• 제목/요약/키워드: Long-Term Memory

검색결과 773건 처리시간 0.034초

가상현실교육게임의 장기기억효과 (The Long Term Memory Effects of Virtual Reality Edutainment with HMD)

  • 이대영;이승제;정의준
    • 한국게임학회 논문지
    • /
    • 제18권2호
    • /
    • pp.69-76
    • /
    • 2018
  • HMD의 대중적 도입으로 인해 가상현실에 대한 관심이 커지고 있다. 이런 가상현실에서의 활동은 현실과는 다른 효과들 가져올 것으로 예상되어 가상현실과 현실 간 비교 효과연구가 필요하다. 특히 가상현실에서의 교육적 효용성은 여러 연구에서 입증하고 있으나, 아직 특수교육의 경험적 맥락에 그치고 있다. 이 연구는 가상현실의 환경 안에서 교육게임콘텐츠의 기억 습득이 이루어 질 때 나타나는 장기기억효과에 대한 실증적 연구를 실시하였다. 가상현실이 아닌 e-러닝 조건과 가상현실조건 e-러닝 두 조건 내에서 학습기억실험을 실시하여 장기기억 감소율의 차이에 대한 평균차이를 검증한 결과 가상현실그룹에서 보다 낮은 기억감소율이 나타났다. 또한 배경의 유무에 따라 차이를 확인한 결과 가상환경배경이 제시된 경우에만 유의미한 차이가 나타나 가상현실의 가상환경이 장기기억의 중요한 요인임을 확인하였다.

Self-adaptive testing to determine sample size for flash memory solutions

  • Byun, Chul-Hoon;Jeon, Chang-Kyun;Lee, Taek;In, Hoh Peter
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제8권6호
    • /
    • pp.2139-2151
    • /
    • 2014
  • Embedded system testing, especially long-term reliability testing, of flash memory solutions such as embedded multi-media card, secure digital card and solid-state drive involves strategic decision making related to test sample size to achieve high test coverage. The test sample size is the number of flash memory devices used in a test. Earlier, there were physical limitations on the testing period and the number of test devices that could be used. Hence, decisions regarding the sample size depended on the experience of human testers owing to the absence of well-defined standards. Moreover, a lack of understanding of the importance of the sample size resulted in field defects due to unexpected user scenarios. In worst cases, users finally detected these defects after several years. In this paper, we propose that a large number of potential field defects can be detected if an adequately large test sample size is used to target weak features during long-term reliability testing of flash memory solutions. In general, a larger test sample size yields better results. However, owing to the limited availability of physical resources, there is a limit on the test sample size that can be used. In this paper, we address this problem by proposing a self-adaptive reliability testing scheme to decide the sample size for effective long-term reliability testing.

The adverse impact of personal protective equipment on firefighters' cognitive functioning

  • Park, Juyeon
    • 복식문화연구
    • /
    • 제27권1호
    • /
    • pp.1-10
    • /
    • 2019
  • Firefighters wear Personal Protective Equipment (PPE) for protection from environmental hazards. However, due to the layers of protective functions, the PPE inevitably adds excessive weight, bulkiness, and thermal stress to firefighters. This study investigated the adverse impact of wearing PPE as an occupational stressor on the firefighter's cognitive functioning. Twenty-three firefighters who had been involved in firefighting at least for 1 year were recruited. The overall changing trend in the firefighter's cognitive functioning (short-term memory, long-term memory, and inductive reasoning) was measured by the scores of three standardized cognitive tests at the baseline and the follow-up, after participating in a moderate-intensity physical activity, wearing a full ensemble of the PPE. The study findings evinced the negative impact of the PPE on the firefighter's cognitive functioning, especially in short-term memory and inductive reasoning. No significant influence was found on the firefighter's long-term memory. The results were consistent when the participant's age and BMI were controlled. The outcomes of the present study will not only fill the gap in the literature, but also provide critical justification to stakeholders, including governments, policymakers, academic communities, and industry, for such efforts to improve human factors of the firefighter's PPE by realizing the negative consequences of the added layers and protective functions on their occupational safety. Study limitations and future directions were also discussed.

