• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.22.3-22
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• 2001

An attention task, in which context information should be extracted from the first presented pattern, and the recognition answer of the second presented pattern should be generated using the context information, is employed in this paper. An Elman-type recurrent neural network is utilized to extract and keep the context information. A reinforcement signal that indicates whether the answer is correct or not, is only a signal that the system can obtain for the learning. Only by this learning, necessary context information became to be extracted and kept, and the system became to generate the correct answers. Furthermore, the function of an associative memory is observed in the feedback loop in the Elman-type neural network.

• The Journal of Korean Physical Therapy
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• v.19 no.4
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• pp.25-32
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• 2007

Purpose: The purpose of this study was to evaluate the effect of computerized neurocognitive function program on cognitive function about memory and attention with stroke. Methods: 24subjects with stroke were recruited. Twelve of subjects received conventional therapy including physical therapy, occupational therapy and language therapy. Another subjects received additional computer assisted cognitive training using Computer-aided Cognitive rehabilitation training system(COMCOG, MaxMedica Inc., 2004). All patients were assessed their cognitive function of memory and attention using Computerized Neurocognitive Function Test(CNT, MaxMedica Inc., 2004) before treatment and 6 weeks after treatment. Results: Before the treatment, two groups showed no difference in cognitive function(p>0.05). After 6 weeks, two groups showed significantly difference in digit span (forward, backward), verbal learning(A5, $A1{\sim}A5$), auditory CPT(n), visual CPT(n)(p<0.05). After treatment, the experimental group showed a significant improvement of digit span(forward, backward), verbal learning(A5, $A1{\sim}A5$), visual span (forward, backward), auditory CPT(n, sec), visual CPT(n, sec), and trail-making (A, B)(p<0.05). Conclusion: Computerized neurocognitive function program would be improved cognitive function of memory and attention in patients with stoke.

• Journal of Ginseng Research
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• v.41 no.2
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• pp.151-158
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• 2017

Background: Chong-Myung-Tang (CMT) extract is widely used in Korea as a traditional herbal tonic for increasing memory capacity in high-school students and also for numerous body ailments since centuries. The use of CMT to improve the learning capacity has been attributed to various plant constituents, especially black ginseng, in it. Therefore, in this study, we have first investigated whether black ginseng-enriched CMT extracts affected spatial learning using the Morris water maze (MWM) test. Their molecular mechanism of action underlying improvement of learning and memory was examined in vitro. Methods: We used two types of black ginseng-enriched CMT extracts, designated as CM-1 and CM-2, and evaluated their efficacy in the MWM test for spatial learning behavior and their anti-inflammatory effects in BV2 microglial cells. Results: Our results show that both black ginseng-enriched CMT extracts improved the learning behavior in scopolamine-induced impairment in the water maze test. Moreover, these extracts also inhibited nitric oxide production in BV2 cells, with significant suppression of expression of proinflammatory cytokines, especially inducible nitric oxide synthase, cyclooxygenase-2, and $interleukin-1{\beta}$. The protein expression of mitogen-activated protein kinase and nuclear $factor-{\kappa}B$ pathway factors was also diminished by black ginseng-enriched CMT extracts, indicating that it not only improves the memory impairment, but also acts a potent anti-inflammatory agent for neuroinflammatory diseases. Conclusion: Our research for the first time provides the scientific evidence that consumption of black ginseng-enriched CMT extract as a brain tonic improves memory impairment. Thus, our study results can be taken as a reference for future neurobehavioral studies.

• Journal of Digital Convergence
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• v.4 no.2
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• pp.143-151
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• 2006

The purpose of this paper is to make a design and implementation of a diagnosis system of learning misconception of students who learn 'be' verb in the English language by using fuzzy theory. In this system, a fuzzy cognitive map exposes the fact that students' perception and misunderstanding about 'the English' language have an intertwined relationship, and diagnoses causes of misconceptions of students by using fuzzy memory associative memory. It suggests that since most existing systems of rule based expert system have had several limitations, this system will be applied to diagnose learners' misconception of learning in varieties of education areas.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.451-459
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• 2006

The purpose of this paper is to make a design and implementation of a diagnosis system of learning misconception of students who learn 'be' verb in the English language by using fuzzy theory. In this system, a fuzzy cognitive map exposes the fact that students' perception and misunderstanding about 'the English' language have an intertwined relationship, and diagnoses causes of misconceptions of students by using fuzzy memory associative memory. It suggests that since most existing systems of rule based expert system have had several limitations, this system will be applied to diagnose learners' misconception of learning in varieties of education areas.

• Earthquakes and Structures
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• v.25 no.1
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• pp.15-26
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• 2023

It is of great importance to assess the residual displacement demand in the performance-based seismic design. In this paper, a hybrid deep learning model for predicting the residual displacement spectra under near-fault (NF) ground motions is proposed by combining the long short-term memory network (LSTM) and back-propagation (BP) network. The model is featured by its capacity of predicting the residual displacement spectrum under a given NF ground motion while considering the effects of structural parameters. To construct this model, 315 natural and artificial NF ground motions were employed to compute the residual displacement spectra through elastoplastic time history analysis considering different structural parameters. Based on the resulted dataset with a total of 9,450 samples, the proposed model was finally trained and tested. The results show that the proposed model has a satisfactory accuracy as well as a high efficiency in predicting residual displacement spectra under given NF ground motions while considering the impacts of structural parameters.

