• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.389-395
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• 2022

Because of improvement of deep learning techniques, deep learning using computer vision such as classification, detection and segmentation has also been used widely at many fields. Expecially, automatic driving is one of the major fields that applies computer vision systems. Also there are a lot of works and researches to combine multiple tasks in a single network. In this study, we propose the network that predicts the individual depth of pedestrians and vehicles. Proposed model is constructed based on YOLOv3 for object detection and Monodepth for depth estimation, and it process object detection and depth estimation consequently using encoder and decoder based on hard parameter sharing. We also used attention module to improve the accuracy of both object detection and depth estimation. Depth is predicted with monocular image, and is trained using self-supervised training method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.799-812
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• 2017

Backfill grouting and realistic convergence distribution were not properly considered in previous studies on 2D numerical analysis of a shield TBM tunnel. In this study, a modeling method was suggested to cope with this problem by considering a realistic convergence distribution and proper properties of backfill grouting. To this end, the influence of gap parameter and depth of rock cover on volume loss and composed of ground volume loss around tunnel excavation and surface volume loss were analyzed with a single layer of weathered soil. As a result, most of surface settlements were occurred immediately after excavation. Additional, as depth of rock cover and gap parameter increased, the influence range of surface settlement curves obtained from 2D numerical analyses became broader than a suggested theoretical equation. Therefore, it is inferred that gap parameter should be applied based on load distribution ratio and the property of backfill grouting properly considered for the estimation of the precise behavior of a shield TBM tunnel in 2D numerical analysis.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1509-1518
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• 2011

Shield TBM tunneling method has been getting the spotlight for urban tunneling. It can be minimized the civil complaint during construction and possible safe tunneling. But the settlement has occurred inevitably due to characteristics of shield TBM equipment. For this reason, the civil complaint can occur in urban areas when tunnel with shallow depth passes through neighboring building or residential area. In this study, the occurrence factors of settlement according to shield TBM tunneling and the tendency of ground settlement by strata condition had analyzed. It is suggested that the practical settlement estimation method and minimizing method of ground settlement under simultaneous backfill grouting condition through measurement results and back analysis data using gap parameter.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.11a
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• pp.357-358
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• 2006

Accurate calibration matching for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of Intra parameter is calibrated with known points, such error can be compensated in some amount and showed the variable experiments for accurate effects.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.123-130
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• 2008

In order to clarify detailed mechanism of the flexible disk grinding system, workpiece length was introduced and its performance was evaluated. Flat zone ratio increased as the workpiece length increased. Increasing wheel speed and depth of cut also enhanced process performance by producing larger flat zone ratio. Neural network system was successfully applied to predict minimum depth of engagement and flat zone ratio. An additional input parameter as workpiece length to the neural network system enhanced the prediction performance by reducing error rate. By rearranging the Input combinations to the network, the workpiece length was precisely predicted with the prediction error rate lower than 2.8% depending on the network structure.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.1
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• pp.74-83
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• 1991

A study on the Correlation of Orthogonal Cutting Parameter (Cutting speed, Depth of cut, Feed Rate) and Acoustic Emission Signal. It is well known that acoustic emission (AE) is the emission of elastic wave resulting from the deformation and fracture of materials. This study estabished correlation of orthogonal cutting parameter and AE signal, and researched into in-process monitoring of tool wear and failure. The results are as follow; 1. AE RMS was under the influence of cutting speed but hardly influenced by depth of cut and feed rate. 2. AE RMS was under the influence of flank wear. 3. AE count rate increased by increased cutting speed. 4. AE RMS value was rapidly increased in 130 m flank wear.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.321-322
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• 2002

This paper presents study of effects of cutting parameters such as cutting speed, feed rate and depth of cut on the surface roughness in hard turning. Taguchi Method and linear regression model of design parameters were utilized to identify the controlling process parameters that can monitor the surface roughness in the hard turning operation. In the process optimization, experimental planning was performed using the orthogonal array and concept of the signal-to-noise ratio. Cutting parameters such as speed, feed rate, and depth of cut were selected as process parameters and the ANOVA analysis showed that feed rate and cutting speed had more effect on the roughness variation that depth of cut.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.61-68
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• 1998

The form accuracy of parts has become an important parameter. Therefore, dimensional tolerance and geometric tolerance are used in the design stage to satisfy required quality and functions of parts. But the informations on the machining conditions, which can satisfy the assigned geometric tolerance in design, are insufficient. The objectives of this research are to study the effects of the grinding parameters such as traverse speed, work speed, depth of cut, and dwell time on the after-ground workpiece shape, and to find out the major parameters among them. The results are as follows, The effects of work speed and depth of cut on workpiece shape are negligible compared with the effect of traverse speed. There is an optimal dwell time depending on the traverse speed. The optimal dwell time is decreasing as the traverse speed is increased.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.53-63
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• 2007

This study is to evaluate the probable snowfall depth by the point frequency analysis and to draw the map of probable snowfall depth in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum depth of snowfall data. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. The estimated parameters were checked by parameter validity conditions of each assumed probability distribution. Four tests that are $X^2-test$, Kolmogorov-Smirnov test, Cramer von Mises test and probability plot correlation coefficient test are used in this study to determine the goodness of fit of the distributions. Mostly the 2-parameter gamma distribution was determined as appropriate distribution for the annual maximum new snowfall depth. The probable snowfall depth were obtained from appropriate distribution for the selected return periods and the maps of probable snowfall depth were presented. It will be useful to specify the snowfall load for the design of agricultural facilities such as vinyl house and cattle shed.

• KSTLE International Journal
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• v.6 no.1
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• pp.1-7
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• 2005

Wear model for predicting the vehaviour of a depth is considered in this paper. It is deduced from the energy and volume based wear models such as the Archard equation and the workrate model. A new parameter of the equivalent depth ($D_e$= wear volume /worn area) is considered for the wear model of a depth prediction. A concenpt of a dissipated shear energy density is accommodated for in the suggested models. It is found that $D_e$ can distinguish the worn area shape. A cubic of $D_e$($D_e^3$) gives a better linear regression with the volume than that of the maximmum depth $D_{max}e$($D_{max}^3$) does. Both $D_{max}$ and $D_e$ are used for the presently suggested depth-based wear model. As a result, a wear depth profile can be simulated by a model using $D_{max}$. Wear resistance from the concern of an overall depth can be identified by the wear coefficient of the model using $D_e$.