• Smart Structures and Systems
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• v.24 no.2
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• pp.193-207
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• 2019

This study concerns with morphing structures, e.g. as applied in the aerospace industry. A morphing aerofoil structure capable of variable geometry was developed, which was shown to be able to cater for the different aerodynamic requirements at different stages of flight. In this work, the useful and relatively simple method has been applied, which provides a direct method for calculating required morphing shape displacements via finding the most effective bar through calculating bar sensitivity to displacement and calculating set of length actuations for bar assembly to control/adjust shape imperfection of prestressable structural assemblies including complex elements ("macro-elements", e.g., the pantographic element), involving Matrix Condensation. The technique has been verified by experiments on the physical model of an aerofoil shaped morphing pantographic structure. Overall, experimental results agree well with theoretical prediction. Furthermore, the technique of multi-iteration adjustment was presented that effective in eliminating errors that occur in the practical adjustment process itself. It has been demonstrated by the experiments on the physical model of pantographic morphing structure. Finally, the study discusses identification of the most effective bars with the objective of minimal number of actuators or minimum actuation.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.413-418
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• 2001

In this paper, we propose a new camera calibration method which is based on a fuzzy model instead of a physical camera model of the conventional method. The camera calibration is to determine the correlation between camera image coordinate and real world coordinate. The camera calibration method using a fuzzy model can not estimate camera physical parameters which can be obtained in the conventional methods. However, the proposed method is very simple and efficient because it can determine the correlation between camera image coordinate and real world coordinate without any restriction, which is the objective of camera calibration. With calibration points acquired out of experiments, 3-D real world coordinate and 2-D image coordinate are estimated using the fuzzy modeling method and the results of the experiments demonstrate the validity of the proposed method.

• Journal of the Ergonomics Society of Korea
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• v.6 no.1
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• pp.3-8
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• 1987

This paper develops a statistical mode which estimates mental and physical loads of light work from sinus arrhythmia (SA) scores. During experiments, various levels of mental and physical loads (respectively scored by information processing and finger tapping rates) were imposed on subjects and SA scores were measured from the subjects. Two methods were used in developing workload estimation model. One is an algebraic inverse function of a multivariate regression equation, where mental and physical loads are independent variables and SA scores are dependent variables. The other is a statistical multivariate inverse regression. Of the two methods, inverse function resulted in larger mean squqre error in predicting mental and physical loads. Hence, inverse regression model is recommended for precise workload estimation.

• Journal of the Korean Solar Energy Society
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• v.22 no.2
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• pp.61-69
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• 2002

Daylighting is a powerful vehicle of architectural expression and provides buildings a living quality due to constantly changing properties in intensity and color. As an environmental system, daylighting should be subjected to the same level of rigorous analysis and review that any environmental system receives. For example, increasing cooling loads and causing visual displeasure are easily occurred owing to the excessive sunlight through windows. Therefore, daylighting performance attributes and physical characteristics must be described qualitatively and quantitatively in early design process. In various architectural daylighting performance evaluation methods, the scale model experiment can be applied due to it's simplicity and usefulness. So, this study aims to evaluate the validation of scale model experiments in architectural daylighting performance. For the purpose, two scale model experiments under clear sky are conducted. And, the validation of the experiments are evaluated by computer simulations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.691-701
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• 2017

The barbell squat is a fundamental physical exercise for strengthening the lower body and core muscles. It is an integral part of training and conditioning programs in sports, rehabilitation, and fitness. In this paper, we proposed a virtual test framework for squat exercises using a Smith machine to simulate joint torques and muscle forces, based on an integrated product-human model and motion synthesis algorithms. We built a muscular skeletal human model with boundary conditions modeling the interactions between the human body and a machine or the ground. To validate the model, EMG, external forces, and squat motions were captured through physical experiments by varying the foot position. A regression-based motion synthesis algorithm was developed based on the captured squat motions to generate a new motion for a given foot position. The proposed approach is expected to reduce the need for physical experiments in the development of training programs.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.1-8
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• 2021

