• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.125-134
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• 2021

With the rapid development of the film industry, the number of films is significantly increasing and movie recommendation system can help user to predict the preferences of users based on their past behavior or feedback. This paper proposes a movie recommendation system based on the latent factor model with the adjustment of mean and bias in rating. Singular value decomposition is used to decompose the rating matrix and stochastic gradient descent is used to optimize the parameters for least-square loss function. And root mean square error is used to evaluate the performance of the proposed system. We implement the proposed system with Surprise package. The simulation results shows that root mean square error is 0.671 and the proposed system has good performance compared to other papers.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1207-1216
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• 2015

This study aims to compare the model power in developing corporate credit rating models and to suggest a good way to build models based on the characteristic of data. Among many measurement methods, AR is used to measure the model power under various conditions. SAS/MACRO is in use for similar repetitions to reduce time to build models under several combination of conditions. A corporate credit rating model is composed of two sub-models; a credit scoring model and a default prediction model. We verify that the latter performs better than the former under various conditions. From the result of size comparisons, models of large size corporate are more powerful and more meaningful in financial viewpoint than those of small size corporate. As a corporate size gets smaller, the gap between sub-models becomes huge and the effect of outliers becomes serious.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.39-46
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• 2005

The RMR ratings, one by horizontal pre-boring in a tunnel and another by tunnel face mapping, are compared at the fault zone in a tunnel. Generally. the horizontal pre-borings were so effective as to forecast reasonably the supporting patterns after tunnel excavation. But the maximum difference in RMR ratings estimated by two methods was about 50 at a certain section of a tunnel. The differences were analyzed on each parameter of the RMR system: the rating differences were 24 in the condition of discontinuities, 15 in the RQD and 13 in the uniaxial compressive strength of rock. To minimize the gap between RMR by pre-borings and by face mappings, it is necessary to select the horizontal pre-boring location where tunnel stability could be critical and to evaluate in detail the sub-parameters of the condition of discontinuities.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.73-81
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• 2003

The Government presented improvement plans such as "Traffic Accident Frequent Point" and "Hazardous Roads" to reduce traffic accidents on the increase after 1980s. In case of the hazardous roads, they are expressed by grades which are marked by geometric elements such as width, radius, grade. sight distance. and other environmental factors. As each business for improving roads goes by only focusing on improvement of geometric elements, excessive expense can be invested too much nowadays causing economical waste. Therefore, as improvement plans approached by economic access are needed, this paper shows the cost-effective improvement of the business to keep safety related to traffic accident and economical waste. The hazardous roads which authorized by Gwang-ju National Road Preservation Office of Construction and Transportation Ministry in 1995 for business for improvement of roads, were investigated before 1999. First of all, estimating traffic accident models are presented by using existed data statistically. The models help to maximize traffic accident decrease through control of the presented factor. Secondly, optimum construction cost of improvement is presented to prevent overcapitalization. However, this paper is limited because it was difficult to sort the data with various areas and to approach various ways.