• 한국공간구조학회논문집
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• 제1권1호
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• pp.125-134
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• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. In the genetic process of the simple GAs, there are three basic operators: reproduction, cross-over, and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying GAs to optimum design examples.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.489-497
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• 2007

Named entity translation plays an important role in many applications, such as information retrieval and machine translation. In this paper, we focus on translating person names, the most common type of name entity in Korean-Chinese cross language information retrieval (KCIR). Unlike other languages, Chinese uses characters (ideographs), which makes person name translation difficult because one syllable may map to several Chinese characters. We propose an effective hybrid person name translation method to improve the performance of KCIR. First, we use Wikipedia as a translation tool based on the inter-language links between the Korean edition and the Chinese or English editions. Second, we adopt the Naver people search engine to find the query name's Chinese or English translation. Third, we extract Korean-English transliteration pairs from Google snippets, and then search for the English-Chinese transliteration in the database of Taiwan's Central News Agency or in Google. The performance of KCIR using our method is over five times better than that of a dictionary-based system. The mean average precision is 0.3490 and the average recall is 0.7534. The method can deal with Chinese, Japanese, Korean, as well as non-CJK person name translation from Korean to Chinese. Hence, it substantially improves the performance of KCIR.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• Structural Engineering and Mechanics
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• 제9권2호
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• pp.169-180
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• 2000

An optimization procedure has been prescribed for the minimum weight design of symmetrical parabolic arches subjected to arbitrary loading. The cross section is assumed to be a symmetrical box section with variable depth and flange areas. The webs are unstiffened and have constant thickness. The proposed sequential, iterative search technique determines the optimum geometrical configuration of the parabolic arch which includes the optimum depth profile and the optimum lengths and areas of the required flange plates corresponding to the prescribed number of curtailments. The study shows that the optimum value of rise to span ratio (h/L) of a parabolic arch is maximum at 0.41 for uniformly distributed loading over the entire span. For any other loading, the optimum value of h/L is less than 0.41.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.963-968
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• 2006

The main purpose of this paper is to investigate the stability of water tower with a relatively small footing. The water tower is modeled that the column carrying a container is supported by a rotational spring at the base and is of constant cross-section, with a weight per unit length of column axis. The column model is based on the Bernoulli-Euler beam theory. The Runge-Kutta method and Determinant Search method are used to perform the integration of the governing differential equation and to determine the critical values(critical own weight. and critical buckling load), respectively. The critical buckling loads are calculated over a range of system parameters: the rotational stiffness parameter, the dimensionless radius of container and the own weight parameter of the column. The relation between the rotational stiffness parameter and the critical own weight parameter of the column is analyzed.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.904-907
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• 2019

Nuclear energy remains one of the world's major energy sources, making up over 10% of global electricity generation in 2017. Public acceptance of nuclear energy is essential for its adoption. From a practical perspective, it is beneficial to have a simple indicator that can predict the actual adoption of nuclear energy. Based on practical experience, the authors suggest tolerance and self-sufficiency as potential indicators that may predict the adoption of nuclear energy. By evaluating the cross-sectional data of 18 countries in 2013, this research assesses the actual impact of tolerance and self-sufficiency on public acceptance in order to identify the validity of the two variables. The results indicate that the two variables are statistically significant, while public acceptance is insignificant in explaining national adoption of nuclear energy. This may be because tolerance reflects national willingness to accept potential risk, while self-sufficiency explains a government's likelihood of developing non-carbon energy sources.

• 예술인문사회 융합 멀티미디어 논문지
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• 제9권6호
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• pp.757-772
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• 2019

본 논문에서는 아시아 38개 컨테이너항만 들을 대상으로 10년(2007년-2016년)동안의 4개의 투입요소(선석길이, 수심, 총면적, 크레인 수)와 1개의 산출요소(컨테이너화물 처리량)를 이용하여 인공신경망모형(다층퍼셉트론, 방사형기저함수)으로 클러스터링에 영향을 미친 요소들을 파악하였으며, 1단계 교차효율성 메트릭스를 이용한 군집 수를 사회연결망모형과 타부서치모형에 적용하여 클러스터링을 파악하고 효율성을 측정하였다. 또한 2단계효율성 메트릭스모형을 이용한 클러스터링을 파악하고 효율성을 측정하여 1단계 교차효율성 메트릭스에 의한 측정결과와 비교하였다. 주요한 실증분석 결과는 다음과 같다. 첫째, 인공신경망모형에 의해서 측정해 보았을 때, 군집에 영향을 많이 미친 요소별로 제시해 보면 컨테이너화물 처리량, 선석길이와 수심, 총면적, 크레인 수의 순서로 나타났다. 둘째, 사회연결망분석에서는 2단계 교차효율성(Type IV)메트릭스에 의한 군집은 benevolent 와 aggressive 모형에서 매년 동일한 결과를 보였다. 셋째, 클러스터링 후에 1단계 교차효율성 모형에 비해서 사회연결망 모형 분석과 타부서치 모형 분석에서 국내항만들의 효율성이 거의(사회연결망 모형에서 인천항의 경우 제외) 악화되는 것으로 나타났다. 다섯째, 일반적인 투입지향, 규모수확불변하의 CCR모형의 효율성 측정결과와 비교했을 때는 클러스터링이 모든 항만들에 대해서 약 37%이상의 효율성을 증대시켰다. 여섯째, 사회연결망모형과 타부서치모형에 의해서 클러스터링 되는 항만들은 부산항(고베, 오사카, 포트클랑, 탄중 펠파스, 마닐라항), 인천항(사히드 라자히, 광양), 광양항(아카바, 포트 슐탄 카바스, 담만, 크호르 파칸, 인천)으로 나타났다. 한국항만당국은 본 연구에서 이용된 방법을 도입하여 항만개선방안을 마련해야만 한다.

