoku. The intervention period is 5weeks. The VR group will be asked to train at home for 30min 5days per week. Each participant will be assessed at baseline with neuropsychological tests and questionnaires, after the end of the intervention (5weeks), and 16weeks after baseline. After the end of the intervention period, focus group interviews will be conducted with 10 of the participants in the intervention group, in order to investigate acceptance and tolerability of VR as a training method. This study will contribute to improve understanding of how VR is tolerated and experienced by the ABI population. If proven effective, the study can contribute to new rehabilitation methods that persons with ABI can utilize in a home setting, after the post-acute rehabilitation has ended.

On some Aspects of the Work of the Faculty of Higher Education

The article is devoted to the issue of attracting teachers to carry out professional activities in higher educational institutions. Reform and optimization of higher education affects nature and conditions of employment of teachers of Russian universities. There is a decrease in the status and prestige of teaching. Legislative changes do not always contribute to increasing the prestige of the profession, as well as the desire of practitioners to transfer their experience to the younger generation in educational organizations. An important role in this is played by the requirements for persons applying for the positions of faculty of higher education. If you look at other problematic aspects of the legal regulation of the labor of education workers, taking into account the optimization of the labor process by the employer, then the status of a teacher of higher education does not become one of the goals of a future career for young professionals. It seems that a more thoughtful approach is needed to establish the requirements for the teaching staff of the university. To achieve the main task of vocational training, an effective system of replacing teaching positions should be established, taking into account the realities of our time.

Towards accurate unsupervised video captioning with implicit visual feature injection and explicit

In the realm of the video captioning field, acquiring large amounts of high-quality aligned video–text pairs remains laborious, impeding its practical applications. Therefore, we explore the modelling techniques for unsupervised video captioning. Using text inputs similar to the video representation to generate captions has been a successful unsupervised video captioning generation strategy in the past. However, this setting relies solely on the textual data for training, neglecting vital visual cues related to the spatio-temporal appearance within the video. The absence of visual information increases the risk of generating erroneous video captions. In view of this, we propose a novel unsupervised video captioning method that introduces visual information related to text features keywords to implicitly enhance training for text generation tasks. Simultaneously, our method incorporates sentence to explicitly augment the training process. our method injects additional implicit visual features and explicit keywords into the model, Which can inject the generated captions with more accurate semantics. the experimental analysis demonstrates the merit of the proposed formulation, achieving superior performance against the state-of-the-art unsupervised studies.

Participation in a Prison-Based Training Programme Is Beneficial for Rescue Dogs.

Dogs are often relinquished because of behavioural issues which may be exacerbated in rehoming centres. Prison-based dog training programmes (DTPs) may enhance outcomes for rescue dogs by providing socialisation and training opportunities to improve behaviour, welfare and likelihood of rehoming. We assessed whether dogs benefitted from participation, 1-3 times per week, in a prison-based DTP in which male young offenders learn how to train and care for dogs waiting to be rehomed. Within DTP sessions, there was significant improvement on a range of training tasks (n = 42 dogs). Analyses of videos (n = 17 dogs) in the kennels and a training barn pre- and post-DTP participation showed improvement in some positive behaviours, but no significant change in other behaviours. Subjective ratings by staff of the dogs' behaviour were made (n = 20 dogs). Desirable behaviours (e.g., playful/friendly) increased, and most undesirable behaviours (e.g., frustrated and noisy) decreased. Participation in the DTP did not mitigate all negative behaviours. However, improvements are consistent with enhanced welfare and likelihood of successful rehoming. Prison-based DTPs can be effective in supporting the work of animal rescue organisations to improve outcomes for dogs, while offering people in custody an opportunity to engage in purposeful activity and provide a community service.

