• 한국빅데이터학회지
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• 제5권1호
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• pp.1-9
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• 2020

이 연구는 2018년도 정부(농림축산식품부)의 재원으로 농림식품기술기획평가원 지원을 받아 수행된 연구이다. 최근 시계열 및 텍스트 마이닝에서 활발히 사용되는 모델은 딥러닝(Deep Learning) 모델 구조를 활용한 LSTM(Long Short-Term Memory models) 모델이다. LSTM 모델은 RNN의 BPTT(Backpropagation Through Time) 과정에서 발생하는 Long-Term Dependency Problem을 해결하기 위해 등장한 모델이다. LSTM 모델은 가변적인 Sequence data를 활용하여 예측하는 문제를 굉장히 잘 해결했고, 지금도 널리 사용되고 있다. 본 논문 연구에서는 KT가 제공하는 CDR(Call Detailed Record) 데이터를 활용하여 바이러스와 밀접한 관계가 있을 것으로 예측되는 사람의 이동 경로를 파악하였다. 해당 사람의 경로를 활용하여 LSTM 모델을 학습시켜 이동 경로를 예측한 결과를 소개한다. 본 연구 결과를 활용하여 HPAI가 전파되는 경로를 예측하여 방역에 중점을 둘 경로 또는 지역을 선정해 HPAI 확산을 줄이는 데 이용될 수 있을 것이다.

• 한국인터넷방송통신학회논문지
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• 제19권5호
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• pp.79-85
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• 2019

본 연구에서는 Long Short Term Memory (LSTM) 신경망과 Gated Recurrent Unit(GRU) 신경망을 Internet of Things (IoT) 파워미터에 적용하여 단기 전력사용량 예측방법을 제안하고, 실제 가정의 전력사용량 데이터를 토대로 예측 성능을 분석한다. 성능평가 지표로써 Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Percentage Error (MPE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE)를 이용한다. 실험 결과는 GRU 기반의 모델이 LSTM 기반의 모델에 비해 MAPE 기준으로 4.52%, MPE 기준으로 5.59%만큼의 성능개선을 보였다.

• Journal of Korean Biological Nursing Science
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• 제22권2호
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• pp.111-118
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• 2020

Purpose: The purpose of this study was to understand the impact of long- and short-term energy drinks on anxiety-like, depressionlike, and cognitive behavior in adolescent rats. Methods: Adolescent rats (age six weeks) were randomly classified into a control group (CON), a long-term administration group (LT), and a short-term administration group (ST). The LT group was orally administered 1.5 mL/100 g (body weight) of energy drink twice daily for 14 days, the ST group was orally administered for one day, and the control group applied the same amount of normal saline. Later, an open-field test, a forced swim test, novel object recognition test, and an 8-arm radial maze test was conducted to assess the rats' anxiety, depression, and cognitive function. Results: There were different effects in the long- and short-term groups of energy drink administration. In the LT group, anxiety- and depressive-like behavior increased because of increased movement in the side corner and decrease of immobility time. Also, the time to explore novel objects decreased, and the number of correct responses was reduced, indicating a learning and memory function disorder. However, the ST group was not different from the control group. Conclusion: These results indicate that long-term consumption of energy drinks can increase anxiety-like, depression-like behavior, and this can lead to decrease in learning and memory functions. Thus, nurse and health care providers should understand the impact of energy drink consumption in adolescence to provide appropriate practices and education.

• JSTS:Journal of Semiconductor Technology and Science
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• 제15권6호
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• pp.658-663
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• 2015

In the previous work, we have proposed an integrate-and-fire neuron circuit and synaptic device based on the floating body MOSFET [1-3]. Integrate-and-Fire(I&F) neuron circuit emulates the biological neuron characteristics such as integration, threshold triggering, output generation, refractory period using floating body MOSFET. The synaptic device has short-term and long-term memory in a single silicon device. In this paper, we connect the neuron circuit and the synaptic device using current mirror circuit for summation of post synaptic pulses. We emulate spike-timing-dependent-plasticity (STDP) characteristics of the synapse using feedback voltage without controller or clock. Using memory device in the logic circuit, we can emulate biological synapse and neuron with a small number of devices.

