• 대한치매학회지
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• 제23권3호
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• pp.117-126
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• 2024

Background and Purpose: The Korean-Mini Mental State Examination, 2nd edition (K-MMSE~2) was recently released. This study aimed to determine whether the K-MMSE~2: Standard Version (K-MMSE~2:SV) had the same test characteristics as the K-MMSE. Methods: A total of 1,514 healthy community-based participants aged 19 to 90 years were administered the K-MMSE~2:SV Blue Form along with the language items from the K-MMSE. The item and test characteristics and test information for the K-MMSE~2:SV and K-MMSE were compared using Item Response Theory analysis. Results: Item discriminations for the K-MMSE~2:SV and K-MMSE were above the moderate range for all items except Recall. Most of the items on the K-MMSE~2:SV and K-MMSE had item category difficulty in the very easy or easy range. The test information curve (TIC) showed that the K-MMSE~2:SV and K-MMSE provide almost the same amount of information (27.86 vs. 28.44), with both tests providing the most information at an ability level of -1.57. The generalizability (G) coefficient for the K-MMSE~2:SV and K-MMSE was 0.99. Conclusions: These results indicate that the K-MMSE~2:SV and K-MMSE are equally optimal tests for screening for mild cognitive impairment and early dementia. Given that the amount of test information provided by the two tests was almost identical, the shapes of the TICs were very similar, and the G coefficient was close to 1, we can conclude that the K-MMSE and K-MMSE~2:SV are equivalent tests.

• 재활간호학회지
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• 제7권2호
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• pp.179-187
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• 2004

Purpose: This study was performed to assess the degree of cognitive function of elderly by MMSE-K performances and of that effect. Method: The subjects were 185 aged over 65 in Daejeon Metropolitan city. Data were collected through personal interview using the questionnaire from 10 to 31, Jan. 2003. The measures were Korean version of Mini-Mental State Examination(MMSE-K). Results: The mean score of MMSE-K was $22.60{\pm}5.39$. The prevalence of cognitive impairment was estimated as 48.6% by MMSE-K ${\leq}23$ and significantly age, gender, and education effect. The subtype score of MMSE-K were significantly lower in female group in each items : orientation in time and place, attention/calculation, language except registration and recall. And the scores were significantly lower in the older group and non-educated group in the all items of MMSE-K. Conclusion: Gender, age, and education showed significant effects on total and subtype MMSE-K score. Cognitive function decline were higher in female, older age group, and non-educated group. Therefore, those three factors are thought to be one of important risk factors for development of dementia, also it is assumed to be affected by other variables than age, gender, education effect.

• 생물정신의학
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• 제12권2호
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• pp.98-106
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• 2005

Objectives:Donepezil is a widely used drug for the treatment of patients with Alzheimer's disease(AD). The aim of the present study was to clarify the efficacy and the characteristics of responders to donepezil. Methods:Patients with probable AD(n=80;75.7 years) and small vessel dementia(SVD)(n=18;77.8 years) who received donepezil were retrospectively analyzed using Alzheimer's registry, and three questions were asked:1) Does donepezil therapy improves cognitive symptoms in patients with dementia? 2) If donepezil improves cognitive symptoms, which items of the K-MMSE are improved? 3) What are the characteristics of responder to donepezil medication? Results:1) After donepezil medication, cognitive function measured by the K-MMSE was significantly improved in both types of dementia(AD and SVD), However, statistical differences were not found between these groups. 2) In a clinical trial of donepezil, the patients performed better than before mediation on K-MMSE items assessing orientation, recall, construction, concentration, calculation. 3) In AD, the K-MMSE score before medication was closely related with response of donepezil. Conclusion:This study suggests that donepezil improves various cognitive functions in both types of dementia, and the responsive group had significantly lower K-MMSE scores than the non-responsive group before medication.