Feasibility of decoding covert speech in ECoG with a Transformer trained on overt speech

Several attempts for speech brain–computer interfacing (BCI) have been made to decode phonemes, sub-words, words, or sentences using invasive measurements, such as the electrocorticogram (ECoG), during auditory speech perception, overt speech, or imagined (covert) speech. Decoding sentences from covert speech is a challenging task. Sixteen epilepsy patients with intracranially implanted electrodes participated in this study, and ECoGs were recorded during overt speech and covert speech of eight Japanese sentences, each consisting of three tokens. In particular, Transformer neural network model was applied to decode text sentences from covert speech, which was trained using ECoGs obtained during overt speech. We first examined the proposed Transformer model using the same task for training and testing, and then evaluated the model’s performance when trained with overt task for decoding covert speech. The Transformer model trained on covert speech achieved an average token error rate (TER) of 46.6% for decoding covert speech, whereas the model trained on overt speech achieved a TER of 46.3% (p>0.05;d=0.07)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$( p > 0.05; d=0.07)$$\\end{document}. Therefore, the challenge of collecting training data for covert speech can be addressed using overt speech. The performance of covert speech can improve by employing several overt speeches.

Boosting wisdom of the crowd for medical image annotation using training performance and task features.

A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International Skin Lesion Challenge 2018 into 7 different categories. There was a large dispersion in the geographical location, experience, training, and performance of the recruited individuals. We tested several wisdom of the crowd algorithms of varying complexity from a simple unweighted average to more complex Bayesian models that account for individual patterns of errors. Using a switchboard analysis, we observe that the best-performing algorithms rely on selecting top performers, weighting decisions by training accuracy, and take into account the task environment. These algorithms far exceed expert performance. We conclude by discussing the implications of these approaches for the development of medical AI.

Attention control training and transfer effects on cognitive tasks

Attention control is the common element underlying different executive functions. The backward Masking Majority Function Task (MFT-M) requires intensive attention control, and represents a diverse situation where attentional resources need to be allocated dynamically and flexibly to reduce uncertainty. Aiming to train attention control using MFT-M and examine the training transfer effects in various executive functions, we recruited healthy young adults (n = 84) and then equally randomized them into two groups trained with either MFT-M or a sham program for seven consecutive days. Cognitive evaluations were conducted before and after the training, and the electroencephalograph (EEG) signals were recorded for the revised Attention Network Test (ANT-R), N-back, and Task-switching (TS) tasks. Compared to the control group, the training group performed better on the congruent condition of Flanker and the double-congruency condition of Flanker and Location in the ANT-R task, and on the learning trials in the verbal memory test. The training group also showed a larger P2 amplitude decrease and P3 amplitude increase in the 2-back task and a larger P3 amplitude increase in the TS task's repeat condition than the control group, indicating improved neural efficiency in two tasks' attentional processes. Introversion moderated the transfer effects of training, as indicated by the significant group*introversion interactions on the post-training 1-back efficiency and TS switching cost. Our results suggested that attention control training with the MFT-M showed a broad transfer scope, and the transfer effect was influenced by the form of training task. Introversion facilitated the transfer to working memory and hindered the transfer to flexibility.

Training task planning-based adaptive assist-as-needed control for upper limb exoskeleton using neural network state observer

Training task planning-based adaptive assist-as-needed control for upper limb exoskeleton using neural network state observer

The influence of sports games on the formation of technical skills of athletes in ukrainian belt wrestling

The article reveals current issues of forming the high level of technical fitness of athletes in Ukrainian belt wrestling. The main task of a technical training of an athlete is the formation of skills and abilities to perform competitive actions that allow to effectively use the athlete's capabilities in the process of sports activity. Technical skills training in any sport is aimed at teaching an athlete the technique of movements, improving them to perfection. The purpose of the research: to determine the influence of sports games on the formation of the level of technical skills of athletes in Ukrainian belt wrestling at the stage of preparation for major competitions. Research methods: analysis and synthesis of literary sources, methods of observation and comparison, pedagogical research methods (testing of physical qualities: coordination, speed and strength, power abilities, flexibility), medical and biological research methods, methods of mathematical statistics. Conclusions: the level of athletes' technical skills in the experimental group during the period of the pedagogical experiment by the indicator - throws of the partner, the speed of throws increased by 21.8% in relation to the control group - 4.7%.

