• Applied Microscopy
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• 제33권3호
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• pp.195-204
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• 2003

Imaging plate에 기록된 전자회절 자료의 면간 거리 분석과 상동정시 나타나는 오차 요인들을 고찰하고 실험적인 보정방법을 도출하였다. 각각의 회절방향에 대한 radial intensity distribution plot과 실험적으로 도출된 면간 거리 보정식에 의해 전자회절 자료의 디지털 이미지에서 면간 거리 측정오차는 약 0.5%로 낮아짐을 알 수 있었다. Al 표준시료를 이용하여 imaging plate에 기록된 전자회절 자료의 면간 거리 편차 경향을 분석한 후 [001] gibbsite 시편에 동일한 실험적 보정을 수행하여 120분간의 전자빔 조사로부터 형성된 여러 전이 상들에 대한 면간 거리 측정 및 상 동정을 보다 정밀히 수행할 수 있었다. 그 결과, gibbsite로부터 형성된 주요 전이상들은 ${\chi}$-알루미나, ${\gamma}$-알루미나, ${\sigma}$-알루미나로 구성됨을 명확하게 동정할 수 있었다.

• Journal of Microbiology and Biotechnology
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• 제26권3호
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• pp.588-595
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• 2016

IFN-γ release assays (IGRAs) have been developed as viable alternative diagnostic tools for detecting latent tuberculosis infection (LTBI). A customized homogeneous sandwich luminescent oxygen channeling immunoassay (LOCI) was used to quantify IFN-γ levels in IGRAs. Samples were collected from healthy volunteers (n = 40) who were T-Spot-negative and T-Spot-positive patients (n = 32) at rest. Then the amount of IFN-γ in the supernatant of IGRAs was measured by LOCI. The results demonstrated a low background, and high sensitivity, specificity, accuracy, and reproducibility, and a short assay time (only 30 min) with LOCI for IFN-γ. The recovery range was 81.63-102.06%, the coefficients of variation were below 5%, and the limit of detection was 19.0 mIU/ml. Excellent agreement between LOCI IFN-γ and the T-SPOT.TB test was obtained (97.2% agreement, κ = 0.94). The LOCI IFN-γ concentrations were significantly higher in T-Spot-positive patients than in the healthy group (p < 0.001). Moreover, as observed for the comparative LOCI IFN-γ assay, IFN-γ concentrations were related to the numbers of T-SPOT.TB spots. We have established an in vitro blood test for LTBI diagnosis, defined as LOCI IFN-γ. A high level of agreement between the LOCI IFN-γ method and T-SPOT.TB assay was observed in clinical studies that showed the LOCI IFN-γ method could determine LTBI. This study shows acceptable performance characteristics of the LOCI IFN-γ assay to diagnose LTBI.

• Elastomers and Composites
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• 제43권3호
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• pp.173-182
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• 2008

고무나 우레탄과 같은 고 탄성력을 이용하여 튜브를 임의의 형상으로 성형하는 고 탄성체 성형방법은 타 공정에 비해 높은 치수 정밀도와 생산 공정의 단축, 에너지 절감 등을 기대할 수 있는 차세대 성형기술이라 할 수 있다. 본 연구에서는 탄성체에 대한 소재 물성시험과 특성평가를 통해 고 탄성체 성형에 적합한 소재를 선정하고 시험으로 얻어진 응력-변형률을 이용하여 비선형 재료상수를 결정하여 성형해석에 필요한 물성 데이터를 확보하였다. 또한, 랙튜브에 대한 유한요소해석을 통해 탄성체의 두께변화에 따른 공정변수의 영향을 검토하였다.

• 한국정밀공학회지
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• 제25권4호
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• pp.134-139
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• 2008

A spirally arrayed nano-pattern is designed as a model pattern for the next generation optical storage media. The pattern consists off types of embossed rectangular dot, which are 50nm, 100nm, 150nm and 200nm in length and 50nm in width. The height of the dot is designed to be 50nm. The pitch of the spiral track of the pattern is 100nm. A ER(Electron resist) master for this pattern is fabricated by e-beam lithography process. The ER is first spin-coated to be 50nm thick on a Si wafer and then the model pattern is written on the coated ER layer by e-beam. After developing this pattern written wafer in the solution, a ER pattern master is fabricated. The most conventional e-beam machine can write patterns in orthogonal way, so we made our own pattern generator which can write the pattern in circular or spiral way. This program generates the patterns to be compatible with the e-beam machine from Raith(Raith 150). To fabricate 50nm pattern master precisely, a series of experiments were done including the design compensation for the pattern size, optimization of the dose, acceleration voltage, aperture size and developing. Through these experiments, we conclude that the higher accelerating voltages and smaller aperture size are better for mastering the nano pattern which is in order of 50nm. With the optimized e-beam lithography process, a spiral arrayed 50nm pattern master adopting PMMA resist was fabricated to have dimensional accuracy over 95% compared to the designed. Using this pattern master, a metal pattern stamp will be fabricated by Ni electro plating for injection molding of the patterned plastic substrate.