• 대한치매학회지
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• 제22권2호
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• pp.69-77
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• 2023

Background and Purpose: The Montreal Cognitive Assessment (MoCA) has been known as a screening test for detecting mild cognitive impairment (MCI) better than Mini-Mental State Examination (MMSE). However, in previous domestic studies, no significant difference was found in the discriminability between MoCA and MMSE. Researchers have suggested that this might be because older Koreans are less educated than older Westerners. This study was conducted to examine the effect of education on the discriminability of MoCA compared to the MMSE. Methods: Participants were 123 cognitively normal elderly, 118 with vascular MCI, 108 with amnestic MCI, 121 with vascular dementia, and 113 with dementia of the Alzheimer's type. The Korean-MoCA (K-MoCA) and Korean-MMSE (K-MMSE) were administered. Multiple regression analyses and receiver operating characteristic (ROC) curve analyses were performed. Results: In all participants, education significantly affected both K-MoCA and K-MMSE scores along with age. The effect of education was re-examined by subgroup analysis after dividing subjects according to the level of education. Effect of education on K-MoCA and K-MMSE was only shown in the group with <9 years of education. ROC curve analyses revealed that the discriminability of K-MoCA to differentiate between vascular MCI and normal elderly was significantly higher than that of K-MMSE. When re-examining subgroups divided by education level, however, this higher discriminability of K-MoCA disappeared in the group with <9 years of education. Conclusions: These results indicate no difference in discriminating cognitive deficits between K-MoCA and K-MMSE in Korean elderly with <9 years of education.

• 한국항행학회논문지
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• 제15권3호
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• pp.392-404
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• 2011

본 논문에서는 최근 4세대 이동통신에서 논의 되고 있는 기술인 셀 간 협력 통신이 가능한 다중 셀 환경에서 상향링크에서의 다중 사용자 신호 검출기술에 대해서 다루었다. 먼저 기존 검출 기술로 ML, ZF, MMSE 그리고 SIC 등을 다루었고, 보통 ML은 최적의 성능을 보이지만, 복잡도가 지수적으로 증가하며, ZF나 MMSE는 간단하지만 성능이 떨어지며, SIC는 복잡하고 오류전파 현상이 발행 할 수 있는 문제점을 가지고 있다. 이에 기존의 ZF/MMSE 에 비해서는 성능 개선이 이루어지면서, 복잡도를 유지 또는 감소시킬 수 있는 구조 제안을 위해서 ZF/MMSE 방식과 ML 의 적용구조를 단순화 시킨 부분 ML 복호 방식을 결합한 검출 방식을 제안하였다. 모의실험 결과, 제안방식은 ZF/MMSE 기반의 SIC 방식에 비해 BER 성능이 개선 또는 유지 되었으며, 복잡도 측면에서 감소하는 효과를 보였으며, 또한 복잡도 감소는 협력 기지국 및 안테나 수가 증가할수록 더 감소 효과가 커질 수 있음을 알 수 있었다.

• 한국통신학회논문지
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• 제39A권9호
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• pp.566-568
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• 2014

본 논문에서는 대규모 MIMO 시스템을 위한 MMSE 기반 반복 연판정 간섭 제거 기법을 제안한다. 제안 기법은 기존 기법에서의 연산량 감소를 위해 Sherman-Morrison-Woodbury 식을 사용하여 매 Iteration 마다 단 한 번의 역행렬 계산으로 모든 송신 심볼의 MMSE 검출 벡터를 계산한다. 모의실험을 통해 제안 기법이 대규모 MIMO 시스템에서 기존 기법과 거의 동일한 BER을 달성함을 확인하였다.

• 한국치위생학회지
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• 제16권2호
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• pp.295-301
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• 2016

Objectives: The purpose of the study was to investigate the association between denture wearing and dementia using a Mini-Mental State Examination (MMSE-K) in the community dwelling elderly. Methods: The study subjects were 184 community dwelling elderly using Korean version of mini-mental state examination(MMSE-K). The variables included the general characteristics of the subjects, denture earing, number of mastication tooth, subjective mastication ability, and MMSE(dementia). Denture wearing was divided into two groups of the natural dentition including the fixed prosthesis and removable denture including the complete and/or partial denture. The data were analyzed by ${\chi}^2$ test, t-test, and binary logistic regression using SPSS version 22.0 program. Logistic regression was used to analyze the association of MMSE-K score and denture wearing, and 95% confidence interval was calculated. The subjective mastication ability was measured by Likert 5 points scale. Dementia was measured by MMSE-K. Results: There was a significant association between MMSE-K score and denture wearing. The odds ratio(OR) of denture waering was 6.01(95% CI: 2.824-12.784). After adjusting the age, gender, residence and education, OR was 5.53(95% CI: 2.364-12.935). Conclusions: This study showed a significant association between MMSE-K score and denture wearing in the Korean elderly.

