• Journal of Gastric Cancer
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• v.12 no.2
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• pp.81-87
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• 2012

Purpose: The aim of the present study was to assess the association between the pre-operative plasma fibrinogen level and the adjacent organ involvement in advanced gastric cancer. Materials and Methods: A total of 923 pre-operative plasma samples were obtained from 923 patients diagnosed clinically as having advanced gastric cancer, and fibrinogen levels were measured by immunoassay. Associations between fibrinogen levels and clinicopathologic findings (depth of tumor, adjacent organ involvement, and lymph node metastasis), along with survival were examined by univariate and multivariate analyses. Results: Tumor size, tumor depth, and the presence of lymph node metastasis were found to be positively correlated with the preoperative plasma fibrinogen levels (P<0.001). Fifty (5.4%) patients had adjacent organ involvement. Lymphatic invasion (P<0.001), tumor size (P<0.001), clinical T (depth of invasion) stage (P<0.001), and clinical nodal stage (P=0.018) were found to be associated with adjacent organ involvement. Univariate and multivariate regression analyses showed that a preoperatively elevated plasma fibrinogen level was associated with adjacent organ involvement (P<0.001, 0.028), and Kaplan-Meier analysis showed that it was associated with poorer survival (P<0.001). Conclusions: Plasma fibrinogen was found to be a clinically useful marker of adjacent organ involvement and overall survival. When a high fibrinogen level is encountered, preoperatively, adjacent organ involvement should be suspected in clinically advanced gastric cancer.

• 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.

• Structural Engineering and Mechanics
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• v.67 no.6
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• pp.629-641
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• 2018

The paper describes the development of a two-dimensional (2D) co-rotational nonlinear beam finite element that includes advanced path-following capabilities for detecting bifurcation instability in elasto-plasticity of steel elements subjected to fire without introducing imperfections. The advantage is twofold: i) no need to assume the magnitude of the imperfections and consequent reduction of the model complexity; ii) the presence of possible critical points is checked at each converged time step based on the actual load and stiffness distribution in the structure that is affected by the temperature field in the elements. In this way, the buckling modes at elevated temperature, that may be different from the ones at ambient temperature, can be properly taken into account. Moreover, an improved displacement predictor for estimating the displacement field allowed significant reduction of the computational cost. A co-rotational framework was exploited for describing the beam kinematic. In order to highlight the potential practical implications of the developed finite element, a parametric analysis was performed to investigate how the beam element compares both with the EN1993-1-2 buckling curve and with experimental tests on axially compressed steel members. Validation against experimental data and numerical outcomes obtained with commercial software is thoroughly described.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.562-567
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• 2002

Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.336-342
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• 2003

Noise predictive maximum likelihood(NPML) detector embeds noise prediction/whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This thesis random sequences are applied to linear channel. In perpendicular magnetic recording density KP=2.5, NP(121)ML and NP(1221)ML detection system which is based on a noise predictive PR-equalized signal are evaluated by the Performance through a computing simulation. Therefore, NPML systems are implemented and are verified by VHDL.

• Genomics & Informatics
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• v.5 no.4
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• pp.168-173
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• 2007

In previous nuclear genomic association studies, Random Forests (RF), one of several up-to-date machine learning methods, has been used successfully to generate evidence of association of genetic polymorphisms with diseases or other phenotypes. Compared with traditional statistical analytic methods, such as chi-square tests or logistic regression models, the RF method has advantages in handling large numbers of predictor variables and examining gene-gene interactions without a specific model. Here, we applied the RF method to find the association between mitochondrial single nucleotide polymorphisms (mtSNPs) and diabetes risk. The results from a chi-square test validated the usage of RF for association studies using mtDNA. Indexes of important variables such as the Gini index and mean decrease in accuracy index performed well compared with chi-square tests in favor of finding mtSNPs associated with a real disease example, type 2 diabetes.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.296-303
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• 2017

Background: To achieve a prolonged therapeutic effect in patients with lumbar facet joint syndrome, radiofrequency medial branch neurotomy (RF-MB) is commonly performed. The purpose of this study was to evaluate the prognostic value of paravertebral muscle twitching when performing RF-MB in patients with lumbar facet joint syndrome. Methods: We collected and analyzed data from 68 patients with confirmed facet joint syndrome. Sensory stimulation was performed at 50 Hz with a 0.5 V cut-off value. Patients were divided into 3 groups according to the twitching of the paravertebral muscle during 2 Hz motor stimulation: 'Complete', when twitching was observed at all needles; 'Partial', when twitching was present at 1 or 2 needles; and 'None', when no twitching was observed. The relationship between the long-term effects of RF-MB and paravertebral muscle twitching was analyzed. Results: The mean effect duration of RF-MB was 4.6, 5.8, and 7.0 months in the None, Partial, and Complete groups, respectively (P = 0.47). Although the mean effect duration of RF-MB did not increase significantly in proportion to the paravertebral muscle twitching, the Complete group had prolonged effect duration (> 6 months) than the None group in subgroup analysis. (P = 0.03). Conclusions: Paravertebral muscle twitching while performing lumbar RF-MB may be a reliable predictor of long-term efficacy when sensory provocation under 0.5 V is achieved. However, further investigation may be necessary for clarifying its clinical significance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.891-897
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• 2003

