• Structural Engineering and Mechanics
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• 제68권5호
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• 융합보안논문지
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• 제18권1호
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• pp.3-11
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• 2018

오늘날 새롭게 등장한 Science of Security (SoS)라는 분야는 사이버 보안 영역에 대한 과학적인 접근 방법을 적용한 연구분야로서 보안 영역에서 등장한 새로운 패러다임이라고 할 수 있다. 복잡하고, 큰 규모 네트워크 환경의 동적인 변화와 다수의 프로토콜과 메커니즘 환경이 존재하는 현대에 이러한 네트워크 환경에 대한 보안을 위해 Formal Model과 자동화 분야를 연구하는 방향이다. 따라서 본 연구에서는 SoS와 같은 최신 사이버 보안 연구 동향에 대해서 분석하고, 선진국들의 연구 동향사례들을 조사하여 국내의 사이버 보안 개발 방향에 대해 새로운 접근 방법을 검토하고자 한다. 또한 다양한 사이버 보안의 패러다임에 대한 과학적 보안 연구 방법에 대해 국내의 현황을 분석해 보고 국내 사이버 보안 활성화에 대한 방향을 제시하고자 한다.

• 대한융합한의학회지
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• 제3권1호
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• pp.15-27
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• 2022

Objectives: This study was conducted to review the overall concept of nutritional evaluation of infants and young children. Methods: Literature search was done to study definition, method and importance of nutritional evaluation of infants and young children. Pubmed and Google scholarship were used in the research. Search words were 'Nutritional evaluation', 'infants' and 'young children'. Results: Nutrition evaluation is mainly used by physical measurement, clinical evaluation, dietary intake survey, and biochemical test depending on the age and disease. The treatment method for 治未病, which is a concept of korean medicine, and 健兒法 for treating the concept of weak children are considered to have very high applicability in solving various problems found through nutrition evaluation in korean medical approach. Conclusion: Infants and children are the fastest growing period of their lives, showing rapid growth in physical, and emotional development along with rapid brain growth. Therefore, inadequate nutrition during this period affects mental and physical growth and development not only during that period but also throughout life. Nutrition evaluation is divided into regular evaluation that includes children in all growing seasons and screening evaluation for problem solving, and follow-up nutritional evaluation that evaluates nutritional status in the long run. For each nutritional evaluation, evaluation is conducted by physical measurement, clinical evaluation, dietary intake survey, and biochemical test. By comprehensively interpreting them, nutritional status is determined. This study provides basic data on the proper nutrition evaluation method to identify and correct nutritional problems such as growth level, nutritional deficiency, and nutritional excess early.

• 인터넷정보학회논문지
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• 제24권6호
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• 센서학회지
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• 제32권5호
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• pp.259-266
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• 2023

The use of various adulterants and harmful chemicals is rapidly increasing in various sectors such as agriculture, food, and pharmaceuticals, and they are also present in our surroundings in the form of pollutants. The regular and repeated intake of harmful chemicals often adversely affects human health. The prolonged exposure of living beings to such adverse components can lead to severe health complications. To avoid the unlimited utilization of these chemical components, a sensing technology that is sensitive and reliable for low-concentration detection is beneficial. Surface-enhanced Raman spectroscopy (SERS) is a powerful method for identifying low-range concentrations of analytes, leading to great applications in molecular identification, including various diagnostic biomarkers. SERS in chemical, gas, and biological sensors can be an excellent approach in the sensing world to achieve rapid and multiple-analyte detection, leading to a new and efficient approach in healthcare monitoring.

• 한국환경보건학회지
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• 제43권3호
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• pp.223-232
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• 2017

Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

• 융합정보논문지
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• 제8권6호
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• pp.257-263
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• 2018

치위생학과 학생들의 창의와 인성에 영향을 미치는 요인을 파악하고자 한다. 2018년 5월 14일부터 2018년 6월 1일까지 광주광역시에 있는 S 대학교에 재학중인 치위생학과 114명 대상으로 시행하였다. 메타인지의 전체 평균은 3.26점으로 나타났다. 연구변인에 따른 차이를 살펴보면, 전공 만족도의 만족 3.36점이 보통/불만족 3.16점과 유의한 차이가 있었다(p<0.05). 숙달접근목표의 전체 평균은 3.26점으로 나타났다. 연구변인에 따른 차이를 살펴보면, 전공 만족도의 만족이 3.38점이 보통/불만족 3.14점과 유의한 차이가 있었다(p<0.05). 자율적 교육풍토의 전체 평균은 3.08점으로 나타났다. 연구변인에 따른 차이를 살펴보면, 전공 만족도의 만족 3.17점이 보통/불만족 2.98점과 유의한 차이가 있었다(p<0.01). 창의 인성의 전체평균은 3.37점으로 나타났다. 연구변인에 따른 차이를 살펴보면, 전공 만족도의 만족이 3.47점이 보통/불만족 3.26점과 유의한 차이가 있었다(p<0.01). 대학생의 창의 인성에 영향을 미치는 요인은 메타인지와 숙달접근목표로, 메타인지와 숙달접근목표 점수가 높을수록 창의 인성이 높게 나타나 주요 요인으로 확인되었다.

• 한국가금학회지
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• 제49권3호
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• pp.157-165
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• 2022

RGB 조건에서 하나의 픽셀은 255의 세제곱 개 이상의 색상을 표현할 수 있다. 현재까지의 컴퓨터 비전 연구는 조류에서 나타나는 다양한 깃털색 표현형에 대해 세밀히 분석하여 종을 구분하였지만, GWAS에 이용될 목적을 위해 다양하게 유전되는 색상을 단순화하지 못하였다고 판단된다. 본 연구는 연산오계(YO)와 백색레그혼(WL) 상호역교배 F₂ 집단을 이용하였으며 이미지 양자화를 통하여 이미지의 크기를 줄이고 저장을 용이하게 하였으며 깃털색의 원인 유전자 탐색을 위한 기초 자료를 제공하기 위하여 육안으로 결정하였던 다양한 깃털색을 단순화하였다. 특히, GWAS 연구에 필요한 수치화된 표현형을 제시하였다는 측면에서 가치가 있다고 판단된다.

• 한국융합학회논문지
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• 제5권4호
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• pp.87-92
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• 2014

오늘날의 급변하는 시대는 더 이상 제품 혹은 서비스 자체만으로 혁신하는 것은 어렵다. 새로운 것에 대한 고객들의 욕구가 빠르게 변화는 상황에 빠르게 대처하기 위해서는 제품 및 서비스 자체 보다는 이종 산업 간의 융합이 중요하다. 기술과 서비스가 융합하여 탄생한 새로운 창조물인 온라인 서비스 플랫폼은 서비스 혁신을 위한 성장동력 중 하나로 주목받고 있다. 따라서 온라인 서비스 플랫폼을 어떻게 성공시킬 수 있는지 살펴보는 것은 매우 중요하다고 판단된다. 이를 위해 본 연구는 온라인 서비스 플랫폼 중 하나인 JJS Media에서 출시한 MyMusicTaste 서비스에 대해 사례조사를 수행하고자 한다. 이를 통해 온라인 서비스 플랫폼을 준비하고 있는 기업들이 어떻게 해당 서비스를 성공적으로 운영할 수 있는지 그 힌트를 제공하고자 한다.