• 성인간호학회지
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• 제27권6호
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• pp.707-717
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• 2015

Purpose: This study was to develop and verify the effects of the exercise-cognitive combined dual-task training program on cognitive function and depression of the elderly with mild cognitive impairment (MCI). Methods: A non-equivalent control group pretest-posttest design was used. The participants were assigned into two groups: an experimental group receiving an exercise-cognitive combined dual-task (n=20) and a control group receiving a simple-task (n=18). After 8 weeks of intervention (2 days per week), the change in depression and cognitive functions were compared between the groups. Results: General cognitive function (t=-2.81, p=.011), frontal cognitive function (Z=-3.50, p<.001), attention/working memory function (U=-2.91, p=.004), depression (t=4.96, p<.001) of the experimental group were significantly increased than those of the control group. Conclusion: The findings of the study showed that an exercise-cognitive combined dual-task program for MCI was effective in improving general cognitive function, frontal and executive function, attention/working memory function, and reducing depression.

• 한국재료학회지
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• 제22권8호
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• pp.385-389
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• 2012

Significant improvements in the switching voltage distribution are required for the development of unipolar resistive memory devices using $MnO_x$ thin films. The $V_{set}$ of the as-grown $MnO_x$ film ranged from 1 to 6.2 V, whereas the $V_{set}$ of the oxygen-annealed film ranged from 2.3 to 3 V. An excess of oxygen in an $MnO_x$ film leads to an increase in $Mn^{4+}$ content at the $MnO_x$ film surface with a subsequent change in the $Mn^{4+}/Mn^{3+}$ ratio at the surface. This was attributed to the change in $Mn^{4+}/Mn^{3+}$ ratios at the $MnO_x$ surface and to grain growth. Oxygen annealing is a possible solution for improving the switching voltage distribution of $MnO_x$ thin films. In addition, crystalline $MnO_x$ can help stabilize the $V_{set}$ and $V_{reset}$ distribution in memory switching in a Ti/$MnO_x$/Pt structure. The improved uniformity was attributed not only to the change of the crystallinity but also to the redox reaction at the interface between Ti and $MnO_x$.

• Journal of Information Technology Applications and Management
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• 제21권3호
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• pp.1-17
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• 2014

In this study, various characteristics of R&D related economic variables were studied to analyze complexity of science and technology activities in Korea, as reliance of R&D activities of the private sector is growing by the day. In comparison to other countries, this means that it is likely to be fluctuated by economic conditions. This complexity characteristic signifies that the result of science and technology activities can be greatly different from the anticipated results - depending on the influences from economic conditions and the results of science and technology activities which may be unpredictable. After reviewing the results of 17 variables related to science and technology characteristics of complex systems intended for time-series data - in the total R&D expenditure, and private R&D expenditure, numbers of SCI papers, the existence of chaotic characteristics were. using Lyapunov Exponent, Hurst Exponent, BDS test. This result reveals science and technology activity of the three most important components in Korea which are; heavy dependence on initial condition, the long term memory of time series, and non-linear structure. As stable R&D investment and result are needed in order to maintain steady development of Korea economy, the R&D structure should be less influenced by business cycles and more effective technology development policy for improving human resource development must be set in motion. And to minimize the risk of new technology, the construction of sophisticated technology forecasting system should take into account, for development of R&D system.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.989-997
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• 2018

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.30-32
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• 2014

최근 낸드 플래시 메모리는 임베디드 저장 장치로 많이 사용되고 있다. 비휘발성인 플래시 메모리는 기존의 하드디스크와 달리 저 전력, 좋은 내충격성 및 집적도 등 많은 장점이 있지만 데이터 업데이트 시 덮어쓰기가 안 되어 쓰기 연산 전 해당 블록을 지우는 작업이 선 진행되어야 하며 이로 인해 부분 페이지 업데이트가 자주 일어난다. 이런 플래시메모리와 더불어 최근 차세대 메모리연구가 많이 진행 중인데, 이 중에서 PCM 이라는 메모리는 비휘발성으로 정전 시 데이터가 날라 가버리는 DRAM에 반해 전원이 공급 안 되더라도 데이터가 보존되는 특성이 있다. 하지만 PCM 역시 플래시 메모리와 마찬가지로 블록 당 쓰기연산 작업이 제한되어 있어서 근래에 DRAM과 같이 사용하는 하이브리드 구조를 채택하여 많은 연구가 진행되고 있다. 따라서 본 논문에서는 플래시 메모리의 문제점을 해결함으로서 수명을 연장시키고 정 전시 데이터가 보존되지 않는 DRAM의 단점을 하이브리드 메모리를 기반으로하여 데이터의 신뢰성을 높이는 FTL알고리즘을 제안한다.

