• Asian Pacific Journal of Cancer Prevention
• /
• 제15권15호
• /
• pp.6181-6186
• /
• 2014

This meta-analysis was conducted to examine whether the genotype status of Val158Met polymorphism in catechol-O-methyltransferase (COMT) is associated with endometrial and ovarian cancer risk. Eligible studies were identified by searching several databases for relevant reports published before January 1, 2014. Pooled odds ratios (ORs) were appropriately derived from fixed-effects or random-effects models. In total, 15 studies (1,293 cases and 2,647 controls for ovarian cancer and 2,174 cases and 2,699 controls for endometrial cancer) were included in the present meta-analysis. When all studies were pooled into the meta-analysis, there was no evidence for significant association between COMT Val158Met polymorphism and ovarian cancer risk (Val/Met versus Val/Val: OR=0.91, 95% CI=0.76-1.08; Met/Met versus Val/Val: OR=0.90, 95% CI=0.73-1.10; dominant model: OR=0.90, 95% CI=0.77-1.06; recessive model: OR=0.95, 95% CI=0.80-1.13). Similarly, no associations were found in all comparisons for endometrial cancer (Val/Met versus Val/Val: OR 0.97, 95% CI=0.77-1.21; Met/Met versus Val/Val: OR=1.02, 95% CI=0.73-1.42; dominant model: OR=0.98, 95% CI=0.77-1.25; recessive model: OR=1.02, 95% CI=0.87-1.20). In the subgroup analyses by source of control and ethnicity, no significant associations were found in any subgroup of population. This meta-analysis strongly suggests that COMT Val158Met polymorphism is not associated with increased endometrial and ovarian cancer risk.

• Asian Pacific Journal of Cancer Prevention
• /
• 제13권5호
• /
• pp.2249-2252
• /
• 2012

Objective: Methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms have been reported to be associated with pancreatic cancer, but the published studies had yielded inconsistent results.We therefore performed the present meta-analysis. Methods: A search of Google scholar, PubMed, Cochrane Library and CNKI databases before April 2012 was conducted to summarize associations of MTHFR polymorphisms with pancreatic cancer risk. Assessment was with odds ratios (ORs) and 95% confidence intervals (CIs). Publication bias were also calculated. Results: Four relative studies on MTHFR gene polymorphisms (C667T and A1298C) were involved in this meta-analysis. Overall, C667T(TT vs. CC : OR = 1.61, 95%CI = 0.78 - 3.34; TT vs. CT : OR = 1.41, 95%CI = 0.88-2.25; dominant model: OR = 0.68, 95%CI = 0.40-1.17; recessive model: OR = 0.82, 95%CI = 0.52-1.30) and A1298C(CC vs. AA:OR=1.01, 95%CI=0.47-2.17; CC vs. AC: OR=0.99,95%CI=0.46-2.14; dominant model: OR=1.01, 95%CI = 0.47-2.20; recessive model: OR = 1.01, 95%CI = 0.80-1.26) did not increase pancreatic cancer risk. Conclusion: This meta-analysis indicated that MTHFR polymorphisms (C667T and A1298C) were not associated with pancreatic cancer risk.

• 한국정보통신학회논문지
• /
• 제18권4호
• /
• pp.848-854
• /
• 2014

메타분석은 여러 실증연구의 정량적인 결과를 통합과 분석을 통해 전체 결과를 조망할 기회를 제공하는 통계적 통합 방법이다. 스마트폰 관련 연구에서 기술수용모델 선행요인에 관한 연구들을 문헌적 고찰 및 메타분석을 실시하였다. 본 연구는 2008년부터 2013년까지 우리나라 학술지에 게재된 연구 중 기술수용모델의 인과관계를 설정한 총 106편의 연구논문을 대상으로 하였다. 메타분석의 결과 선행 요인과 인지된 유용성의 경로에 가장 큰 효과 크기는 유희성으로 나타났다. 인지된 유용성과 유희성의 경로에 효과 크기는 0.536이었다. 그리고 선행 요인과 인지된 사용 용이성의 경로에 가장 큰 효과 크기는 자기 효능감으로 나타났다. 인지된 사용 용이성과 자기 효능감 경로에 효과 크기는 0.626이었다. 분석결과를 바탕으로 이론적 실무적 시사점을 제시하고 선행연구와 비교분석을 통해 차이점을 논의하였다.

