• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.605-612
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• 2015

Three dimensional (3D) position determination and motion recognition using a 3D depth sensor camera are applied to a developed penguin-shaped robot, and its validity and closeness are investigated. The robot is equipped with an Asus Xtion Pro Live as a 3D depth camera, and a sound module. Using the skeleton information from the motion recognition data extracted from the camera, the robot is controlled so as to follow the typical three mode-reactions formed by the operator's gestures. In this study, the extraction of skeleton joint information using the 3D depth camera is introduced, and the tracking performance of the operator's motions is explained.

• Nuclear Engineering and Technology
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• v.7 no.4
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• pp.285-293
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• 1975

A result of the study to determine the depth-dose distribution along the central axis of a polyethylene sphere in diameter of 30cm is described. Depth-dose distribution in the polyethylene sphere for broad beam of monoenergetic photons has been experimentally determined with thermoluminescent dosimeter as a cavity dosimeter. The conversion of dose absorbed in the LiF TLD to dose in the surrounding medium was carried out on the basis of Burlin's generalized cavity theory. Presented in graphical forms are the results obtained. The maximum absorbed doses in the sphere were observed at the depth of about 0.3cm and 0.5cm from the surface of the sphere for the gamma-rays of $^{137}$ Cs and $^{60}$ Co, respectively.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.249-252
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• 2005

Recently, as the industrial demand for small quantity batch production of sheet metal components, the application of dieless forming technology to production of these component rise with the advantages of the reduction in manufacturing cost and time. In dieless forming processes, the determination of moving path of tool plays an important role in producing successfully formed parts. In order to obtain the optimized moving path of tool avoiding forming failure, it is necessary to examine the forming limit of sheet material. Therefore, in this study, as the new criterion to evaluate the formability of sheet material in dieless forming processes FDD(feeding depth diagram) with respect to feeding depth and punch diameter is proposed. Thus, the FDD for the sheet materials of STS304 and Ti-grade2 were obtained from a series of FDT(feeding depth test). In addition the possibility of the application of FLD in judging forming severity in dieless forming processes was investigated by comparing the results of FE analyses based on FLD and experimental FDT.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.99-110
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• 2021

This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.

• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.671-680
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• 2022

The shear capacity of beams is an essential parameter in designing beams carrying shear loads. Precise estimation of the ultimate shear capacity typically requires comprehensive calculation methods. For steel fiber reinforced concrete (SFRC) beams, traditional design methods may not accurately predict the interaction between different parameters affecting ultimate shear capacity. In this study, artificial neural network (ANN) modeling was utilized to predict the ultimate shear capacity of SFRC beams using ten input parameters. The results demonstrated that the ANN with 30 neurons had the best performance based on the values of root mean square error (RMSE) and coefficient of determination (R²) compared to other ANN models with different neurons. Analysis of the ANN model has shown that the clear shear span to depth ratio significantly affects the predicted ultimate shear capacity, followed by the reinforcement steel tensile strength and steel fiber tensile strength. Moreover, a Genetic Algorithm (GA) was used to optimize the ANN model's input parameters, resulting in the least cost for the SFRC beams. Results have shown that SFRC beams' cost increased with the clear span to depth ratio. Increasing the clear span to depth ratio has increased the depth, height, steel, and fiber ratio needed to support the SFRC beams against shear failures. This study approach is considered among the earliest in the field of SFRC.

• Physical Therapy Rehabilitation Science
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• v.13 no.1
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• pp.106-112
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• 2024

Objective: This study aimed to evaluate the validity of a depth camera-based system for monitoring physical function, assessing its feasibility for accurately monitoring activities of daily living. Design: A cross-sectional study. Methods: Twenty-three participants were enlisted to perform fifteen activities of daily living within a living laboratory designed to simulate a home environment. Activities were monitored using a depth camera system capable of classifying actions into standing, sitting, and lying down, with a conventional video camera employed for activity recording. The duration of each activity, as measured by the system, was compared to direct observations made by a physical therapist which were analyzed using a motion analysis software. The association between these two measurement approaches was assessed through correlation analysis, coefficient of determination, intraclass correlation coefficient (ICC), and Bland-Altman plots. Results: Our findings indicated that standing activities exhibited the highest correlation (r=0.847) between the system measurements and physical therapist observations, followed by sitting (r=0.817) and lying down (r=0.734), which demonstrated lower correlations. However, the ICC and Bland-Altman plots revealed notable variances between the two measurement methods, particularly for activities involving lying down. Conclusions: In this study, the depth camera-based physical monitoring system showed promise feasibility in distinguishing standing, sitting, and lying down activities at home environments. However, the current study also underlined some necessities of enhancements in capturing lying down activities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2271-2288
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• 2015

