• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.363-372
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• 2007

Password, a traditional user confirmation method that is used for more than 100 years, has become useless as a lot of transactions are dealt by indirect contacts. As a result, an alternative for password is required now. In this paper, we propose a novel confirmation method, which is called Brain-Key. It uses an indirect password input method. It reduces the risks due to hacking, and prevents a big credit accident because it prevents passwords to be reused. Our proposed model has general applicability so that it can be applied in domestic market as well as international markets. This research may provide solutions for the security problems in the electronic commerce.

• Biomolecules & Therapeutics
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• v.28 no.1
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• pp.58-73
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• 2020

Sleep is an essential physiological process, especially for proper brain function through the formation of new pathways and processing information and cognition. Therefore, when sleep is insufficient, this can result in pathophysiologic conditions. Sleep deficiency is a risk factor for various conditions, including dementia, diabetes, and obesity. Recent studies have shown that there are differences in the prevalence of sleep disorders between genders. Insomnia, the most common type of sleep disorder, has been reported to have a higher incidence in females than in males. However, sex/gender differences in other sleep disorder subtypes are not thoroughly understood. Currently, increasing evidence suggests that gender issues should be considered important when prescribing medicine. Therefore, an investigation of the gender-dependent differences in sleep disorders is required. In this review, we first describe sex/gender differences not only in the prevalence of sleep disorders by category but in the efficacy of sleep medications. In addition, we summarize sex/gender differences in the impact of sleep disorders on incident dementia. This may help understand gender-dependent pathogenesis of sleep disorders and develop therapeutic strategies in men and women.

• Journal of Yeungnam Medical Science
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• v.36 no.3
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• pp.183-191
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• 2019

Some patients with type 1 and type 2 diabetes mellitus (DM) present with cognitive dysfunctions. The pathophysiology underlying this complication is not well understood. Type 1 DM has been associated with a decrease in the speed of information processing, psychomotor efficiency, attention, mental flexibility, and visual perception. Longitudinal epidemiological studies of type 1 DM have indicated that chronic hyperglycemia and microvascular disease, rather than repeated severe hypoglycemia, are associated with the pathogenesis of DM-related cognitive dysfunction. However, severe hypoglycemic episodes may contribute to cognitive dysfunction in high-risk patients with DM. Type 2 DM has been associated with memory deficits, decreased psychomotor speed, and reduced frontal lobe/executive function. In type 2 DM, chronic hyperglycemia, long duration of DM, presence of vascular risk factors (e.g., hypertension and obesity), and microvascular and macrovascular complications are associated with the increased risk of developing cognitive dysfunction. The pathophysiology of cognitive dysfunction in individuals with DM include the following: (1) role of hyperglycemia, (2) role of vascular disease, (3) role of hypoglycemia, and (4) role of insulin resistance and amyloid. Recently, some investigators have proposed that type 3 DM is correlated to sporadic Alzheimer's disease. The molecular and biochemical consequences of insulin and insulin-like growth factor resistance in the brain compromise neuronal survival, energy production, gene expression, plasticity, and white matter integrity. If patients claim that their performance is worsening or if they ask about the effects of DM on functioning, screening and assessment are recommended.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.4
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• pp.311-321
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• 2022

The report reviews recent research efforts in demonstrating a computing system whose operation principle mimics the dynamics of biological neurons. The temporal variation of the membrane potential of neurons is one of the key features that contribute to the information processing in the brain. We first summarize the neuron models that explain the experimentally observed change in the membrane potential. The function of ion channels is briefly introduced to understand such change from the molecular viewpoint. Dedicated circuits that can simulate the neuronal dynamics have been developed to reproduce the charging and discharging dynamics of neurons depending on the input ionic current from presynaptic neurons. Key elements include volatile memristors that can undergo volatile resistance switching depending on the voltage bias. This behavior called the threshold switching has been utilized to reproduce the spikes observed in the biological neurons. Various types of threshold switch have been applied in a different configuration in the hardware demonstration of neurons. Recent studies revealed that the memristor-based circuits could provide energy and space efficient options for the demonstration of neurons using the innate physical properties of materials compared to the options demonstrated with the conventional complementary metal-oxide-semiconductors (CMOS).

