• Journal of Digital Convergence
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• v.18 no.9
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• pp.191-198
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• 2020

In this study, in order to propose an improvement plan for fire simulation training to improve fire response capability, fire simulation training is conducted for three business facilities, and changes according to whether training materials are used and whether the response time for each response stage is reflected in the training evaluation. The response posture and response ability of the training participants were observed and analyzed. As a result of the analysis, it was analyzed that most of the training participants improved their participation in training, response posture, and response ability when the use of training textbooks and response time for each response stage were reflected in the training evaluation. In the event of a fire simulation training, a number of training materials that can similarly implement the fire situation are used to improve and maintain the fire response capabilities (fire notification and fire report, initial extinguishing, and evacuation) of the training participants, and the target time for each response step. The result was that it can be used as a useful index for improving fire response capability and improving fire simulation training in the future and feedback only when quantitative training evaluation is conducted based on this setting.

• Transactions of Materials Processing
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• v.4 no.3
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• pp.214-221
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• 1995

In the paper, we have proposed a new method to determine the initial billet for the forged products using a function approximation in the neural network. The architecture of neural network is a three-layer neural network and the back propagation algorithm is employed to train the network. By utilizing the ability of function approximation of a neural network, an optimal billet is determined by applying the nonlinear mathematical relationship between the aspect ratios in the initial billet and the final products. The amount of incomplete filling in the die is measured by the rigid-plastic finite element method. The neural network is trained with the initial billet aspect ratios and those of the unfilled volumes. After learning, the system is able to predict the filling regions which are exactly the same or slightly different to the results of finite element simulation. This new method is applied to find the optimal billet size for the plane strain rib-web product in cold forging. This would reduce the number of finite element simulation for determining the optimal billet size of forging product, further it is usefully adapted to physical modeling for the forging design.

• Transactions of Materials Processing
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• v.29 no.5
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• pp.272-281
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• 2020

As the thickness of mobile communication devices is getting thinner, the size of the internal parts is also getting smaller. Among them, the battery case requires a high-level deep drawing technique because it has a rectangular shape with a large aspect ratio. In this study, the initial blank shape was optimized to minimize earing in a multi-stage deep drawing process using an artificial neural network(ANN). There has been no reported case of applying artificial neural network technology to the initial blank optimal design for a square case with large aspect ratio. The training data for ANN were obtained though simulation, and the model reliability was verified by performing comparative study with regression model using random sample test and goodness-of-fit test. Finally, the optimal design of the initial blank shape was performed through the verified ANN model.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.118-124
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• 1995

In the paper, we have proposed a new technique to determine the initial billet for the forged products using a function approximation in neural network. A three-layer neural network is used and a back propagation algorithm is employed to train the network. An optimal billet which satisfied the forming limitation, minimum of incomplete filling in the die cavity, load and energy as well as more uniform distribution of effective strain, is determined by applying the ability of function approximation of the neural network. The amount of incomplete filling in the die, load and forming energy as well as effective strain are measured by the rigid-plastic finite element method. This new technique is applied to find the optimal billet size for the axisymmetric rib-web product in hot forging. This would reduce the number of finite element simulation for determining the optimal billet of forging products, further it is usefully adopted to physical modeling for the forging design

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.306-314
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• 2000

In this paper we present a new approach to estimate link travel speed based on the hybrid neuro-fuzzy network. It combines the fuzzy ART algorithm for structure learning and the backpropagation algorithm for parameter adaptation. At first, the fuzzy ART algorithm partitions the input/output space using the training data set in order to construct initial neuro-fuzzy inference network. After the initial network topology is completed, a backpropagation learning scheme is applied to optimize parameters of fuzzy membership functions. An initial neuro-fuzzy network can be applicable to any other link where the probe car data are available. This can be realized by the network adaptation and add/modify module. In the network adaptation module, a CBR(Case-Based Reasoning) approach is used. Various experiments show that proposed methodology has better performance for estimating link travel speed comparing to the existing method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.199-201
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• 2016

The performance of navigational equipments is advanced, but the importance of the practical capability of bridge device by ship's officer, ie the ability of risk prediction and the obligation of avoidance for reducing sea accident, has been constantly augmenting. This abilities and obligation may be represented in the cognitive competence of navigational officer. Different levels of ship's bridge team was carried out rescue maneuvering by ship handling simulator and then it analyzed the resulting of initial response in cognitive progress by case based on trajectory. Further, the data will be used as training and evaluation model of cognitive situation.

