• Informatization Policy
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• v.31 no.1
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• pp.32-52
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• 2024

This study investigates the effectiveness of virtual reality agents as foreign language instructors with focus on the impact of different native language backgrounds and instructional roles. The agents were first distinguished as native or non-native speakers treated as a between-subject factor, and then assigned roles as either teachers or salespersons considered within-subject factors. An immersive virtual environment was developed for this experiment, and a 2×2 mixed factorial design was carried out. In an experimental group of 72 university students, statistically significant interactions were found in learning satisfaction, memory, and recall between the native/non-native status of the agents and their roles. With regard to learning confidence and presence, however, no statistically significant differences were observed in both interaction effects and main effects. Contextual learning in a virtual environment was found to enhance learning effectiveness and satisfaction, with the nativeness and the role of agents influencing learners' memory; thus highlighting the effectiveness of using virtual reality agents in foreign language learning. This suggests that varied approaches can have positive cognitive and emotional impacts on learners, thereby providing valuable theoretical and empirical implications.

• Journal of Ginseng Research
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• v.24 no.1
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• pp.8-17
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• 2000

Estrogen can influence on the expression of behaviors not associated directly with reproduction, including learning and memory. Recently estrogen has received considerable attention for its effects on neuroprotection and neural circuits in brain areas associated with cognition. Although estrogen replacement therapy may be helpful to postmenopausal women, it also results in a number of harmful side effects. Ginseng also has steroidal qualities and contains several ginsenoside components which have similar backbone structure to estrogen. The objectives of this experiment were 1) to examine the effects of estrogen and 2) to investigate the effects of ginsenosides as estrogenic agent on learning and memory using the Morris water maze, a traditional experimental task for spatial memory. In the experiments designed here, ovariectomized mice were implanted subcutaneously with Sila, itic capsules containing 17${\beta}$-estradiol (100∼250 $\mu\textrm{g}$/$m\ell$), panaxadiol (PD) and panaxatriol (PT) saponins (15∼100 $\mu\textrm{g}$/$m\ell$) diluted with sesame oil. In the first set of experiment, the effects of estradiol on learning and memory during the Morris water maze was examined. When estradiol was delivered via Silastic capsules following training improved spatial memory performance in ovariectomized female mice. In the second set of experiment, three different PD and PT saponin concentrations were delivered via Silastic implants to ovariectomized female mice and their effects were compared with estrogenic effects. Results of three separate experiments demonstrated that estradiol, PD and PT administrated by Silastic implants for 2 weeks prior to water maze training significantly improved spatial memory performance compared to ovariectomized (OVX) mice, as indicated by lower escape latency over trial. The positive effect of estradiol suggests that estrogen can affect performance on learning and memory. In addition, the positive effect of PD and PT saponins suggest that ginsenosides have an estrogen-like effects in mediating learning and memory related behavior action.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.1-8
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• 1998

In this paper, we propose a Neural Call Admission Control (CAC) method using a Sparse Distributed Memory(SDM). CAC is a key technology of TM network traffic control. It should be adaptable to the rapid and various changes of the ATM network environment. conventional approach to the ATM CAC requires network analysis in all cases. So, the optimal implementation is said to be very difficult. Therefore, neural approach have recently been employed. However, it does not mett the adaptability requirements. because it requires additional learning data tables and learning phase during CAC operation. We have proposed a neural network CAC method based on SDM that is more actural than conventioal approach to apply it to CAC. We compared it with previous neural network CAC method. It provides CAC with good adaptability to manage changes. Experimenatal results show that it has rapid adaptability and stability without additional learning table or learning phase.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.385-386
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• 2019

This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.98-101
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• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.395-402
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• 2022

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

• Biomolecules & Therapeutics
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• v.16 no.4
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• pp.320-327
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• 2008

