• Journal of Korean Institute of Industrial Engineers
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• v.13 no.1
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• pp.11-24
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• 1987

Automatic Guided Vehicle Systems feature battery powered driverless vehicles with programming capabilities for path selection and positoning. Vehicles serve the machines in shop, following a guide path system installed on the shop floor. The basic problem in the system is to determine a fixed set of vehicle routes of minimal total distance(time) while keeping capacity and distance(time) constraints. In this paper, a heuristic algorithm is presented for scheduling the automatic guided vehicles. The algorithm routes the machines based on their distances and polor coordinate angles, taking into account the structural feature of the system. Computational experiments are performed on several test problems in order to evaluate the proposed algorithm. Finally, a framework for dealing with the case where supplies from the machines are probabilistic is described.

• Journal of Fashion Business
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• v.7 no.5
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• pp.45-53
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• 2003

Rei Kawakubo is known for her provocative aesthetics: she often deliberately seeks beauty in what is seen by convention as taboo. With her highly informed and invariably provocative aesthetic, Rei Kawakubo has advanced historical forms of dress using radical functional and structural transpositions. She is considered as a pioneer showing firmly important elements of modern fashion design in her works by fashion journalists. In this paper, I'd like to analysis features of modern fashion design through Rei Kawakubo's works. I will analysis important elements of Rei Kawakuvo's design and devote study of the connection between the feature of her design and the feature of modern fashion design.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.143-148
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• 2015

The study examined the relationship between workers' safety awareness, safety performance and the components of the intelligent image analysis system in accordance with preventing the workers from safety hazard in dangerous working area. Based on the safety performance model, we include safety knowledge, safety motivation, safety compliance and safety participation, and we also define three additional factors of the intelligent image analysis system such as functional feature, penalty and incentive by using factor analysis. SEM(Structural Equation Modeling) analyses on the data from the total of 73 workers showed that functional feature of intelligent analysis system and incentive were positively related to safety knowledge and safety motivation. And mediation effects of the relationship were verified to safety compliance and safety participation through safety knowledge as well.

• Journal of Korean Association for Spatial Structures
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• v.21 no.1
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• pp.61-70
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• 2021

This paper describes a novel zero-stress member selecting method for sizing optimization of truss structures. When a sizing optimization method with static constraints is implemented, the member stresses are affected sensitively with changing the variables. However, because some truss members are unaffected by specific loading cases, zero-stress states are experienced by the elements. The zero-stress members could affect the computational cost and time of sizing optimization processes. Feature selection approaches can be then used to eliminate the zero-stress member from the whole variables prior to the process of optimization. Several numerical truss examples are tested using the proposed methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.212-215
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• 2021

본 논문에서는 6 Fisheye lens 원본 영상에 대하여 Insta360 stitcher, AutoStitch[4], As-Projective-AsPossible(APAP)[5] 스티칭 방법으로 360 도 파노라마 영상을 생성하고 기하학적 왜곡과 컬러 왜곡을 비교 평가한다. 360 도 파노라마 Image Quality Assessment(IQA) 메트릭으로 Natural Image Quality Evaluator(NIQE)[6], Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE)[7], Perception based Image Quality Evaluator(PIQE)[8], Feature Similarity(FSIM)[9] 그리고 high frequency feature 에 대한 Structural Similarity(SSIM)[10]을 측정하여 정량적 평가를 하며 정성적인 비교를 통하여 파노라마 영상의 품질과 평가 메트릭에 대한 벤치마크를 제공한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.1
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• pp.13-19
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• 2017

Human sterol ${\Delta}8-{\Delta}7$ isomerase, commonly known as emopamil binding protein (EBP), is an essential protein in the cholesterol-synthetic pathway, and mutations of this protein are critically associated with human diseases such as Conradi-Hunermann-Happle or male EBP disorder with neurological defects syndrome. Due to such a clinical importance, EBP has been intensively investigated and some important features have been reported. EBP is a tetra-spanning membrane protein, of which $2^{nd}$, $3^{rd}$, and $4^{th}$ membrane-spanning ${\alpha}$ helices play an important role in its enzymatic function. However, detailed structural feature at atomic resolution has not yet been elucidated, due to characteristic difficulties in dealing with membrane protein. Here, we over-expressed EBP using Escherichia coli and performed detergent screening to find suitable membrane mimetics for structural studies of the protein by NMR. As results, DPC and LMPG could be evaluated as the most favorable detergents to acquire promising NMR spectra for structural study of EBP.

• Wind and Structures
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• v.26 no.1
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• pp.45-56
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• 2018

Wind damage of urban trees arises to be a serious issue especially in the typhoon-prone areas. As a family of tree species widely-planted in Southeast China, the structural behaviors of Plane tree is investigated. In order to accommodate the complexities of tree morphology, a fractal theory based finite element modeling method is proposed. On-site measurement of Plane trees is performed for physical definition of structural parameters. It is revealed that modal frequencies of Plane trees distribute in a manner of grouped dense-frequencies; bending is the main mode of structural failure. In conjunction with the probability density evolution method, the fragility assessment of urban trees subjected to wind excitations is then proceeded. Numerical results indicate that small-size segments such as secondary branches feature a relatively higher failure risk in a low wind level, and a relatively lower failure risk in a high wind level owing to windward shrinks. Besides, the trunk of Plane tree is the segment most likely to be damaged than other segments in case of high winds. The failure position tends to occur at the connection between trunk and primary branches, where the logical protections and reinforcement measures can be implemented for mitigating the wind damage.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.209-216
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• 2020

In this paper, parametric structural analysis is presented utilizing the co-rotational(CR) shell analysis utilizing EDISON. CR shell analysis shows faster convergence than the commercial software, NASTRAN, does. The 1st natural frequency of the rear frame is obtained, which is close to that of the engine during high speed cruise. Three cases under two design variables are presented and analyzed. Gusset is shown to be more effective among those which feature the same weight change. The results presented in this paper will be applicable for further researches to improve the durability of a motorcycle rear frame.

• Smart Structures and Systems
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• v.17 no.3
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.