• Safety and Health at Work
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• 제11권3호
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• pp.262-265
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• 2020

Coronavirus disease 2019 (Covid-19) poses an important occupational health risk to health workers (HWs) that has attracted global scrutiny. To date, several thousand HWs globally have been reported as infected with the severe acute respiratory syndrome coronavirus 2 virus that causes the disease. It is therefore a public health priority for policymakers to understand risk factors for this vulnerable group to avert occupational transmission. A rapid review was carried out on 20 April 2020 on Covid-19 risk factors among HWs in PubMed, Google Scholar, and EBSCOHost Web (Academic Search Complete, CINAHL Complete, MEDLINE with Full Text, CINAHL with Full Text, APA PsycInfo, Health Source-Consumer Edition, Health Source: Nursing/Academic Edition) and WHO Global Database. We also searched for preprints on the medRxiv database. We searched for reports, reviews, and primary observational studies (case control, case cross-over, cross-sectional, and cohort). The review included studies conducted among HWs with Covid-19 that reported risk factors irrespective of their sample size. Eleven studies met the inclusion criteria. Lack of personal protective equipment, exposure to infected patients, work overload, poor infection control, and preexisting medical conditions were identified as risk factors for Covid-19 among HWs. In the context of Covid-19, HWs face an unprecedented occupational risk of morbidity and mortality. There is need for rapid development of sustainable measures that protect HWs from the pandemic.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권7호
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• pp.939-948
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• 2004

본 논문에서는 동일 환자에 대해 시간차를 두고 촬영한 뇌 CT-CT 혈관조영영상간 움직임을 보정하기 위한 강인하고 고속의 정합방법을 제안한다. 먼저, 두 영상에서 3차원 경계검출 기법을 이용하여 특징점을 추출하고, 기준영상에서는 이를 지역적 가중치 3차원 거리맵으로 변환한다. 부유영상을 기준영상으로 강체변환하면서 두 경계간의 상관관계가 최대인 위치를 탐색한다. 이 때, 최대위치가 더 이상 변화하지 않고 일정 이상 반복되면 해당위치를 최적위치로 하여 부유영상을 최적위치로 변환시켜 두 영상을 정합한다. 실험을 위하여 인공영상을 사용하여 정화성과 강인성을 평가하였고, 육안평가를 위하여 뇌 CT-CT 혈관조영영상을 사용하였다. 본 제안방법은 지역적 가중치 3차원 거리맵을 이용함으로써 적은 샘플링 개수에도 국부최대인 위치에 수렴하지 않고 최적위치로 강인하면서 고속으로 영상이 정합되었다

• ETRI Journal
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• 제34권1호
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• pp.87-97
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• 2012

This study presents an automatic matching method for generating a dense, accurate, and discontinuity-preserved digital surface model (DSM) using multiple images acquired by an aerial digital frame camera. The proposed method consists of two main procedures: area-based multi-image matching (AMIM) and stereo-pair epipolar line matching (SELM). AMIM evaluates the sum of the normalized cross correlation of corresponding image points from multiple images to determine the optimal height of an object point. A novel method is introduced for determining the search height range and incremental height, which are necessary for the vertical line locus used in the AMIM. This procedure also includes the means to select the best reference and target images for each strip so that multi-image matching can resolve the common problem over occlusion areas. The SELM extracts densely positioned distinct points along epipolar lines from the multiple images and generates a discontinuity-preserved DSM using geometric and radiometric constraints. The matched points derived by the AMIM are used as anchor points between overlapped images to find conjugate distinct points using epipolar geometry. The performance of the proposed method was evaluated for several different test areas, including urban areas.