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.62-74
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• 2023

In response to diverse external stimuli, sensory receptors generate spiking nerve signals. These generated signals are transmitted to the brain along the neural pathway to advance to the stage of recognition or perception, and then they reach the area of discrimination or judgment for remembering, assessing, and processing incoming information. We review research trends in neuromorphic sensory perception technology inspired by biological sensory perception functions. Among the various senses, we consider sensory nerve decoding technology based on sensory nerve pathways focusing on touch and smell, neuromorphic synapse elements that mimic biological neurons and synapses, and neuromorphic processors. Neuromorphic sensory devices, neuromorphic synapses, and artificial sensory memory devices that integrate storage components are being actively studied. However, various problems remain to be solved, such as learning methods to implement cognitive functions beyond simple detection. Considering applications such as virtual reality, medical welfare, neuroscience, and cranial nerve interfaces, neuromorphic sensory recognition technology is expected to be actively developed based on new technologies, including combinatorial neurocognitive cell technology.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.224-238
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• 2004

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2101-2101
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• 2001

Near-infrared spectroscopy is now being used in clinical diagnosis as a non-invasive monitor of tissue oxygenation state. However, due to lack of the optical pathlength information within tissues, it is still difficult to quantitate the hemoglobin concentration with present CW techniques. Time-resolved spectroscopy (TRS), which measures temporal profiles of emerging light from tissues, enables to estimate the pathlength distribution within tissues by converting time to distance. Consequently, quantitative measurement of tissue oxygenation is possible by analyzing the data with optical diffusion equation 1) or our Microscopic Beer-Lambert law2). Time-Resolved Spectroscopy System : TRS-1O3) Our TRS-10 system consists of a three-wavelength (759, 797, 833 nm) PLP as pulsed light source, a high speed PMT with high sensitivity and three signal-processing circuits for time-resolved measurement (CFD/TAC, A/D converter and histogram memory). Optical pulse train consisting of 759, 797 and 833nm is generated by PLP at 5㎒ repetition rate and irradiated a sample through a single optical fiber. The diffuse-reflected light from the sample is collected by a bundle fiber and then detected by the PMT for single photon measurement. After being amplified by a following fast amplifier, the electrical signals for each wavelength are picked out by CFD/TAC module. Then, a signal processing circuit integrated the TRS data for each wavelength individually. The simultaneous TRS measurement for three wavelengths achieved without any optical or mechanical switch. Experiment and Results Input and detection fibers of TRS-10 were attached at the human forehead with a fiber separation of 3cm. TRS measurements were continuously performed for about 20 minutes including 2 minutes hyper ventilation. It was observed that the total hemoglobin concentration was decreasing during the hyper ventilation and recovered until 2 minutes after hyper ventilation. On the other hand, the deoxy-hemoglobin concentration began to increase after hyper ventilation and had its peak at around 2 minute later, showing 502 drop from 75% to 60% due to inhibition of breathing by performing hyper ventilation. The results showed that this system might be able to quantitate the concentrations of oxy- and deoxy-hemoglobin in the human brain.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.539-550
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• 2020

This study establishes the scientific basis for the use of digital learning materials through the education-neurological research method and derives implications for education based on education-neurological understandings. The main findings of the education-neurological analysis of digital learning materials are as follows: First, various sensory stimuli go through multiple sensory neurons and deep sections of the upper sphere and make possible the cooperative processing of information. Second, indirect experience from digital learning materials helps students understand the learning contents vividly through the mirror neuron system. Third, positive emotions originating from digital learning materials promote functions of dopamine, the reticular activating system, frontal-striatal circuit, cerebrum cortex. Based on the findings, the study suggests the following educational implications. First of all, when selecting digital learning materials, teachers should consider expression forms, learning contents, the flow of classes, and the adverse effects of digital learning materials. Next, it is effective to utilize digital learning materials in the lecture for provoking curiosity and enjoyment, maintaining interest and effort, and reviewing what students learned.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.39-48
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• 2021

According to International Associating for the Study of Pain (IASP) definition, neuropathic pain is a disorder characterized by dysfunction of the nervous system that, under normal conditions, mediates virulent information to the central nervous system (CNS). This pain can be divided into a disease with provable lesions in the peripheral or central nervous system and states with an incorporeal lesion of any nerves. Both conditions undergo long-term and chronic processes of change, which can eventually develop into chronic pain syndrome, that is, nervous system is inappropriately adapted and difficult to heal. However, the treatment of neuropathic pain itself is incurable from diagnosis to treatment process, and there is still a lack of notable solutions. Recently, several studies have observed the responses of CNS to harmful stimuli using image analysis technologies, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and optical imaging. These techniques have confirmed that the change in synaptic-plasticity was generated in brain regions which perceive and handle pain information. Furthermore, these techniques helped in understanding the interaction of learning mechanisms and chronic pain, including neuropathic pain. The study aims to describe recent findings that revealed the mechanisms of pathological pain and the structural and functional changes in the brain. Reflecting on the definition of chronic pain and inspecting the latest reports will help develop approaches to alleviate pain.