• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.621-626
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• 2009

This paper presents a multiple branch predictor using perceptrons. The key idea is to apply neural networks to the multiple branch predictor. We describe our design and evaluate it with the SPEC 2000 integer benchmarks. Our predictor achieves increased accuracy than the Bi-Mode and the YAGS multiple branch predictor with the same hardware cost.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.803-804
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• 2006

This paper presents a multiple branch predictor with perceptrons. We describe our design and evaluate it with the SPEC 2000 benchmarks. Our predictor achieves increased accuracy than the previous multiple branch predictors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1443-1449
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• 2009

This paper presents a profiling model of a wide-window superscalar microprocessor using multiple branch prediction. The key idea is to apply statistical profiling technique to the superscalar microprocessor with a wide instruction window and a multiple branch predictor. The statistical profiling data are used to obtain a synthetical instruction trace, and the consecutive multiple branch prediction rates are utilized for running trace-driven simulation on the synthesized instruction trace. We describe our design and evaluate it with the SPEC 2000 integer benchmarks. Our performance model can achieve accuracy of 8.5 % on the average.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.5
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• pp.297-305
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• 2006

Trace-driven simulation is widely used for measuring the performance of a microprocessor in its initial design phase. However, since it requires much time and disk space, the statistical simulation has been studied as an alternative method. In this paper, statistical simulations are performed for a high performance superscalar microprocessor with a perceptron-based multiple branch predictor. For the verification, various hardware configurations are simulated using SPEC2000 benchmarks programs as input. As a result, we show that the statistical simulation is quite accurate and time saving for the evaluation of microprocessor architectures with multiple branch prediction.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.49-56
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• 2012

Objective: This study was an attempt to identify associations between health behavior, such as smoking, alcohol consumption, healthy diet, and physical activity, and psychosocial factors. Methods: This crosssectional study was conducted among 1,500 participants aged between 30 and 69 years, selected from a population-based database in October 2009 through multiple-stratified random sampling. Information was collected about the participants' smoking and drinking habits, dietary behavior, level of physical activity, stress, coping strategies, impulsiveness, personality, social support, sense of coherence, self-efficacy, health communication, and sociodemographics. Results: Agreeableness, as a personality trait, was negatively associated with smoking and a healthy diet, while extraversion was positively associated with drinking. The tendency to consume a healthy diet decreased in individuals with perceived higher stress, whereas it increased in individuals who had access to greater social support. Self-efficacy was found to be a strong predictor of all health behaviors. Provider-patient communication and physical environment were important factors in promoting positive healthy behavior, such as consumption of a healthy diet and taking regular exercise. Conclusions: Psychosocial factors influence individuals' smoking and drinking habits, dietary intake, and exercise patterns.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.4
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• pp.67-74
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• 2020

PURPOSE: The progression of the center of pressure (COP) velocity of the stance phase may have important roles for predicting gait speed in older adults with cognitive decline. This study was conducted to identify the correlation between gait speed and the velocity of COP progression during the stance phase in older adults with cognitive decline. METHODS: Forty adults aged 65 years or older (twenty participants without cognitive decline, 20 participants with cognitive decline) were recruited. The COP progression velocity was measured using an F-scan pressure-sensitive insole system. The stance phase was divided into four sub-stages. (loading response, mid-stance, terminal stance, and pre-swing). Gait speed, double support phase, and cadence were also measured. Correlations and multiple regression analyses were performed. RESULTS: Gait speed was associated with the COP progression velocity in midstance (r = .719, p < .05), cadence (r = .719, p < .05) and the COP progression velocity in loading response velocity (r = .515, p < .05) in older adults with cognitive decline. However, no correlation was found in older adults without cognitive decline. In multiple regression analysis using gait speed as a dependent variable, the COP progression velocity in midstance and cadence were significant predictors of gait speed, with the COP progression velocity being the most significant predictor. CONCLUSION: The COP progression velocity is an important factor for predicting gait speed in older adults with cognitive decline, suggesting that the cognitive function influences gait speed and the velocity of COP progression.

• Korean Circulation Journal
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• v.48 no.11
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• pp.1002-1011
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• 2018

Background and Objectives: The prognostic impact of left axis deviation (LAD) on clinical outcomes in acute heart failure syndrome (AHFS) with left bundle branch block (LBBB) is unknown. The aim of this study was to determine the prognostic significance of axis deviation in acute heart failure patients with LBBB. Methods: Between March 2011 and February 2014, 292 consecutive AHFS patients with LBBB were recruited from 10 tertiary university hospitals. They were divided into groups with no LAD (n=189) or with LAD (n=103) groups according to QRS axis <-30 degree. The primary outcome was all-cause mortality. Results: The median follow-up duration was 24 months. On multivariate analysis, the rate of all-cause death did not significantly differ between the normal axis and LAD groups (39.7% vs. 46.6%, adjusted hazard ratio, 1.01; 95% confidence interval, 0.66, 1.53; p=0.97). However, on the multiple linear regression analysis to evaluate the predictors of the left ventricular ejection fraction (LVEF), presence of LAD significantly predicted a worse LVEF (adjusted beta, -3.25; 95% confidence interval, -5.82, -0.67; p=0.01). Right ventricle (RV) dilatation was defined as at least 2 of 3 electrocardiographic criteria (late R in lead aVR, low voltages in limb leads, and R/S ratio <1 in lead V5) and was more frequent in the LAD group than in the normal axis group (p<0.001). Conclusions: Among the AHFS with LBBB patients, LAD did not predict mortality, but it could be used as a significant predictor of worse LVEF and RV dilatation (Trial registry at KorAHF registry, ClinicalTrial.gov, NCT01389843).