• 디지털산업정보학회논문지
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• 제5권4호
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• pp.169-177
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• 2009

In come cases, people differently respond on the same joke or thoughtless behavior - sometimes like it and laugh, another time feel annoyed or angry. This fact is explained that experiences which we had in the past are remembered by emotional memory, so they cause different responses. When people face similar situation or feel similar emotion, they evoke the emotion experienced in the past and the emotional memory affects current emotion. This paper suggested the mechanism of the emotional memory using SOM through the similarity between the emotional memory and SOM learning algorithm. It was assumed that the mechanism of the emotional memory has also the characteristics of association memory, long-term memory and short-term memory in its process of remembering emotional experience, which are known as the characteristics of the process of remembering factual experience. And then these characteristics were applied. The mechanism of the emotional memory designed like this was applied to toy hammer game and I measured the change in the power of toy hammer caused by differently responding on the same stimulus. The mechanism of the emotional memory suggest in above is expected to apply to the fields of game, robot engineering, because the mechanism can express various emotions on the same stimulus.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.70-73
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• 1992

This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathematically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTNI Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.577-594
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• 2002

For the estimation and test of long memory feature in volatilities of stock indices and individual companies semiparametric approach, Geweke and Porter-Hudak (1983), is employed. Empirical study supports the strong evidence of volatility persistence in Korean stock market. Most of indices and individual companies have the feature of long term dependence of volatility. Hence the short memory models are unable to explain the volatilities in Korean stock market.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제7권8호
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• pp.307-324
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• 2018

최근 순환 신경 망(Recurrent Neural Networks)은 시간에 대한 의존성을 고려한 구조를 통해 순차 데이터(Sequential data)의 예측 문제 해결에서 각광받고 있다. 하지만 순차 데이터의 시간 스텝이 늘어남에 따라 발생하는 그라디언트 소실(Gradients vanishing)이 문제로 대두되었다. 이를 해결하기 위해 장단기 기억 모델(Long Short-Term Memory)이 제안되었지만, 많은 데이터를 저장하고 장기간 보존하는 데에 한계가 있다. 따라서 순환 신경망과 메모리 요소(Memory component)를 활용한 학습 모델인 메모리-증대 신경망(Memory-Augmented Neural Networks)에 대한 연구가 최근 활발히 진행되고 있다. 본 논문에서는 딥 러닝(Deep Learning) 분야의 화두로 떠오른 메모리-증대 신경망 주요 모델들의 구조와 특징을 열거하고, 이를 활용한 최신 기법들과 향후 연구 방향을 제시한다.

• 한국인터넷방송통신학회논문지
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• 제20권3호
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• pp.1-7
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• 2020

증가하는 사이버공격에 대응하기 위하여 머신러닝을 적용한 자동화된 침입탐지기술이 연구되고 있다. 최근 연구결과에 따르면, 순환형 학습모델을 적용한 침입탐지기술이 높은 탐지성능을 보여주는 것으로 확인되었다. 하지만 단순한 순환형 모델을 적용하는 것은 통신이 중첩된 환경일수록 연관된 통신의 특성을 반영하기 어려워 탐지성능이 저하될 수 있다. 본 논문에서는 이 같은 문제점을 해결하고자 세션관리모듈을 설계하여 LSTM(Long Short-Term Memory) 순환형 모델에 적용하였다. 실험을 위하여 CSE-CIC-IDS 2018 데이터 셋을 사용하였으며, 정상통신비율을 증가시켜 악성통신의 연관성을 낮추었다. 실험결과 통신연관성을 파악하기 힘든 환경에서도 제안하는 모델은 높은 탐지성능을 유지할 수 있음을 확인하였다.

• 말소리와 음성과학
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• 제8권1호
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• pp.63-69
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• 2016

The aims of the present study are two-fold: 1) to explore differences on speech perception between younger and older adults according to noise conditions; and 2) to investigate which cognitive domains are correlated with speech perception. Data were acquired from 15 younger adults and 15 older adults. Sentence recognition test was conducted in four noise conditions(i.e., in-quiet, +5 dB SNR, 0 dB SNR, -5 dB SNR). All participants completed auditory and cognitive assessment. Upon controlling for hearing thresholds, the older group revealed significantly poorer performance compared to the younger adults only under the high noise condition at -5 dB SNR. For older group, performance on Seoul Verbal Learning Test(immediate recall) was significantly correlated with speech perception performance, upon controlling for hearing thresholds. In older adults, working memory and verbal short-term memory are the best predictors of speech-in-noise perception. The current study suggests that consideration of cognitive function for older adults in speech perception assessment is necessary due to its adverse effect on speech perception under background noise.