• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.117-117
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• 2006

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.8
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• pp.510-516
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• 2005

Rapid advances in telecommunication make emergency telemedicine possible that specialist offers medical care to an emergency case in moving vehicle. Although there were many telemedicine projects delivering the image or video of patient over several wireless networks, none of them considered effective solutions for optimizing video transmission over error-prone environments, such like wireless links. To alleviate the effect of channel errors on compressed video bit-stream, this paper analyzed the error resilient features of MPEG-4 standard and measured the quality of transmitted MPEG-4 encoded video over commercially available CDMA2000 1xEV-DO networks, transmitting different IP packet sizes and RM positions. we propose an error resilient transmission methods for emergency telemedicine over real 3G network.

• The Korean Journal of Physiology and Pharmacology
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• v.16 no.2
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• pp.97-106
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• 2012

The pharmacokinetics/pharmacodynamics analysis software NONMEM$^{(R)}$ output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM$^{(R)}$ VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.6
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• pp.296-301
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• 2006

Even though the emergency telecommunication make possible that specialist offers medical care over emergency cases in moving vehicle, we still have many problems in transmitting the image or video of patient over several wireless networks. To alleviate the effect of channel errors on compressed video bit-stream, this paper analyzed the error resilient features of JPEG2000 standard and measured the quality of transmission over noisy wireless channel, CDMA2000 1xEV-DO networks, compared to the features of error resilient tool of MPEG-4. We also proposed the optimum solution of transmitting images over real 3G network using JPEG2000 error resilient tool.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.74-81
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• 2017

Recently, there are many companies that use systems based on artificial intelligence. The accuracy of artificial intelligence depends on the amount of learning data and the appropriate algorithm. However, it is not easy to obtain learning data with a large number of entity. Less data set have large generalization errors due to overfitting. In order to minimize this generalization error, this study proposed DGA(Dropout Genetic Algorithm) which can expect relatively high accuracy even though data with a less data set is applied to machine learning based genetic algorithm to deep learning based dropout. The idea of this paper is to determine the active state of the nodes. Using Gradient about loss function, A new fitness function is defined. Proposed Algorithm DGA is supplementing stochastic inconsistency about Dropout. Also DGA solved problem by the complexity of the fitness function and expression range of the model about Genetic Algorithm As a result of experiments using MNIST data proposed algorithm accuracy is 75.3%. Using only Dropout algorithm accuracy is 41.4%. It is shown that DGA is better than using only dropout.

• Journal of Korean Academy of Nursing Administration
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• v.18 no.1
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• pp.23-32
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• 2012

Purpose: The purpose of this study was to assess the clinical application of a bar code medication administration and blood transfusion system and to identify its effects from the aspect of patient safety and nurse satisfaction in a tertiary hospital. Methods: The system in this study was PDA with bar code reading capability and wireless networking function. The logs created during application of the system and administration error reports were analyzed. For nurses' satisfaction with the system, data were collected from 337 nurses using the instrument developed by Otieno et al. and analyzed using descriptive statistics. Results: The system application rate was 98.8%, and the main failure cases in the system application included bar code or network related factors. When the system was applied, 0.02% of errors were prevented. The nurses were satisfied with the system from the aspect of patient safety, however relatively less satisfied with the system from the aspect of work efficiency. Conclusion: The results of the study indicate the usefulness for patient safety of applying the bar code medication administration and blood transfusion system to clinical practice. However technological improvements including bar code and network communication are necessary to ensure higher work efficiency in nursing practice.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1681-1685
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• 2014

The visual quality of medical image is an important factor for diagnosis accuracy. Therefore, the methods to improve the quality of medical image have studied. Among them, frequency domain filter is very powerful method to impove the visual quality of image. In this paper, the X-ray medical image using optimized high-pass filter was improved edges. The result image was improved edge and contrast of flat area using optimized high frequency emphasis filter. At last, the result image is to minimize the noise using the minimum mean square error(MMSE) filter. As a result, the proposed method has enhanced contrast and edge of the image in the contrast of existing filters, with the noise canceling effect.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.125-139
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• 2017

Recently, interest in improving the quality of EMS(emergency medical services) has been increasing. Much effort is being made to innovate the EMS process. The rapid progress of ICT technology has accelerated the automation or intelligence of EMS processes. This study suggests an emergency room management method based on real-time data considering resource utilization optimization, minimization of human error and enhancement of predictability of medical care. Emergency room operation indices - Emergency care index, Short stay index, Human error inducing index, Waiting patience index - are developed. And emergency room operation rules based on these indices are presented. Simulation was performed on a virtual emergency room to verify the effectiveness of the proposed operating rule. Simulation results showed excellent performance in terms of length of stay.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.146-157
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• 2024

Despite numerous air mattresses marketed to prevent Pressure Ulcers (PU), none have fully succeeded due to residual pressure surpassing critical levels. We introduces an innovative medical bed system aiming at complete PU prevention. This system employs a unique 4-bar link mechanism, moving keys up and down to manage body pressure. Each of the 17 keys integrates a sensor controller, reading pressure from 10 sensors. By regulating motor input, we maintain body pressure below critical levels. Keys are equipped with a servo drive and sensor controller, linked to the main controller via two CAN series. Using fuzzy or PI/IP controllers, we adjust keys to minimize total error, dispersing body pressure and ensuring comfort. In case of controller failure, keys alternate swiftly, preventing ulcer development. Through experimental tests under varied conditions, the fuzzy controller with tailored membership functions demonstrated swift performance. PI control showed rapid convergence, while IP control exhibited slower convergence and oscillations near zero error. Our specialized medical robot bed, incorporating 4-bar links and pressure sensors, underwent testing with three controllers-fuzzy, PI, and IP-showcasing their effectiveness in keeping body pressure below critical ulcer levels. Experimental results validate the proposed approach's efficacy, indicating potential for complete PU prevention.