• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.

• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.101-127
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• 2016

The present study was conducted to examine the effect of meta-cognitive strategy and transfer appropriate processing(TAP) on prospective memory performance. In two experiments, encoding strategy for PM target words was manipulated by instructions. Participants who were assigned to meta strategic condition were engaged to rate task difficulty(EOL) in addition to predict their own performance(JOL), while participants in cognitive strategy condition were to remember target words by pleasantness ratings and sentence generation. In experiment1 and experiment 2, all participants in both conditions performed not only TAP ongoing task but also TIP ongoing task. Results revealed the benefit of meta cognition and transfer appropriate processing on PM performance. Furthermore, the benefit of TAP was diminished in cognitive strategy condition. There were no-costs on judgement tasks across conditions. The findings suggest that meta-cognition allows to sustain PM targets and intention without regard to cognitive resource.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.359-373
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• 2015

Cognitive reserve(CR) is the ability to optimize or maximize performance through complementary brain networks. CR is relevant to normal aging in cognitive-linguistic abilities. There are few domestic systematic reviews or meta-analyses that analyze the relationships between multiple CR and cognitive-linguistic domains in healthy older people. This meta-analysis included 32 studies published since 2000. In result, education level topped the list, followed by the occupation, cognitively stimulating activities, and the multilingualism. Most studies were related to memory, global cognition, and language. CR had a modest positive association with cognitive-linguistic performance. Multiple domains including memory and language also showed the significant correlations across most measures of CR. This study provides evidence-based information to support cognitive-linguistic ability in normal aging.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.854-860
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• 2009

Ubiquitous is a new computing environment with IT technology and information communication, and appling various equipments likes PDA and application parts. Recently, user's using environment is changing to smart phone and is expanded learning tools to learner without educational environment. Thus, in this paper, we designed SCORM based meta-data to use smart phone. For this purpose, we made U-learning server and smart phone process server that is to handling with existence LMS and SCORM. To apply smart phones characteristics that have different ones each other, meta-data was able to have some resource information as like CPU, screen size and memory. The meta-data adapter could be process the characteristics.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1204-1208
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• 2010

In this paper, we propose a flash memory wear-leveling scheme that makes use of meta-data storage region as a regulation pool. By concentrating program and erase operations on the blocks with lower erase counts in the regulation pool, the proposed scheme achieve an even wear-leveling in a simple and efficient way. Experiments with an implementation of the proposed scheme in RS-FTL showed that the erase count deviation is reduced by around 40% through the erase count regulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.58-65
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• 2021

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• The Korean Journal of Rehabilitation Nursing
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• v.5 no.2
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• pp.205-216
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• 2002

This quasi-experimental study was done to test the effects of meta-memory enhancing program for elderly women. Data were collected 12 to 30, August 2002 from 34elderly women over 65 years living in Busan city. Subjects were 15 of experimental group and 19 of control group. The metamemory enhancing program was developed by five sessions composing of 1.5-2.0 hours one session. In experiment group, this program was performed for three weeks, twice per week. The degrees of four memory performance tasks were measured using instrument of Elderly Verbal Learning Test(Choi Kyung Mi, 1988) and Face Recognition Instrument(Min Hye Sook, 1999) and the metamemory were measured using MIA questionnaire(Dixon et al., 1988). Research results are as following. 1. After participating in five times memory training programs, experimental group has the significant increase of metamemory in comparison with control group.(t=59.58, p< 0.0001). In particular, the concepts of strategy(t=20.44, p< 0.0001), achievement (t=21.94, p< 0.0001), and locus degree (t=59.58, p< 0.0001) among sub-concepts of the metamemory are increasing significantly. 2. After participating in five time memory training programs, the degree of immediate word recall(t=17.25, p< 0.0001) and face recognition(t=16.69, p< 0.0001) among four memory tasks in experimental group are increasing significantly compared with those measures of control group. Considering this results, this metamemory enhancing program was found as an effective nursing program for metamemory improvement of elderly women's memory.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.292-299
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• 2010

Recently, as flash memory is used as digital storage devices, necessity for digital forensics is growing in a flash memory area for digital evidence analysis. For this purpose, it is important to recover crashed files stored on flash memory efficiently. However, it is inefficient to apply the hard disk based file recovery techniques to flash memory, since hard disk and flash memory have different characteristics, especially flash memory being unable to in-place update. In this paper, we propose a flash-aware file recovery technique for digital forensics. First, we propose an efficient search technique to find all crashed files. This uses meta-data maintained by FTL(Flash Translation Layer) which is responsible for write operation in flash memory. Second, we advise an efficient recovery technique to recover a crashed file which uses data location information of the mapping table in FTL. Through diverse experiments, we show that our file recovery technique outperforms the hard disk based technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1073-1083
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• 2015

As an empirical study focused on how transactive memory concept influence the four processes of knowledge growth, this study aimed at explaining the function of transactive memory in the dynamic process of knowledge growth. To verify the research model, this study carried out a path analysis of 130 team memebers and as a result, part of the team transactive memory measurements does affect the knowledge growth. Consequentially, transactive memory especially based on team level, is relevant with knowledge growth. According to team level, this study targeted at the team members, and by adopting the team transactive memory concept in Cognitive Psycology, theoretically explained and analysed how to approach personal knowledge in internal organizations. To accelerate the knowledge process, the work should be modified collaboratively by trusting the team members' duty relations more than specialized knowledge. Furthermore, managers had better assign team members the work where they can make the most of their personal knowledge, and this study presented that the whole team performance could be improved by doing that.