• Journal of Ginseng Research
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• v.20 no.1
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• pp.7-14
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• 1996

This study was performed to examine the effect of red ginseng total saponin and extract on memory in mice using one trial step-down type passive avoidance method. Red ginseng total saponins (No. 1: PD/PT ratio=1.24, No. 2: PD/PT ratio=1.47) were prepared with the different mixing ratio by using the parts of red ginseng. In single administration of total saponin No. 1 (100 mg/ kg, bw) or No. 2 (50 mg/kg, bw) increased the latency time as compared with control group but was not statistically significant. Treatment of total saponin No. 1 (50 mg/kg, bw) for 10 days produced an increase of latency time but was not statistically significant. In scopolamine-induced memory deficient mice total saponin No. 1 (50 mg/kg, bw) and No. 2 (100 mg/kg, bw) significantly improved the latency time. These results show that red ginseng total saponin may improve the memory of sco-polamine-induced memory deficient mice and have nootropic activity.

• The Journal of Internal Korean Medicine
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• v.27 no.1
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• pp.253-264
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• 2006

Object: This research investigated effects of Jujadokseo-hwan on mice with Alzheimer's Disease induced by $amyloid-{\beta}$. According to Dongyibogam, Jujadokseo-hwan can cure amnesia. Amyloid-B is believed to induce oxidative stress and inflammation in the brain, postulated to play important roles in the pathogenesis of Alzheimer's disease. In this way $Amyloid-{\beta}$ induces Alzheimer's Disease. Methods : In order to make an efficient prescription and cope with dementia, learning and memory functions of mice were tested on passive avoidance test and V-maze task. $NF-{\kappa}B$ were measured from protein derived from the brain. RT-PCR was done for !gene analysis. Primers were protein kinase Band $NGF-{\alpha}$. Results : 1. Jujadokseo-hwan was effective for memory capacity on passive avoidance test. but noneffective for spatial memory capacity and locomotor activity on Y -maze task. 2. The measurement of $NF-{\kappa}B$ showed upward tendancies and the result of RT-PCR showed up-regulation when given Jujadokseo-hwan by mouth. Conclusion: Results suggest that Jujadokseo-hwan is effective on mice with Alzheimer's Disease induced by $amyloid-{\beta}$.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.5
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• pp.976-988
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• 2002

The aim of this study was to examine the memory and attention enhancement effect of YMG-1 and YMG-2, which are modified herbal extracts from Yukmijihwang-tang (YMJ). YMJ, composing six herbal medicine, has been used for restoring the normal functions of the body to consolidate the constitution, nourishing and invigorating the kidney functions for hundreds years in Asian countries. A series of studies reported that YMJ and its components enhance memory retention, protects neuronal cell from reactive oxygen attack and boost immune activities. Recently the microarray analysis suggested that YMG-1 protects neurodegeneration through modulating various neuron specific genes. A total of 55 subjects were divided into three groups according to the treatment of YMG-1 (n=20), YMG-2 (n=20) and control (C; n=15) groups. Before treatments, all of subjects were subjected to the assessments on neuropsychological tests of K-WAIS test, Rey-Kim memory test, and psychophysiological test of Event-Related Potential (ERP) during auditory oddball task and repeated word recognition task. They were repeatedly assessed with the same methods after drug treatment for 6 weeks. Although no significant effect of drug was found in Rey-Kim memory test, a significant interaction (P = .010, P < 0.05) between YMG-2 and C groups was identified in the scores digit span and block design, which are the subscales of K-WAIS. The very similar but marginal interaction (P = .064) between YMG-1 and C groups was found too. In ERP analysis, only YMG-1 group showed decreasing tendency of P300 latency during oddball task while the others tended to increase, and it caused significant interaction between session and group (p= .004). This result implies the enhancement of cognitive function in due to consideration of relationship between P300 latency and the speed of information processing. However, no evidence which could demonstrate the significant drug effect was found in neither amplitude or latency. These results come together suggest that YMG-1, 2 may enhance the attention, resulting in enhancement of memory processing. For elucidating detailed mechanism of YMG on learning and memory, the further studies are necessary.

• Journal of KIISE
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• v.44 no.6
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• pp.607-612
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• 2017

This paper presents an attempt to apply Deep Learning technology to solve the problem of forecasting floods in urban areas. We employ Recurrent Neural Networks (RNNs), which are suitable for analyzing time series data, to learn observed data of river water and to predict the water level. To test the model, we use water observation data of a station in the Trinity river, Texas, the U.S., with data from 2013 to 2015 for training and data in 2016 for testing. Input of the neural networks is a 16-record-length sequence of 15-minute-interval time-series data, and output is the predicted value of the water level at the next 30 minutes and 60 minutes. In the experiment, we compare three Deep Learning models including standard RNN, RNN trained with Back Propagation Through Time (RNN-BPTT), and Long Short-Term Memory (LSTM). The prediction quality of LSTM can obtain Nash Efficiency exceeding 0.98, while the standard RNN and RNN-BPTT also provide very high accuracy.