Revolutionizing motor dysfunction treatment: A novel closed-loop electrical stimulator guided by multiple motor tasks with predictive control

Functional electrical stimulation (FES) has been demonstrated as a viable method for addressing motor dysfunction in individuals affected by stroke, spinal cord injury, and other etiologies. By eliciting muscle contractions to facilitate joint movements, FES plays a crucial role in fostering the restoration of motor function compromised nervous system. In response to the challenge of muscle fatigue associated with conventional FES protocols, a novel biofeedback electrical stimulator incorporating multi-motor tasks and predictive control algorithms has been developed to enable adaptive modulation of stimulation parameters. The study initially establishes a Hammerstein model for the stimulated muscle group, representing a time-varying relationship between the stimulation pulse width and the root mean square (RMS) of the surface electromyography (sEMG). An online parameter identification algorithm utilizing recursive least squares is employed to estimate the time-varying parameters of the Hammerstein model. Predictive control is then implemented through feedback corrections based on the comparison between predicted and actual outputs, guided by an optimization objective function. The integration of predictive control and roll optimization enables closed-loop control of muscle stimulation. The motor training tasks of elbow flexion and extension, wrist flexion and extension, and five-finger grasping were selected for experimental validation. The results indicate that the model parameters were accurately identified, with a RMS error of 3.83 % between actual and predicted values. Furthermore, the predictive control algorithm, based on the motor tasks, effectively adjusted the stimulus parameters to ensure that the stimulated muscle groups can achieve the desired sEMG characteristic trajectory. The biofeedback electrical stimulator that was developed has the potential to assist patients experiencing motor dysfunction in achieving the appropriate joint movements. This research provides a foundation for a novel intelligent electrical stimulation model.

Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial

BackgroundOver 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, which may improve finger grasping performance after stroke, while augmented therapy may lead to a better treatment outcome. As a new technology-supported training, the hand rehabilitation robot provides opportunities to improve the therapeutic effect by increasing the training intensity. However, most hand rehabilitation robots commonly applied in clinics are based on a passive training mode and lack the sensory feedback function of fingers, which is not conducive to patients completing more accurate grasping movements. A force feedback hand rehabilitation robot can compensate for these defects. However, its clinical efficacy in patients with stroke remains unknown. This study aimed to investigate the effectiveness and added value of a force feedback hand rehabilitation robot combined with task-oriented training in stroke patients with hemiplegia.MethodsIn this single-blinded randomised controlled trial, 44 stroke patients with hemiplegia were randomly divided into experimental (n = 22) and control (n = 22) groups. Both groups received 40 min/day of conventional upper limb rehabilitation training. The experimental group received 20 min/day of task-oriented training assisted by a force feedback rehabilitation robot, and the control group received 20 min/day of task-oriented training assisted by therapists. Training was provided for 4 weeks, 5 times/week. The Fugl-Meyer motor function assessment of the hand part (FMA-Hand), Action Research Arm Test (ARAT), grip strength, Modified Ashworth scale (MAS), range of motion (ROM), Brunnstrom recovery stages of the hand (BRS-H), and Barthel index (BI) were used to evaluate the effect of two groups before and after treatment.ResultsIntra-group comparison: In both groups, the FMA-Hand, ARAT, grip strength, AROM, BRS-H, and BI scores after 4 weeks of treatment were significantly higher than those before treatment (p < 0.05), whereas there was no significant difference in finger flexor MAS scores before and after treatment (p > 0.05). Inter-group comparison: After 4 weeks of treatment, the experimental group’s FMA-Hand total score, ARAT, grip strength, and AROM were significantly better than those of the control group (p < 0.05). However, there were no statistically significant differences in the scores of each sub-item of the FMA-Hand after Bonferroni correction (p > 0.007). In addition, there were no statistically significant differences in MAS, BRS-H, and BI scores (p > 0.05).ConclusionHand performance improved in patients with stroke after 4 weeks of task-oriented training. The use of a force feedback hand rehabilitation robot to support task-oriented training showed additional value over conventional task-oriented training in stroke patients with hand dysfunction.Clinical trial registration informationNCT05841108

Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning.

Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, validation, and application. Several modern strategies aim to mitigate the challenges associated with data scarcity by learning from data on related tasks. These knowledge-sharing approaches encompass transfer learning, multitask learning, and meta-learning. A key question remaining to be answered for these approaches is about the extent to which their performance can benefit from the relatedness of available source (training) tasks; in other words, how difficult ("hard") a test task is to a model, given the available source tasks. This study introduces a new method for quantifying and predicting the hardness of a bioactivity prediction task based on its relation to the available training tasks. The approach involves the generation of protein and chemical representations and the calculation of distances between the bioactivity prediction task and the available training tasks. In the example of meta-learning on the FS-Mol data set, we demonstrate that the proposed task hardness metric is inversely correlated with performance (Pearson's correlation coefficient r = -0.72). The metric will be useful in estimating the task-specific gain in performance that can be achieved through meta-learning.

THE CONCEPT OF SUSTAINABLE DEVELOPMENT AS THE BASIS OF CONTINUOUS ECOLOGICAL TRAINING OF FUTURE TEACHERS

Increasing attention to the ecological training of young people in the system of modern education is one of the important problems nowadays. Guarantees of environmental protection are presented in ecological knowledge, abilities and skills, as well as in the socio-cultural behavior and worldview of the population. Therefore, one of the priority tasks of the educational system is the formation of the ecological culture of the younger generation through the implementation of a system of continuous environmental education based on the principles of sustainable development. The purpose of the article is to investigate the problem of continuous ecological training of future teachers based on sustainable development. Research methods: analysis and synthesis of scientific literature (to clarify key research concepts), systematization, and generalization (for the purpose of forming the author's conclusions). It is established that ensuring the sustainable development of society involves positive life activities of people through the creation of conditions that contribute to the harmonization of their relationships, development, and satisfaction of their needs in the socio-natural environment, providing opportunities for the formation of ecological culture in the educational sphere. The peculiarities of continuous ecological training of future teachers based on the concept of sustainable development are studied, and the content and results of this process are highlighted. The goal of continuous ecological training for sustainable development is to teach people to manage the quality of life; the formation of an ecological culture in the young generation, which involves the ecological orientation of the individual, the ability to increase their ecological education and literacy, to carry out social-ecological and ecological-project activities for the benefit of sustainable development. The main tasks of continuous ecological training are the formation of scientific knowledge and ecologically oriented knowledge, the development of environmental protection skills and abilities aimed at improving the state of the environment and improving the quality of life of people, and the upbringing of a highly educated and ecologically cultural personality. Continuous ecological education for the benefit of sustainable development originates in preschool education institutions, where for the first time children master the basics of environmental education and culture, and form an idea of their unity with nature. The next stage is general secondary education, where students form environmental competence and develop an environmental outlook. The next level of the continuous ecological education system is the higher school, where the professional ecological training of the future teacher is carried out, the value-meaning sphere of the individual is formed, social-ecological norms of professional activity are mastered.

PCA-TANN with model-based transfer learning for predicting blast load time series on structures

A comprehensive understanding of blast load information is crucial for evaluating structural response. Machine learning has demonstrated its efficiency in predicting blast loads. However, the high costs associated with acquiring blast load data limit the development of machine learning. A novel method, PCA-TANN, is proposed for predicting blast load time series on structures and improving the problem of insufficient training data by integrating transfer learning concepts and combining artificial neural networks (ANN) with principal component analysis (PCA). The main idea of this model involves preprocessing the time series data using PCA to extract essential features, employing artificial neural networks based on transfer learning (TANN) for knowledge transfer from the previous task to the new task, and integrating a few preprocessed data of the new task for training. The blast load data obtained from a single square column is utilized to assess the performance of PCA-TANN and PCA-ANN models. The findings demonstrate that in situations with limited data availability, PCA-TANN reasonably replicates the blast load characteristic, resulting in accurate time series predictions of overpressure with R2 scores exceeding 0.85. This performance significantly surpasses that of the used PCA-ANN model, which achieves R2 scores below 0.4.