• The Korean Journal of Emergency Medical Services
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• v.8 no.1
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• pp.19-32
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• 2004

This study was conducted to identify an initial fire station experience of EMT students, so to better understand their' practice experience in fire station. The subjects were 28 EMT students of C department of Emergency Medical technology in C city, who were demonstrating at the fire station in C city. This study was approached by phenomenological method, collected data were analyzed by Colaizzi's method, the results were as a follows. From the protocol, 201 significant statements were organized into 93 formulated meanings. From the formulated meanings, 30 themes were identified, organized into 16 theme clusters, and then 7 categories. EMT students got experienced 'tension' in resulting from new training situation and at the field practice, 'comport and gratitude', in feeling of identity and a bond sympathy with senior EMT, in training environment and heartfelt care, 'stress' from lack of knowledge and skill, difficulties in field practice for 24 hours, in dealing with making interpersonal relationship with patient and staffs and from the insufficiency of instruction, 'confidence feeling' from the participation of field treatment, in improving of learning, in self-esteem of EMT job, 'confusing feeling' of conflict of the path in work, 'disappointment and doubt' by the discrepancy between learning and actuality, and disappointment of actuality, 'feeling of lack' based on the passive attitude. The results of this study are to use as basic data for students attending fire station experience for the first time.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.4
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• pp.342-347
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• 2016

This paper dealt with the economic analysis on the application of shipboard LED (Light Emitting Diode) luminaires to replace incandescent and fluorescent lamps, which account for over 80 % of light source on a training or naval vessel. The rates of savings achieved in the power consumption, initial investment, maintenance cost, and fuel cost were analyzed. The break-even points and the $CO_2$ emissions were also calculated. For the training vessel, the initial investment was increased by 3.8 times, while the maintenance cost over five years was reduced by 51 %. When 40 %, 50 %, and 60 % of luminaires were turned on, the calculated break-even points were 11 months, 9 months, and 7 months, respectively. On the other hand, the initial investment was increased by 3.5 times while the maintenance cost over five years was saved by 55 % for the naval vessel. The break-even points were calculated as 15 months, 12 months, and 10 months, respectively. Moreover, the $CO_2$ emissions of the training and the naval vessels were reduced by 69 % and 65 %, respectively. From the results, it was revealed that the maintenance cost can be reduced by more than 50 %, and that the power consumption, fuel cost, and $CO_2$ emissions can be reduced by more than 60 % if LED luminaires are used on two types of vessels.

• International Journal of Industrial Entomology and Biomaterials
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• v.2 no.1
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• pp.75-78
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• 2001

The whitefly, Dialeuropora decempuncta Quaintance and Baker (Homoptera : Aleyrodidae) causing considerable damage to mulberry, Morus alba. Crop loss caused by the whitefly was estimated in mulberry. Quantitative yield loss was estimated on the basis of harvest data from both sprayed and unsprayed plots. Data on pest incidence has been recorded at weekly intervals in both sprayed and unsprayed plots from 30 th day of plant age till harvesting i.e., 60 days after pruning in August October season. An attempt has been made to establish a relationship between whitefly population and percentage of crop loss due to it. Percentage of crop loss due to whitefly has got a linear relationship with the whitefly population. An initial population of 24 adults/top leaf would be able to cause 24% loss (l,630 Kg leaf/ha ) in a period of 30 days. Economic analysis postulates that application of pesticide can stove a net amount of 1,630 Kg leaf/ha which is sufficient to produce 67.65 Kg of additional multivoltine cocoons. This determines the cost/benefit ratio which will enable to workout the economics of management practices.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.112-122
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• 2007

Training a statistical model for semantic role labeling requires a large amount of manually tagged corpus. However. such corpus does not exist for Korean and constructing one from scratch is a very long and tedious job. This paper suggests a modified algorithm of self-training, an unsupervised algorithm, which trains a semantic role labeling model from any raw corpora. For initial training, a small tagged corpus is automatically constructed iron case frames in Sejong Electronic Dictionary. Using the corpus, a probabilistic model is trained incrementally, which achieves 83.00% of accuracy in 4 selected adverbial cases.