• Structural Engineering and Mechanics
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• 제68권4호
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• 한국재료학회지
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• 제15권7호
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• pp.444-447
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• 2005

In this study, $Hydroxyapatite+TiO_2(HAp+TiO_2)$ composite sol coatings on Cp-Ti substrates were deposited by using a sol-gel derived precursor. Prior to hydroxyapatite coating, the samples were micropolished and divided into three sets. The first set was coated with hydroxyapatite (HAp) directly on Cp-Ti. The second set was first coated with intermediate titania layer and then coated with HAp. The third set samples were coated with $HAp+TiO_2$ (50:50) composite sol. Each samples were predried at $200^{\circ}C$, and heat treated at $600^{\circ}C$. The formation of hydroxyapatite has been confirmed by XRD analyses and the substrate material was found to be oxidized with negligible amount of CaO in the coating. The NaOH treated samples showed the presence of rutile crystal. The SEM studies revealed surface morphologies of each samples. $HAp+TiO_2$ composite sol coating layer was found to be smooth. The bonding strength of each samples were calculated using pull out tests. The bonding strength of the $HAp+TiO_2$ composite sol coating on substrate was 29.35MPa.

• Structural Engineering and Mechanics
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• 제86권5호
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• pp.673-686
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• 2023

Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (S_u), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R² larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R² and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.

• 한국정밀공학회지
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• 제23권3호
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• pp.163-170
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• 2006

Thin films play an important role in many technological applications including microelectronic devices, magnetic storage media, MEMS and surface coatings. It is well known that a thin film's material properties can be very different front the corresponding bulk properties and thus there has been a strong need for the development of a miniature tester to measure the mechanical properties of a thin film. Two testers are designed and set up in small size of 62 mm width, 20 mm depth and 90-120 mm height to fit in a chamber of scanning electron microscope (SEM). One tester has a homemade 0.2 N load cell and a low-priced electromagnetic actuator. The other has a commercial 5 N load cell, a $52{\mu}m$ piezoelectric actuator and some novel grips. Two types of 3.5 microns thick polysilicon specimen are tested to prove the testers' applicability. The strain is measured by the two ways. Firstly, it is measured by an ISDG system in the atmosphere far the reference. Secondly, the same test is repeated in a SEM chamber to monitor the strain as an in-situ experiment. The strain is evaluated by observing the gap change between two markers.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권5호
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• pp.386-393
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• 2010

영상에서 일정 영역의 화소들이 불규칙적인 형태를 이루는 것을 불량이라 하는데 이를 수학적으로 정확히 정의하기 어렵다는 점이 불량 검출을 쉽지 않게 한다. 하지만 주어진 영상이 다수의 반복되는 패턴을 가지고 있다면 불량이 아닌 영역은 그 외의 다른 영역들로 설명되어 될 수 있다는 점을 이용하여 영상내의 불량 영역을 찾아낼 수 있다. 따라서 본 논문은 이러한 특성을 이용하여 다양한 패턴이 반복되는 영상에 존재하는 불량을 검출하는 방법을 제시한다. 제시된 방법은 크게 세 단계로 이루어진다. 첫 번째 단계는 interest point 검출단계이다. 두 번째 단계는 적절한 패치의 크기를 결정하는 단계이다. 마지막으로 세 번째 단계는 불량을 검출하는 단계이다. 제시된 방법은 반도체 wafer를 SEM을 이용하여 촬영한 영상들을 통하여 예증된다.

• 한국정보처리학회논문지
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• 제1권4호
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• pp.511-516
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• 1994

본 논문에서는 전송 잡음 환경 하에서 전자파 산란 물체의 식별을 위하여 사용하 는 파라메타 측정 기법에 관한 연구이다. 최대 유사측정(Maximum Likelihood Estimation : MLE)기법은 물체 식별에 변형하여 응용되면 종래 잘 알려져 사용되어온 함수군속(Pencil of Functions) 기법보다 더 좋은 측정결과를 가진다는 것을 본 논문 은 보여주고 있다. MLE 기법을 포함하여 파라메타 식별을 위한 도구로서 지금까지 여러 제안기법들이 있었으나, 본 논문에서는 샘플 데이타의 길이에 관계없이 목표시 스템의 파라메타 양에만 관계하는 최소단위의 메트릭스 연산이 사용됨을 보여주므로 잡음이 상재하는 추출 데이타로부터 목표식별에 가장 강한 강점이 있다.