Single-pixel imaging based on self-supervised conditional mask classifier-free guidance

Reconstructing high-quality images at a low measurement rate is a pivotal objective of Single-Pixel Imaging (SPI). Currently, deep learning methods achieve this by optimizing the loss between the target image and the original image, thereby constraining the potential of low measurement values. We employ conditional probability to ameliorate this, introducing the classifier-free guidance model (CFG) for enhanced reconstruction. We propose a self-supervised conditional masked classifier-free guidance (SCM-CFG) for single-pixel reconstruction. At a 10% measurement rate, SCM-CFG efficiently completed the training task, achieving an average peak signal-to-noise ratio (PSNR) of 26.17 dB on the MNIST dataset. This surpasses other methods of photon imaging and computational ghost imaging. It demonstrates remarkable generalization performance. Moreover, thanks to the outstanding design of the conditional mask in this paper, it can significantly enhance the accuracy of reconstructed images through overlay. SCM-CFG achieved a notable improvement of an average of 7.3 dB in overlay processing, in contrast to only a 1 dB improvement in computational ghost imaging. Subsequent physical experiments validated the effectiveness of SCM-CFG.

Developing 21st century skills through PISA-based assessment-learning tasks

Relevance. Currently, the textbooks used in educational schools in Kazakhstan largely lack tasks that require decision-making under conditions of uncertainty. The relevance of this study lies in addressing a significant gap in the educational curriculum of the Republic of Kazakhstan. Purpose. The purpose of this study is to form and develop schoolchildren�s decision-making skills in conditions of uncertainty, and 21st century skills, by drawing up model assessment and learning tasks and assignments for them. Methodology. Diagnostic written work was carried out to identify the success of the developed method for constructing assessment and learning tasks, teaching schoolchildren to solve practice-oriented problems in the experimental (33 students) and control (32 students) classes. Results. Monitoring showed that out of 33 students from the experimental class 22% did not score points corresponding to the mandatory threshold level (13 out of 26 points), 72% achieved an average level of learning (from 14 to 21 points), 6% achieved a high level of learning (from 22 to 26 points). In the control class, 68% of schoolchildren did not reach the mandatory threshold level, 29% reached the average level, 3% reached a high level of development of practice-oriented knowledge. To establish the success of the developed methodology for constructing assessment and training tasks for practical problems, a survey was conducted among mathematics teachers (17 people). The survey results showed that this approach allowed all 17 teachers to successfully create assessment and teaching tasks for selected educational tasks from a mathematics textbook. Conclusions. Experimental studies confirm that teaching schoolchildren to solve practice-oriented problems and assessment tasks enhances their practice-oriented knowledge, including mathematical literacy, 21st-century thinking skills, and decision-making in uncertain conditions. Keywords: decision making; thinking skills; mathematical reasoning; exam

The Effectiveness Of Virtual Reality Along With Task Specific Training On Quality Of Life Of C6-C7 Level- Incomplete Spinal Cord Injury Patients

Background- Spinal cord injury is a devastating condition. In recent years, traumatic spinal cord injury has become one of the major disabling conditions in young males. These chronic complications negatively impact patients’ functional independence and thus affect the quality of life. Methods-Thirty-seven spinal cord injury patientsC6-C7 with American Spinal Cord Injury Association (C, D) who full-filled the inclusion criteria were recruited, out of which 7 discontinued the therapy program, 15 spinal cord injury patients in Group I (Virtual Reality with Task Specific Training) and 15 spinal cord injury patients in the Group II (only task specific) completed the study.Virtual Reality training was given as an intervention using NIRVANA which is a semi-immersive Virtual Reality training. Results-Group I, which received only Task Specific Training, revealed a statistically significantly positive change in Quality of life (Z = -2.671, p = 0.008) with a medium effect size of (r = 0.48). For Group II, which received Virtual Reality along with Task Specific Training,revealed a statistically significantly positive change in Quality of life (Z = -3.415 p = 0.001) with a large effect size of (r = 0.62) Conclusion-Both the groups showed significant positive improvements in quality of life inspinal cord injury patients, indicating that both task-oriented training and the use of Virtual Reality as treatment modalities have a direct impact on QoL. However, more significant improvement was seen in Group 2 where Virtual Reality was combined with Task Specific Training.

