• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.37-46
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• 2000

A company needs low cost and high efficient S/W tools to improve the white color productivity in daily operation, These needs may be satisfied by end-user knowledge management system to be suggested in this paper. We suggest that the end-user knowledge management is not made by specialized developer but directly made by end-users of some related managers using company-wide DB and department DB. We expect that this end-user knowledge management system will increase the efficiency of end-user daily operation and minimize the total life cycle cost of end-user computing system in industry. The suggested end-user knowledge management system has been tested in some companies through the training course.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.141-146
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• 2009

Support vector machine is a classification algorithm based on statistical learning theory. It has shown many results with good performances in the data mining fields. But there are some problems in the algorithm. One of the problems is its heavy computing cost. So we have been difficult to use the support vector machine in the dynamic and online systems. To overcome this problem we propose to use stratified sampling of statistical sampling theory. The usage of stratified sampling supports to reduce the size of training data. In our paper, though the size of data is small, the performance accuracy is maintained. We verify our improved performance by experimental results using data sets from UCI machine learning repository.

• Journal of Nutrition and Health
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• v.5 no.2
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• pp.53-58
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• 1972

Organized feeding programmes can contribute to the health and well-being of students All such programme must be planned carefully, taking into account the nutritional needs of the group to be fed, available food supplies, facilities for food preparation and distribution, and available funds. In most instances provision must be made for training staff to operate large-scale feeding proframmes. Nutrition education should be an important aspect of all feeding programme, and should provide simple clear information on food and nutrition in relation to health. The early participation of parents and the local community in the programme, particularly through the production of local low-cost foods of high nutritional value will help to insure continuity after external aid has ceased. Programmes should be evaluated in order to measure the benefits obtained in relation to the cost of the operation. Anthropometric data, absenteeism and scholastic achievement may serve as indicators in school feeding programmes.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.179-186
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• 2021

For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.

• Journal of KIBIM
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• v.12 no.2
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• pp.40-48
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• 2022

It is very important to accurately predict construction costs in the early stages of the construction project. However, it is difficult to accurately predict construction costs with limited information from the initial stage. In recent years, with the development of machine learning technology, it has become possible to predict construction costs more accurately than before only with schematic construction characteristics. Based on machine learning technology, this study aims to analyze plans to more accurately predict construction costs by using only the factors influencing construction costs. To the end of this study, the effect of the error rate according to the activation function and the node configuration of the hidden layer was analyzed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Korean Security Journal
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• no.6
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• pp.167-193
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• 2003

Korean social structure is changing by leaps and bounds caused by industrialization, urbanization and information. Because of this, the sense of value, and moral consciousness of Korean people have been edteriorating and all kinds of social evils have been increasing also. However, the police who ought to be in charge of public well-being, security, social order are not playing their role on account of bad working conditions, and lack of budget. For this reason, individuals are desirous of preserving their security and lives at their cost. Private security has emerged at this background.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.46.2-46
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• 2002

Plasma processing plays a crucial role in fabricating integrated circuits (ICs). Manufacturing ICs in a cost effective way, it is increasingly demanded a computer model that predicts plasma properties to unknown process inputs. Physical models are limited in the prediction accuracy since they are subject to many assumptions. Expensive computation time is another hindrance that prevents their widespread used in manufacturing site. To circumvent these difficulties inherent in physical models, neural networks have been used to learn nonlinear plasma data [1]. Among many types of networks, a backpropagation neural network (BPNN) is the most widely used architecture. Many training variables are...

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.91-94
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• 1995

A newly developed discrete-time control design method for impact machines is proposed. It is composed of identification and control using neural networks, where the optimal controller with saturationn and no use of velocity measurements is obtained. By computer simulation, the proposed method is demonstrated to be effective: as the training progresses, the cost function becomes smaller, the proposed control is superior to PID control tuned with Ziegler-Nichols (Z-N) parameters; robust performance with respect to uncertainty, disturbances and working time is so good.

• MALSORI
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• no.63
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• pp.101-112
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• 2007

Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognition, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editing corpus and training each model, we need more systematic and efficient working environment. For the working environment, we propose DialogStudio as a spoken dialog system workbench.