• 한국음향학회지
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• 제42권3호
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• pp.262-269
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• 2023

본 논문에서는 선형 예측 분석을 기반으로 한 딱총새우 잡음 검출을 위한 특징을 제안한다. 딱총새우는 천해에 서식하는 종으로, 높은 진폭의 신호를 생성하고 빈번하게 발생하기 때문에 수중 잡음의 주된 원인 중 하나이다. 제안된 특징은 딱총새우 잡음이 갑작스럽게 발생하고 빠르게 소멸하는 특징을 활용하기 위해 선형 예측 분석을 이용하여 정확한 잡음 구간을 검출하고 딱총새우 잡음의 영향을 줄인다. 선형 예측 분석으로 예측한 값과 실제 측정값 사이의 오차가 크기 때문에 이를 통해 효과적으로 딱총새우 구간 검출이 가능해진다. 추가적으로 제안된 특징에 일정 오경보 확률 탐지기를 결합하여 잡음 구간 검출 성능을 추가적으로 개선한다. 제안한 방법을 딱총새우 잡음 구간 검출 최신 방법으로 알려진 다층 웨이블릿 패킷 분해와 비교한 결과, 제안한 방법이 수신자 조작 특성 곡선과 곡선 아래의 면적 측면에서 성능이 평균적으로 0.12만큼 우수하였고 계산량 측면에서도 계산 복잡도가 더 낮았다.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.297-306
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• 2018

Cardiovascular disease (CVD) is the leading cause of death worldwide and has a high mortality rate after onset; therefore, the CVD management requires the development of treatment plans and the prediction of prevalence rates. In our study, age, income, education level, marriage status, diabetes, and obesity were identified as risk factors for CVD. Using these 6 factors, we proposed a nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model for CVD. The attributes for each factor were assigned point values between -100 and 100 by Bayes' theorem, and the negative or positive attributes for CVD were represented to the values. Additionally, the prevalence rate can be calculated even in cases with some missing attribute values. A receiver operation characteristic (ROC) curve and calibration plot verified the nomogram. Consequently, when the attribute values for these risk factors are known, the prevalence rate for CVD can be predicted using the proposed nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model.

• Asian Pacific Journal of Cancer Prevention
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• 제14권3호
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• pp.1803-1806
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• 2013

Purpose: Carbohydrate antigen (CA) 242 is inversely related to prognosis in many cancers. However, few data regarding CA 242 in esophageal cancer (EC) are available. The aim of this study was to determine the prognostic value of CA 242 and propose an optimum cut-off point in predicting survival difference in patients with esophageal squamous cell carcinoma (ESCC). Methods: A retrospective analysis was conducted of 192 cases. A receiver operating characteristic (ROC) curve for survival prediction was plotted to verify the optimum cuf-off point. Univariate and multivariate analyses were performed to evaluate prognostic parameters for survival. Results: The positive rate for CA 242 was 7.3% (14/192). The ROC curve for survival prediction gave an optimum cut-off of 2.15 (U/ml). Patients with CA 242 ${\leq}$ 2.15 U/ml had significantly better 5-year survival than patients with CA 242 >2.15 U/ml (45.4% versus 22.6%; P=0.003). Multivariate analysis showed that differentiation (P=0.033), CA 242 (P=0.017), T grade (P=0.004) and N staging (P<0.001) were independent prognostic factors. Conclusions: Preoperative CA 242 is a predictive factor for long-term survival in ESCC, especially in nodal-negative patients. We conclude that 2.15 U/ml may be the optimum cuf-off point for CA 242 in predicting survival in ESCC.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2003년도 봄 학술발표회 논문집
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• pp.555-560
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• 2003

Fatigue strength of concrete is ususlly presented by the Wohler Curve. But, new dimension T(time) from the view point of cyclic creep concept should be considerd. This paper presented four variable F-N-T-R relationship, this four variable relationship simultaneously accounts for the time effect and the effect of load rate. And analytical models are presented to predict fatigue strength of R/C beam strengthened with steel plate and carbon fiber sheet. Also, the correlation between the ratio of stress and the fatigue life was investigated.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.369-384
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• 2021

In a personalized product recommendation system, when the amount of log data is large or sparse, the accuracy of model recommendation will be greatly affected. To solve this problem, a personalized product recommendation method using deep factorization machine (DeepFM) to analyze user behavior is proposed. Firstly, the K-means clustering algorithm is used to cluster the original log data from the perspective of similarity to reduce the data dimension. Then, through the DeepFM parameter sharing strategy, the relationship between low- and high-order feature combinations is learned from log data, and the click rate prediction model is constructed. Finally, based on the predicted click-through rate, products are recommended to users in sequence and fed back. The area under the curve (AUC) and Logloss of the proposed method are 0.8834 and 0.0253, respectively, on the Criteo dataset, and 0.7836 and 0.0348 on the KDD2012 Cup dataset, respectively. Compared with other newer recommendation methods, the proposed method can achieve better recommendation effect.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.172-175
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• 2009