• 대한지역사회영양학회지
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• 제13권1호
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• pp.13-23
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• 2008

This study investigated the association between the weight status of middle school students and the various weight-related characteristics including desired weight, weight perception, weight-related practice, physical activity, and overeating behavior. Questionnaires were administered to 473 middle school students (178 boys and 295 girls) in Daejeon. Boys and girls were divided into three groups respectively; (1) underweight (BMI<$5^{th}$ percentile) (2) normal weight ($5^{th}$ percentile$\leq$BMI<$85^{th}$ percentile) (3) overweight (BMI$\leq85^{th}$ percentile). Using BMI calculated from measured height and weight, 14.0% of boys and 6.8% of girls were underweight, and 16.3% of boys and 14.2% of girls were overweight. However, among this sample of students, 38.4% of boys and 13.6% of girls perceived themselves as underweight and 29.4% of boys and 44.9% of girls perceived themselves as overweight. We found that overweight students reported their body weights lower and their heights higher compared to non-overweight students, resulting in an underestimation of BMI. Based on desired BMI, 79.9% of the girls desired to be underweight and 73.0% of the boys desired to be normal weight. Overweight or normal weight students were less satisfied with their body weights than underweight students. Girls had more weight control experience and concern compared to boys. Overweight girls spent longer times in watching TV compared to non-overweight girls (p < 0.001) and had more overeating behaviors (p < 0.05). Overweight students reported that they ate snacks less frequently than non-overweight students, which may be due to their tendency to report less eating. In conclusion, significant gender differences and weight status differences existed in weight perception, weight satisfaction, and weight control experience and concern. Because perception of overweight is likely to lead to unhealthy eating behaviors and weight control, efforts for adolescents to improve accuracy of weight perceptions and to understand the benefits of being healthier are needed.

• Advances in nano research
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• 제10권2호
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• pp.151-163
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• 2021

The main target of this study is to investigate nonlinear transient responses of moving polymer nano-size plates fortified by means of Graphene Platelets (GPLs) and resting on a Winkler-Pasternak foundation under a transverse pressure force and a temperature variation. Two graphene spreading forms dispersed through the plate thickness are studied, and the Halpin-Tsai micro-mechanics model is used to obtain the effective Young's modulus. Furthermore, the rule of mixture is employed to calculate the effective mass density and Poisson's ratio. In accordance with the first order shear deformation and von Karman theory for nonlinear systems, the kinematic equations are derived, and then nonlocal strain gradient scheme is used to reflect the effects of nonlocal and strain gradient parameters on small-size objects. Afterwards, a combined approach, kinetic dynamic relaxation method accompanied by Newmark technique, is hired for solving the time-varying equation sets, and Fortran program is developed to generate the numerical results. The accuracy of the current model is verified by comparative studies with available results in the literature. Finally, a parametric study is carried out to explore the effects of GPL's weight fractions and dispersion patterns, edge conditions, softening and hardening factors, the temperature change, the velocity of moving nanoplate and elastic foundation stiffness on the dynamic response of the structure. The result illustrates that the effects of nonlocality and strain gradient parameters are more remarkable in the higher magnitudes of the nanoplate speed.

• Advances in nano research
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• 제12권2호
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• 미래기술융합논문지
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• 제2권4호
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• pp.43-48
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• 2023

전세계적으로 기후변화 대응을 위한 글로벌 탄소중립을 공조하고 있다. 한국의 경우 온실가스 배출량이 빠른 속도로 증가하고 있어 해결이 시급한 상황이다. 이에 본 연구는 스팀트랩이라는 열 에너지 수집 디바이스를 개발하고, 스팀트랩으로 에너지 사용량을 데이터로 수집하여 향후 전력 사용량에 대해서 예측이 가능한 AI 모델을 개발하였다. 해당 AI 모델의 전력 사용량 예측 정확도 평균은 96.7%로 높은 정확도를 보여주었다. 따라서 해당 AI 모델을 통해 어느날 전력 사용량이 높은지와 어떤 설비에서 전력 사용량이 높은지를 예측하고 관리 할 수 있게 되었다. 향후 연구는 스팀트랩의 이상탐지를 통한 효율적인 장비 운용과 에너지 관리 시스템의 표준화를 통해 에너지 소비 효율을 최적화하여 온실가스 배출을 줄이고자 한다.

• Advances in nano research
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• 제16권5호
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• pp.509-519
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• 2024

In this study, the static analysis of carbon nanotube-reinforced composites (CNTRC) beams resting on a Winkler-Pasternak elastic foundation is presented. The developed theories account for higher-order variation of transverse shear strain through the depth of the beam and satisfy the stress-free boundary conditions on the top and bottom surfaces of the beam. To study the effect of carbon nanotubes distribution in functionally graded (FG-CNT), we introduce in the equation of CNT volume fraction a new exponent equation. The SWCNTs are assumed to be aligned and distributed in the polymeric matrix with different patterns of reinforcement. The rule of mixture is used to describe the material properties of the CNTRC beams. The governing equations were derived by employing Hamilton's principle. The models presented in this work are numerically provided to verify the accuracy of the present theory. The analytical solutions are presented, and the obtained results are compared with the existing solutions to verify the validity of the developed theories. Many parameters are investigated, such as the Pasternak shear modulus parameter, the Winkler modulus parameter, the volume fraction, and the order of the exponent in the volume fraction equation. New results obtained from bending and stresses are presented and discussed in detail. From the obtained results, it became clear the influence of the exponential CNTs distribution and Winkler-Pasternak model improved the mechanical properties of the CNTRC beams.