• Clinical and Experimental Pediatrics
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• v.52 no.7
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• pp.752-755
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• 2009

It is well known that hemodynamic load is one of the most important determinants of cardiac structure and function. Circadian variations in blood pressure (BP) are usually accompanied by consensual changes in peripheral resistance and/or cardiac output. In recent years, reduction in circadian variations in BP and, in particular, loss of nocturnal decline of BP were observed in hypertensive patients with left ventricular hypertrophy (LVH). The patients with only a slight or no loss of nocturnal decline of BP were considered "non-dippers". Regression of LVH was observed after prolonged antihypertensive therapy. Restoration of the circadian rhythm of BP was also observed. However, the classification of patients into "dippers" and "non-dippers" is arbitrary and poorly standardized and repeatable, and in the recent studies, most hypertensive patients with LVH were "dippers". Therefore, we should be particularly cautious about the conclusions drawn using this index. On the other hand, reduced activity of low-pressure cardiopulmonary baroreceptors and impaired day-to-night modulation of autonomic nervous system activity were observed in patients with only LVH. Therefore, alterations in cardiac structure may impair BP modulation. On the other hand, the reverse can also be trueprimary alterations in BP modulation, through a persistently elevated afterload, can increase cardiac mass. Thus, the interrelationship between cardiac structure and BP modulation is complex. Hence, new and more specific methods of evaluating circadian changes in BP are needed to better clarify the abovementioned reciprocal influences.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.455-458
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• 2002

A control of the body posture and movement is maintained by the vestibular system, vision, and proprioceptors. Especially, vestibular system has a very important function that controls the eye movement through vestibuloocular reflex and contraction of skeletal muscles through vestibulospinal reflex. However, postural disturbance caused by loss of vestibular function results in nausea, vomiting, vertigo and loss of craving for life. Lose of vestibular function leads to abnormal reflex of eye movements named nystagmus. Analysis of the nystagmus is needed to diagnose the vertigo, which is performed by means of electronystagmography (ENG). The purpose of this study is to develop a computerized system for data processing and an algorithm for the automatic evaluation of the slow component velocity (SCV) of nystagmus Induced by optokinetic(OKN) stimulation system. A new algorithm using recursive least square method (RLSM) to detect SCV of nystagmus is suggested in this paper. This method allows a fast and precise evaluation of the nystagmus, through artifact rejection techniques. The results are depicted in this paper.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2099-2106
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• 2018

This study presents a novel approach of discriminative feature vectors based on manifold learning using nonlinear dimension reduction (DR) technique to improve loss function, and combine with the Adversarial examples to regularize the object function for image classification. The traditional convolutional neural networks (CNN) with many new regularization approach has been successfully used for image classification tasks, and it achieved good results, hence it costs a lot of Calculated spacing and timing. Significantly, distrinct from traditional CNN, we discriminate the feature vectors for objects without empirically-tuned parameter, these Discriminative features intend to remain the lower-dimensional relationship corresponding high-dimension manifold after projecting the image feature vectors from high-dimension to lower-dimension, and we optimize the constrains of the preserving local features based on manifold, which narrow the mapped feature information from the same class and push different class away. Using Adversarial examples, improved loss function with additional regularization term intends to boost the Robustness and generalization of neural network. experimental results indicate that the approach based on discriminative feature of manifold learning is not only valid, but also more efficient in image classification tasks. Furthermore, the proposed approach achieves competitive classification performances for three benchmark datasets : MNIST, CIFAR-10, SVHN.

• The Korean Journal of Physiology and Pharmacology
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• v.20 no.5
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• pp.499-505
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• 2016

The quantitative sudomotor axon reflex testing (QSART) is a classic test of routine postganglionic sudomotor function. We investigated sudomotor function by QSART after summer (July 2012) and winter (January 2013) seasonal acclimation (SA) in the Republic of Korea. QSART with acetylcholine (ACh) iontophoresis were performed to determine directly activated (DIR) and axon reflex-mediated (AXR1, 2) sweating rate. Onset time of axon reflex, activated sweat gland density (ASGD), activated sweat gland output (ASGO), tympanic and skin temperatures ($T_{ty}$, $T_{sk}$), basal metabolic rate (BMR), and evaporative loss volume changes were measured. Tympanic and mean body temperature (${\bar{T}}_b$; calculated from $T_{ty}$, $T_{sk}$) were significantly lower after summer-SA than that of winter-SA. Sweat onset time was delayed during winter-SA compared to that after summer-SA. BMR, AXR(1), AXR(2), and DIR sweat rates, ASGD and ASGO, and evaporative loss volume were significantly diminished after winter-SA relative to after summer-SA. In conclusion, changes in sweating activity measured by QSART confirmed the involvement of the peripheral nervous system in variation of sudomotor activity in seasonal acclimation.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.484-497
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• 2021

