• Korean Journal of Cognitive Science
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• v.23 no.4
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• pp.487-515
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• 2012

The purpose of this study was to investigate the effect of the individual differences in cognitive processes on paragraph comprehension. To do so, the lexical decision task and the pattern comparison task were used to measure the low-level cognitive processes. Digit span task was used to test the phonological loop capacity. The individual differences of the central executive processing capacity were measured by operational span task. Reading span task was used to test the working memory capacity related with the sentence processing. Reading times and accuracies of the logically valid inferences and logically void inferences were tested to measure the high-level cognitive processes. Reading times and accuracies for the target sentences with and without prior explicit causal sentence were measured to test individuals' paragraph comprehension abilities. The results showed that the speed of the low-level cognitive processes was related with the speed of the high-level cognitive processes. Also, the accuracy of the low-level cognitive processes was related with the accuracy of the high-level cognitive processes while there was no significant correlation between the speed and the accuracy in any measures of the cognitive processes. Working memory capacity was related with the accuracy of the cognitive processes while it was not significantly correlated with the speed of the cognitive processes. Most importantly, the speed of low-level cognitive processes significantly affected the speed of the paragraph comprehension while the working memory capacity and the high-level cognitive processes had influences on the accuracies of the paragraph comprehension. The speed of the paragraph comprehension had no influence on the accuracies of the paragraph comprehension.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.797-806
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• 2005

The objective of the In-h(High Level Architecture) have recommended by DoD(Department of Defense) is to facilitate interoperability among simulations and to promote reuse of their components. There are many legacy simulation softwares developed before the HLA becomes simulation standard. The integration of legacy simulations into federations using the HLA is an important research topic in M&S(Modeling and Simulation) area. Legacy simulation softwares of the mission critical industry such as nuclear and aerospace are generally use Fortran language. However, the reuse of those is not easy because the HLA is not support Fortran language. This paper suggests a integration method which minimizes the modification of legacy simulation software and migrates the legacy simulation software to HLA federation. Each federate participating in federation have the separated executables that communicate via a shared memory created at run-time. Two types of shared memory blocks are used for publication and subscription. Declaration block for global variables used in legacy simulation software is separated for publication and subscription and then mapped as classes of objects and interactions for the HLA FOM design. To validate the suggested method, we approached the HLA integration of legacy nuclear simulation code being used in plant design and to observe the integration results, we used the FMT(Federation Management Tool). The diagnostic information which the FTM displays showed that our method can be successfully and effectively used for a HLA federation.

• Journal of agricultural medicine and community health
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• v.47 no.4
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• pp.242-254
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• 2022

Purpose: This study was designed to test structural equation modeling of the quality of life of elderly diagnosed dementia living in the community in order to provide guidelines for development of intervention and strategies to improve their quality of life. Methods: The participants in the study were elderly who visited the public health center in C rural between May 30 and september 15, 2017. Data collection was carried out through one-on-one interviews. Demographic factors, knowledge, Attitude, Self-Efficacy, social support, accessibility, request for Information, health practice, depression, subjective memory complaints, dependence scale and quality of life were investigated. Results: The final analysis included 192 elderly. Fitness of the hypothesis model was appropriate(χ²=192.89, p=.000, GFI=0.90, SRMR=0.08, NNFI=0.94, CFI=0.95, PNFI=0.72, RMSEA=0.07). Depression, subjective memory complaints and dependence were found to be significant explaining varience in quality of life. Social support, dementia preventive behavior and health practice had an indirect effect on the quality of life. Conclusions: To improve the quality of life of elderly diagnosed dementia living in the community, comprehensive interventions are necessary to manage knowledge, attitude, self-efficacy, social support, health practice, depression, subjective memory complaints and dependence that can contribute to enchance the quality of life of elderly diagnosed dementia living in the community.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1161-1164
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• 1998

We designed a DSP core simulator with C language, that is able to simulate 5-stage pipelined DSP core, named YS-DSP. It can emulate all 5 stage pipelines in the DSP core. It can also emulate memory access, exception processing, and DSP parallel processing. Each pipeline stage is implemented by combination of one or more functions to process parts of each stage. After modeling and validating the simulator, we can use it to verify and to complement the DSP core HDL model and to enhance its performance.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.325-328
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• 2002

In this paper, we present a SystemC model of a 32-Bit RISC core wi)ich is based on the ARMTTDMI architecture. The RISC core model was first modeled in C for architecture verification and then refined down to a level that allows concurrent behavior lot hardware timing using the SystcmC class library. It was driven in timed functional level that uses handshake protocol. It was compiled using standard C++ compiler. The functional simulation result was verified by comparing the contents of memory, the result of execution with the result from the ARMulator of ADS(Arm Developer Suite).