Partial response maxim likelihood (PRML) is a powerful and indispensable detection scheme for perpendicular magnetic recording channels. The performance of PRML can be improved by incorporating a noise prediction scheme into branch metric computations of Viterbi algorithm (VA). However, the systems constructed by VA have shortcomings in the form of high complexity and cost. In this connection, a new simple detection scheme is proposed by exploiting the minimum run-length parameter d=1 of RLL code. The proposed detection scheme have a slicer instead of Viterbi detector and a noise predictor as a feedback filter. Therefore, to improve BER performance, the proposed detection scheme is extended to dual detection scheme for improving the BER performance. Simulation results show that the proposed scheme has a comparable performance to noise-predictive maximum likelihood (NPML) detector with less complexity when the partial response (PR) target is (1,2,1).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.149-153
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• 1999

Prediction of rice developmental stage is necessary for proper crop management and a prerequisite for growth simulation as well. The objectives of the present study were to find out the relationship between the plastochrone index(PI) and the developmental index(DVI) estimated by non-parametric phenology model which simulates the duration from seedling emergence(DVI=0) to heading(DVI=l) by employing daily mean air temperature and daylength as predictor variables, and to confirm the correspondency of developmental indice to panicle developmental stages based on this relationship. Four japonica rice cultivars, Kwanakbyeo, Sangpungbyeo, Dongjinbyeo, and Palgumbyeo which range from very early to very late in maturity, were grown by sowing directly in dry paddy field five times at an interval of two weeks. Data for seedling emergence, leaf appearance, differentiation stage of primary rachis branch and heading were collected. The non-parametric phenology model predicted well the duration from seedling emergence to heading with errors of less than three days in all sowings and cultivars. PI was calculated for every leaf appearance and related to the developmental index estimated for corresponding PI. The stepwise polynomial analysis produced highly significant square-rooted cubic or biquadratic equations depending on cultivars, and highly significant square-rooted biquadratic equation for pooled data across cultivars without any considerable reduction in accuracy compared to that for each cultivar. To confirm the applicability of this equation in predicting the panicle developmental stage, DVI at differentiation stage of primary rachis branch primordium was calculated by substituting PI with 82 corresponding to this stage, and the duration reaching this DVI from seedling emergence was estimated. The estimated duration revealed a good agreement with that observed in all sowings and cultivars. The deviations between the estimated and the observed were not greater than three days, and significant difference in accuracy was not found for predicting this developmental stage between those equations derived for each cultivar and for pooled data across all cultivars tested.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.202-204
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• 2003

EISC ISA를 기반으로 한 64 비트 고성능 내장형 마이크로프로세서 AE64000의 효과적인 성능 향상을 위해서 비용 대비 성능 향상이 우수한 분기 예측 기법을 도입하여 AE64000 파이프라인에 적합한 분기 예측기를 추가로 설계하고 SPEClnt 벤치마크 및 타 내장형 벤치마크의 성능 분석 시뮬레이션을 통해 최적의 분기 예측기의 구조를 결정하였다. AE64000에서 LERI 명령 처리를 위해 AE64000 파이프라인에 추가된 독특한 IFU에 의하여 복잡성을 갖지만, IF 단계의 PC 대신에 IFU 단계의 PrePC를 이용하여 분기 명령을 명령어 prefetch 단계에서 예측함으로써, 올바른 분기 예측시 분기로 인한 손실을 제거할 수 있다. 결과적으로 최종 선정된 최적의 분기 예측기는 Verilog로 구현하여 AE64000 프로세서 코어 모델과 통합 합성하였고 아울러 추가되는 면적과 최종 목표 클럭에 동작하기 위한 타이밍 분석을 통해 최종 생산에 적합하도록 설계된 분기 예측기의 기능 및 타이밍 검증을 수행하였다. 최종 구현된 분기 예측기는 프로세서 칩 전체의 1% 미만의 비용으로 최고 12%의 성능 향상을 달성하여 성능 대비 면적의 효율성에서 높은 결과를 보였다.