This paper proposes an extended time uncertainty analysis approach in Level 2 human reliability analysis (HRA) considering severe accident management (SAM) strategies. The method is a time-based model that classifies two time distribution functions-time required and time available-to calculate human failure probabilities from delayed action when implementing SAM strategies. The time required function can be obtained by the combination of four time factors: 1) time for diagnosis and decision by the technical support center (TSC) for a given strategy, 2) time for strategy implementation mainly by the local emergency response organization (ERO), 3) time to verify the effectiveness of the strategy and 4) time for portable equipment transport and installation. This function can vary depending on the given scenario and includes a summation of lognormal distributions and a choice regarding shifting the distribution. The time available function can be obtained via thermal-hydraulic code simulation (MAAP 5.03). The proposed approach was applied to assess SAM strategies that use portable equipment and safety depressurization system valves in a total loss of component cooling water event that could cause reactor vessel failure. The results from the proposed method are more realistic (i.e., not conservative) than other existing methods in evaluating SAM strategies involving the use of portable equipment.

• Biomolecules & Therapeutics
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• v.31 no.2
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• pp.148-160
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• 2023

Depression is a neuropsychiatric disorder associated with persistent stress and disruption of neuronal function. Persistent stress causes neuronal atrophy, including loss of synapses and reduced size of the hippocampus and prefrontal cortex. These alterations are associated with neural dysfunction, including mood disturbances, cognitive impairment, and behavioral changes. Synaptic plasticity is the fundamental function of neural networks in response to various stimuli and acts by reorganizing neuronal structure, function, and connections from the molecular to the behavioral level. In this review, we describe the alterations in synaptic plasticity as underlying pathological mechanisms for depression in animal models and humans. We further elaborate on the significance of phytochemicals as bioactive agents that can positively modulate stress-induced, aberrant synaptic activity. Bioactive agents, including flavonoids, terpenes, saponins, and lignans, have been reported to upregulate brain-derived neurotrophic factor expression and release, suppress neuronal loss, and activate the relevant signaling pathways, including TrkB, ERK, Akt, and mTOR pathways, resulting in increased spine maturation and synaptic numbers in the neuronal cells and in the brains of stressed animals. In clinical trials, phytochemical usage is regarded as safe and well-tolerated for suppressing stress-related parameters in patients with depression. Thus, intake of phytochemicals with safe and active effects on synaptic plasticity may be a strategy for preventing neuronal damage and alleviating depression in a stressful life.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.1
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• pp.56-74
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• 2023

In order to obtain practical and high-quality satellite images containing high-frequency components, a large aperture optical system is required, which has a limitation in that it greatly increases the payload weight. As an attempt to overcome the problem, many multi-aperture optical systems have been proposed, but in many cases, these optical systems do not include high-frequency components in all directions, and making such an high-quality image is an ill-posed problem. In this paper, we use deep learning to overcome the limitation. A deep learning model receives low-quality images as input, estimates the Point Spread Function, PSF, and combines them to output a single high-quality image. We model images obtained from three rectangular apertures arranged in a regular polygon shape. We also propose the Modulation Transfer Function Loss, MTF Loss, which can capture the high-frequency components of the images. We present qualitative and quantitative results obtained through experiments.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.501-516
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• 2023

Knowledge distillation (KD) refers to extracting knowledge from a large and complex model (teacher) and transferring it to a relatively small model (student). This can be done by training the teacher model to obtain the activation function values of the hidden or the output layers and then retraining the student model using the same training data with the obtained values. Recently, relational KD (RKD) has been proposed to extract knowledge about relative differences in training data. This method improved the performance of the student model compared to conventional KDs. In this paper, we propose a new method for RKD by introducing a new loss function for RKD. The proposed loss function is defined using the area difference between the teacher model and the student model in a specific hidden layer, and it is shown that the model can be successfully compressed, and the generalization performance of the model can be improved. We demonstrate that the accuracy of the model applying the method proposed in the study of model compression of audio data is up to 1.8% higher than that of the existing method. For the study of model generalization, we demonstrate that the model has up to 0.5% better performance in accuracy when introducing the RKD method to self-KD using image data.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.610-621
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• 1998

In parameter design introduced by Taguchi, we analyze a signal-to-noise(SN) ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing SN ratios is presented, which can be used to several quality characteristics simultaneously in parameter design. To develop such multivariate SN ratios, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.75-86
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• 1993

This paper deals with the problem of estimating a reliability function for the Rayleigh distribution. Using the priors about a reliabity of real interest some Bayes estimators and Bayes credible sets are proposed and studied under squared error loss and Harris loss.