• 융합정보논문지
• /
• 제11권1호
• /
• pp.109-117
• /
• 2021

본 논문에서는 해양자동채염기의 구조중량 최소화를 위해 구조설계에 대한 메타모델 기반 근사최적화를 수행하였다. 구조해석은 해양자동채염기의 초기설계에 대한 강도성능을 평가하기 위해 유한요소법을 이용하여 수행하였다. 구조해석에서는 설계하중조건에 대한 강도성능을 평가하였다. 최적설계문제는 강도성능 제한조건을 만족하면서 중량을 최소화할 수 있는 구조두께의 설계변수를 결정하도록 정식화하였다. 근사최적화에는 반응표면법, 크리깅 모델 및 체비쇼프 직교 다항식의 메타모델을 사용하였다. 수치계산 특성을 검토하기 위해 근사최적화 결과는 비근사최적화 결과와 비교하였다. 근사최적화에 사용된 메타모델 중 체비쇼프 직교 다항식이 해양자동채염기의 구조설계에 가장 적합한 최적설계 결과를 나타내었다.

• Journal of Positioning, Navigation, and Timing
• /
• 제11권3호
• /
• pp.163-172
• /
• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권12호
• /
• pp.7149-7154
• /
• 2013

Objective: Increasing scientific evidence suggests that common variants in the PALB2 gene may confer susceptibility to breast cancer, but many studies have yielded inconclusive results. This meta-analysis aimed to derive a more precise estimation of the relationship between PALB2 genetic variants and breast cancer risk. Methods: An extensive literary search for relevant studies was conducted in PubMed, Embase, Web of Science, Cochrane Library, CISCOM, CINAHL, Google Scholar, CNKI and CBM databases from their inception through September 1st, 2013. A meta-analysis was performed using the STATA 12.0 software and crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: Six case-control studies were included with a total of 4,499 breast cancer cases and 6,369 healthy controls. Our meta-analysis reveals that PALB2 genetic variants may increase the risk of breast cancer (allele model: OR>1.36, 95%CI: 1.20~1.52, P < 0.001; dominant model: OR>1.64, 95%CI: 1.42~1.91, P < 0.001; respectively). Subgroup analyses by ethnicity indicated PALB2 genetic variants were associated with an increased risk of breast cancer among both Caucasian and Asian populations (all P < 0.05). No publication bias was detected in this meta-analysis (all P > 0.05). Conclusion: The current meta-analysis indicates that PALB2 genetic variants may increase the risk of breast cancer. Thus, detection of PALB2 genetic variants may be a promising biomarker approach.

• 산업경영시스템학회지
• /
• 제32권3호
• /
• pp.59-70
• /
• 2009

This study is the result of meta evaluation for the self evaluation of defense R&D programs in Korea by using meta evaluating indicators. The overall meta evaluation result of defense R&D programs gained 74.3 points out of 100, so it was evaluated as 'Good'. But it demonstrated that further improvement for overall system of defense R&D programs evaluation is required. And especially, it demonstrated that more alternatives are necessary in order to improve the utilizations and the feedbacks of evaluation results. The evaluation context component gained 80.2 points out of 100, so it was evaluated as 'Very Good'. The evaluation input component gained 73.1 points out of 100, so it was evaluated as 'Good'. The evaluation process component gained 74.8 points out of 100, so it was evaluated as 'Good'. And the evaluation outcome component gained 69.0 points out of 100, so it was evaluated as 'Good'. Basic model of meta evaluation was derived from the literature review and brain storming. And this meta evaluation model was determined by adopting the result of experts who performed evaluations for defense R&D programs in recent years. The reliability of components and items was verified by Cronbach's a coefficient. It was over 0.6 in evaluation components and items. And the reliability of evaluation context was 0.877, that of evaluation input was 0.755, that of evaluation process was 0.755, that of evaluation output was 0.755 respectively. From the analysis, it is attempted to identify possible problems and to find out the ways of improvements related to the self evaluation system of defense R&D programs. The ultimate objective of this study is to manage the programs effectively and improve the reliability and the objectiveness of the defense R&D programs.