• 한국항공운항학회지
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• 제20권3호
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• pp.76-89
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• 2012

The number of foreign cabin crews consist of 7% of total crews in K-airline, of which Chinese crews are of 38%. The number of foreign crews are 433 from 10 countries as of the end of July 2012. The airline has continued to hire foreign cabin crews to increase efficiency of human resourcing qualified flight attendants. This paper tried to do empirical research through SEM(Structural Equation Model) to overview confirmatory factors and course effects integrally. Cultural stress, aggressive coping, social support and job adaption have been chosen to be a factors. Especially, the SEM was set to show indirect effects of cultural stress and aggressive coping through social support to the dependant variable, job adaptation. According to the analysis result, cultural stress has a direct negative effect on job adaptation. Aggressive coping has also a direct positive effect on job adaptation. It has also proven cultural stress and aggressive coping has a indirect effect to job adaptation through social support. This paper is expect to contribute to develop such training and administrative programs as enhancing foreign crews' job adaptability and managing them effectively.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.223-231
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• 2021

The study aimed to investigate the impact of social networks safety (SNS) on the marketing information quality (MIQ) during the COVID-19 pandemic in Saudi Arabia. The study examines the statistical differences in social networks safety SNS and marketing information quality MIQ according to the demographics such as age, sex, income, and education. For this study purpose, information security and privacy are two components of social networks safety. The research materials are website resources, regular books, journals, and articles. The population includes all Saudi users of social networks. The figures show that active users of the social network reached 25 Million in 2020. The snowball method was used and sample size is 500 respondents and the questionnaire is the tool for the data collection. The Structural Equation Modelling SEM technique is used. Convergent Validity, Discriminate Validity, and Multicollinearity are the main assumptions of structural equation modeling SEM. The findings show the high positive impact of SNS networks safety on MIQ and the statistical differences in such variables refer to education. Finally, the study presents a set of future suggestions to enhance the safety of social networks in Saudi Arabia.

• Structural Engineering and Mechanics
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• 제81권6호
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• Journal of Forest and Environmental Science
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• 제33권2호
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• pp.113-121
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• 2017

In flight particulate matter particularly emissions generated by incomplete combustion processes has become a subject of global concern due to the health problems and environmental impacts associated with them. This has compelled most countries to set standards for coarse and fine particles due to their conspicuous impacts on environment and public health. This contribution therefore explores forest fire emissions and how its particulates affects air quality, damage to vegetation, water bodies and biological functions as architects for lung diseases and other degenerative illnesses such as oxidative stress and aging. Soot was collected from simulated forest fire using a clean glass surface and carefully transferred into amber vials for analysis. Volatile components of soot were collected over 10 mL dichloromethane and analyzed using a QTOF Premier-Water Corp Liquid Chromatography hyphenated to a mass selective detector (MSD), and Gas Chromatograph coupled to a mass spectrometer (GC-MS). To characterize the size and surface morphology of soot, a scanning electron microscope (SEM) was used. The characterization of molecular volatiles from simulated forest fire emissions revealed long chain compounds including octadec-9-enoic acid, octadec-6-enoic acid, cyclotetracosane, cyclotetradecane, and a few aromatic hydrocarbons (benzene and naphthalene). Special classes of organics (dibenzo-p-dioxin and 2H-benzopyran) were also detected as minor products. Dibenzo-p-dioxin for instance in chlorinated form is one of the deadliest environmental organic toxins. The average particulate size of emissions using SEM was found to be $11.51{\pm}4.91{\mu}m$. This study has shown that most of the emissions from simulated forest fire fall within $PM_{10}$ particulate size. The molecular by-products of forest fire and particulate emissions may be toxic to both human and natural ecosystems, and are possible precursors for various respiratory ailments and cancers. The burning of a forest by natural disasters or man-made fires results in the destruction of natural habitats and serious air pollution.