• Nuclear Medicine and Molecular Imaging
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• v.42 no.sup1
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• pp.52-59
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• 2008

In the management of colo-retal and anal cancer, accurate staging, treatment evaluation, early detection of recurrence are main clinical problems. F-18 FDG PET (PET/CT) has been reported as useful in the management of colo-rectal and anal cancer because that PET has high diagnostic performance comparing to conventional studies. In case of liver metastases, for confirmation of no extrahepatic metastases, in case of high risk of metastasis, for avoiding unnecessary operation, PET (PET/CT) is expected more useful. In anal cancer, PET is expected useful in lymph node staging. For the early prediction of chemotherapy or radiation therapy effect PET has been reported as useful, also. In early detection of recurrence by PET, cost-benefit advantages has been suggested, also. PET/CT is expected to have higher diagnostic performance than PET alone.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.235-242
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• 2016

The emerging High-Efficiency Video Coding (HEVC) standard attempts to improve coding efficiency by a factor of two over H.264/Advanced Video Coding (AVC) at the expense of an increase in computational complexity. Mode decision with motion estimation (ME) is still one of the most time-consuming computations in HEVC, as it is with H.264/AVC. Thus, fast mode decisions are not only an important issue to be researched, but also an urgent one. Several schemes for fast mode decisions have been presented in reference software and in other studies. However, the conventional hierarchical mode decision can be useless when block-level parallelism is exploited. This paper proposes operation-level exploration that offers more chances for early termination. An early termination condition is checked between integer and fractional MEs and between the parts of one partition type. The fast decision points of the proposed algorithm do not overlap those in previous works. Thus, the proposed algorithms are easily used with other fast algorithms, and consequently, independent speed-up is possible.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.114-121
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• 1996

This study presented a simple test method of early decision on the quality of concrete by the way of refrigeration curing. It is a method of early decision for the quality of hardened concrete, after 28days, through the using refrigeration curing, at -18$\pm$$3^{\cire}C$ for five hours. I could find that there were fixed connections between the solidities after 28days and 48days, by the test of compression on the Re-Mi-Con through the test of standard curing and refergeration curing. (F = 1.02X + 13, $r^2$ = 0.964, S = 10.6kg/$\textrm{cm}^2$) I except that we can reduce the mistakes of construction work by forecasting the quality through the refrigeration curing.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05b
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• pp.51-52
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• 2010

In this study, it is confirmed that the use of equivalent age method can be applied to predict the early-age strength in case of using the new early strength concrete developed for the reduction of construction work period by our company, in apartment.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2034-2051
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• 2021

Metabolic encephalopathy is a critical condition that can be challenging to diagnose. Imaging provides early clues to confirm clinical suspicions and plays an important role in the diagnosis, assessment of the response to therapy, and prognosis prediction. Diffusion-weighted imaging is a sensitive technique used to evaluate metabolic encephalopathy at an early stage. Metabolic encephalopathies often involve the deep regions of the gray matter because they have high energy requirements and are susceptible to metabolic disturbances. Understanding the imaging patterns of various metabolic encephalopathies can help narrow the differential diagnosis and improve the prognosis of patients by initiating proper treatment regimen early.

• 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.

• The Journal of Information Technology
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• v.2 no.2
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• pp.13-22
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• 1999

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime by introduction a neural network. In the proposed method, we use AE(acoustic emission) sensing system and calculate a quantitative statistic parameter by pulse number and amplitude. Using statically parameters such as the center of gravity(G) and the gradient if the discharge distribute(C), we analyzed the early stage and the middle stage. the quantitative statistic parameters are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.2
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• pp.266-272
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• 2006

Numerous reports have evaluated the predictive ability of carcass probes for meat quality using measurements taken early postmortem or near 24 h. The intervening time period, however, has been largely ignored. In this study, the capacity of three probes [pH, electrical conductivity (EC), and grading probe light reflectance (GP)] to predict pork longissimus muscle quality (drip and cooking losses, Warner-Bratzler shear, $L^*$, n = 30) was evaluated at 45 min, 90 min, 3, 6, 12, 24, and 48 h postmortem. The strongest relationships were observed between cooking loss and 6 h EC and GP ($R^2$ = 0.66, 0.72), and $L^*$ and GP ($R^2$ = 0.57-0.66, 12-48 h). pH was most valuable early postmortem ($R^2$ = 0.63, 90 min with cooking loss). GP at 6 h most effectively ($R^2$ = 0.84) predicted a two factor (cooking loss+$L^*$) meat quality index. Results emphasize the predictive value of measures taken between 3 and 12 h postmortem.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.149-157
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• 2015

The 3D-AVC standard aims at improving coding efficiency by applying new techniques for utilizing intra, inter and view predictions. 3D video scenes are rendered with existing texture video and additional depth map. The depth map comes at the expense of increased computational complexity of the encoding process. For real-time applications, reducing the complexity of 3D-AVC is very important. In this paper, we present a fast intra mode decision algorithm to reduce the complexity burden in the 3D video system. The proposed algorithm uses similarity between texture video and depth map. The best intra prediction mode of the depth map is similar to that of the corresponding texture video. The early decision algorithm can be made on the intra prediction of depth map coding by using the coded intra mode of texture video. Adaptive threshold for early termination is also proposed. Experimental results show that the proposed algorithm saves the encoding time on average 29.7% without any significant loss in terms of the bit rate or PSNR value.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.83-90
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• 2010

The demands of analysis for the physical errors of systems and prediction system using this has increased steadily with computing environment growth linking real system just like IT Convergence. The physical errors are unpredictable because of relations of various elements such as natural phenomenon and mechanical errors. Especially, the elevator system occurs various problems because of the complexity of system so that we need to efficient approach for this. In this paper, we propose the analysis and management system for elevator based on data minining that predict the error to gather information about physical or natural phenomenon. This helps actively responding in early stage and saving lives through prediction of error and an early warning for just such an eventuality.