Several lines of evidence indicate that adenosine $A_{2A}$ agonist disrupts spatial working memory. However, it is unclear which stages of learning and memory are affected by the stimulation of adenosine $A_{2A}$ receptor. To clarify these points, we employed CV-1808 as adenosine $A_{2A}$ agonist and investigated its effects on acquisition, consolidation, and retrieval phases of learning and memory using passive avoidance and the Morris water maze tasks. During the acquisition phase, CV-1808 (2-phenylaminoadenosine, 1 and 2 mg/kg, i.p.) decreased the latency time in passive avoidance task and the mean savings in the Morris water maze task, respectively. During the consolidation and retrieval phase tests, CV-1808 did not exhibited any effects on latency time in passive avoidance task and the mean savings in the Morris water maze task. These results suggest that CV-1808 as an adenosine $A_{2A}$ agonist impairs memory acquisition but not consolidation or retrieval.

• Journal of Ginseng Research
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• v.18 no.3
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• pp.165-174
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• 1994

To investigate the significant indicators Improving the undisturbed memory in animal behavior, we employed several behavioral methods (learning, relearning in radial maze, and active avoidance) with ginseng components. Results showed that the repeated intranasal administration of $Rb_1$ and total saponins from Korean red ginseng induced direct effects on the brain mechanisms in rats, and improved the spatial memory during the learning, relearning and retention in the 12-arm radial maze test. The intranasal treatment of the total saponins also effectively improved the disturbed memory (amnesia) by pentylentetrazole, and simultaneously protected the brain by decreasing the severity of motor epileptic seizures. The intraperitonial administration of polysaccharide fraction of Korean red ginseng could improve avoidance behavior (amount of the total ecapes) in the active-avoidance test. In addition, local changes of the temperature and resistance of skin observed after Rb, administration were suggested to reflect some action of sympathetic nerve Key words Memory, intranasal administration, pentylenetetrazole, Korea red ginseng.

• Journal of the Korean Society of Earth Science Education
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• v.3 no.1
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• pp.18-27
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• 2010

The purpose of this study is to investigate effects of instruction with stories on elementary school students' science learning and memory. For the purpose, this researcher sampled 3 classes in their 3th grade from an elementary school. Out of the three classes, two were designated as the comparative group consisting of 70 students and the other, the experimental group, 32 students. The former group was applied instruction treatment under the 7th national curriculum of education. The other group was instructed with a story book that contained stories students already knew which were somewhat rearranged to comply with contents of a relevant curricular course. Results of the study can be described as follows. First, academic achievement test was made immediately after the treatment to show that the experimental group was significantly higher in scores for memory and understanding in the section of 'Finding Constellations' that the other group. Second, the two groups' academic achievements in relation to the section, 'Finding Constellations' were tested 3 months after the treatment to show that the experimental group was significantly higher in scores for memory and understanding than the comparative group. Such achievements within the groups were tested 3 months after the treatment to find that both of the two groups didn't show statistically significant differences.

• Molecules and Cells
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• v.23 no.3
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• pp.259-271
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• 2007

Investigation of molecular and cellular mechanisms of synaptic plasticity is the major focus of many neuroscientists. There are two major reasons for searching new genes and molecules contributing to central plasticity: first, it provides basic neural mechanism for learning and memory, a key function of the brain; second, it provides new targets for treating brain-related disease. Long-term potentiation (LTP), mostly intensely studies in the hippocampus and amygdala, is proposed to be a cellular model for learning and memory. Although it remains difficult to understand the roles of LTP in hippocampus-related memory, a role of LTP in fear, a simplified form of memory, has been established. Here, I will review recent cellular studies of LTP in the anterior cingulate cortex (ACC) and then compare studies in vivo and in vitro LTP by genetic/pharmacological approaches. I propose that ACC LTP may serve as a cellular model for studying central sensitization that related to chronic pain, as well as pain-related cognitive emotional disorders. Understanding signaling pathways related to ACC LTP may help us to identify novel drug target for various mental disorders.