• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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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.

• Biomolecules & Therapeutics
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• v.23 no.3
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• pp.251-260
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• 2015

Propofol is an anesthetic agent that gained wide use because of its fast induction of anesthesia and rapid recovery post-anesthesia. However, previous studies have reported immediate neurodegeneration and long-term impairment in spatial learning and memory from repeated neonatal propofol administration in animals. Yet, none of those studies has explored the sex-specific long-term physical changes and behavioral alterations such as social (sociability and social preference), emotional (anxiety), and other cognitive functions (spatial working, recognition, and avoidance memory) after neonatal propofol treatment. Seven-day-old Wistar-Kyoto (WKY) rats underwent repeated daily intraperitoneal injections of propofol or normal saline for 7 days. Starting fourth week of age and onwards, rats were subjected to behavior tests including open-field, elevated-plus-maze, Y-maze, 3-chamber social interaction, novel-object-recognition, passive-avoidance, and rotarod. Rats were sacrificed at 9 weeks and hippocampal protein expressions were analyzed by Western blot. Results revealed long-term body weight gain alterations in the growing rats and sex-specific impairments in spatial (female) and recognition (male) learning and memory paradigms. A markedly decreased expression of hippocampal NMDA receptor GluN1 subunit in female- and increased expression of AMPA GluR1 subunit protein expression in male rats were also found. Other aspects of behaviors such as locomotor activity and coordination, anxiety, sociability, social preference and avoidance learning and memory were not generally affected. These results suggest that neonatal repeated propofol administration disrupts normal growth and some aspects of neurodevelopment in rats in a sex-specific manner.

• Sleep Medicine and Psychophysiology
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• v.5 no.2
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• pp.177-184
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• 1998

Objectives : Disturbance of sleep with or without sleep apnea may impair the memory function. Sleep deficiency, sleepiness, sleep apnea and emotional problem in sleep disorders can induce an impairment of memory function. Methods : In this study, the polysomnographies were administered to 58 sleep apnea patients and 38 sleep disorder patients without sleep apnea. Their clinical symptoms were quantitatively evaluated. Short term and long term memory were evaluated before and after polysom no graphy with Digit symbol test and Rey-Osterrieth complex figure test. And correlations among various sleep, repiratory and clinical variables were statistically studied in order to explore which variables may influence on memory function. Results and Conclusions : Results are as follows. Depth of sleep cis positively correlated with memory function. As sleep apnea increases and average saturation of blood oxygen decreases, memory function is more impaired. Emotional depression, high blood pressure, obesity or alcohol impaired memory function. However, daytime sleepiness was not significantly correlated with memory function. The possible mechanisms how above factors influence on the memory function were discussed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.3
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• pp.103-110
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• 2018

The long-term flexural behavior of reinforced concrete (RC) beams strengthened with an iron based-shape memory alloys (Fe-SMAs) by a near-surface mounted (NSM) method was evaluated. The pre-strained values of 2% and 4% and introduced prestressing force by an activation of a shape memory effect of the Fe-SMA strengthening material were considered as experimental variables. Deflections at the center of the RC beams were measured for six months after the 1 tonf concrete weight was loaded on the beam. Experimental results show that the deflections decreased because of the increased flexural stiffness of beams strengthened with the Fe-SMA strips. On the contrary, with increased pre-strained values, the deflection increased due to stiffness reduction of the strengthening material. It was confirmed that the specimens incorporating the prestressed force showed the deflection reduction of about 30%, compared to the ones without the prestressed force.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.209-214
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• 2019

Precise point positioning (PPP) requires precise orbit and clock products. International GNSS service (IGS) real-time service (RTS) data can be used in real-time for PPP, but it may not be possible to receive these corrections for a short time due to internet or hardware failure. In addition, the time required for IGS to combine RTS data from each analysis center results in a delay of about 30 seconds for the RTS data. Short-term orbit prediction can be possible because it includes the rate of correction, but the clock correction only provides bias. Thus, a short-term prediction model is needed to preidict RTS clock corrections. In this paper, we used a long short-term memory (LSTM) network to predict RTS clock correction for three minutes. The prediction accuracy of the LSTM was compared with that of the polynomial model. After applying the predicted clock corrections to the broadcast ephemeris, we performed PPP and analyzed the positioning accuracy. The LSTM network predicted the clock correction within 2 cm error, and the PPP accuracy is almost the same as received RTS data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.37-45
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• 2006

In this paper, we propose the development of MHLA(Modulatory Hippocampus Learning Algorithm) which remodel a principle of brain of hippocampus. Hippocampus takes charge auto-associative memory and controlling functions of long-term or short-term memory strengthening. We organize auto-associative memory based 3 steps system(DG, CA3, CAl) and improve speed of learning by addition of modulator to long-term memory learning. In hippocampal system, according to the 3 steps order, information applies statistical deviation on Dentate Gyrus region and is labelled to responsive pattern by adjustment of a good impression. In CA3 region, pattern is reorganized by auto-associative memory. In CAI region, convergence of connection weight which is used long-term memory is learned fast by neural networks which is applied modulator. To measure performance of MHLA, PCA(Principal Component Analysis) is applied to face images which are classified by pose, expression and picture quality. Next, we calculate feature vectors and learn by MHLA. Finally, we confirm cognitive rate. The results of experiments, we can compare a proposed method of other methods, and we can confirm that the proposed method is superior to the existing method.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.333-339
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• 2013

This research explores the effect of TV news anchor's gender on affect of viewer and memory of news based on elaboration likelihood model. For this experimental research, 2 groups of subjects composed of university students were exposed to different types of TV news and responded to survey questions about affect and short-term and long-term memory. This research found that subjects exposed to woman anchor's news showed higher degree of affect and short-term memory, but lower degree of trust than subjects exposed to man anchor's news, but interactive effect of viewers' involvement and anchor's gender as an peripheral clue was not found.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.63-89
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• 2007

This study aims at empirically verifying whether long memory properties exist in returns and volatility of the financial time series and then, empirically observing influential factors of long-memory properties. The presence of long memory properties in the financial time series is examined with the Hurst exponent. The Hurst exponent is measured by DFA(detrended fluctuation analysis). The empirical results are summarized as follows. First, the presence of significant long memory properties is not identified in return time series. But, in volatility time series, as the Hurst exponent has the high value on average, a strong presence of long memory properties is observed. Then, according to the results empirically confirming influential factors of long memory properties, as the Hurst exponent measured with volatility of residual returns filtered by GARCH(1, 1) model reflecting properties of volatility clustering has the level of $H{\approx}0.5$ on average, long memory properties presented in the data before filtering are no longer observed. That is, we positively find out that the observed long memory properties are considerably due to volatility clustering effect.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.1-7
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• 2020

With the increase in cyber attacks, automated IDS using machine learning is being studied. According to recent research, the IDS using the recursive learning model shows high detection performance. However, the simple application of the recursive model may be difficult to reflect the associated session characteristics, as the overlapping session environment may degrade the performance. In this paper, we designed the session management module and applied it to LSTM (Long Short-Term Memory) recursive model. For the experiment, the CSE-CIC-IDS 2018 dataset is used and increased the normal session ratio to reduce the association of mal-session. The results show that the proposed model is able to maintain high detection performance even in the environment where session relevance is difficult to find.