• 지능정보연구
• /
• 제24권2호
• /
• pp.111-124
• /
• 2018

본 연구는 만성질환 중의 하나인 고지혈증 유병을 예측하는 분류모형을 개발하고자 한다. 이를 위해 SVM과 meta-learning 알고리즘을 이용하여 성과를 비교하였다. 또한 각 알고리즘에서 성과를 향상시키기 위해 변수선정 방법을 통해 유의한 변수만을 선정하여 투입하여 분석하였고 이 결과 역시 각각 성과를 비교하였다. 본 연구목적을 달성하기 위해 한국의료패널 2012년 자료를 이용하였고, 변수 선정을 위해 세 가지 방법을 사용하였다. 먼저 단계적 회귀분석(stepwise regression)을 실시하였다. 둘째, 의사결정나무(decision tree) 알고리즘을 사용하였다. 마지막으로 유전자 알고리즘을 사용하여 변수를 선정하였다. 한편, 이렇게 선정된 변수를 기준으로 SVM, meta-learning 알고리즘 등을 이용하여 고지혈증 환자분류 예측모형을 비교하였고, TP rate, precision 등을 사용하여 분류 성과를 비교분석하였다. 이에 대한 분석결과는 다음과 같다. 첫째, 모든 변수를 투입하여 분류한 결과 SVM의 정확도는 88.4%, 인공신경망의 정확도는 86.7%로 SVM의 정확도가 좀 더 높았다. 둘째, stepwise를 통해 선정된 변수만을 투입하여 분류한 결과 전체 변수를 투입하였을 때보다 각각 정확도가 약간 높았다. 셋째, 의사결정나무에 의해 선정된 변수 3개만을 투입하였을 때 인공신경망의 정확도가 SVM보다 높았다. 유전자 알고리즘을 통해 선정된 변수를 투입하여 분류한 결과 SVM은 88.5%, 인공신경망은 87.9%의 분류 정확도를 보여 주었다. 마지막으로, 본 연구에서 제안하는 meta-learning 알고리즘인 스태킹(stacking)을 적용한 결과로서, SVM과 MLP의 예측결과를 메타 분류기인 SVM의 입력변수로 사용하여 예측한 결과, 고지혈증 분류 정확도가 meta-learning 알고리즘 중에서는 가장 높은 것으로 나타났다.

• Clinical and Experimental Pediatrics
• /
• 제64권12호
• /
• pp.642-651
• /
• 2021

Background: Infantile colic (IC) is excessive crying in otherwise healthy children. Despite vast research efforts, its etiology remains unknown. Purpose: Most treatments for IC carry various side effects. The collection of evidence may inform researchers of new strategies for the management and treatment of IC as well as new clues for understanding its pathogenesis. This review and meta-analysis aimed to evaluate the efficacy and possible mechanisms of probiotics for mananaging IC. Methods: Ten papers met the study inclusion and exclusion criteria, and the meta-analysis was conducted using Review Manager (RevMan) software and a random-effects model. Results: This meta-analysis revealed that probiotics are effective for treating infantile colic, while the review showed that this efficacy may be due to their anti-inflammatory effects. Conclusion: Probiotics may be an important treatment option for managing infantile colic due to their anti-inflammatory properties.

• 한국운동역학회지
• /
• 제32권2호
• /
• pp.56-68
• /
• 2022

Objective: The purpose of this systematic review and meta-analysis was to investigate potential effects of HRT (hormone replacement therapy) on motor functions in postmenopausal women. Method: In this meta-analysis, 19 studies that examined changes in motor functions between postmenopausal women with and without HRT intervention were qualified. We additionally conducted moderator variable analyses including: (1) motor function type, (2) hormone type, and (3) duration of HRT intervention. Results: The random effects model showed no significant overall effects (SMD = 0.199; SE = 0.115; 95% CI = -0.026~0.425; Z = 1.730; p = 0.084; I² = 93.258%). Additional three moderator variable analyses revealed no significant effect sizes indicating that specific HRT protocols did not improve different motor functions in postmenopausal women. Conclusion: These meta-analytic findings suggest that HRT had no positive effects on motor functions in postmenopausal women.