The efficacy of hazard perception training and education: A systematic review and meta-analysis

BackgroundHazard perception (HP) has been argued to improve with experience, with numerous training programs having been developed in an attempt to fast track the development of this critical safety skill. To date, there has been little synthesis of these methods. Objective: The present study sought to synthesise the literature for all road users to capture the breadth of methodologies and intervention types, and quantify their efficacy.Data Sources: A systematic review of both peer reviewed and non-peer-reviewed literature was completed. A total of 57 papers were found to have met inclusion criteria. Results: Research into hazard perception has focused primarily on drivers (with 42 studies), with a limited number of studies focusing on vulnerable road users, including motorcyclists (3 studies), cyclists (7 studies) and pedestrians (5 studies). Training was found to have a large significant effect on improving hazard perception skills for drivers (g = 0.78) and cyclists (g = 0.97), a moderate effect for pedestrians (g = 0.64) and small effect for motorcyclists (g = 0.42). There was considerable heterogeneity in the findings, with the efficacy of training varying as a function of the hazard perception skill being measured, the type of training enacted (active, passive or combined) and the number of sessions of training (single or multiple). Active training and single sessions were found to yield more consistent significant improvements in hazard perception. Conclusions: This study found that HP training improved HP skill across all road user groups with generally moderate to large effects identified. HP training should employ a training method that actively engages the participants in the training task. Preliminary results suggest that a single session of training may be sufficient to improve HP skill however more research is needed into the delivery of these single sessions and long-term retention. Further research is also required to determine whether improvements in early-stage skills translate to improvements in responses on the road, and the long-term retention of the skills developed through training.

Stimulating prefrontal cortex facilitates training transfer by increasing representational overlap.

A recent hypothesis characterizes difficulties in multitasking as being the price humans pay for our ability to generalize learning across tasks. The mitigation of these costs through training has been associated with reduced overlap of constituent task representations within frontal, parietal, and subcortical regions. Transcranial direct current stimulation, which can modulate functional brain activity, has shown promise in generalizing performance gains when combined with multitasking training. However, the relationship between combined transcranial direct current stimulation and training protocols with task-associated representational overlap in the brain remains unexplored. Here, we paired prefrontal cortex transcranial direct current stimulation with multitasking training in 178 individuals and collected functional magnetic resonance imaging data pre- and post-training. We found that 1mA transcranial direct current stimulation applied to the prefrontal cortex paired with multitasking training enhanced training transfer to spatial attention, as assessed via a visual search task. Using machine learning to assess the overlap of neural activity related to the training task in task-relevant brain regions, we found that visual search gains were predicted by changes in classification accuracy in frontal, parietal, and cerebellar regions for participants that received left prefrontal cortex stimulation. These findings demonstrate that prefrontal cortex transcranial direct current stimulation may interact with training-related changes to task representations, facilitating the generalization of learning.

Design and Implementation of Simulation Training System for Ground Maintenance Pannel of a Certain Type of Aircraft

According to the design requirements of ground maintenance pannel simulation training system of a certain type of aircraft, a set of training system with the functions of ground handling practice, aircraft maintenance operation training and PMA interactive operation training is developed. The system design fully considers the requirements of generalization and modularization design. The function division of each module is clear, the signal interface is clear, and one of the modules can be replaced quickly to facilitate the positioning and elimination of failure. It has the dual expansibility of training task and training model, and can continuously add training task package, including procedure training, troubleshooting guidance training, etc., and can adapt to change in aircraft state.