The emerging high efficiency video coding (HEVC) standard adopts the quadtree-structured transform unit (TU) in the residual quadtree (RQT) coding. Each TU allows to be split into four equal sub-TUs recursively. The RQT coding is performed for all the possible transform depth levels to achieve the highest coding efficiency, but it requires a very high computational complexity for HEVC encoders. In order to reduce the computational complexity requested by the RQT coding, in this paper, we propose a fast TU size decision method incorporating an adaptive maximum transform depth determination (AMTD) algorithm and a full check skipping - early termination (FCS-ET) algorithm. Because the optimal transform depth level is highly content-dependent, it is not necessary to perform the RQT coding at all transform depth levels. By the AMTD algorithm, the maximum transform depth level is determined for current treeblock to skip those transform depth levels rarely used by its spatially adjacent treeblocks. Additionally, the FCS-ET algorithm is introduced to exploit the correlations of transform depth level between four sub-CUs generated by one coding unit (CU) quadtree partitioning. Experimental results demonstrate that the proposed overall algorithm significantly reduces on average 21% computational complexity while maintaining almost the same rate distortion (RD) performance as the HEVC test model reference software, HM 13.0.

• Korean Journal of Social Welfare Studies
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• no.39
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• pp.83-113
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• 2008

The purpose of the study is to explore the mental health social workers' experiences concerning client's self-determination by grounded theory, one of the qualitative method. Although a lot of previous studies has proved that the practitioners have suffered from the ethical considerations in their practice, on which the matter of client's self-determination is centered, little attention is paid to deep exploration of practitioners' real experience about those aspects. To carry out the research question, first, through literature reviews focusing on clarify the underlying issues about client's self-determination, three intrinsic clues are found out; incompetence, medical benefits, the harm to the third party. Data obtained by in-depth interview with 10 participants are analyzed by employing the methode developed by Corbin and Strauss, which could categorize the raw data into several high-level concepts and constructs. The findings of the study show that most practitioners would consider the clients as the intrinsic subject of self-determination. Therefore, in practice, they are trying to support the client's self-determination even within the some constraints. In addition, they also experience the clients' latent potential in actualizing autonomy and self-determination, and identifies the positive effect of self-determination not only on the client's self-help and mental health but also on the practitioners themselves. The results of the study clearly suggests that it is critical to provide the practitioners with adequate ethical education and training to help them to overcome their ethical suffering concerning clients self-determination.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.133-140
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• 2002

The object of this paper is to predict the surface roughness using the experiment equation of surface roughness, which is developed with a full factorial design in turning. $3^3$ full factorial design has been used to study main and interaction effects of main cutting parameters such as cutting speed, feed rate, and depth of cut, on surface roughness. For prediction of surface roughness, the arithmetic average (Ra) is used, and stepwise regression has been used to check the significance of all effects of cutting parameters. Using the result of these, the experimental equation of surface roughness, which consists of significant effects of cutting parameters, has been developed. The coefficient of determination of this equation is 0.9908. And the prediction ability of this equation was verified by additional experiments. The result of that, the coefficient of determination is 0.9718.

• Journal of Power System Engineering
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• v.3 no.4
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• pp.63-68
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• 1999

The determination of the optimal machining parameters in metal cutting, such as cutting speed, feed rate, and depth of cut, is an important aspect in an economic manufacturing process. The main objective in general is either to minimize the production cost or to maximize the production rate. Also there are constraints on all the machining operations which put restrictions on the choice of the machining parameters. In this paper as an objective function the production cost is considered with two constraints, surface finish and cutting power. Genetic Algorithm is applied to determine the optimum machining parameters, and the effectiveness of the applied algorithm is demonstrated by means of an example, turning operation.