To simulate a process model in the field of chemical engineering, it is very important to identify the physical properties of novel materials as well as existing materials. However, it is difficult to measure the physical properties throughout a set of experiments due to the potential risk and cost. To address this, this study aims to develop a property prediction model based on the group contribution method for aromatic chemical compounds including benzene rings. The benzene rings of aromatic materials have a significant impact on their physical properties. To establish the prediction model, 42 important functional groups that determine the physical properties are considered, and the total numbers of functional groups on 147 aromatic chemical compounds are counted to prepare a dataset. Support vector regression is employed to prepare a prediction model to handle sparse and high-dimensional data. To verify the efficacy of this study, the results of this study are compared with those of previous studies. Despite the different datasets in the previous studies, the comparison indicated the enhanced performance in this study. Moreover, there are few reports on predicting the physical properties of aromatic compounds. This study can provide an effective method to estimate the physical properties of unknown chemical compounds and contribute toward reducing the experimental efforts for measuring physical properties.

• Structural Engineering and Mechanics
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• v.8 no.3
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• pp.273-283
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• 1999

Two physical experiments are performed to verify the effectiveness of beam-particle model for simulating the progressive failure of particulate composites such as sandstone and concrete. In the numerical model, the material is schematized at the meso-level as an assembly of discrete, interacting particles which are linked through a network of brittle breaking beams. The uniaxial compressive tests of cubic and parallelepipedal specimens made of carbon steel rod assembly which are glued together by a mixture are represented. The crack patterns and load-displacement response observed in the experiments are in good agreement with the numerical results. In the application respect of beam-particle model to the particulate composites, the influence of defects, particle arrangement and boundary conditions on crack propagation is approached, and the correlation existing between the cracking evolution and the level of loads imposed on the specimen is characterized by fractal dimensions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.172-176
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• 2000

A series of preliminary experiments were carried out to quantify the annoyance are noisiness caused by floor impact noise. From the results of the experiments. the heavy impact source was found to be felt louder and noisier than the light impact source. Measurements of noise were also conducted by a diagnostic system based on the model(the model consists of the autocorrelators and the cross-correlation for signals arriving at two ear entrants) of the human auditory-brain system. Physical factors in the model were calculated by use of the ACF(autocorrelation function) and IACF(interaural cross correlation function) of binaural signals. From the ACF/IACF analysis, it was found that perceived loudness of floor impact noise could be represented by the factors of the ACF/IACF model.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.24-31
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• 2023

The solid-state drive (SSD) possesses higher input and output speeds, more resistance to physical shock, and lower latency compared with regular hard disks; hence, it is an increasingly popular storage device. However, tiny components on an internal printed circuit board (PCB) hinder the manual detection of malfunctioning components. With the rapid development of artificial intelligence technologies, automatic detection of components through convolutional neural networks (CNN) can provide a sound solution for this area. This study proposes applying the YOLOv5 model to SSD PCB component detection, which is the first step in detecting defective components. It achieves pioneering state-of-the-art results on the SSD PCB dataset. Contrast experiments are conducted with YOLOX, a neck-and-neck model with YOLOv5; evidently, YOLOv5 obtains an mAP@0.5 of 99.0%, essentially outperforming YOLOX. These experiments prove that the YOLOv5 model is effective for tiny object detection and can be used to study the second step of detecting defective components in the future.

• Journal of the Geological Society of Korea
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• v.54 no.6
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• pp.605-614
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• 2018

For physical experiments like analogue modeling that designed for studying geological deformation, reproducibility of the deformation is important to guarantee the reliability of the experiment. In this study, the normal fault generated by extensional stress is benchmarked using a sand box model. The scaling factors for the modeling test are considered and the experiments are conducted by setting the appropriate material, extensional stress, and boundary condition in the same way as in a benchmark experiment. In addition, a large centrifuge facility is used to vary the centrifugal acceleration and extension rate in the same sized model to account for the scaling factors of the physical quantity during extensional behavior. At 1 g benchmark condition and a centrifugal field at 10 g, a constant rate of the extensional stress is implemented and the topographic evolution is reliably measured. In this study, the reliability and applicability of large centrifuge model tests are evaluated for formulating experiments designed to study geological deformation.