Evaluation of the Effect of Educational Smartphone App for Nursing Students

  • Yeon, Seunguk;Seo, Sukyong
    • International Journal of Advanced Culture Technology
    • /
    • 제7권2호
    • /
    • pp.60-66
    • /
    • 2019
  • The purpose of this study was to compare the effect of educational smartphone app with the effect of learning using conventional paper material. We developed an educational app for nursing students to learn how to read blood pressure and how to take a pulse. Evaluated was the effect of the app-based education by measuring the short term memory (right after the education), the long term memory (a week later) and the satisfaction. 25 college nursing students participated for the experiment group using the app-based education and 25 for the control group using paper-based education. We applied for statistical analysis Fisher's exact test and Independent t-test. The satisfaction of the app user's appeared significantly higher than that of the paper material user's (t=2.322, p=0.024). The short term memory score was 0.23 points higher in the experimental group (6.46 points) than in the control group (6.23 points), which was not statistically significant (t =0.422, p =0.675). Similar result came for the long term memory (t=1.006, p=0.320). After adjusting for the effect of a college grade using ANCOVA, the effect on memory was significantly higher in the experiment group. There might be differences in learning ability between the experimental and the control groups.

천연 소재 BF-7의 어린이 장.단기 기억력 향상 효과 (The Improvement of Short- and Long-term Memory of Young Children by BF-7)

  • 김도희;김옥현;여주홍;이광길;박금덕;김대진;정윤희;김경용;이원복;윤영철;정윤화;이상형;현주석
    • 한국식품영양과학회지
    • /
    • 제39권3호
    • /
    • pp.376-382
    • /
    • 2010
  • 본 연구는 BF-7이 어린이의 장기 및 단기 기억을 현저하게 촉진시킴을 보여주었다. 기존 임상 시험 결과를 통해 입증된 바와 같이 천연 소재인 BF-7의 안전성을 고려할 때, BF-7은 어린이 장기 및 단기 기억력, 기억유지도 및 기억의 효과적 활용 등 전반적인 기억 수행 능력 향상에 도움을 주는 매우 안전하면서 효과가 탁월한 천연소재임을 확인하였다.

의미기억과 일화기억의 구분은 필요한가 (Is it necessary to distinguish semantic memory from episodic memory\ulcorner)

  • 이정모;박희경
    • 인지과학
    • /
    • 제11권3_4호
    • /
    • pp.33-43
    • /
    • 2000
  • 정보처리 이론은 기억을 단기기억과 장기기억으로 구분하였다. 기억체계 이론은 기억이 정보처리 이론에서 가정하는 하나의 장기기억이 아닌 중다기억 체계로 기억이 조직화되어 lT다고 주장한다. 대표적인 기억체계정보처리 이론은 기억을 단기기억과 장기기억으로 구분하였다. 기억체계 이론은 기억이 정보처리 이론에서 가정하는 하나의 장기기억이 아닌 중다기억 체계로 기억이 조직화되어 lT다고 주장한다. 대표적인 기억체계 이론으로는 Schacter와 Tulving 의 기억모형(1994)과 Squire 의 장기기억 분류 모형(1987)이 있다 두 모형은 단기기억과 장기기억의 구분, 기억장애에 보존된 암묵기억 수행에는 견해가 일치하지만, 기억장애가 일화기억만의 손상인지 아니면 의미기억을 포함하는지는 견해가 다르다. 그러나 현재의 자료로서는 일화기억과 의미기억의 구분이 더 정확한 설명인가 아니면 서술기억과 비서술기억의 구분이 더 나은 설명인가는 분명하지 않다. 전두엽에 대한 더 자세한 연구가 일화기억과 의미기억의구분과 관련되어 있다. 이론으로는 Schacter와 Tulving 의 기억모형(1994)과 Squire 의 장기기억 분류 모형(1987)이 있다 두 모형은 단기기억과 장기기억의 구분, 기억장애에 보존된 암묵기억 수행에는 견해가 일치하지만, 기억장애가 일화기억만의 손상인지 아니면 의미기억을 포함하는지는 견해가 다르다. 그러나 현재의 자료로서는 일화기억과 의미기억의 구분이 더 정확한 설명인가 아니면 서술기억과 비서술기억의 구분이 더 나은 설명인가는 분명하지 않다. 전두엽에 대한 더 자세한 연구가 일화기억과 의미기억의구분과 관련되어 있다.

