• Journal of Korea Game Society
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• v.18 no.2
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• pp.69-76
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• 2018

HMD makes big issues about virtual reality in these days. Experience of virtual reality may cause different effects with experience of real world, so this is the reason why comparison studies are needed. There are many works about usefulness of virtual reality education but most of studies were considered as special training. This study was started for the long term memory effect of virtual reality education game. Difference study of memory between real world education game and virtual reality education game shows virtual reality system has smaller diminution of memory than real world. And environment existence was defined as a main effect of long term memory through the test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2139-2151
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• 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 Research Journal of the Costume Culture
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• v.27 no.1
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• pp.1-10
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• 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.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.60-66
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• 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.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.3
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• pp.376-382
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• 2010

It has been shown that BF-7 enhances short- and long-term memory and attention in normal person. BF-7 was addressed to clinical study for children if BF-7 is also effective to children, since accumulated verification of safety and effectiveness is needed for young ages, in special. We administered BF-7 and a placebo control to two different groups of children (7-12 years old, 9.78 on averages). Their memory enhancement was tested with Rey-Kim Memory Test for Children before and after the administration of BF-7 and a placebo, in a double blinded way. The results showed that long- and short-term memories were significantly improved by the administration of BF-7. Interestingly, the degree of memory preservation, the ability of memory application and awareness of complex thing were also significantly improved. These results indicate that BF-7 is a promising substance from natural resource improving learning and memory of children as well as cognitive function of adults

• Korean Journal of Cognitive Science
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• v.11 no.3_4
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• pp.33-43
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• 2000

The distinction between short-term store (STS) and long-term store (LTS) has been made in the perspective of information processing. Memory system theorists have argued that memory could be conceived as multiple memory systems beyond the concept of a single LTS. Popular memory system models are Schacter & Tulving (994)'s multiple memory systems and Squire (987)'s the taxonomy of long-term memory. Those m models agree that amnesic patients have intact STS but impaired LTS and have preserved implicit memory. However. there is a debate about the nature of the long-term memory impairment. One model considers amnesic deficit as a selective episodic memory impairment. whereas the other sees the deficits as both episodic and semantic memory impairment. At present, it remains unclear that episodic memory should be distinguished from semantic memory in terms of retrieval operation. The distinction between declarative memory and nondeclarative memory would be the alternative way to reflect explicit memory and implicit memory. The research focused on the function of frontal lobe might give clues to the debate about the nature of LTS.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.497-506
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• 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.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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• pp.1-14
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• 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.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.137-142
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• 2020

Many studies based on I-vector have been conducted in a variety of environments, from text-dependent short-utterance to text-independent long-utterance. In this paper, we propose a speaker verification system employing a combination of I-vector with Probabilistic Linear Discriminant Analysis (PLDA) and speaker embedding of Long Short Term Memory (LSTM) with attention mechanism in far-field and noisy environments. The LSTM model's Equal Error Rate (EER) is 15.52 % and the Attention-LSTM model is 8.46 %, improving by 7.06 %. We show that the proposed method solves the problem of the existing extraction process which defines embedding as a heuristic. The EER of the I-vector/PLDA without combining is 6.18 % that shows the best performance. And combined with attention-LSTM based embedding is 2.57 % that is 3.61 % less than the baseline system, and which improves performance by 58.41 %.

• Journal of the Chungcheong Mathematical Society
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• v.34 no.2
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• pp.157-168
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• 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.