• Proceedings of the Safety Management and Science Conference
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• 2010.11a
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• pp.113-129
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• 2010

Proper pre-safety training is one of core mandatory in order to reduce injuries at the construction fields. In this study, we investigate the employee's opinions of safety training, safety recognition, the actual conditions of safety through survey. As a result of study, incident factors are roughly divided into technical factor, managerial factor, and educational factor. We confirmed that the educational factor led by deficiency of safety awareness and knowledge was the major factor. It needs to be resettled or revised properly to match with the incident trends and the safety training curriculum should also be improved and drastically revised with special quality. The managerial workers' safety recognition is lower than the site ones regarding the correct understanding of the importance of the training.. It suggest that the education method and system in construction fields might have fundamental problems.

• Korean Business Review
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• v.9
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• pp.99-121
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• 1996

On the job training is useful : a part of on the job training has increased the marginal productivity of future and rate of wage. Investment in a human capital depends on character of investment and market conditions. The innovation role of small and medium firms has recently received increasing attention in newly industrializing countries as they attempt to transform their industries from labor intensive to technology intensive. It also suggests some implications to the small and medium firms' strategies and public policies accelerating research and development. Lack of qualified scientists and engineers often inhibits the small and medium firms' ability to access and assimilate external technical information. Such technical personnel are particularly scarce in NICs. Therefore, how to employ these technical staff should be an important issue for small and medium firms seeking to acquire distinctive competences. Small and medium firms must invest further education and training to its labor.

• Journal of Biomedical Engineering Research
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• v.35 no.6
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• pp.197-202
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• 2014

The cognitive rehabilitation training is important for treating many cognitive impairment conditions, including Parkinson's disease, stroke, and ADHD. In this study, we developed a new evaluation system to improve the measurement of the conventional evaluation systems for cognitive rehabilitation training. The developed system measured the activity of dopamine(DA) and an autonomic nervous system(ANS) with photoplethysmography and electromyography. The results demonstrated that the cognitive capacity was increased but the activity of DA was decreased with unbalanced ANS by short-term stress. Based on the results, the effect of short-term stress should be recognized for the cognitive rehabilitation training.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.3 s.258
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• pp.373-379
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• 2007

In this study, we observe the application of shape memory alloy(SMA) into smart structures for repeatable actuation, because SMA changes its material properties and characteristics progressively under cyclic loading conditions and finally reaches stable path(state) after a certain number of stress/temperature loading-unloading cycles, so called 'training'. In this paper, SMA wires that have been in a stable state through the training are used. Stress-strain curve of the SMA wire at different temperature levels are measured. In addition, we observe other important effects such as the rate effect according to strain rates for rapid actuation response. The current work presents the experimental test using SMA wire after training completion by mechanical cycling. Through these tests, we measure the characteristics of SMA. With the estimated SMA properties and effects, we compare the experimental results with the simulation results based on the SMA constitutive equations.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2889-2891
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• 2000

We developed the training simulator for KEPCO operators to maintain small-scale distribution automation system effectively. The training simulator has the same screen form and operating environments in comparison with using system in field. It is to be wished that the operating techniques of KEPCO operators will progress to solve the fear of system operation and to training simulations of distribution conditions again and again.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.101-117
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• 2008

As the rapidly changing e-business environment and development of IT, it is difficult to predict appropriate demand and supply of human resources in e-business industry. Such problem causes the imbalance of needs in demand and supply and the difficulty of proving useful information about fostering necessary e-business human resource and so forth. This study present a manpower training plan in e-business industry by investigating e-business human resource in the market and by analyzing curriculums in selected universities. To achieve this objective, we conducted a survey study of e-business companies, educational organizations and workers. From the results of this study, we present the current status of e-business human resource market and the problems of past manpower training system, and provide recommendations. This study would help policy makers, the private companies and academic institutions in developing effective strategies for the e-Biz human resource sector.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.143-148
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• 2021

The article considers the training of specialists in education in the conditions of distance learning. It is lights up the advantages of distance learning and determined the characteristic features of distance learning of students training in the implementation of these technologies in the educational process. The article focuses on the main aspects of computerization of studies as a technological breach in methodology, organization and practical realization of educational process and informative culture of a teacher. Information technologies are intensive involved in life of humanity, educational process of schools and higher educational establishments. Intercommunication is examined between the processes of informatization of the society and education.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3515-3524
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• 2023

A reinforcement learning framework is proposed for the control problem of outlet steam pressure of the once-through steam generator(OTSG) in this paper. The double-layer controller using Proximal Policy Optimization(PPO) algorithm is applied in the control structure of the OTSG. The PPO algorithm can train the neural networks continuously according to the process of interaction with the environment and then the trained controller can realize better control for the OTSG. Meanwhile, reinforcement learning has the characteristic of difficult application in real-world objects, this paper proposes an innovative pretraining method to solve this problem. The difficulty in the application of reinforcement learning lies in training. The optimal strategy of each step is summed up through trial and error, and the training cost is very high. In this paper, the LSTM model is adopted as the training environment for pretraining, which saves training time and improves efficiency. The experimental results show that this method can realize the self-adjustment of control parameters under various working conditions, and the control effect has the advantages of small overshoot, fast stabilization speed, and strong adaptive ability.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.95-101
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• 1999

In this paper, a comparison between different methods to combine predictions from neural networks will be given. These methods are bagging, bumping, and balancing. Those are based on the analysis of the ensemble generalization error into an ambiguity term and a term incorporating generalization performances of individual networks. Neural Networks and AI machine learning models are prone to overfitting. A strategy to prevent a neural network from overfitting, is to stop training in early stage of the learning process. The complete data set is spilt up into a training set and a validation set. Training is stopped when the error on the validation set starts increasing. The stability of the networks is highly dependent on the division in training and validation set, and also on the random initial weights and the chosen minimization procedure. This causes early stopped networks to be rather unstable: a small change in the data or different initial conditions can produce large changes in the prediction. Therefore, it is advisable to apply the same procedure several times starting from different initial weights. This technique is often referred to as training ensembles of neural networks. In this paper, we presented a comparison of three statistical methods to prevent overfitting of neural network.