The purpose of this study is to predict the forming limit diagram (FLD) of strain-rate sensitive materials on the basis of the Marciniak and Kuczynski (M-K) theory. The strain-rate effect is taken into consideration in such a way that the stress-strain curves for various strain-rates are inputted into the formulation as point data, not as curve-fitted models such as power function. To solve the nonlinear system of equations derived from the equilibrium and constraints in the groove region and the safe zone, the Newton-Raphson method is used. The theoretical FLDs using four different yield criteria, that are von Mises, Hill (1948), Hill (1979), Logan and Hosford, are compared with the experimental, numerical (FEA) and other theoretical results. A new trial is made where a modified M-K model having n-step grooves is introduced to describe a real localized neck.

• 전기학회논문지
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• 제61권12호
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• pp.1836-1842
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• 2012

Torque is proportional to the rate of change of inductance in a switched reluctance motor (SRM), and hence, phase inductance is an important parameter in determining the behavior of an SRM. Therefore, the accurate prediction of inductance with respect to rotor position makes a significant contribution to designing an SRM and its analytical approach is not straightforward due to nonlinear flux distribution. Although several different approaches using a finite element analysis (FEA) or curve-fitting tool have been employed to compute phase inductance [2-5], they are not suitable for a simple design procedure because the FEA necessitates a large amount of time in both modeling and solving with complexity for every motor design, and the curve-fitting requires the data of flux linkage from either an experimental test or an FEA simulation. In this paper, phase inductance is predicted by means of a permeance method, and the proposed approach is analytically verified in terms of the accuracy of estimated inductance compared to inductance obtained by FEA.

• Journal of Mechanical Science and Technology
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• 제20권8호
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• pp.1209-1216
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• 2006

An AZ31 magnesium alloy was tested at constant temperatures ranging from 423 to 473 K (0.46 to 0.51 Tm) under constant stresses. All of the creep curves exhibited two types depending on stress levels. At low stress (${\sigma}/ G < 4 {\times}10^{-3}$), the creep curve was typical of class A (Alloy type) behavior. However, at high stresses (${\sigma}/ G > 4 {\times}10^{-3}$), the creep curve was typical of class M (Metal type) behavior. At low stress level, the stress exponent for the steady-state creep rate was of 3.5 and the true activation energy for creep was 101 kJ/mole which is close to that for solute diffusion. It indicates that the dominant deformation mechanism was glide-controlled dislocation creep. At low stress level where n=3.5, the present results are in good agreement with the prediction of Fridel model.

• International Journal of Advanced Culture Technology
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• 제7권1호
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• pp.8-13
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• 2019

Despite technical advances in healthcare, the rates of hospital-acquired pressure injury (HAPI) are still high although many are potentially preventable. The purpose of this study was to determine whether tree-based prediction modeling is suitable for assessing the risk of HAPI in ICU patients. Retrospective cohort study has been carried out. A decision tree model was constructed with Age, Weight, eTube, diabetes, Braden score, Isolation, and Number of comorbid conditions as decision nodes. We used RStudio for model training and testing. Correct prediction rate of the final prediction model was 92.4 and the Area Under the ROC curve (AUC) was 0.699, which means there is about 70% chance that the model is able to distinguish between HAPI and non-HAPI. The results of this study has limited generalizability as the data were from a single academic institution. Our research finding shows that the data-driven tree-based prediction modeling may potentially support ICU sensitive risk assessment for HAPI prevention.

• 소성∙가공
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• 제8권6호
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• pp.576-582
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• 1999

The high temperature behavior of Al 6061 alloy was characterized by the hot torsion test in the temperature ranges of 400∼550℃ and the strain rate ranges of 0.05∼5/sec. To decide optimum deformation condition, three types of deformation maps were individually made from the critical strain (εc). deformation resistance(σp) and deformation efficiency (η). The critical strain(εc) for dynamic recrystallization (DRX) which was decided from the inflection point of strain hardening rate(θ) - effective stress (σ) curve was about 0.65 times of peak strain (εp). The relationship among deformation resistance (peak stress, σp), strain rate (ε), and temperature (T) could be expressed by ε=2.9×1013[sinh(0.0256σp]7.3exp (-216,000/RT). The deformation efficiency (η)which was calculated on the basis of the dynamic materials model (DMM) showed high values at the condition of 500∼550℃, 5/sec for 100% strain. The results from three deformation maps were compared with microstructures. The best condition of plastic deformation could be determined as 500℃ and 5/sec.