• 전자공학회논문지C
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• 제36C권6호
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• pp.44-51
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• 1999

HMM-Net은 은닉 마르코프 모델(HMM)의 계산과정을 신경망 구조로 구현한 것으로, HMM이 갖고 있는 시계열 모델링 능력과 신경망이 갖고 있는 우수한 변별력을 결합한 것이다. HMM-Net 분류기를 학습하는 방법으로는 HMM의 학습에 이용되는 最尤法(ML)과 신경망 학습의 最小二乘誤差法(MMSE)를 적용할 수 있다. 이들 중 ML이 MMSE보다 안정된 학습을 보장하는 반면 초기 학습조건을 적절하게 설정하였을 경우에는 MMSE가 ML보다 우수하다고 알려져 있다[3]. 따라서 이 논문에서는 먼저 ML을 이용하여 초기학습을 수행한 다음 보다 학습성능이 우수한 MMSE로 바꾸어 최적 또는 준최적으로 학습하는 하이브리드 학습법(ML/MMSE)을 제안한다. 실험용 시계열 패턴으로 /0/부터 /9/까지의 고립 숫자음을 이용하여 실험한 결과, 제안한 방법이 학습특성 및 인식률면에서 ML이나 MMSE만을 이용하는 기존의 방법보다 우수하였음을 확인하였다.

• 한국산학기술학회논문지
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• 제13권12호
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• pp.5976-5985
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• 2012

본 연구는 장기요양서비스의 질 제고를 위해 장기요양서비스 이용 노인들의 신체적 및 정신적 기능 상태를 평가해 보고, 그에 영향을 미치는 관련 요인을 규명하고자 시도하였다. 조사대상은 대전지역에 거주하는 65세 이상 노인 중 장기요양서비스 이용자 350명(재가급여 178명, 시설급여 172명)으로 하였으며, 자료 수집은 2011년 2월 16일부터 3월 31일까지의 기간 동안에 표준화된 무기명식 면접조사용 설문지를 사용하여 면접조사를 통해 이루어졌다. 연구결과, 재가급여 노인의 IADL과 MMSE-K는 시설급여 노인보다 유의하게 높았으나 ADL과 CES-D는 유의한 차이를 보이지 않았다. ADL, IADL, CES-D 및 MMSE-K 상호 간의 상관관계를 보면, 재가 및 시설급여 이용노인 모두 ADL은 IADL 및 MMSE-K와 양의 상관관계를 보인 반면, CES-D와는 음의 상관관계를 나타내었다. IADL은 MMSE-K와 양의 상관관계를 보인 반면, CES-D와는 음의 상관관계를 나타내었다. 다중회귀분석 결과 재가 및 시설 급여 이용 노인 모두 ADL과 IADL에 유의하게 영향을 미치는 변수로는 건망증 증상 유무, 규칙적 운동 및 MMSE-K가 선정되었다. 또한 CES-D와 MMSE-K는 주관적 건강상태, 건망증 증상 유무 및 IADL이 유의하게 영향을 주는 것으로 나타났다. 이상과 같은 결과는 장기요양서비스 이용 노인들의 신체적 및 정신적 기능은 개인의 건강상태나 건강관련행위 특성과 밀접한 관련성이 있음을 시사하고 있다.

• IEIE Transactions on Smart Processing and Computing
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• 제3권1호
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• pp.35-39
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• 2014

This paper proposes a Modified Minimum Mean Square Error (M-MMSE) estimator for an Orthogonal Frequency Division Multiplexing (OFDM) System over fast fading Rayleigh channel. The proposed M-MMSE estimator considered the effects of the efficient placement of pilots based on the channel energy distribution. The pilot symbols were placed in a non-linear manner according to the density of the channel energy. Comparative analysis of the MMSE estimator for a comb-type pilot arrangement and M-MMSE estimator for the proposed pilot insertion scheme revealed significant performance improvement of the M-MMSE estimator over the MMSE estimator.