• 전자통신동향분석
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• 제34권4호
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.297-309
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• 2021

In this study, to capture the skewness and kurtosis detected in both conditional and unconditional return distributions of the stock markets of Kazakhstan and Russia, two versions of normal mixture GARCH models are employed. The data set consists of daily observations of the Kazakhstan and Russia stock prices, and world crude oil price, covering the period from 1 June 2006 through 1 March 2021. From the empirical results, incorporating the long memory effect on the returns not only provides better descriptions of dynamic behaviors of the stock market prices but also plays a significant role in improving a better understanding of the return dynamics. In addition, normal mixture models for time-varying volatility provide a better fit to the conditional densities than the usual GARCH specifications and has an important advantage that the conditional higher moments are time-varying. This implies that the volatility skews implied by normal mixture models are more likely to exhibit the features of risk and the direction of the information flow is regime-dependent. The findings of this study contain useful information for diverse purposes of cross-border stock market players such as asset allocation, portfolio management, risk management, and market regulations.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• 농촌의학ㆍ지역보건
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• 제45권3호
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• pp.121-129
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• 2020

치매가 진행되면서 인지기능 저하로 인해 기억력 감퇴, 언어능력 저하, 시공간 파악능력 저하, 판단력 저하가 오게 되어 일상생활과 관련된 과제들을 수행하는데 어려움이 발생하게 된다. 경도인지장애를 동반한 치매 환자들을 위한 지역사회 기반 비 약물적 중재치료는 인지, 운동치료, 예술과 같은 활동을 포함 작업, 운동, 오락치료가 있고, 환자들의 삶의 질, 라이프케어의 증진에 영향을 준다. 본 연구는 라이프케어 증진을 위한 후마네트 운동 프로그램이 노인의 인지기능, 우울기능에 미치는 영향을 알아보고자, 경기도에 소재한 데이케어센터에서 실험군 15명, 대조군 15명을 8주간 실시하였다. 두 집단간에 지남력, 기억회상, 주의집중 및 계산, 우울기능에 유의한 차이가 있었고, 기억등록, 언어기능, 이해 및 판단에는 유의한 결과를 얻지 못하였다. 후마네트 운동은 치매 노인에게 인지기능 향상과, 우울기능에 효과가 있다고 판단되었다. 집안 내 생활이 많아지고, 운동기능, 우울기능, 인지기능이 감소될 수 있는 노인, 치매, 경도인지장애 환자들을 대상으로 라이프케어 증진을 위한 후마네트 운동 프로그램을 적용할 수 있는 방안을 마련하고 그 효과를 반복 측정하는 연구를 제언한다.

• 디지털콘텐츠학회 논문지
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• 제19권4호
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• pp.789-799
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• 2018

이 논문에서는 이러한 산업 단지 시스템에서의 비정상적인 동작이 일어날 때, 시간 계열의 데이터를 분석하기 위하여 Big 데이터를 이용한 접근을 기반으로 하는 머신 러닝을 보여줍니다. Long Short-Term Memory (LSTM) 네트워크는 향상된 RNN버전으로서 입증되었으며 많은 작업에 유용한 도움이 되었습니다. 이 LSTM 기반 모델은 시간적 패턴뿐만 아니라 더 높은 레벨의 시간적 특징을 학습 한 다음, 미래의 데이터를 예측하기 위해 예측 단계에 사용됩니다. 예측 오차는 예측 인자에 의해 예측 된 결과와 실제 예상되는 값의 차이입니다. 오차 분포 추정 모델은 가우스 분포를 사용하여 관찰 스코어의 이상을 계산합니다. 이러한 방식으로, 우리는 하나의 비정상적 데이터의 개념에서 집단적인 비정상적 데이터 개념으로 바뀌어 갑니다. 이 작업은 실패를 최소화하고 제조품질을 향상시키는 Smart Factory의 모니터링 및 관리를 지원할 수 있습니다.