  • PDF

The roles of differencing and dimension reduction in machine learning forecasting of employment level using the FRED big data

  • Choi, Ji-Eun;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
    • /
    • 제26권5호
    • /
    • pp.497-506
    • /
    • 2019
  • Forecasting the U.S. employment level is made using machine learning methods of the artificial neural network: deep neural network, long short term memory (LSTM), gated recurrent unit (GRU). We consider the big data of the federal reserve economic data among which 105 important macroeconomic variables chosen by McCracken and Ng (Journal of Business and Economic Statistics, 34, 574-589, 2016) are considered as predictors. We investigate the influence of the two statistical issues of the dimension reduction and time series differencing on the machine learning forecast. An out-of-sample forecast comparison shows that (LSTM, GRU) with differencing performs better than the autoregressive model and the dimension reduction improves long-term forecasts and some short-term forecasts.

기억의 신경심리학 (Neuropsychology of Memory)

  • 이민규
    • 수면정신생리
    • /
    • 제4권1호
    • /
    • pp.1-14
    • /
    • 1997
  • This paper reviewed models to explain memory and neuropsychological tests to assess memory. Memory was explained in cognitive and neuroanatomical perspectives, Cognitive model describes memory as structure and process. In structure model, memory is divided into three systems: sensory memory, short-term memory(working memory), and long-term memory. In process model, there are broadly three categories of memory process: encoding, storage, and retrieval. Memory process work in memory structure. There are two prominent models of the neuroanatomy of memory, derived from the work of Mishkin and Appenzeller and that of Squire and Zola-Morgan. These two models are the most useful for the clinician in part because they take into account the connections between the limbic and frontal cortical regions. The major difference between the two models concerns the role of the amygdala in memory processess. Mishkin and his colleagues believe that the amygdala plays a significant role while Squire and his colleagues do not. The most popular and widely used tests of memory ability such as WMS-R, AVLT, CVLT, HVLT. RBMT, CFT, and BVRT-R, were reviewed.

  • PDF

Attention-long short term memory 기반의 화자 임베딩과 I-vector를 결합한 원거리 및 잡음 환경에서의 화자 검증 알고리즘 (Speaker verification system combining attention-long short term memory based speaker embedding and I-vector in far-field and noisy environments)

  • 배아라;김우일
    • 한국음향학회지
    • /
    • 제39권2호
    • /
    • pp.137-142
    • /
    • 2020
  • 문장 종속 짧은 발화에서 문장 독립 긴 발화까지 다양한 환경에서 I-vector 특징에 기반을 둔 많은 연구가 수행되었다. 본 논문에서는 원거리 잡음 환경에서 녹음한 데이터에서 Probabilistic Linear Discriminant Analysis(PLDA)를 적용한 I-vector와 주의 집중 기법을 접목한 Long Short Term Memory(LSTM) 기반의 화자 임베딩을 추출하여 결합한 화자 검증 알고리즘을 소개한다. LSTM 모델의 Equal Error Rate(EER)이 15.52 %, Attention-LSTM 모델이 8.46 %로 7.06 % 성능이 향상되었다. 이로써 본 논문에서 제안한 기법이 임베딩을 휴리스틱 하게 정의하여 사용하는 기존 추출방법의 문제점을 해결할 수 있는 것을 확인하였다. PLDA를 적용한 I-vector의 EER이 6.18 %로 결합 전 가장 좋은 성능을 보였다. Attention-LSTM 기반 임베딩과 결합하였을 때 EER이 2.57 %로 기존보다 3.61 % 감소하여 상대적으로 58.41 % 성능이 향상되었다.

FORECASTING GOLD FUTURES PRICES CONSIDERING THE BENCHMARK INTEREST RATES

  • Lee, Donghui;Kim, Donghyun;Yoon, Ji-Hun
    • 충청수학회지
    • /
    • 제34권2호
    • /
    • pp.157-168
    • /
    • 2021
  • This study uses the benchmark interest rate of the Federal Open Market Committee (FOMC) to predict gold futures prices. For the predictions, we used the support vector machine (SVM) (a machine-learning model) and the long short-term memory (LSTM) deep-learning model. We found that the LSTM method is more accurate than the SVM method. Moreover, we applied the Boruta algorithm to demonstrate that the FOMC benchmark interest rates correlate with gold futures.