• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.4
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• pp.1-6
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• 2023

EBT has designed and implemented a training program that relies on evidence from events such as Flight Operation Quality Assurance (FOQA), accidents, and incidents specific to each airline. The goal is to enhance the overall skills of the flight crew. This involves assessing the capabilities of individual crew members and, based on the findings, providing additional training to address any shortcomings. To create a training program aligned with the objectives of EBT, this study focused on analyzing data from hard landing incidents in domestic airlines obtained through FOQA events. A practical EBT training program was then developed, specifically targeting adverse weather conditions. The program evaluates landing capabilities, and the results guide the supplementation of any deficiencies in the landing skills of each flight crew member, ultimately aiming to enhance their confidence.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.25-32
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• 2020

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.129-141
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• 2018

In this paper, two different flight training devices were constructed to verify the effectiveness of a pilot training system based on a Virtual Reality Head Mount Display. VFR Flight Procedure and IFR Flight Procedure were conducted by high level pilots with Commercial Pilot Licence. Flight data and pilot's visual data for each flight procedure were extracted, compared and analyzed with two training systems. Finally, the effectiveness of the training systems based on the VR HMD was demonstrated by assessing the given mission and the flight results.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.90-96
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• 2023

Securing large amounts of training data in deep learning neural networks, including convolutional neural networks, is of importance for avoiding overfitting phenomenon or for the excellent performance. However, securing labeled training data in deep learning neural networks is very limited in reality. To overcome this, several augmentation methods have been proposed in the literature to generate an additional large amount of training data through transformation or manipulation of the already acquired traing data. However, unlike training data such as images and texts, it is barely to find an augmentation method in the literature that additionally generates bio-signal training data for convolutional neural network based human activity recognition. Thus, this study proposes a simple but effective augmentation method of bio-signal training data for convolutional neural network based human activity recognition. The usefulness of the proposed augmentation method is validated by showing that human activity is recognized with high accuracy by convolutional neural network trained with its augmented bio-signal training data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.151-152
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• 2019

In this paper, we propose an improved learning method based on a small data set for animal image classification. First, CNN creates a training model for a small data set and uses the data set to expand the data set of the training set Second, a bottleneck of a small data set is extracted using a pre-trained network for a large data set such as VGG16 and stored in two NumPy files as a new training data set and a test data set, finally, learn the fully connected network as a new data set.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.499-506
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• 2020

The study examines the influence of individual characteristics, training content, and manager support on the effectiveness of on-the-job (OJT) training in the banking and finance industry. A simple random sampling technique was used to select the samples. Questionnaires were distributed to respondents in order to obtain the data. Using cross-sectional data obtained from 396 respondents in Bank A in Malaysia, the multiple regression results show that self-efficacy, motivation to learn, training content, and manager support have positive influence on OJT training effectiveness. Among all these factors, manager support is very highly correlated with OJT training effectiveness. The findings have given fruitful insight of the crucial roles of OJT training in the respective bank, particularly to bring forward the roles of systematic design and implementation of OJT training. This study is not only expanding knowledge in OJT and training, but offers managers practical insights in developing good OJT training program by considering employees need, capabilities, skills and job requirement. Furthermore, this study also provides a valuable framework in identifying the effectiveness of OJT training program for certain jobs. Further discussion of the research findings and its implications to theoretical knowledge of training and managers are promised at the end of the article.

• Journal of Sport and Applied Science
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• v.8 no.2
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• pp.13-18
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• 2024

Purpose: The purpose of this study is to determine the effects of a 6-week weight training and complex training program on the Y-balance test (YBT) in high school soccer players. Research design, data, and methodology: This study included 26 high school soccer players from City S. Subjects were divided into a weight training group (WTG: n=13) and a complex training group (CTG: n=13) based on their willingness to participate without medical problems. The YBT measured anterior (AT), posteromedial (PM), posterolateral (PL), and composite scores (CS), and was measured twice: before the start and after the end of training. The data were analyzed using the SPSS 25.0 statistical program to compare pre- and post-training using paired-t tests, between training groups using independent-t tests, and left-right comparisons using independent-t tests. Results: Training resulted in a significant pre- to post-training change in PL in the left foot WTG group (p<.05), with no significant change in the other measures. There were no significant differences between training groups and between left and right sides. Conclusion: To improve YBT in high school soccer players, a program to improve ankle and hip mobility and strength should be added along with improving large muscle strength through weights and comflex training.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.129-138
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• 2022

Collecting and labeling sufficient training data, which is essential to deep learning-based visual inspection, is difficult for manufacturers to perform because it is very expensive. This paper presents a steel plate surface defect detection system with industrial-grade detection performance by training a small amount of steel plate surface images consisting of labeled and non-labeled data. To overcome the problem of lack of training data, we propose two data augmentation techniques: program-based augmentation, which generates defect images in a geometric way, and generative model-based augmentation, which learns the distribution of labeled data. We also propose a 4-step semi-supervised learning using pseudo labels and consistency training with fixed-size augmentation in order to utilize unlabeled data for training. The proposed technique obtained about 99% defect detection performance for four defect types by using 100 real images including labeled and unlabeled data.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.294-303
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• 2022

The purpose of this study is to examine the effects of sensory integration training on children with developmental delays. To achieve this goal, an educational experiment is conducted in five main areas: gross motor ability, fine motor ability, adaptive ability, language and social ability in children with developmental delay. The study subjects were children with developmental delays aged 3-6 years diagnosed at Beijing Institute of Pediatrics and Beijing Medical University and received sensory integration intervention and homebased training at the Golden Rain Forest Beijing Tongzhou Center from 2018 to 2021. According to the purpose of the analysis, the data collected are subjected to descriptive statistics using SPSS 21.0 statistical program, Two-way MANOVA analysis, and data analysis method of multivariate analysis is used to process the collected data. In addition, a total of 39 subjects were selected, including 19 children who received sensory integration training and 20 children who only received family training. The results show that the sensory integration training group outperformed the home training group in all aspects and developmental quotient, but the home training group also showed higher levels of significance for improvements in gross motor, fine motor and developmental quotient.

• The Research Journal of the Costume Culture
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• v.7 no.4
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• pp.155-167
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• 1999

The present study investigated various sales training programs used by apparel companies and compared each other in order to provide an important information for developing effective training programs for professional salesperson. Sixty eight companies were used and grouped into four categories based on brand characteristics : domestic national brand(DNB), casual brand(CB), foreign brand(FB) and domestic designer brand(DDB). Data were collected from the managers in charge or training salesperson by both questionnaires and personal and telephone interviews. Data were collected during July in 1998, and analyzed by using ANOVA, Duncan\`s multiple range test, and Chi-square test. Since the sample size was small, Yates\` correction formula was used to maximize statistical validity in non-parametric procedure of Chi-square test. The main purpose of sales training indicated by the companies were to satisfy customers and to maximize the profit. Significant differences were found among the groups in the importance level of training contents such as knowledge, and customer relation, training methods, place, and duration/frequency of training at training center.