• Food Science of Animal Resources
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• v.29 no.2
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• pp.278-282
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• 2009

Previous studies indicate that BF-7 enhances learning and memory in normal and elderly individuals. Here, we evaluated whether milk containing BF-7 (BF-7 milk) could improve the brain function, with thirty normal university students $(21{\pm}1.2 years)$. Two versions of the Paced Auditory Serial Addition Test were used under double-blinded conditions to measure the efficacy of BF-7 milk on learning and memory, especially working memory and attention, and on mathematical ability. As a result, BF-7 milk improved the accuracy of the task more than 3-fold. Furthermore, BF-7 milk protected cultured neuronal cells from 3-hydroxykynurenine, a normal endogenous brain stress agent. These results indicate that BF-7 milk enhances memory, attention and mathematical ability in normal persons.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.369-378
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• 2004

In partially free word order languages like Korean and Japanese, the rule-based method is effective for text chunking, and shows the performance as high as machine learning methods even with a few rules due to the well-developed overt Postpositions and endings. However, it has no ability to handle the exceptions of the rules. Exception handling is an important work in natural language processing, and the exceptions can be efficiently processed in memory-based teaming. In this paper, we propose a hybrid of rule-based method and memory-based learning for Korean text chunking. The proposed method is primarily based on the rules, and then the chunks estimated by the rules are verified by memory-based classifier. An evaluation of the proposed method on Korean STEP 2000 corpus yields the improvement in F-score over the rules or various machine teaming methods alone. The final F-score is 94.19, while those of the rules and SVMs, the best machine learning method for this task, are just 91.87 and 92.54 respectively.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.258-264
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• 2017

Background: Pulpal pain is one of the most common and severe orofacial pain conditions with considerable adverse effects on physiological processes including learning and memory. Regular exercise is known to be effective on cognitive function as well as pain processing in the central nervous system. Here, the possible effects of regular exercise on pulpal pain response as well as pain-induced changes in learning and memory efficiency in rats were investigated. Methods: Twenty-four male Wistar rats were randomly assigned to the control, capsaicin, exercise, and exercise plus capsaicin groups. Rats in exercise groups were forced to run on a treadmill with a moderate exercise protocol for 4 weeks. Capsaicin was used to induce dental pulp pain. Passive avoidance learning and memory performance was assessed by using a shuttle box apparatus. Results: According to the results, regular exercise could decrease the time course of capsaicin-induced pulpal pain (P < 0.001). Moreover, in capsaicin-treated rats, passive avoidance acquisition was impaired as compared to the control (P < 0.05) and exercise (P < 0.001) groups. Additionally, regular exercise before capsaicin injection could attenuate capsaicin-induced memory impairments (P < 0.05). Conclusions: Taken together, the present data showed that regular exercise has inhibitory effects on capsaicin-induced pulpal pain as well as pain-induced cognitive dysfunction in rats.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.319-332
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• 2013

Previous research on learning and memory has focused on how they are constructed through past experiences. Recent studies, however, have shed light on that such cognitive processes are in service of higher goals of maximizing future rewards. This review paper aims to introduce and discuss a related line of research. First, this paper introduces researches that show goal-directed model-based reinforcement learning, in which agents choose a behavior that does not necessarily bring immediate rewards but will allow future rewards, based on generalization and analogical extrapolation. It also reviews studies on neural substrates of goal-directed learning, and discusses that cognitive process implicated in striatal dopaminergic signals can also influence memory. Especially, memory is not a merely passive process of storing and retrieving past experiences homogeneously, but rather results of a decision-making process to serve higher goals. The body of research suggests that information on future rewards can have influence on current cognitive processing in a retrospective manner.

• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.

• Sleep Medicine and Psychophysiology
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• v.3 no.1
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• pp.15-24
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• 1996

After rapid eye movement(REM) sleep was idenified in 1953, a lively interest developed concerning a possible role of this kind of sleep in memory processes. The author reviewed studies relating REM to memory/learning. Many studies in animals and humans gave substantial evidence for relating REM sleep to memory function. The evidence supporting the position taken in this paper comes from experiments showing that : (1) learning session is followed by the significant augmentation of REM sleep : (2) REM sleep deprivation, prior to learning or immediately thereafter, impairs the formation of a permanent memory/learning : (3) there is a vulnerable period of time(eg, REM sleep "window") following succussful learning, during which REM sleep deprivation results in memory impairment : (4) theta rhythm which develops during REM sleep induces long-term potentiation in hippocampus : (5) there are some evidences providing the relationship of neurotransmitter systems to the maintenance of REM sleep and memory storage processes.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.139-147
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• 2009

The memory based reasoning just stores in the memory in the form of the training pattern of the representative pattern. And it classifies through the distance calculation with the test pattern. Because it uses the techniques which stores the training pattern whole in the memory or in which it replaces training patterns with the representative pattern. Due to this, the memory in which it is a lot for the other machine learning techniques is required. And as the moreover stored training pattern increases, the time required for a classification is very much required. In this paper, We propose the EAS(Evaluation And Selection) algorithm in order to minimize memory usage and to improve classification performance. After partitioning the training space, this evaluates each partitioned space as MDL and PM method. The partitioned space in which the evaluation result is most excellent makes into the representative pattern. Remainder partitioned spaces again partitions and repeat the evaluation. We verify the performance of Proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• International Journal of Industrial Entomology and Biomaterials
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• v.15 no.1
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• pp.39-45
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• 2007

Extracts of adult worker bodies of Vespa simillima in 2 % NaCl or acidified methanol were administered orally to mice for 70 days. Following this period, memory at one-day and one-month periods, and the effects on scopolamine-induced amnesia were examined using a step-through passive avoidance task. Changes in MK-801-induced disability after 8 days of training, and in memory one month after the trial were also assessed. Mice treated with the 2% NaCl extract showed significant improvement in memory in the behavioral tests one month after the trial, whereas mice receiving the extract in acidified methanol, did not differ from the controls in any trial. The results inidicate that Vespa simillima contains substances acting favorably on the cerebral functions of mammals.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.203-208
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• 2020

This study examined whether Mild Cognitive Impairment (MCI) is related to the reduction of specific memory among linguistic memory and visuospatial memory, and to identify the most predictive index for discriminating MCI from normal elderly. The subjects were analyzed for 189 elderly (103 healthy elderly, 86 MCI). The verbal memory was used by the Seoul Verbal Learning Test. visuospatial memory was measured using the Rey Complex Figure Test. As a result of multiple logistic regression, verbal memory and visuospatial memory showed significant predictive performance in discriminating MCI from normal elderly. On the other hand, when all the confounding variables were corrected, including the results of each memory test, the predictive power was significant in distinguishing MCI from normal aging only in the immediate recall of verbal memory, and the predictive power was not significant in the immediate recall of visuospatial memory. This result suggests that delayed recall of visuospatial memory and immediate recall of verbal memory are the best combinations to discriminate memory ability of MCI.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.101-101
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• 2020

Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.