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.442-445
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• 1987

In this paper, a new ARMA spectrum estimation algorithm based on Circular Lattice filter is presented. Since APMA model is used in signal modeling, high-resolution spectrum can be obtained. And the computational burden is reduced by using Circular Lattice filter. By modifying the input estimation part of other proposed methods, we can get high-resolution spectrum with less computation and less memory compared with other Lattice methods. Some computer simulations are performed.

• Journal of the Semiconductor & Display Technology
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• v.3 no.3
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• pp.19-21
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• 2004

This paper presents a 3-dimensional diffusion simulation with adaptive solution strategy. The developed diffusion simulator VLSIDIF-3 was designed to re-refine areas. Refine scheme was calculated by the difference of doping concentration between any of two nodes. Each element is greater than tolerance and redo diffusion process until error is tolerable. Numerical experiment in low doping diffusion problem showed that this adaptive solution strategy is very efficient in both memory and time, and expected this scheme would be more powerful in complex diffusion model.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1485-1488
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• 1997

The capacity of memory chip has increased vert quickly and 64MDRAM becomes main product in semiconductor manufacturing lines consists of many sequential processes, including etching process. although it needs direct sensing of wafer state for the accurae detching, it depends on indirect esnsing and sample test because of the complexity of the plasma etching. This equipment receives the inner light of etch chamber through the viewport and convets it to the voltage inetnsity. In this paper, EDP voltage signal has a new role to detect etching failure. First, we gathered data(EPD sigal, etching time and etchrate) and then analyzed the relationships between the signal variatin and the etch rate using two neural network modeling. These methods enable to predict whether ething state is good or not per wafer. For experiments, it is used High Density Inductive coupled Plasma(HDICP) ethcing equipment. Experiments and results proved to be abled to determine the etching state of wafer on-line and analyze the causes by modeling and EPD signal data.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.47-53
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• 1999

CD-ROM(Compact Disk-Read Only Memory) is very attractive storage media because it has much storage space but is small size and portable. Optical pickup, one of the most important parts for reading data on a CD-ROM, is not produced tuned up. For the use of goods, we must tune up the optical pickup by adjusting the screw for adjustment. First, we developed analog servo system for optical pickup tuners. For eliminating some problems in analog servo system, this paper designed the modeling of digital servo system for optical pickup tuner. Though the characteristics of optical pickup are changed, the digital servo system for optical pickup tuner can easily apply to all pickup, and can reduce the measurement error among the optical pickup tuners. For the purpose of confirming the designed digital servo system, we produced data that specify the disk vibration and the disk eccentricity, and simulated servo system with MATLAB.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.111-124
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• 1999

This evapaper is toluate the forecasting performance of three neural network(NN) approaches against ARIMA model using the famous time series analysis competition data. The first NN approach is to analyze the second Makridakis (M2) Competition Data using Multilayer Perceptron (MLP) that has been the most popular NN model in time series analysis. Since it is recently known that MLP suffers from bias/variance dilemma, two approaches are suggested in this study. The second approach adopts Cascade Correlation Network (CCN) that was suggested by Fahlman & Lebiere as an alternative to MLP. In the third approach, a time series is separated into two series using Noise Filtering Network (NFN) that utilizes autoassociative memory function of neural network. The forecasts in the decomposition analysis are the sum of two prediction values obtained from modeling each decomposed series, respectively. Among the three NN approaches, Decomposition Analysis shows the best forecasting performance on the M2 Competition Data, and is expected to be a promising tool in analyzing socio-economic time series data because it reduces the effect of noise or outliers that is an impediment to modeling the time series generating process.